oversight

Small Business: Update of Information on SBA's Small Business Investment Company Programs

Published by the Government Accountability Office on 1997-02-21.

Below is a raw (and likely hideous) rendition of the original report. (PDF)

                     United States General Accounting Office

GAO                  Report to the Chairman, Committee on
                     Ways and Means; and the Chairman,
                     Subcommittee on Oversight, Committee
                     on Ways and Means, House of
                     Representatives
March 1997
                     TAX CREDITS
                     Opportunities to
                     Improve Oversight of
                     the Low-Income
                     Housing Program




GAO/GGD/RCED-97-55
      United States
GAO   General Accounting Office
      Washington, D.C. 20548

      General Government Division

      B-274542

      March 28, 1997

      The Honorable Bill Archer
      Chairman, Committee on Ways and Means

      The Honorable Nancy L. Johnson
      Chairman, Subcommittee on Oversight
      Committee on Ways and Means
      House of Representatives

      This report responds to your request to determine the characteristics of the residents and
      properties that have benefited from low-income housing tax credits as well as to assess the
      controls the Internal Revenue Service (IRS) and states have over program operations. It makes
      recommendations to IRS and the Office of Management and Budget on improving program
      operations.

      As agreed with your offices, unless you publicly announce its contents earlier, we plan no
      further distribution of this report until 30 days from the date of this letter. At that time we will
      send copies of this report to the Secretary of the Treasury; Commissioner of Internal Revenue;
      Director, Office of Management and Budget; and appropriate congressional committees and
      Members of Congress. Copies will also be made available to others on request.

      Major contributors to this report are listed in appendix VII. If you have any questions about this
      report, please contact James White on (202) 512-5594 or Judy England-Joseph on
      (202) 512-7631.




      James R. White
      Associate Director, Tax Policy
        and Administration Issues




      Judy England-Joseph
      Director, Housing and Community
        Development Issues
Executive Summary


             The low-income housing tax credit is currently the largest federal program
Purpose      to fund the development and rehabilitation of housing for low-income
             households. Under this program, states are authorized to allocate federal
             tax credits as an incentive to the private sector to develop rental housing
             for low-income households. The tax credits awarded may be taken
             annually for 10 years by investors in qualified low-income housing projects
             to offset federal taxes otherwise owed on their income. If all the credits
             authorized over a 10-year period were awarded by the states to completed
             housing projects and used by investors, the annual cost would be over
             $3 billion.

             As a part of the Committee’s oversight of the tax credit program, the
             Chairman, House Committee on Ways and Means, asked GAO to determine
             the characteristics of the residents and properties that have benefited from
             tax credits as well as to assess the controls the Internal Revenue Service
             (IRS) and states have to ensure that (1) state priority housing needs are
             met; (2) housing project costs, including tax credit costs, are reasonable;
             and (3) states and project owners comply with program requirements.

             GAO’s analysis of the low-income housing tax credit program is based
             primarily on a survey of tax credit policies and procedures in 50 states and
             4 additional jurisdictions that have delegated tax credit allocation
             authority. As a part of that survey, GAO reviewed 423 randomly selected
             housing projects to assess the application of state controls and to
             ascertain project costs and characteristics. Information based on the 423
             housing projects provide a statistically representative picture of the tax
             credit projects that were placed in service in the continental United States
             from 1992 through 1994.


             Congress established the low-income housing tax credit program as an
Background   incentive for developers and investors to provide affordable rental housing
             for households whose income is at or below specified income levels. The
             incentive was needed because rental income and other returns from
             investment in low-income housing would generally not be sufficient to
             cover the costs of developing and maintaining such properties. The
             program is jointly administered by IRS and state tax credit allocation
             agencies. Annually, IRS allocates tax credits to each state in an amount
             equal to $1.25 per state resident. Under the Internal Revenue Code, the
             state agencies are responsible for determining which housing projects
             should receive tax credits and the dollar amount of tax credits each should




             Page 2                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Executive Summary




receive. In making these determinations, the states are to consider both
housing needs and costs.

The Code gives states general guidance on how to consider needs and
costs. The state tax credit agencies are required to have an allocation plan
that identifies the states’ priority housing needs and contains selection
criteria for awarding credits to help meet those needs. Housing needs are
intended to include consideration of such matters as the availability of
low-income housing over extended periods of time. To ensure that no
more tax credits are awarded than necessary to stimulate low-income
housing development, the state agency is required to evaluate such factors
as the reasonableness of development costs and the sources and uses of
project funds.

After the state allocates tax credits to developers, the developers typically
offer the credits to private investors. The private investors use the tax
credits to offset taxes otherwise owed on their tax returns. The money
private investors pay for the credits is paid into the projects as equity
financing. This equity financing is used to fill the gap between the
development costs for a project and the non-tax credit financing sources
available, such as mortgages that could be expected to be repaid from
rental income.

Generally, developers must place the projects in service within 2 years of
credit allocation or return the credits to the state for reallocation to other
projects. Investors can claim the credits to offset taxes otherwise owed on
their tax returns for each year of a 10-year period called the “credit period”
as long as a minimum percentage of the projects’ units are rented to
low-income tenants at restricted rents for a 15 year tax credit compliance
period. Individual and corporate investors are to attach tax credit
schedules to their income tax returns when they claim the credits.

Once projects have been placed in service, state agencies are also
responsible for monitoring the projects for compliance with federal
requirements concerning household income and rents and project
habitability. If noncompliance is not corrected, IRS may recapture or deny
credit for previously used or issued tax credits.

IRSis responsible for issuing regulations on state monitoring requirements,
ensuring that taxpayers take no more tax credits than they are entitled to
take, and ensuring that states allocate no more credits than they were
authorized to allocate. IRS requires annual reports from the states on the



Page 3                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                   Executive Summary




                   amount of tax credit allocations made in total and amounts awarded to
                   individual projects. IRS also requires reports from states on findings of
                   project noncompliance.


                   Given the results of its random sample, GAO estimates that about 4,100
Results in Brief   low-income housing projects were placed in service during the period 1992
                   through 1994. The resident and property characteristics of the projects
                   varied widely, as did the costs to build the projects. For these projects, GAO
                   estimates that the states annually awarded tax credits with a potential
                   value over their 10-year lifetime of about $2 billion (about $1.6 billion in
                   present value terms), or about $6.1 billion for the 3 years combined. States
                   have programs in place for allocating tax credits and monitoring
                   implementation of low-income housing projects, but policies and
                   procedures differ among the states and some procedures, including
                   certification of project costs and monitoring project compliance, should
                   be implemented more effectively in some states. IRS monitors tax credit
                   allocations through state reports and has been developing a program to
                   evaluate taxpayer use of tax credits. However, IRS needs additional
                   information to adequately monitor tax credit allocations and taxpayer
                   compliance with credit program requirements.

                   GAO  estimates that the average household income of residents of tax
                   credit-funded low-income housing projects placed in service between 1992
                   and 1994 was about $13,000, and that a substantial majority of the
                   households had income levels considered “very low” by the Department of
                   Housing and Urban Development. Also, GAO estimates that almost
                   three-fourths of the households in these projects benefited either directly
                   or indirectly from other housing assistance, such as rental assistance to
                   residents or loan subsidies to project owners.

                   The low-income housing developments were located throughout the
                   United States in both urban and rural areas, and the types of buildings
                   varied from walk-up/garden-style apartments to high-rise apartments. Most
                   were new construction, but some were rehabilitated. The average per-unit
                   development costs were an estimated $60,000, but they ranged from less
                   than $20,000 to more than $160,000. GAO estimated the present value of the
                   average tax credit cost per unit over the 10 year tax credit period to be
                   $27,300.

                   All the states had developed qualified tax credit allocation plans, required
                   by the Internal Revenue Code to direct tax credit awards to meet priority



                   Page 4                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Executive Summary




housing needs. The plans generally targeted the credits to the priority
housing needs identified by the states. Consistent with the latitude given
them in the Code, the states had defined and weighted the selection
criteria for awarding credits in different ways. There was also
considerable variation in their plans and in the data and analyses used in
assessing housing needs.

Although all states had qualified allocation plans, GAO identified several
additional factors that could affect the housing actually delivered over
time. For example, some states used discretionary judgement in addition
to the criteria in the allocation plans in making final credit allocation
decisions. In addition, IRS and state data indicate that many tax credits that
were initially allocated may not have been used. Further, the long-term
economic viability of tax credit projects as low-income housing has not
been tested because projects have not yet been operational beyond the
credit period. Determining whether, or how, these factors affect the
long-term delivery of low-income housing that meets state housing
priorities was beyond the scope of this report.

In ensuring the reasonableness of project costs and estimating the amount
of tax credits needed, state allocation agencies are dependent on
information submitted by developers about sources of financing and uses
of funds. All states had some cost control procedures in place that were
intended to help ensure the reasonableness of the tax credits awarded to
projects. Consistent with the flexibility in the Code, these cost control
procedures varied. Although all but one state required some form of
independent verification of cost and financing data, the scope of the
required verifications varied from limited verification of some developers’
cost information to independent audits conducted in accordance with
established auditing standards. GAO observed that some projects lacked
complete information on the sources and uses of project funds, and some
did not include certification of key data used in determining the basis for
the tax credit. Without verification of cost and financing information,
states are vulnerable to providing more (or fewer) tax credits to projects
than are actually needed.

States have established compliance monitoring programs consistent with
IRSregulations, but GAO determined that not all states fulfilled the
requirements of those programs in 1995. Several states conducted fewer
than the agreed-upon compliance monitoring site visits or desk audits in
their plans, and, because IRS regulations do not require states to report on
the number of monitoring inspections they have made, IRS could not



Page 5                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                            Executive Summary




                            determine states’ compliance with their monitoring plans. In addition, IRS
                            regulations do not require on-site inspections or other reviews to evaluate
                            project habitability, and many states do not conduct such reviews. Without
                            such information, states are unlikely to detect violations of the Code’s
                            habitability requirements.

                            IRSrecently developed a tax credit audit program to assess whether
                            taxpayers were appropriately claiming valid tax credits. However, because
                            the audits conducted were identified through state reports of project
                            noncompliance, the audit program is unlikely to provide sufficient
                            information to estimate overall taxpayer compliance with the tax credit
                            program. IRS is also developing a system to verify that states do not issue
                            more tax credits than they are authorized, but more data on returned
                            credits are needed from the states for the system to accurately verify total
                            state allocations.

                            Finally, although IRS conducts various tax credit oversight activities, there
                            is no specific requirement or authorization in the Internal Revenue Code
                            for IRS to evaluate state agencies’ tax credit operations for compliance
                            with laws and regulations. Unlike other federal housing programs that are
                            generally administered by state agencies, such as the Community
                            Development Block Grant program, the tax credit program is not covered
                            by the Single Audit Act under which state operations are independently
                            audited for compliance with federal laws and regulations.



Principal Findings

Low-Income Housing Tax      From its sample, GAO estimates that about 4,100 low- income housing
Credit Projects Vary in     projects containing about 172,000 tax credit supported units were placed
Tenant Characteristics,     in service during the period 1992 through 1994. About an estimated
                            three-quarters of the households had incomes in 1996 that were at or
Property Characteristics,   below 50 percent of their area’s median income, which the Department of
and Costs                   Housing and Urban Development considered to be “very-low income.”
                            Also, an estimated 71 percent of the households benefited directly or
                            indirectly from one or more types of housing assistance besides tax
                            credits, such as rental assistance, other government loans, loan subsidies,
                            or grants. For example, about 39 percent of the households received rental
                            assistance, which allowed households that had an average of 25 percent of
                            their area’s median income to rent units. Households with rental




                            Page 6                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                        Executive Summary




                        assistance had an estimated average current income of $7,860 versus
                        $16,700 for households without rental assistance.

                        Tax credit properties placed in service from 1992 through 1994 were
                        located throughout the country. The most common type of property was a
                        walk-up/garden-style apartment building. GAO estimates that the average
                        project contained 43 units, about 73 percent of the projects were newly
                        constructed, and the average monthly rent was about $435.

                        GAO estimates that the average cost of developing the units placed in
                        service from 1992 through 1994 was about $60,000; however, the per unit
                        costs varied substantially. About 10 percent of the units cost less than
                        $20,000 to develop while about 10 percent cost more than $100,000. Since
                        tax credits are generally a function of development costs, the cost of these
                        properties to the federal government also varied. GAO estimated the
                        present value of the average tax credit cost per unit over the 10 year tax
                        credit period to be about $27,300. About 60 percent of the units had tax
                        credit costs at or below the estimated average, and 2 percent had
                        estimated tax credit costs of $100,000 or more. Costs varied for many
                        possible reasons, such as the types of buildings constructed or
                        rehabilitated, the size and location of the units, and the amount of fees
                        paid to developers.


State Controls for      The Internal Revenue Code gives state agencies wide latitude in
Allocating Credits to   determining which projects should receive tax credits. The Code requires
Housing Needs Vary      that states develop qualified allocation plans that target the tax credits to
                        proposed projects that meet their priority housing needs and are
                        appropriate to local conditions. The agencies must also give preference to
                        proposed projects that serve the lowest income tenants and serve qualified
                        tenants for the longest periods. State agencies have defined the tax credit
                        program’s requirements in different ways. For example, all state agencies
                        have used 1990 Census data to define their priority housing needs. Some
                        states supplemented these data with more current and detailed data.
                        Similarly, most agencies relied on market studies to define local
                        conditions, but the specificity of the market studies differed among the
                        states. State agencies also used different income levels to define lowest
                        income, and they defined extended-use requirements differently.

                        The qualified allocation plans generally combined the Code’s selection
                        criteria with thresholds, set-asides, points, or rankings to determine which
                        projects were awarded tax credits. According to state allocation agency



                        Page 7                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                 Executive Summary




                                 officials, these direct controls were often augmented by competition
                                 among developers for tax credits. Most of the state agencies reported that
                                 they gave preference to project proposals that committed to serving the
                                 lowest income tenants by assigning higher scores or bonus points.
                                 Similarly, 49 of the 54 state agencies reported giving preference to project
                                 proposals with agreements to serve qualified tenants for longer periods of
                                 time than the federal law required.

                                 Under the tax credit program, it is up to the states to identify best
                                 practices, consider the costs and benefits of alternative approaches, and
                                 select the approaches best suited to their conditions. The National Council
                                 of State Housing Agencies has a commission examining ways to improve
                                 various aspects of the tax credit program, including how allocation plans
                                 allocate credits to needs.

                                 Although all states had qualified allocation plans, GAO identified several
                                 additional factors that could affect the actual housing delivered over time.
                                 First, nearly all of the agencies used discretionary judgement in addition to
                                 the criteria in the allocation plans in making final credit allocation
                                 decisions. Second, a significant proportion of the tax credits that IRS and
                                 state data showed had been allocated could not be reconciled with IRS and
                                 state data on the number of tax credits awarded to projects that were
                                 placed in service, which may indicate that not all credits allocated have
                                 been used. Third, because no tax credit properties have yet reached the
                                 end of the 15 year tax credit compliance period, the long-term economic
                                 viability of tax credit projects as low-income housing has not been tested.
                                 Determining whether, or how, these factors impact the delivery of
                                 low-income housing that meets state housing priorities was beyond the
                                 scope of this report.


Opportunities for                In order to limit the federal share of housing development project costs,
Improving States’ Controls       states are to provide no more tax credits to projects than necessary for
Over Project Costs               their financial viability. The Internal Revenue Code provides broad
                                 guidance to states for controlling tax credit awards, requiring them to
                                 consider the following aspects:

                             •   the reasonableness of a project’s development cost;
                             •   the extent of a project’s financing gap, which is the difference between the
                                 cost of a project and the amount of non-tax credit financing that a project
                                 can raise to cover those development costs; and




                                 Page 8                         GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
    Executive Summary




•   the yield obtained from a project’s tax credit award, which is the amount
    of equity investment a project could raise for each tax credit dollar
    received.

    To control the costs to the federal government of individual projects,
    states are required to evaluate the sources of all financing available to a
    housing project and the uses to which the financing is to be put.
    Controlling the amount of tax credits awarded to individual projects limits
    federal taxpayers’ cost for the project and allows a state, with an overall
    tax credit allocation proportional to its population, to finance more
    projects.

    Consistent with the flexibility given them by the Code, GAO found that
    states had established controls that varied in their coverage and stringency
    for helping ensure appropriate tax credit awards. All state agencies had
    controls over development costs. Many states relied on HUD cost
    standards, others believed their own standards were more effective in
    limiting costs, and some relied on their staffs’ expertise because they said
    that differences in project types and location made setting standards
    impractical. Additionally, most supplemented these practices by using
    competition among project developers to control costs, i.e., they
    introduced cost considerations into the ranking systems used to consider
    projects for tax credit awards. State agency practices for determining the
    reasonableness of the non-tax credit financing varied, but they generally
    included reviewing projects’ rents and operating expenses, private
    mortgage terms, and non-tax credit public subsidies. States generally
    relied on the market to determine the yield obtained from a project’s tax
    credit award.

    In controlling costs—that is, in evaluating the reasonableness of project
    costs, financing gap, and tax credit proceeds—allocating agencies are
    largely dependent on information submitted by developers. If the agencies
    do not have complete and reliable information, they are less assured their
    controls are effective.

    GAO  found some control weaknesses in terms of the way states used data
    to evaluate the sources and uses of project funds. For example, although
    all but one state required some form of independent verification of cost
    and financing data, the scope of the required cost verification work varied.
    It ranged from audits that provided an independent public accountant with
    a reasonable basis for expressing an opinion on the overall reliability of a
    project’s financial information taken as a whole to more limited work,



    Page 9                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                        Executive Summary




                        such as the application of procedures that provided a public accountant
                        with a basis to issue a report of findings based on the procedures agreed
                        to with the state agency but not provide assurances on the reliability of the
                        financial information. Additionally, some of the procedures agreed to by
                        state agencies did not require verification of costs eligible for inclusion in
                        the base for calculating the tax credit. Also, on the basis of the sampled
                        projects, GAO estimates that for about 14 percent of the projects, the states
                        lacked complete information on the sources and uses of project funds.
                        Without assurance of the validity of developer costs and without a
                        complete and documented basis for determining equity needs, such as a
                        detailed sources and uses of funds analysis, states are vulnerable to
                        providing more (or fewer) credits to projects than needed.

                        As with practices relating to meeting state housing needs, it is up to the
                        states to identify best practices, consider the costs and benefits of
                        alternative approaches, and select the approaches best suited to their
                        conditions. In the area of costs, the National Council of State Housing
                        Agencies has issued some recommended standards and best practices that
                        some states have adopted.


Improvements Can Be     Not all states fulfilled the requirements of their compliance monitoring
Made in State and IRS   programs, and, although IRS has been developing oversight programs, it did
Oversight Activities    not have sufficient information to determine overall state or taxpayer
                        compliance. All states reported that they had established compliance
                        monitoring procedures that met the requirements established by IRS. In
                        1995, however, several states did not do the number of desk reviews and
                        on-site inspections they had agreed to do under IRS regulations. Because
                        IRS’ regulations do not require states to submit annual reports to IRS on the
                        number of monitoring inspections made, it was not in a position to readily
                        determine whether states met their agreed-upon monitoring
                        responsibilities.

                        Also, IRS’ monitoring regulations do not require states to make on-site
                        visits to projects or obtain information from other sources, such as local
                        government reports on building code violations, that would allow states to
                        detect violations of the Code’s habitability requirements. For IRS to better
                        ensure that habitability problems are identified during monitoring reviews,
                        states would have to do on-site inspections or obtain information on these
                        types of problems from other sources.




                        Page 10                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Executive Summary




GAO found that states were generally sending the reports IRS required on
noncompliance found during their monitoring inspections. However, some
state agencies expressed concerns about the types of noncompliance that
should be reported. In response to state concerns, IRS was revising the
noncompliance form states submit so that it lists 10 types of
noncompliance that should be reported. GAO found that the proposed form
would be more useful for determining whether IRS needed to recapture tax
credits from project owners if the form contained data on the number of
units out of compliance by type of noncompliance and the date the
noncompliance was corrected.

In late 1995, IRS instituted an audit program to determine whether
taxpayers are entitled to the credits claimed on their tax returns. IRS is
relying on the results of this audit program to provide information on the
extent and types of noncompliance that exist in the tax credit program.
Without this information, IRS is not in a position to determine how best to
allocate resources to tax credit compliance efforts. GAO found that the
audit results from IRS’ program will not provide statistically reliable
compliance data because the audits were selected on the basis of state
reports of noncompliance. IRS needs to explore ways to get more reliable
data on taxpayer compliance.

IRS is currently developing a document matching program using state tax
credit reports to determine whether states have allocated more credits
than allowed by law. However, the reports do not contain information on
the allocation year of the tax credits that developers returned to the
allocating agencies for reallocation to other projects. IRS needs this
information in order to determine whether states stay within their tax
credit ceilings.

Unlike most programs operated by state and local governments that
receive federal financial assistance, the low-income housing tax credit
program operations are not subject to independent audits under the Single
Audit Act, because tax credits are not considered as federal financial
assistance under Office of Management and Budget implementing
guidance. However, other state agency operations that receive other types
of federal financial assistance, such as Community Development Block
Grants, are covered by the Single Audit Act. IRS currently does not have
plans to undertake examinations of state agencies’ operations and would
not do so without congressional direction. Including low-income housing
tax credits in the definition of federal financial assistance so that the tax
credit program could be subject to the Single Audit Act is one way of



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                     Executive Summary




                     promoting state compliance with tax credit laws and regulations. The
                     Code allows state agencies to charge developers fees to cover the
                     administrative costs associated with evaluating project proposals and
                     monitoring projects that are awarded credits. Any additional costs that
                     states may incur could be incorporated into states’ administration and
                     monitoring fees.


                     The low-income housing tax credit program has stimulated low-income
Recommendations      housing development in the United States and states’ implementation of
                     the allocation process generally meets the requirements of the Internal
                     Revenue Code. However, the procedures that some states and IRS use for
                     review of project proposals and implementation and for oversight of
                     general compliance with laws and regulations should be improved.
                     Accordingly, GAO recommends that the Commissioner of Internal Revenue
                     amend regulations for the tax credit program to (1) establish clear
                     requirements to ensure independent verification of key information on
                     sources and uses of funds submitted to states by developers that form the
                     basis of decisions about the value of tax credits granted for low-income
                     housing projects; (2) require that states report sufficient information about
                     monitoring inspections or reviews, including the number and types of
                     inspections made, so that IRS can determine whether states have complied
                     with their monitoring plans; and (3) require that states’ monitoring plans
                     include specific steps that will provide information to permit IRS to more
                     effectively ensure that the Code’s habitability requirements are met. GAO
                     also recommends that the Commissioner explore alternative ways to
                     obtain better information to verify that states’ allocations do not exceed
                     tax credit authorizations and to evaluate taxpayers’ and housing projects’
                     compliance with the requirements of the Code.

                     Finally, to help ensure appropriate oversight of state allocating agencies’
                     overall compliance with tax credit laws and regulations, GAO recommends
                     that the Director, Office of Management and Budget, incorporate the
                     low-income housing tax credit program in the definition of federal
                     financial assistance included in implementing guidance for the Single
                     Audit Act, as amended, so that the program would be subject to audits
                     conducted under the Single Audit Act.


                     GAO received written comments on a draft of this report from IRS and the
Federal Agency and   National Council of State Housing Agencies and oral comments from the
State Association
Comments

                     Page 12                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
    Executive Summary




    Office of Management and Budget. IRS agreed with the recommendations
    and, separately, orally advised GAO that it had started to implement them.

    OMB advised GAO that it did not take exception to strengthening
    accountability over the low-income housing tax credit program by building
    on an existing accountability mechanism such as the single audit concept.
    However, OMB said that incorporating the low-income housing tax credit in
    the definition of federal financial assistance included in implementing
    guidance for the Single Audit Act would likely require a broader evaluation
    of accountability for tax credit programs in general, and the application of
    the single audit concept in particular. Also, OMB indicated that any changes
    in tax credit accountability might be more appropriately accomplished
    through legislation than administrative initiative.

    GAO does not object to OMB’s premise about an approach for considering
    how to make the low-income housing tax credit program subject to audits
    conducted under the Single Audit Act. GAO also notes that an evaluation
    along the lines suggested by OMB could also include an assessment of
    whether and, if so, what legislation might be most appropriate.

    In commenting on this report, the National Council of State Housing
    Agencies noted that while it had previously expressed concerns about
    potential bias and prejudgment in some aspects of GAO’s work, the report
    answered many of those concerns. Nonetheless, the Council had a number
    of comments. These comments are discussed at the end of the appropriate
    chapters. Principal among the comments are the following five.

•   First, the Council said that the report “vindicates public predictions by GAO
    officials that nothing in the report could justify Housing Credit repeal.” In
    response, GAO emphasizes that it has never taken a position on whether the
    tax credit should be retained or repealed. Further, GAO notes that its work
    focused on controls established by IRS and the states in implementing tax
    credit requirements and that making judgments as to the merits of the tax
    credit program was not part of that work.
•   Second, the Council indicated that the report also addresses some of its
    concerns in that the report documents how the credit is “exceeding” its
    objectives and cited as evidence a number of income, rent and cost
    estimates in the report. Contrary to the Council’s interpretation, GAO did
    not take a position on whether the tax credit program is exceeding its
    objectives and notes that some results cited by the Council were attributed
    in the report to the use of other government subsidies, such as federal
    rental assistance programs, in combination with tax credits.



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•   Third, the Council expressed concerns because the report implies that
    state deviations from Council-recommended best practices are
    deficiencies. GAO disagrees and notes that the report repeatedly points out
    that the states were given flexibility in the administration of the program.
    The report clearly makes the point that state agencies have no legal
    requirement to follow Council-recommended best practices, such as
    making site visits. GAO’s recommendations were based on Internal
    Revenue Code requirements and were developed with the intent of better
    positioning IRS to carry out its responsibilities for assuring compliance.
•   Fourth, the Council said GAO’s sample was arbitrary because it includes all
    large housing projects. GAO strongly disagrees with this characterization
    and rationale. GAO oversampled large projects in order to reduce sampling
    error. GAO produced estimates from this sample using a standard statistical
    technique that compensates for the oversampling by weighting each
    sample project by its population weight. This statistical technique is
    commonly used and statisticians have shown it produces unbiased
    estimates. Using this technique, GAO was able to reduce the size and cost of
    the sample while maintaining an adequate level of statistical precision for
    both project and housing unit estimates.
•   Fifth, the Council stated that some of GAO’s recommendations do not take
    into account their cost effectiveness. GAO recognizes that costs associated
    with implementing its recommendations should always be a concern and
    states that it developed its recommendations with that in mind. For
    example, in recommending that the Single Audit Act be used to strengthen
    federal oversight of the tax credit program, GAO notes that the act was
    established to eliminate potentially duplicative and burdensome federal
    oversight reviews. Similarly, in recommending that IRS establish
    requirements for ensuring independent verification of information on
    sources and uses of funds, GAO considered a range of options and
    estimated costs for obtaining such verifications.




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Page 15   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Contents



Executive Summary                                                                                   2


Chapter 1                                                                                          22
                         Background                                                                22
Introduction             Transferring Tax Credits From the Federal Government to the               23
                           Private Sector
                         Overseeing Compliance With the Tax Credit Program’s                       28
                           Requirements
                         Objectives, Scope, and Methodology                                        31
                         State Association Comments and Our Evaluation                             35

Chapter 2                                                                                          37
                         Reported Incomes for Most Tax Credit Households Were Very                 38
Low-Income Housing         Low
Tax Credit Properties:   Tax Credit Households Were Generally Small and Projects Had               42
                           Diverse Resident Populations
Their Residents,         Properties Were Widespread, Units Were Generally Small, and               43
Characteristics, and       Rents Were Restricted
Costs                    Tax Credit and Development Costs Varied Widely                            47
                         Observations                                                              52
                         State Association Comments and Our Evaluation                             52

Chapter 3                                                                                          54
                         Internal Revenue Code Gives Agencies Wide Latitude in                     54
States’ Controls for        Allocating Tax Credits
Allocating Credits to    Agencies Have Defined the Program’s Requirements in Different             55
                            Ways
Housing Needs Vary       Allocation Plans Weight Selection Criteria                                62
                         Allocation Plans Provided for Targeting Tax Credits                       63
                         Several Factors May Affect the Housing Actually Delivered Over            68
                            Time
                         Conclusions                                                               71




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                         Contents




Chapter 4                                                                                          73
                         Tax Code Requirements                                                     73
Opportunities for        Allocating Agency Practices for Ensuring Reasonable                       76
Improving States’           Development Costs
                         Allocating Agency Practices for Determining Project Equity                83
Controls Over Project       Needs
Costs                    State Controls Over Tax Credit Pricing                                    88
                         Effectiveness of Cost Controls Depends on Accuracy of Cost                91
                            Data
                         Conclusion                                                                93
                         Recommendation to the Commissioner of Internal Revenue                    95
                         Federal Agency and State Association Comments and Our                     95
                            Evaluation

Chapter 5                                                                                          96
                         Opportunities to Improve State Oversight                                  99
Opportunities Exist to   Opportunities to Improve IRS’ Oversight Activities                       108
Improve State and        Little Independent Oversight of State Housing Agencies’                  113
                            Operations
Federal Compliance       Conclusions                                                              117
Oversight Activities     Recommendations to the Commissioner of Internal Revenue and              119
                            Director, Office of Management and Budget
                         Federal Agency and State Association Comments and Our                    119
                            Evaluation

Appendixes               Appendix I: Statistical Methodology for Evaluating the                   122
                           Low-Income Housing Tax Credit Program
                         Appendix II: Additional Data on Incomes of Tax Credit                    145
                           Households by Type of Other Housing Assistance Received
                         Appendix III: Tax Credit Project Information Reported by                 148
                           Allocating Agencies and Used in the GAO Sample
                         Appendix IV: Results of Site Visits to GAO Sample Properties             153
                         Appendix V: Comments From the Internal Revenue Service                   170
                         Appendix VI: Comments From the National Council of State                 171
                           Housing Agencies
                         Appendix VII: Major Contributors to This Report                          175

Tables                   Table 2.1: Estimated 1996 Incomes of Households With and                  41
                          Without Additional Rental Assistance Residing in Tax Credit
                          Properties Placed in Service, 1992-94




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Contents




Table 3.1: Tax Credits Awarded to Projects Placed in Service,             69
  1992-94
Table 4.1: Size of Mortgage Deemed Supportable Under                      85
  Alternative Debt Service Coverage Ratios and Amortization
  Periods
Table 4.2: Estimated Sources of Financing for Projects Requiring          87
  Subsidies in Addition to Tax Credits
Table 4.3: Estimated Distribution of Equity Prices Received for           90
  Properties Placed In Service, 1992-1994
Table 5.1: Number of State Agencies That Either Met, Exceeded,           101
  or Failed to Meet IRS’ Monitoring Requirements in 1995
Table 5.2: Number of State Agencies That Either Fully Met,               102
  Partially Met, or Did Not Meet NCSHA’s Monitoring Guidelines in
  1995
Table 5.3: Estimates on the Types of Noncompliance Identified by         103
  Desk Reviews and On-Site Inspections That Found At Least One
  Incident of Noncompliance
Table 5.4: Number of Form 8823s Submitted by State Agencies to           105
  IRS in 1995
Table I.1: Sampling Errors of Estimates From Information in the          126
  Project Questionnaire
Table I.2: Sampling Errors of Estimates About the Households             135
  Occupying LIHTC Units
Table I.3: Sampling Errors for Table 2.1—Economic Data on                141
  Low-Income Households With and Without Additional Rental
  Assistance
Table I.4: Sampling Errors for Income Data on Low-Income                 142
  Households by Type of Housing Assistance Provided
Table I.5: Sampling Errors for Table 2.1—Current Incomes by              143
  Type of Qualifying Household Reported by Property Managers in
  1996 (Properties Placed in Service 1992 Through 1994)
Table I.6: Sampling Errors for the Ratio of Household Current            143
  Income to Applicable Area Median Income by Type of Qualifying
  Household—Properties Placed in Service 1992-1994
Table I.7: Sampling Errors for Table 5.3—Types of                        144
  Noncompliance Found By Desk Review and On-Site Inspections
Table I.8: Sampling Errors for Table 4.2—Sources of Financing            144
  for Projects Requiring Subsidies in Addition to Tax Credits
Table II.1: Income Estimates for Households Residing in Tax              146
  Credit Properties Placed in Service, 1992-94, by Type of Housing
  Assistance Provided




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          Contents




          Table II.2: Current Income Estimates by Type of Qualifying               147
            Household Reported by Property Managers in 1996 for Properties
            Placed in Service, 1992-94
          Table II.3: Ratio of Household Current Income Estimates to               147
            Applicable Area Median Income by Type of Qualifying Household
            for Properties Placed in Service, 1992-94
          Table III.1: Summary of Tax Credit Projects Reported to GAO by           149
            Tax Credit Allocating Agencies as Placed in Service During the
            Period 1992-1994
          Table III.2: Summary of GAO Sample of Tax Credit Projects                150
            Reported to GAO by Tax Credit Allocating Agencies as Placed in
            Service During the Period 1992—1994


Figures   Figure 1.1: Transferring Tax Credits From the Federal                     24
            Government to the Private Sector
          Figure 1.2: Tax Credit Oversight System                                   29
          Figure 2.1: Estimated 1996 Incomes of Households in Tax Credit            39
            Units
          Figure 2.2: Estimated 1996 Incomes of Households in Tax Credit            40
            Units Relative to Applicable Area Median Income
          Figure 2.3: Estimated Size of Households in Tax Credit Properties         42
            Placed in Service, 1992-94
          Figure 2.4: Location Estimates for Tax Credit Properties and              44
            Units Placed in Service, 1992-94
          Figure 2.5: Estimated Average Per-Unit 10 Year Tax Credit Costs           48
            of Properties Placed in Service, 1992-94
          Figure 2.6: Estimated Average Per-Unit Development Costs of               49
            Tax Credit Properties Placed in Service, 1992-94
          Figure 2.7: Estimated Average Per-Unit Costs of Properties                51
            Placed in Service, 1992-94, By Type of Construction, Location,
            and Building
          Figure 4.1: Estimates on Housing Project Sources and Uses of              76
            Funds
          Figure 5.1: Tax Form Flow and Oversight                                   97
          Figure IV.1: Castle Square, Boston, MA                                   154
          Figure IV.2: Turk Street Apartments, San Francisco, CA                   155
          Figure IV.3: Mount Mercy, Grand Rapids, MI                               156
          Figure IV.4: Graham/Terry, Seattle WA                                    157
          Figure IV.5: Providence Square, New Brunswick, NJ                        158
          Figure IV.6: O’Hern House, Atlanta, GA                                   159
          Figure IV.7: Cascade Commons, Sterling, VA                               161




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Figure IV.8: Rancho Del Mar, Tucson, AZ                                 162
Figure IV.9: Covington Court, St. Paul, MN                              163
Figure IV.10: Lakewood Terrace, Lakeland, FL                            164
Figure IV.11: Mansfield Manor, Mansfield, TX                            165
Figure IV.12: Lake Pointe, Conway, AR                                   166
Figure IV.13: Post Glen, Oceana, WV                                     167
Figure IV.14: Edgewood, Belton, SC                                      168
Figure IV.15: Hardwick, Hardwick VT                                     169




Abbreviations

CDBG       Community Development Block Grant
DHCR       Division of Housing and Community Renewal
DHR        Division of Housing and Community Renewal, New York
                State
FMFIA      Federal Managers’ Financial Integrity Act
HUD        Department of Housing and Urban Development
IRS        Internal Revenue Service
NCSHA      National Council of State Housing Agencies
OMB        Office of Management and Budget
RHS        Rural Housing Service


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Page 21   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 1

Introduction


               In the Tax Reform Act of 1986, Congress replaced existing tax incentives
               for construction of low-income housing, such as accelerated depreciation,
               with tax credits to encourage the development of affordable rental
               housing for low-income households. To control the use of the tax credits
               and ensure the delivery of affordable housing to low-income households,
               Congress established a joint federal/state program for transferring federal
               tax credits to the private sector.

               This report responds to a request from the Chairman, House Committee on
               Ways and Means, that we determine the characteristics of low-income
               housing tax credit projects and assess the controls established by the
               Internal Revenue Service (IRS) and the states for implementing the
               requirements of the Low-Income Housing Tax Credit program. These
               controls are to ensure that (1) state priority housing needs are met;
               (2) housing project costs, including tax credit costs, are reasonable; and
               (3) states and project owners comply with program requirements.


               In establishing the tax credit incentive, Congress recognized that a private
Background     sector developer may not receive enough rental income from a
               low-income housing project to (1) cover the costs of developing and
               operating the project, and (2) provide a return to investors sufficient to
               attract the equity investment needed for development. To spur investment,
               Congress authorized the states, within specified limits, to allocate tax
               credits to qualifying housing projects. The credits may then be shared
               among the owners of a project (equity investors), much as income and
               losses are shared among business partners for tax purposes. Generally, the
               investors are recruited by syndicators, and ownership rights are controlled
               by limited partnership agreements.

               Under the Internal Revenue Code, the amount of tax credits that states
               through their tax credit allocating agencies may award to housing projects
               are limited. The maximum tax credit allowed per year depends on the type
               of project, but in many cases it is about 9 percent of a newly constructed
               project’s qualified basis, which is generally equal to the development costs
               allocated to low-income units, less the land and certain other costs. The
               amount of the credit award may be claimed annually on the tax returns of
               the project owners (individuals and corporations) for 10 years, provided
               that the projects remain in compliance with the tax credit program rules.

               Under the Code, the amount of tax credits available to the state tax credit
               allocating agencies are also limited. In general, each year the states receive



               Page 22                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                        Chapter 1
                        Introduction




                        an additional allotment of about $300 million in tax credits to award to
                        new low-income housing projects. Assuming project owners remain
                        eligible, they would be entitled to take the $300 million in tax credits each
                        year for 10 years. Thus, in any one year, 10 years worth of federal tax
                        credits would be outstanding and the aggregate annual cost to the federal
                        government would be $3 billion.

                        At the initiation of our work, no comprehensive data were available on the
                        dollar amount of the tax credits that had been awarded to housing projects
                        since the program began in 1987. In querying the tax credit allocating
                        agencies, we were advised that about 4,200 projects with about 175,600
                        units were placed in service in the continental United States during the
                        period 1992 through 1994. After accounting for misreporting by the
                        allocating agencies, which we identified during our review of 423 sampled
                        projects (see apps. I,II and III), we estimate that about 4,100 projects
                        containing about 172,000 tax qualified units were placed in service in the
                        continental United States during the period 1992 through 1994. We also
                        estimate that, for these projects, the states annually awarded tax credits
                        with a potential value over their 10-year lifetime of about $2 billion (about
                        $1.6 billion in present value terms), or about $6.1 billion for the three years
                        combined. These estimates constitute the universe of projects discussed in
                        this report.


                        To manage the transfer of federal tax credits to the private sector,
Transferring Tax        Congress established a multistep federal/state process, which is depicted
Credits From the        in figure 1.1 and described in the accompanying narrative.
Federal Government
to the Private Sector




                        Page 23                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                                   Chapter 1
                                                   Introduction




Figure 1.1: Transferring Tax Credits From the Federal Government to the Private Sector

                                                                                          Money (equity)


                                                                                                  Tax benefits         Investors
                                                                                                  (tax credits &     (Corporations)
                                                                          Syndicator              deductions)
                                                                     (General partner of an
                                                                    investment partnership)

                                                                                                  Tax benefits         Investors
                                                                                                  (tax credits &      (Individual)
                                                                                                  deductions)


                                                                    Money                Money (equity)
                                                                   (equity)
                                                                                    4 Tax  benefits
                                                                                      (tax credits &
                                                                                      deductions)
                                          Lender                                                                     State housing
                                                                                                                        agency
                             Loan                       Loan
                             payment

                                                                                                                                1 Tax benefits
                                                                                                                                  (tax credits)



                                                                  2 Housing project
                                                                    proposal submission
        Rent                                                                                                              IRS
                                                                  3 Tax benefits
                                                                    (tax credits)
                                       Developer
                                     (General partner
                                      of the project)

        Legend:
                  Money (equity financing/rent)
                  Tax benefits (tax credits/deductions)
                  Housing project proposal submission


                                                   Source: GAO’s discussions with IRS and state agency officials, syndicators, developers, and
                                                   investors.




                                                   (1) IRS Apportions Tax Credits to the Allocating Agencies: The
                                                   Internal Revenue Code directs IRS to provide the tax credit allocating
                                                   agencies with information each year for computing the tax credits




                                                   Page 24                                    GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
    Chapter 1
    Introduction




    available to them for allocation.1 In general, the allocation is limited to
    $1.25 per state resident, a portion of the unused tax credits returned to IRS
    by other states, unused credits from the prior year, and credits initially
    allocated in previous years and returned in the current year.2 The
    allocating agencies have up to 2 years to award the credits to housing
    projects; after that time, they must return any unused credits to IRS for
    reassignment to other states. When the credits have been awarded, they
    are usually available to the owners/investors annually for a 10-year period
    as long as the project meets the Code’s requirements.

    (2) Developers Apply to the Allocating Agencies for Tax Credits:
    To apply for tax credits, a developer must submit a detailed proposal to an
    allocating agency. The proposal must describe the housing project,
    indicate how much it will cost, and identify the sources and uses of the
    funds available to finance the project’s development and operations. In
    describing the project, the developer must identify the total number of
    units and the number of units expected to qualify for tax credits. To
    qualify for consideration, a project must

•   reserve either at least 20 percent of the available units for households
    earning up to 50 percent of the area’s median gross income adjusted for
    family size or at least 40 percent of the units for households earning up to
    60 percent of the area’s median gross income adjusted for family size,
•   restrict the rents (including the utility charges) for tenants in low-income
    units to 30 percent of an imputed income limitation based on the number
    of bedrooms in the unit,
•   meet habitability standards, and
•   operate under the program’s rent and income restrictions for 15 years for
    projects placed in service before 1990 and for up to 30 years for later
    projects.3

    1
     State and local housing agencies are specifically authorized by gubernatorial act or state statute to
    make housing credit allocations on behalf of the state or political subdivision and to carry out the
    low-income housing tax credit provision.
    2
     The annual state credit volume ceiling does not cover tax credits issued for low-income housing
    projects financed by at least 50 percent in tax-exempt multifamily housing bonds. These bonds are
    subject to annual state-by-state caps on the volume of private activity bonds.
    3
     In 1989, Congress amended the low-income housing tax credit provisions in response to concerns that
    tax credit properties, like properties developed under earlier federal housing programs, would be
    converted to market-rate housing at the first opportunity. One amendment extended the requirement
    for tax credit properties to serve low-income tenants from 15 years to 30 years. However, the
    amendment included a provision that left open the possibility of conversion to market rates after 15
    years. In the event of a property’s conversion, the new owner(s) could evict the low-income tenants
    after 3 years. In effect, the amendment guaranteed that tax credit units could remain in an allocating
    agency’s low-income housing inventory for 3 more years, up to 18 years. Nevertheless, the amendment
    also emphasized that more stringent requirements, whether included in the agreement between the
    developer and the allocating agency or imposed by state law, would override the federal law.


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Introduction




(3) Allocating Agencies Award Tax Credits to Selected Housing
Projects: The allocating agencies are responsible for (1) awarding their
tax credits to qualifying projects that meet their state’s qualified allocation
plans and (2) controlling the value of the tax credits awarded to projects.

To select developers’ proposals for tax credit awards, an allocating agency
is required to evaluate the proposed projects against a qualified allocation
plan developed in accordance with the Code’s requirements. The qualified
allocation plan must establish a procedure for ranking the projects on the
basis of how well they meet the state’s identified housing priorities and
meet selection criteria that are appropriate to local conditions. In addition,
the plan must give preference to projects that serve the lowest income
tenants and serve qualifying tenants for the longest period of time.

In awarding tax credits to a project, an allocating agency is to provide no
more credits than it deems necessary to ensure the project’s financial
feasibility throughout the 15 year tax credit compliance period. An
allocating agency must consider any proceeds or receipts expected to be
generated through tax benefits, the percentage of housing credit dollar
amounts used for projects costs other than the cost of intermediaries, and
the reasonableness of developmental and operational costs. In general, the
agency is to compare the proposed project’s development costs with the
non-tax credit financing, both private and governmental. The difference
between the development costs and the non-tax credit financing is the
financing gap. Tax credits are used, up to a ceiling, to attract the equity
investment needed to fill the gap.

The ceiling on tax credits limits the present value of the 10-year stream of
tax benefits to no more than (1) 70 percent of the qualified basis for new
construction or substantial rehabilitation or (2) 30 percent of the qualified
basis of acquired buildings that are substantially rehabilitated. To qualify
as “substantial rehabilitation,” the rehabilitation expenditures must equal
at least 10 percent of the building’s cost or at least $3,000 per low-income
unit, whichever is greater. For buildings placed in service in 1987, the
70-percent and 30-percent ceilings were equivalent to an annual tax credit
rate of 9 percent and 4 percent, respectively. Since 1987, Treasury has




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Chapter 1
Introduction




adjusted the annual credit rate monthly to maintain the present value of
the credit at 70 percent or 30 percent.4

In general, the qualified basis is the portion of a project’s total
costs—excluding the costs of land, obtaining permanent financing, rent
reserves, syndication, and marketing—that is allocable to low-income
units that meet the Code’s requirements for rent, tenants’ income, and
habitability. Costs can include the cost of the residential rental units and
facilities for use by the tenants or required for the project, such as parking
areas and trash disposal equipment.

Low-income housing tax credit projects that use federal subsidies
generally receive a smaller credit. If federally subsidized loans are used to
finance substantial rehabilitation or new construction, either the eligible
basis of the building must be reduced or the 30 percent credit must be
used. Federally subsidized loans include below-market federal loans and
tax-exempt financing. There are exceptions or certain kinds of federal
funds, including Community Development Block Grant (CDBG) funds and
certain projects receiving assistance under the HOME Investment
Partnership Act. Additionally, basis must be reduced by the amount of a
federal grant provided to a project during the 15 year compliance period.

The Code requires an allocating agency to conduct an evaluation of the
financial gap that considers the available private financing, plus all of the
federal, state, and local subsidies a developer plans to use. This evaluation
helps the agency determine the value of a project’s tax credit award.
Although the maximum tax credit award is generally about 9 percent of a
newly constructed or substantially rehabilitated project’s qualified basis,
the maximum award may be reduced to 4 percent when a project’s
financing combines federally subsidized loans with the tax credit.

(4) Tax Benefits Provide a Return on Equity Investments:
Syndicators (investment partnerships) are a primary source of equity
financing for tax credit projects. They recruit investors who are willing to
become partners (generally, limited partners) in housing projects that,
because of rent restrictions, are generally not expected to return rental
profits to investors.5 Rather, the investors expect, for 10 years, to receive

4
 The basis used in calculating the tax credit award may be increased by up to 30 percent for new
construction or substantial rehabilitation in a qualified Census tract or “difficult development area.” In
a qualified Census tract, 50 percent or more of the households have incomes of less than 60 percent of
the area’s median income. In a difficult development area, construction, land, and utility costs are high
relative to the area’s median income.
5
 Individuals and businesses may also invest directly in tax credit housing projects.



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                       Chapter 1
                       Introduction




                       tax credits and other tax benefits, such as business loss deductions, that
                       they can use to offset the taxes they owe on other income. These tax
                       benefits (plus the possibility of cash proceeds from the sale of the project)
                       represent the return on investment. The value of the tax benefits may vary
                       from year to year, since the value of the tax credit depends on the number
                       of habitable, rent-restricted units occupied by qualifying low-income
                       households.


                       To promote compliance with the tax credit program’s requirements, the
Overseeing             Internal Revenue Code establishes a joint federal/state oversight system.
Compliance With the    In summary, the states are the governmental entities responsible for
Tax Credit Program’s   determining whether housing projects qualify for tax credits, allocating
                       credits to qualifying projects, and overseeing the compliance by the
Requirements           selected projects with the program’s restrictions on rents and residents’
                       incomes and on standards for habitability. IRS is the governmental entity
                       responsible for ensuring that the states allocate no more tax credits than
                       they are authorized to allocate and that taxpayers claim no more tax
                       credits than they are entitled to claim. To facilitate the federal
                       government’s oversight, the states are required to report annually to IRS
                       their total tax credit allocation to proposed projects, the tax credit
                       awarded to each building in the project upon its being placed in service,
                       and any instances of noncompliance. Additionally, the private sector (both
                       investors and lenders) has an interest in overseeing the viability of the
                       housing projects and their continuing eligibility for tax credits.

                       This system, depicted in figure 1.2, is supplemented by the private sector’s
                       oversight.




                       Page 28                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                                     Chapter 1
                                                     Introduction




Figure 1.2: Tax Credit Oversight System


                                                                                  1
                                                                                                                     Investors               1
                                                                                                                   (Corporations)
                                                                         Syndicator
                                                                    (General partner of an
                                                                   investment partnership)

                                                                                                                      Investors              1
                                                                                                                     (Individual)

                                                                         3




                                       Lender                                                                       State housing
                                                                                                        2              agency
                                            3




                                                                                                                       1



     Rent                                                                                                                  IRS
                                                               1

                                    Developer
                                  (General partner
                                   of the project)

     Legend:


               Tax return reporting in support of IRS oversight
               Other oversight (state, syndicator, lender)


                                                     Source: GAO’s discussions with IRS and state agency officials, syndicators, developers, and
                                                     investors.




                                                     (1) IRS Is Responsible for Overseeing Compliance: IRS has the
                                                     authority to take actions—such as issuing regulations, requiring reporting,
                                                     and initiating audits—to ensure that the states and taxpayers use no more
                                                     tax credits than authorized. Under this authority, IRS requires annual
                                                     reports from the states on their total tax credit allocations to proposed




                                                     Page 29                                 GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 1
Introduction




projects and on their awards to individual projects when these projects are
placed in service. The purpose of these reports, together with tax returns,6
is to provide IRS with the data it needs to oversee participants’ compliance.
Project owners must certify annually that the project has continuously
complied with the threshold low-income targeting requirements.

(2) Allocating Agencies Are Responsible for Overseeing Projects’
Operations: The states are responsible for monitoring compliance with
restrictions on rents and tenants’ income as well as with standards of
habitability. The state is to notify IRS of any violations of these three
requirements. Such violations could result in the loss of all or a portion of
a project’s tax credits for the years of noncompliance and the recapture of
up to one-third of the tax credits claimed for prior years.7

(3) Investors and Lenders Have an Interest in Oversight: Investors
(usually led by a syndicator) and lenders may help IRS and states to
oversee tax credit housing projects. To ensure that investors receive their
full complement of tax credits over the designated period, investment
groups have an interest in monitoring compliance at housing projects.
Similarly, to ensure that loans are repaid, lenders have an interest in
overseeing the finances of the housing projects. Assessing the extent of
the private sector’s oversight was not part of this review.




6
 At tax year-end, with the filing of tax returns, building owner partnerships are to apportion income or
losses and tax credits among the partners (investors) relative to their shares of the investment. Both
the investors and IRS are to be notified of the amounts via a schedule attached to the partnership’s tax
return. This return is to be filed with IRS and copies are to be sent to the investors. Since there may be
multiple partnerships (e.g., an investment partnership investing in another investment partnership)
between the building owner partnership and the taxpayers (individual and corporate investors), the
apportionment process may be repeated a number of times. Investors (corporations or individuals),
after receiving the apportionment, are responsible for including those amounts in their tax returns.
But, because of the Internal Revenue Code’s passive-loss restriction rules, individuals are generally
limited to using tax credits and loss deductions from rental real estate activities to offset no more than
$25,000 of income from sources such as wages and business activities. For a taxpayer in the 28 percent
tax bracket, this is equivalent to a credit of about $7,000. Also, individuals and corporations are subject
to Alternative Minimum Tax rules and may not use the credit to reduce the Alternative Minimum Tax.
7
 The tax credits, although they can be claimed on tax returns over a 10-year period, are contingent on a
housing project’s complying for 15 years with the program’s standards for habitability and restrictions
on households’ incomes and units’ rents. In effect, the tax credits that would normally be earned on
the basis of a housing project’s performance during years 11 through 15 may be taken by taxpayers on
a prorated basis during the first 10 years of the housing project’s operations, i.e., one-third of the
credits available in years 1 to 10 relate to credits that may be earned in years 11 through 15. To deal
with instances of noncompliance, the Code provides not only for the loss of all credits for the tax year
of noncompliance but also for the recapture of the advance paid portion of the tax credits related to
the noncompliant units.



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                         Chapter 1
                         Introduction




                         The Chairman, House Committee on Ways and Means, asked us to study
Objectives, Scope,       the controls established by the states and IRS for implementing the tax
and Methodology          credit program’s requirements. Specifically, this report discusses the
                         characteristics of the residents of projects placed in service from 1992
                         through 1994 and the characteristics of these projects themselves. The
                         report also assesses the states’ and IRS’ controls for ensuring that

                     •   tax credits are allocated to proposed housing projects that meet the states’
                         identified priority housing needs, meet selection criteria that are
                         appropriate to local conditions, and serve the lowest income households
                         and serve qualifying households for the longest period of time;
                     •   project costs, including tax credit costs, are reasonable so that no more
                         tax credits are awarded than are necessary to ensure the financial viability
                         of the housing projects; and
                     •   states comply with program requirements and project owners comply with
                         the federal tax laws for both maintaining habitable rent- and
                         income-restricted buildings and correctly reporting tax credits on their
                         annual tax returns.

                         This report does not assess the efficiency of tax credits relative to other
                         types of housing assistance for low-income households, such as CDBG
                         loans, HOME Investment Partnership loans, Rural Housing Service (RHS)
                         mortgages, and Section 8 certificates and vouchers.8 Such a study would
                         have to account for several other factors including benefits and costs of
                         the alternatives, oversight, and budgetary outlays.

                         Given the decentralized administration of, and lack of centralized data, on
                         the tax credit program, our approach relied heavily on standardized data
                         collection. To develop descriptive information on the program’s
                         requirements, activities, and results, we worked with the National Council
                         of State Housing Agencies (NCSHA)9 and 54 tax credit allocating agencies,
                         which included 50 state agencies, the District of Columbia, 2 suballocating
                         agencies in New York state, and a suballocating agency in Chicago. We
                         also worked with the allocating agencies in the continental United States
                         to compile an inventory of housing projects that were placed in service
                         from 1992 through 1994. We selected this period because state monitoring
                         requirements did not go into effect until 1992, and 1994 was the latest year


                         8
                          These programs are discussed in chapter 2.
                         9
                          NCSHA is a national, nonprofit organization created in 1970 to assist state housing agencies in
                         advancing the interest of lower-income people through the financing, development, and preservation
                         of affordable housing. NCSHA’s members operate in every state and the District of Columbia, Puerto
                         Rico, and the U.S. Virgin Islands.



                         Page 31                                 GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 1
Introduction




that states had complete information on projects placed in service at the
time we requested information from them. For the continental United
States, the state reported data showed that about 4,200 tax credit projects
(containing about 175,600 tax credit supported units) were placed in
service from 1992 to 1994.

From the project universe data, we selected a stratified random sample of
423 projects containing nearly 50,000 units.10 The project universe was
broken into two strata (large and small projects). All large projects, which
consisted of projects with 300 or more tax credit units, were included in
the sample. The projects in the small strata were drawn with a probability
proportional to the number of units in the projects. The sample was
designed to produce statistically sound estimates of the characteristics of
projects placed in service nationwide during the 3-year period. The
samples from individual agencies are, however, too small to yield reliable
estimates of the characteristics of projects from any one state.

This data collection effort helped us determine how the agencies awarded
tax credits in calendar years 1992 through 1994, as well as obtain
descriptive information—not previously available—on the projects’ costs
and financing. More specifically, after accounting for misreporting by the
allocating agencies, which we identified during our review of 423 sampled
projects (see apps. I,II and III), we estimate that 4,121 projects containing
172,151 tax qualified units were placed in service in the continental United
States during the period 1992 through 1994. We also estimate that, for
these projects, the allocating agencies annually awarded tax credits with a
potential value over their 10-year lifetime of about $2 billion (about
$1.6 billion in present value terms), or about $6.1 billion for the three years
combined.11 These estimates constitute the universe of projects discussed
in this report.

We developed and mailed two questionnaires—one project questionnaire
and one state agency questionnaire—to state allocating agencies and one
project manager questionnaire to project managers. We followed up with
visits to selected agencies and housing projects and reviews of housing
project files maintained by the selected agencies. We developed
instruments to standardize the collection of data from these disparate
sources and, because much of the information was supplied by the

10
 We excluded Alaska and Hawaii projects from our sample since, because of cost considerations, we
would have been unable to visit these states to verify project data.
11
 The discount rate used was 6.7 percent, the average interest rate on U.S. Treasury Securities with a
10 year constant maturity for the period 1992 through 1994.



Page 32                                  GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                              Chapter 1
                              Introduction




                              allocating agencies or project managers, developed procedures to test the
                              reliability of the information.

                              To ensure that data collection was consistent, we pretested the
                              questionnaires with state housing agency officials in three states and
                              property managers in one state and the District of Columbia. In addition,
                              the questionnaires were reviewed by two panels of housing and tax
                              experts convened by NCSHA. Guided by the results of the pretest and expert
                              reviews, we revised the questionnaires to ensure that the questions were
                              fair, relevant, and understandable.

                              Appendix I contains a technical description of our sampling
                              methodologies and discusses the statistical precision of the estimates
                              derived from our samples.


Characteristics of Projects   To determine the characteristics of low-income housing tax credit
and Their Tenants             projects, we used data from the project-specific questionnaire dealing with
                              project size, type, location, development and tax credit costs, and non-tax
                              credit financing. During our visits to 44 state agencies, we verified selected
                              data for 407 of the 423 projects using documents available in the agencies’
                              project files. For the 10 agencies not visited, we requested backup
                              documentation to facilitate a desk review of the responses for the
                              remaining 16 projects.

                              To determine the characteristics of project tenants, we used data from the
                              project manager questionnaire, which contained information on tenants’
                              rents, income, and household size. We judgmentally selected, on the basis
                              of cost considerations, a subsample of 92 projects to visit to more fully
                              validate their conditions and operations. To verify our information on
                              tenant income, we selected a random sample of at least one tenant in each
                              of the sampled projects. We reviewed IRS tax return data on the tenants in
                              the sample to determine whether the current income of these tenants met
                              the program’s income restrictions.


Allocating Credits to Meet    To determine whether state agencies had established controls for
State Priority Housing        appropriately allocating credits to state needs, we used data from the state
Needs                         agency questionnaire that was designed, in part, to identify and evaluate
                              state allocating agencies’ policies, procedures, and controls for ensuring
                              that tax credit allocations satisfy the program’s requirements. We mailed
                              this questionnaire to 54 tax credit allocating agencies, and we made



                              Page 33                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                          Chapter 1
                          Introduction




                          follow-up visits to 44 agencies to review the responses. During these
                          reviews, we traced selected responses to source documents, such as state
                          regulations and policies. From the 10 agencies that we did not visit, we
                          requested key source documents to facilitate our review of each agency’s
                          operations. We received these documents from nine of the agencies; the
                          tenth agency responded to our request for data too late for us to verify the
                          information. In addition, we judgmentally selected and reviewed in detail
                          the qualified allocation plans for 1995 from 20 agencies. These agencies
                          allocate 65 percent of the program’s tax credits; however, the results of
                          our reviews of these plans cannot be generalized to all of the plans from
                          the 54 agencies. Finally, we examined the consolidated plans for a number
                          of states. The Department of Housing and Urban Development (HUD)
                          requires the states to develop these plans to identify and rank their
                          housing needs.


The Reasonableness of     To evaluate the controls state agencies used to determine the
Project Costs and Tax     reasonableness of project costs and tax credit awards, we analyzed the
Credits                   data the agencies reported on both the project-specific and state agency
                          questionnaires. From the project questionnaire, we analyzed data on
                          project costs, financing, and tax credit awards. We also reviewed the cost
                          certifications used by allocating agencies to validate the costs for a
                          subsample of 48 projects to determine the adequacy of these certifications.

                          From the state agency questionnaire, we analyzed data on agencies’
                          policies, procedures, and practices for evaluating project development
                          costs, project equity needs, and tax credit pricing determinations.


State and IRS Oversight   To evaluate state oversight activities, we analyzed data from both the
Activities                project and state agency questionnaires that related to the states’
                          monitoring policies, procedures, and practices. In collecting data from the
                          state agencies, we asked the agencies whether third-party audits had been
                          conducted on their operations. We also reviewed two audit reports, both
                          completed in 1996, on the operations of the tax credit program in Texas
                          and in New York State.

                          To evaluate IRS’ oversight activities, we examined IRS’ automated systems
                          to determine whether they are able to identify instances in which
                          (1) agencies overallocate their tax credits or (2) taxpayers claim credits
                          that they were not entitled to take. As part of this work, we documented
                          relevant IRS policies and procedures; discussed the implementation of



                          Page 34                       GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                    Chapter 1
                    Introduction




                    these procedures with IRS officials in Washington, D.C., and Philadelphia;
                    and observed implementation of the procedures at the Philadelphia
                    Service Center, which is IRS’ centralized processing center for tax credit
                    information reported by state agencies. Furthermore, we reviewed the
                    level of IRS’ audit effort and the audit results, as well as IRS’ use of the
                    information from the state agencies. We performed this work at the
                    Philadelphia District Office, where IRS examines tax credit returns. We also
                    ordered data from IRS on tax year 1995 tax returns for the 396 project
                    owners in our sample who were required to file partnership returns to
                    determine whether the partnerships correctly reported the tax credits they
                    were awarded. At the time we completed our field work, we had received
                    and reviewed tax return data for 253 partnerships.

                    We obtained written comments on this report from IRS and NCSHA and oral
                    comments from the Office of Management and Budget (OMB). We have
                    summarized the relevant portions of their comments at the end of each
                    chapter, if applicable, and reprinted the written comments, in entirety, in
                    appendices V and VI. We also made copies of the report available to the
                    Department of the Treasury and they had no comments on the report.

                    We performed our work between August 1995 and December 1996 in
                    accordance with generally accepted government auditing standards.


                    NCSHA had comments on our methodology in two respects: (1) the number
State Association   of large developments we included in our sample, and (2) the composition
Comments and Our    of the projects we included in appendix IV, “Results of Site Visits to GAO
Evaluation          Sample Properties.”

                    First, NCSHA said that our housing project sampling methodology was
                    arbitrary because the sample included all developments with 300 or more
                    apartments placed in service during the study period. We strongly
                    disagree. We followed generally accepted sampling procedures for
                    selecting a stratified random sample. Using this technique allowed us to
                    reduce the size and cost of the sample while maintaining an adequate level
                    of statistical precision for both project and housing unit estimates.

                    As discussed in this chapter, from the project universe data, we selected a
                    stratified random sample of 423 projects containing nearly 50,000 units.
                    The project universe was broken into two strata (large and small projects).
                    All large projects, which consisted of projects with 300 or more tax credit
                    units, were included in the sample. This eliminated sampling error for the



                    Page 35                       GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 1
Introduction




large projects. The projects in the small strata were drawn with a
probability proportional to the number of units in the projects. The sample
was designed to produce statistically sound, unbiased estimates of the
characteristics of projects placed in service nationwide during the 3-year
period.

We employed a stratified random sampling technique for a number of
reasons. We wanted to select as small a sample as feasible so as not to
burden the low-income housing industry, yet large enough to provide
statistically reliable estimates. With regard to the latter, we also wanted to
be sure to have data on the relatively small number of very large projects
that provide housing for a large number of people and account for a
significant portion of tax credit funding. The stratified random sample
approach enabled us to address both objectives. As more fully described
in appendix I, the estimates in the report were computed so as to adjust
for the oversampling of large projects. Each of our sample of 423 projects
was properly weighted to reflect its proportion in the population (small
projects were more heavily weighted than large ones).

Second, NCSHA was concerned that appendix IV, entitled “Results of Site
Visits to GAO Sample Properties,” includes a disproportionate number of
large projects. As explained in the Objectives, Scope and Methodology
section of this chapter, we judgmentally selected, on the basis of cost
considerations, a subsample of 92 projects to visit to more fully validate
their conditions and operations. Similar language has now been
incorporated into appendix IV. The 15 projects described in that appendix
were not intended to be representative of the population. They were
intended to illustrate some of the project variety in the program. We did
not include any very small projects because of the risk of revealing
information about individual tenants.




Page 36                        GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 2

Low-Income Housing Tax Credit Properties:
Their Residents, Characteristics, and Costs

               Given the results of our sample, we estimate that about 4,100 properties
               with approximately 172,000 tax credit qualified units were placed in
               service in the continental United states between 1992 and 1994.1 We also
               estimate that, for these projects, the states annually awarded tax credits
               with a potential value over their 10-year lifetime of about $2 billion (about
               $1.6 billion in present value terms), or about $6.1 billion for the three years
               combined.

               According to data we collected from property managers, the residents of
               these properties, the properties themselves, and the costs of developing
               the properties differed in many ways. A majority of the residents benefited
               not only from the federal tax credits but also from other federal housing
               assistance, such as rental assistance provided to residents and loan
               subsidies provided to property owners. Although tenant income data
               reported by property managers showed that virtually all of the households
               occupying tax credit units had low incomes, those who received rental
               assistance generally had much lower incomes than those who did not.
               Moreover, without this rental assistance, these households might not have
               been able to have afforded to live in their units. Households included
               families, single persons, elderly persons, and people with special needs.

               Household rents, which we estimated at about $453 a unit, were generally
               below the maximum rents allowed under the tax credit program. The
               properties are located throughout the United States in urban, suburban,
               and rural areas. Most of the buildings were newly constructed, although
               some had been rehabilitated. They included townhouses, garden
               apartments, and high-rise buildings with elevators. The estimated costs of
               developing the properties ranged from under $20,000 per unit to over
               $160,000 per unit, and the estimated potential cost of the tax credits
               awarded over the 10 year authorized period ranged from under $10,000 per
               unit to over $100,000 per unit in present value terms.




               1
                Consistent and complete data on the residents of tax credit properties, the properties themselves, and
               property development costs were not available nationally when we started our work. As discussed in
               chapter 1, we collected these data from the tax credit allocating agencies and tax credit property
               managers. The statistics presented in this chapter are estimates based on our random sample of 423
               projects placed in service between 1992 and 1994. The confidence intervals for estimates made from
               our sample are reported in appendix I.



               Page 37                                  GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                       Chapter 2
                       Low-Income Housing Tax Credit Properties:
                       Their Residents, Characteristics, and Costs




                       As noted in chapter 1, to participate in the tax credit program, an owner
Reported Incomes for   must reserve a specific proportion of the units in the property for lower
Most Tax Credit        income households. At a minimum, the owner must set aside either
Households Were Very   (1) 20 percent or more of the units for households with incomes at or
                       below 50 percent of the area’s median income or (2) 40 percent or more of
Low                    the units for households with incomes at or below 60 percent of the area’s
                       median income. All qualifying income standards are adjusted for family
                       size, generally on the same basis as under HUD section 8 program. About
                       88 percent of the owners of properties placed in service between 1992 and
                       1994 chose the latter option.

                       Our analysis of data provided by tax credit allocating agencies shows that
                       in practice, most owners rented virtually all of their units to qualifying
                       households. We estimate that about 95 percent of the units in projects
                       placed in service between 1992 and 1994 qualified for the credit.

                       On the basis of information provided by the managers of the tax credit
                       properties placed in service during 1992 through 1994, we estimate that the
                       1996 average annual income of households in units qualifying for tax
                       credits was about $13,300 and about 60 percent of the households had
                       incomes below $15,000. (See fig. 2.1.) The majority of these households
                       met HUD’s definition of “very low income”—that is, their incomes were
                       below 50 percent of their area’s median income. Specifically, we estimate
                       that about three-fourths of the qualifying households in these properties
                       had incomes in 1996 at or below 50 percent of their area’s median income.
                       (See fig. 2.2.)




                       Page 38                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                        Chapter 2
                                        Low-Income Housing Tax Credit Properties:
                                        Their Residents, Characteristics, and Costs




Figure 2.1: Estimated 1996 Incomes of
Households in Tax Credit Units
                                        Percent of households

                                        35


                                        30


                                        25


                                        20


                                        15


                                        10


                                         5


                                         0




                                                                                                                                           0
                                                     00




                                                                    99




                                                                                                      99
                                                                                     99




                                                                                                                       99




                                                                                                                                        ,00
                                                  5,0




                                                                 9,9




                                                                                                   9,9
                                                                                  4,9




                                                                                                                    4,9




                                                                                                                                      25
                                                n$




                                                               0-




                                                                                                 -1
                                                                                -1




                                                                                                                  -2




                                                                                                                                    n$
                                                            ,00




                                                                                               00
                                                                              00




                                                                                                                00
                                             tha




                                                                                                                                 tha
                                                                                            5,0
                                                                           0,0




                                                                                                             0,0
                                                          $5
                                          ss




                                                                                          $1
                                                                         $1




                                                                                                           $2




                                                                                                                              re
                                        Le




                                                                                                                            Mo


                                        Household current income in dollars

                                        Source: GAO’s analysis of data provided by tax credit project managers.




                                        Page 39                                           GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                        Chapter 2
                                        Low-Income Housing Tax Credit Properties:
                                        Their Residents, Characteristics, and Costs




Figure 2.2: Estimated 1996 Incomes of
Households in Tax Credit Units
Relative to Applicable Area Median      Percent of households
Income
                                        50




                                        40




                                        30




                                        20




                                        10




                                         0




                                                                                                                     %
                                                                         0%




                                                                                              0%
                                                        s
                                                      es




                                                                                                                   60
                                                                       -5




                                                                                            -6
                                                    dl




                                                                                                                er
                                                                     31




                                                                                          51
                                                  an




                                                                                                              Ov
                                                %
                                              30




                                               Percent of area median income

                                        Note: The small percentage of households whose incomes exceeded the tax credit program’s
                                        limit of 60 percent of area median income may not necessarily indicate noncompliance with the
                                        income limits because residents whose incomes increase while residing in tax credit units may
                                        remain in those units even if their incomes exceed the program’s limits.

                                        Source: GAO’s analysis of data provided by tax credit project managers.




                                        Our analysis of data provided by property managers shows that in 1996, an
                                        estimated 71 percent of the qualifying households in tax credit properties
                                        placed in service between 1992 and 1994 benefited directly or indirectly
                                        from one or more types of housing assistance besides tax credits. One type
                                        of housing assistance, direct rental assistance, enabled the tax credit
                                        program to serve many households whose reported incomes were well
                                        below the qualifying limits established by the program. Without such
                                        subsidies, these households might not have been able to afford these units.
                                        Overall, an estimated 39 percent of the tax credit households received
                                        direct rental assistance. These households would generally have paid a set



                                        Page 40                                GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                        Chapter 2
                                        Low-Income Housing Tax Credit Properties:
                                        Their Residents, Characteristics, and Costs




                                        percentage of their income for rent—typically, 30 percent—and the
                                        balance was subsidized. As table 2.1 shows, we estimate that the average
                                        reported income of households in properties with rental assistance was
                                        about half of the average income of households without rental assistance.
                                        (App. II provides additional information on the current income of
                                        households with and without additional rental assistance.)

Table 2.1: Estimated 1996 Incomes of
Households With and Without                                                                                         Average income as a
Additional Rental Assistance Residing                                       Percent of       Average current        percent of the area’s
in Tax Credit Properties Placed in      Type of Household                  households                income              median income
Service, 1992-94                        Received additional
                                        rental assistancea                            39                $7,858                          25
                                        Did not receive
                                        additional rental
                                        assistancea                                   61                16,709                          45
                                        All households                              100               $13,323                           37
                                        a
                                            Appendix II provides information on income by type of housing assistance provided.

                                        Source: GAO’s analysis of data provided by tax credit property managers.



                                        In addition to receiving rental assistance, many households benefited
                                        indirectly from government subsidized loans and grants provided to
                                        properties. Such assistance may have reduced owners’ operating expenses
                                        or debt service costs, thereby allowing owners to charge lower rents than
                                        would have been possible without this additional assistance. For example,
                                        we estimate that almost one-third of the tax credit properties placed in
                                        service between 1992 and 1994 were financed by RHS mortgages, which
                                        generally carry interest rates of 1 percent. Additionally, an estimated
                                        37 percent of the tax credit properties received subsidized loans or grants
                                        from numerous sources, including other federal programs, such as CDBG
                                        and HOME programs,2 and state and local governments. Although the
                                        credit may be reduced for projects financed with federal funds, this
                                        restriction does not apply to federal financial assistance received under
                                        the CDBG and the HOME programs for projects meeting certain
                                        requirements.




                                        2
                                         The CDBG and HOME programs provide federal block grants to states and localities and are typically
                                        used to provide below-market rate loans. CDBG may be used for housing and community development
                                        in low- and moderate-income communities, whereas HOME is limited to affordable housing projects.



                                        Page 41                                   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                      Chapter 2
                                      Low-Income Housing Tax Credit Properties:
                                      Their Residents, Characteristics, and Costs




                                      Data we obtained from tax credit property managers indicated that the tax
Tax Credit                            credit program primarily served small households. We estimate that about
Households Were                       67 percent of the households included one or two people and the average
Generally Small and                   household consisted of 2.2 persons. Figure 2.3 shows the distribution of
                                      households by size.
Projects Had Diverse
Resident Populations

Figure 2.3: Estimated Size of
Households in Tax Credit Properties
                                                                                                    2 persons
Placed in Service, 1992-94




                                                       24%



                                                                           43%                      1 person

                                                 17%



                                                        11%
                                                                 6%
                                                                                                    5 or more persons


                                                                                                    4 persons

                                                                                                    3 persons

                                      Note: Percentages do not total to 100 due to rounding

                                      Source: GAO’s analysis of 1996 data provided by tax credit property managers.




                                      Our analysis of 1996 data provided by property managers, in which we
                                      used an approximation of HUD’s section 8 subsidy standards,3 indicated
                                      that overcrowding was generally not a problem for the residents of tax

                                      3
                                       HUD’s section 8 guidance states that no more than two people should sleep in a bedroom or
                                      living/sleeping area. Using an approximation of this standard: one person for an efficiency unit, two
                                      persons for a one-bedroom unit, four persons for a two-bedroom unit, six persons for a three-bedroom
                                      unit, and eight persons for a four-bedroom unit, we estimate that 2 percent of qualifying households
                                      live in units exceeding this measure and that about half of these are in one-bedroom units.



                                      Page 42                                  GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                            Chapter 2
                            Low-Income Housing Tax Credit Properties:
                            Their Residents, Characteristics, and Costs




                            credit properties placed in service between 1992 and 1994. Given the
                            preponderance of one- and two-person households, this is not surprising.

                            On the basis of our sample, we estimate that about 26 percent of the
                            properties placed in service between 1992 and 1994 were primarily
                            intended to serve the elderly; and about 5 percent were intended to serve
                            people with special needs, such as those who were disabled or previously
                            homeless.4 The data on residents provided by tax credit property
                            managers also indicated the following:

                        •   approximately 64 percent of the households were headed by women;
                        •   about 44 percent of the households were headed by a person under the age
                            of 35, about 26 percent by a person between the ages of 35 and 54, and
                            about 29 percent by a person aged 55 or older; and
                        •   about 53 percent of the heads of households were white, 33 percent were
                            black, 11 percent were Hispanic, and 3.5 percent were of other races.


                            On the basis of our sample, we estimate that about 4,100 properties
Properties Were             developed under the tax credit program were placed in service between
Widespread, Units           1992 and 1994 in the continental United states. These data also indicate
Were Generally Small,       that about 95 percent of the units in the properties were awarded tax
                            credits because they met the program’s limits for income and rent.
and Rents Were              Appendix III provides further details on all properties placed in service
Restricted                  between 1992 and 1994, as well as additional information on those we
                            sampled.


Properties Were             From our sample, we estimate that approximately 53 percent of the
Widespread                  properties were in rural areas, 36 percent were in urban areas, and the
                            balance were in suburban areas. However, almost half of the units were in
                            urban areas, probably because urban properties often have more units.
                            (See fig. 2.4.)




                            4
                             We did not verify that the intended purposes of the properties, as reported by the tax credit allocating
                            agencies, were met.



                            Page 43                                   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                           Chapter 2
                                           Low-Income Housing Tax Credit Properties:
                                           Their Residents, Characteristics, and Costs




Figure 2.4: Location Estimates for Tax Credit Properties and Units Placed in Service, 1992-94

    Properties                                                             Units



                                                Rural                                                                           Rural

                                                Suburban                                                                        Suburban




                       10%
                                                                                         23%
            53%



                                  36%           Urban                                                        48%                Urban

                                                                                     28%




                                           Note 1: Percentages do not add to 100 due to rounding.

                                           Note 2: Location classifications were reported by tax credit property managers. We did not verify
                                           these classifications.

                                           Source: GAO’s analysis of data provided by tax credit property managers.




                                           As discussed in chapter 1, the tax credit program provides some financial
                                           incentives to encourage the development of housing for low-income
                                           people in certain geographic areas. Specifically, the program provides
                                           incentives for locating properties in areas designated by the Secretary of
                                           HUD as (1) difficult development areas—metropolitan areas and
                                           nonmetropolitan counties where the costs of construction, land, and
                                           utilities are high relative to incomes; and (2) qualified Census
                                           tracts—tracts where at least 50 percent of the households have incomes
                                           less than 60 percent of their area’s median gross income. A recent study
                                           conducted for HUD provides information that augments our property
                                           location data.5 According to the study, about 37 percent of both the

                                           5
                                            Development and Analysis of the National Low-Income Housing Tax Credit Database, Abt Associates,
                                           Inc. (July 1996).



                                           Page 44                                 GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                             Chapter 2
                             Low-Income Housing Tax Credit Properties:
                             Their Residents, Characteristics, and Costs




                             properties and the units placed in service between 1992 and 1994 are
                             located in difficult development areas and qualified Census tracts.


Property Styles Varied and   Our data indicate that the most common type of tax credit property placed
Small Units Were Common      in service between 1992 and 1994 was a walk-up/garden-style apartment
                             building. However, high-rise buildings, townhouses, and row houses were
                             also well represented. Although we estimate that the tax credit properties
                             averaged 43 units per property, about 4 percent of the properties were
                             single-family detached homes. Most of the buildings—an estimated
                             73 percent—were newly constructed; the rest were existing and
                             rehabilitated buildings.

                             Consistent with the large number of one- and two-person households
                             living in the tax credit properties placed in service between 1992 and 1994,
                             we estimate that 82 percent had two bedrooms or less. In addition, about
                             16 percent had three bedrooms, and about 1 percent had four or more
                             bedrooms.


Rents Were Generally         For units that are eligible for tax credits, rents are generally limited by the
Below Allowable              set-aside standard selected by the developer—that is, rents are usually
Maximums                     limited to 30 percent of either 50 or 60 percent of the area’s median
                             income, adjusted for unit size.

                             On the basis of our sample, we estimate that the average rents of tax credit
                             units placed in service between 1992 and 1994 ranged from $342 for an
                             efficiency apartment to $623 for a unit with four or more bedrooms in
                             1996. The average rent for units of all sizes was approximately $453. Our
                             analysis also showed that with some exceptions, the rents for tax credit
                             units were lower than the maximum allowable rents for these units. Gross
                             rents were between 13 and 23 percent lower than the maximum allowable
                             rents, depending on unit size.

                             Under the Internal Revenue Code, for households occupying tax credit
                             units only, the tenants’ rent payments are subject to the rent ceiling of the
                             tax credit program. However, for tax credit units with rental assistance,
                             the contract rent—which includes the household’s payment plus the rental
                             assistance—may exceed the maximum allowable tax credit rent. We
                             estimate that the contract rents for about 25 percent of the households
                             with rental assistance (about 10 percent of all tax credit households)
                             exceeded the tax credit rent limits that would have applied without this



                             Page 45                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 2
Low-Income Housing Tax Credit Properties:
Their Residents, Characteristics, and Costs




exception. For an estimated 7 percent of the households with rental
assistance (less than 3 percent of all tax credit households), the rents
exceeded the general limits by more than 20 percent.

Rental assistance may be project-based or tenant-based. Project-based
assistance is attached to designated property units whose owners receive
a subsidy when the units are rented to qualified low-income households. In
1996, for the tax credit properties placed in service between 1992 and
1994, many households with contract rents above maximum allowable tax
credit rents—and most households with contract rents substantially above
these rent ceilings—resided in properties with project-based assistance.6
For these properties, higher contract rents may have been included in the
initial evaluation of the project’s financial viability and allocation of tax
credits. For example, at a large tax credit property in Michigan with
section 8 project-based assistance, the contract rents for two-bedroom
units were $871. As permitted under the section 8 program, these rents
exceeded the tax credit program’s maximum allowable rent of $550.
According to the manager of this project, the project would not have been
viable at the tax credit ceiling rent. Thus, the guarantee of contract rents
above maximum allowable tax credit rents was essential to the initial
determination of this project’s financial viability.

By comparison, eligible households with tenant-based assistance may
choose their rental units and retain their rental assistance if they relocate.
Because of uncertainty over how many households with tenant-based
assistance would actually choose to live in a tax credit property and for
how long, we would not expect this assistance to have been considered in
the initial determination of a project’s financial viability or allocation of
tax credits. Although information provided by property managers shows
that fewer households with tenant-based assistance than with
property-based assistance had contract rents that exceeded the maximum
allowable tax credit rents, some of these households had contract rents
substantially higher than rents of comparable households without rental
assistance in the same property. In 1996, for example, households with
tenant-based assistance in a New York City property had contract rents
below the maximum allowable tax credit rents; however, their contract
rents for a two-bedroom unit, on average, exceeded rents of comparable
households without rental assistance by almost 30 percent—or about $130

6
 To identify whether rental assistance was project-based or tenant-based, we first removed those
properties with RHS 515 loan subsidies from our tax credit sample. We then contacted nearly all of the
property managers for those remaining properties where at least 50 percent of the residents received a
rental subsidy. If the project managers identified their properties as project-based, we designated them
as such. We defined the remaining subsidized units as tenant-based.



Page 46                                   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                           Chapter 2
                           Low-Income Housing Tax Credit Properties:
                           Their Residents, Characteristics, and Costs




                           a month. (See ch. 4 for further discussion of how rental assistance affects
                           the federal cost of the tax credit program.)


Most Owners Were Limited   Most—an estimated 82 percent—of the tax credit properties placed in
Partners                   service between 1992 and 1994 were owned by limited partners; about
                           12 percent were owned by individuals. The remainder were owned by
                           general partners and corporations. About 22 percent of the properties
                           were developed by either a nonprofit organization or a for-profit
                           subsidiary of a nonprofit organization.


                           When tax credit property owners use their tax credits, taxpayers subsidize
Tax Credit and             the development costs of tax credit properties. However, total federal cost
Development Costs          for tax credit properties includes the costs not only of the tax credits but
Varied Widely              also of other federal housing assistance provided to the majority of tax
                           credit properties. Tax credit costs, other federal assistance, and
                           development costs vary widely across tax credit properties. In chapter 4 of
                           this report we discuss government controls designed to contain the costs
                           of the tax credit program.


Tax Credit Costs Varied    For tax credit properties placed in service between 1992 and 1994, we
Widely                     estimate from our sample that the states had annually awarded tax credits
                           with a potential value over their 10-year lifetime of about $2 billion (about
                           $1.6 billion in present value terms). Thus, the taxpayers’ costs for the tax
                           credits attributable to these 3 years of placed in sevice projects could be
                           as high as $6.1 billion over the 10 year credit period. The federal cost of
                           the tax credits is a function of many factors, including property
                           development costs, the applicable tax credit rate, and the market price of
                           the tax credits. We estimated that the present value of the average tax
                           credit cost per unit over the 10-year period would be about $27,310.
                           However, as figure 2.5 shows, per-unit tax credit costs vary widely.
                           Although an estimated 60 percent of the units had tax credit costs at or
                           below the estimated average, we also estimate that 2 percent had tax
                           credit costs of $100,000 or more.




                           Page 47                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                         Chapter 2
                                         Low-Income Housing Tax Credit Properties:
                                         Their Residents, Characteristics, and Costs




Figure 2.5: Estimated Average Per-Unit
10 Year Tax Credit Costs of Properties
Placed in Service, 1992-94                   Percent of units
                                             30




                                             25




                                             20




                                             15




                                             10




                                                5




                                                0




                                                                                                                                      er
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                                                                                                   $5
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                                         Le




                                         Note: The present value of the annual tax credits over the 10 year award period was calculated
                                         using an annuity-due approach with a discount rate of 6.7 percent. The discount rate is equal to
                                         the 10 year constant maturity of taxable U.S. government securities for calendar years 1992
                                         through 1994.

                                         Source: GAO’s analysis of data provided by tax credit allocating agencies.




                                         The federal costs of providing affordable housing for residents of tax
                                         credit projects are not always limited to the tax credit costs presented in
                                         figure 2.5: they could also include funding from other federal programs,
                                         such as HUD’s section 8 rental assistance program; the Rural Housing
                                         Service’s section 515 loan subsidy and section 521 rental assistance
                                         programs; and other loans, loan subsidies, and grants, including CDBG. In
                                         addition, state and local governments provide various kinds of assistance
                                         to tax credit projects.




                                         Page 48                                       GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                         Chapter 2
                                         Low-Income Housing Tax Credit Properties:
                                         Their Residents, Characteristics, and Costs




Properties’ Physical                     Project development costs, including land acquisition outlays, building
Characteristics,                         acquisition and/or construction costs, builders’ overhead and profit, and
Community Development                    financing costs, varied widely across tax credit properties. We estimate
                                         that the average cost of developing the units placed in service between
Needs, and Controls Affect               1992 and 1994 was about $60,000.7 About two-thirds of these units cost less
Development Costs                        than or the same as the average unit. The per-unit costs of tax credit
                                         properties varied substantially. About 10 percent of the units cost less than
                                         $20,000, and about 10 percent cost more than $100,000—including about
                                         3 percent whose costs exceeded $160,000 per unit. (See fig. 2.6.)


Figure 2.6: Estimated Average Per-Unit
Development Costs of Tax Credit
Properties Placed in Service, 1992-94        Percent of units

                                             40




                                             30




                                             20




                                             10




                                              0                 0
                                                                0



                                                               99



                                                               99



                                                               99




                                                               99



                                                               00
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                                                              99




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                                                         60
                                                         20



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                                                        13



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                                           $8


                                         $1



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                                         $1




                                         Note: Unit costs above $160,000 generally ranged from about $165,000 to $259,000.

                                         Source: GAO’s analysis of data provided by tax credit allocating agencies.




                                         7
                                          Development costs for about 10 percent of the properties include no costs for land because some
                                         allocating agencies either reported zero land costs or left this item blank. The average per-unit cost of
                                         properties with land costs was about $59,700 compared with about $58,200 for properties with no land
                                         costs.



                                         Page 49                                   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 2
Low-Income Housing Tax Credit Properties:
Their Residents, Characteristics, and Costs




Development costs may vary because of differences in the physical
characteristics of properties, the need to meet broader community
development needs, and the extent to which tax credit allocating agencies
use various controls to limit costs.

Differences in the physical characteristics of properties—including the
costs of acquiring land and existing buildings, the types of buildings
constructed, the geographic location, the size of the units, the amenities
provided, the construction standards used, and the environmental issues
encountered—can account for some of the variation in development costs.
We estimate, for example, that the average per-unit cost for newly
constructed buildings was about $68,000, and the average cost for
substantially rehabilitated buildings was approximately $48,000. Figure 2.7
illustrates the variations in cost associated with the type of construction,
the location of the building, and the type of building.




Page 50                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                                           Chapter 2
                                                           Low-Income Housing Tax Credit Properties:
                                                           Their Residents, Characteristics, and Costs




Figure 2.7: Estimated Average Per-Unit Costs of Properties Placed in Service, 1992-94, by Type of Construction, Location,
and Building

Dollars in thousands

120



100



 80



 60



 40



 20



  0
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                   Construction type                              Locations                                         Building type

                                                           Source: GAO’s analysis of data provided by tax credit allocating agencies.




                                                           Other physical characteristics—such as unusually high local construction
                                                           costs, local seismic standards, or requirements for amenities to serve
                                                           residents with special needs—may account for the higher development
                                                           costs of some properties.

                                                           Development costs also vary because some tax credit properties are used
                                                           to meet broader community development goals. For example, as discussed
                                                           earlier, the basis for calculating tax credits may be increased for Census
                                                           tracts where incomes dip below those of the wider area or communities




                                                           Page 51                                           GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                    Chapter 2
                    Low-Income Housing Tax Credit Properties:
                    Their Residents, Characteristics, and Costs




                    where development costs are high relative to incomes. Furthermore, tax
                    credit projects may provide increased security or recreation for the
                    surrounding community. In chapter 3 we discuss in more detail how
                    physical and community development needs relate to the value of tax
                    credits awarded.

                    Variations in allocating agencies’ controls designed to limit development
                    costs may also account for some of the variation in these costs. In chapter
                    4, we discuss allocating agencies’ current efforts to control development
                    costs in more detail and identify opportunities for strengthening these
                    controls.


                    Tax credit allocating agencies target and serve very low-income
Observations        households by combining tax credits with other housing subsidies. Tax
                    credit allocation amounts, which varied widely across the projects placed
                    in service between 1992 and 1994, reflected differences in projects’
                    development costs. Tax credit allocation amounts are also affected by
                    tenant income levels through the rents tenants can afford to pay. Tax
                    credit allocating agencies’ controls over housing needs determinations and
                    housing costs determines credit allocation amounts. These controls will be
                    discussed in the following chapters.


                    In commenting on this report, NCSHA noted that although it had previously
State Association   expressed concerns about potential bias and prejudgment in some aspects
Comments and Our    of our work, the report answered many of those concerns.
Evaluation
                    First, NCSHA said that the report “vindicates public predictions by GAO
                    officials that nothing in the report could justify Housing Credit repeal.” In
                    response, we want to emphasize that GAO has never taken a position on
                    whether the tax credit should be retained or repealed. Moreover, as clearly
                    stated in the Objectives, Scope, and Methodology section of this report,
                    our work was directed toward studying the controls established by the
                    states and IRS for implementing the tax credit requirements. Making
                    judgments as to the merits of the program relative to other low-income
                    housing options was never intended to be, and was not, a part of our work.

                    Next, NCSHA indicated that the report also addresses some of its concern
                    about potential bias and prejudgment on our part because the report
                    documents how the tax credit is “exceeding” its objectives and cited as
                    evidence a number of income, rent, and cost estimates in the report. For



                    Page 52                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 2
Low-Income Housing Tax Credit Properties:
Their Residents, Characteristics, and Costs




example, NCSHA pointed out that although the law allows renters in tax
credit projects to have incomes up to 60 percent of area median income,
our report states that more than three out of four had incomes under
50 percent. Contrary to NCSHA’s interpretation, we did not take a position
as to whether or not the tax credit is exceeding its objectives. Further, we
note that some of the examples cited by NCSHA are clearly attributed in our
report to the use of other government subsidies (loan, grant, and rental
assistance subsidies discussed in this chapter) in conjunction with tax
credits.

Other NCSHA comments regarding its concerns about potential bias and
prejudgment in certain aspects of our work and our responses to those
concerns are presented at the end of chapters 1, 4 and 5.




Page 53                             GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Chapter 3

States’ Controls for Allocating Credits to
Housing Needs Vary

                         The Internal Revenue Code establishes broad requirements for allocating
                         tax credits to proposed housing projects, giving the housing credit
                         allocating agencies wide latitude in implementation. Under the Code, the
                         agencies must develop qualified allocation plans that target their tax
                         credits to proposed projects that meet their housing priorities and contain
                         selection criteria that are appropriate to local conditions. The agencies
                         must also give preference to proposed projects that serve the lowest
                         income tenants and that serve qualified tenants for the longest periods.1

                         Through the allocation process, the agencies have defined and applied the
                         tax credit program’s requirements in various ways. Some have called for
                         more data and analysis than others, particularly in assessing their housing
                         needs, and some have implemented more stringent controls for allocating
                         tax credits than others. For example, all of the agencies have used Census
                         data to identify and rank their housing needs, and some have taken steps
                         to overcome limitations in these data. Similarly, all of the agencies have
                         established controls for allocating tax credits. The 20 allocation plans that
                         we reviewed weighted the selection criteria by using thresholds,
                         set-asides, points, and rankings. Despite the differences among the plans
                         we reviewed, all of them provided for targeting tax credits to proposed
                         projects as required.

                         Several factors could affect the actual housing delivered over time. First,
                         nearly all of the plans we reviewed afford the agencies some discretion for
                         bypassing the results of the process. Second, the tax credits allocated to
                         proposed projects exceeded the tax credits awarded to projects when
                         placed in service, and we were unable to account for this difference.
                         Finally, the long term economic viability of low-income housing projects
                         subject to extended use agreements has not been tested.


                         Section 42 of the Internal Revenue Code requires the housing credit
Internal Revenue         allocating agencies to develop qualified allocation plans to target their tax
Code Gives Agencies      credits to proposed housing projects that meet their “housing priorities”
Wide Latitude in         and that include selection criteria that are “appropriate to local
                         conditions.” In addition, the Code requires the agencies to “give
Allocating Tax Credits   preference” to projects “serving the lowest-income tenants” and projects
                         “obligated to serve qualified tenants for the longest periods.” Because the
                         Code does not define these terms or set forth procedures for implementing


                         1
                          The qualified allocation plan must be approved by the governmental unit of which the agency is a part
                         after a public hearing. The agency must notify the chief executive officer of the jurisdiction in which
                         the project is located and give the official opportunity to comment.



                         Page 54                                  GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                            Chapter 3
                            States’ Controls for Allocating Credits to
                            Housing Needs Vary




                            the program’s requirements, it gives the allocating agencies the flexibility
                            to respond to their particular needs.

                            Besides establishing these broad requirements, the Code specifically
                            directs the agencies to include seven “selection criteria” in their allocation
                            plans. The Code does not define these criteria or provide any guidance for
                            their use. Generally, however, they serve as indicators of housing needs
                            and the ability of proposals or developers to satisfy those needs.

                            In responding to our survey, all 54 allocating agencies reported having
                            developed qualified allocation plans. We reviewed the controls
                            incorporated into the plans but did not test whether housing delivered by
                            the plans satisfied state housing priorities or the other program
                            requirements.

                            Under the low-income housing tax credit program, it is up to the states to
                            identify best practices, consider the costs and benefits of alternative
                            approaches, and select the approaches best suited to their conditions.
                            NCSHA has established a commission to examine ways to improve various
                            aspects of the credit program, including how allocation plans allocate
                            credits to housing needs.

                            The information presented in this chapter is derived primarily from our
                            survey of the 54 allocating agencies and from our review of 20 agencies’
                            qualified allocation plans. Although our sample of 20 agency plans was not
                            random and cannot be projected to all plans, the 20 plans cover about
                            65 percent of the credits awarded annually.


                            Before developing their qualified allocation plans, the allocating agencies
Agencies Have               must define their housing priorities and the terms “appropriate to local
Defined the Program’s       conditions,” “lowest-income”, and “longest periods.” Our review showed
Requirements in             the agencies have defined these program requirements in different ways
                            and, when evaluating the requirements, have used varying amounts of
Different Ways              information and analysis.


Agencies Primarily Relied   Although the Internal Revenue Code does not specify how the allocating
on Consolidated Plans to    agencies are to identify their housing priorities, HUD has, since 1994,
Define Their Housing        required the states to develop consolidated plans to identify and rank their
                            housing needs for several federal programs, including CDBG and the HOME
Priorities                  Investment Partnership programs. In addition, HUD requires the states, in



                            Page 55                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                             Chapter 3
                             States’ Controls for Allocating Credits to
                             Housing Needs Vary




                             their consolidated plans, to develop a strategy for coordinating their
                             housing resources—including their tax credits—to meet their identified
                             housing needs.2

                             Of the 54 allocating agencies we surveyed, all but 1 said that their
                             jurisdictions had developed a consolidated plan and used it to identify the
                             jurisdictions’ housing needs. About two-thirds of the agencies reported
                             relying primarily on this plan to identify their housing needs for the tax
                             credit program. Most of the remaining agencies said they had identified
                             their housing needs using advisory committees, the knowledge of their
                             staff, and/or historical data that complemented or later fed into their
                             consolidated plans.

                             In responding to our survey, the allocating agencies identified their
                             housing needs in terms of problems to be solved and populations to be
                             served. The most frequently cited problems were excessive rent burdens
                             (89 percent), followed by substandard housing (72 percent), a lack of
                             housing (59 percent), deteriorated neighborhoods (52 percent), and
                             excessive concentrations of very low-income housing (30 percent).
                             Translated into solutions, these include needs for less expensive housing,
                             the rehabilitation and maintenance or replacement of existing housing,
                             additional housing, community revitalization, and mixed-income
                             development. The majority of the agencies (78 percent) also expressed a
                             strong need for subsidized housing in rural areas. The populations most
                             frequently identified as needing housing were the elderly (70 percent);
                             large families (67 percent); and persons with special needs, including
                             those who are handicapped, disabled, or homeless or have AIDS
                             (63 percent).

States Used Census Data to   To develop their consolidated plans, the states rely primarily on special
Develop Their Consolidated   tabulations of demographic and housing data from the 1990 Census that
Plans                        HUD developed in collaboration with the Bureau of the Census. For each
                             state, HUD printed a limited set of key indicators of housing supply and
                             demand for all counties and for major cities. Key indicators of supply
                             include the number of rental units by price and size; the vacancy rate; and,
                             to a limited extent, the physical condition of the housing.3 Key indicators

                             2
                              The consolidated plan required by HUD differs from the qualified allocation plan required under the
                             Internal Revenue Code. Whereas the consolidated plan identifies and ranks housing needs, the
                             allocation plan targets tax credits to proposed projects that best satisfy identified housing priorities.
                             The Code does not require the allocating agencies to use the consolidated plan to identify their
                             housing priorities for the qualified allocation plan.
                             3
                              Measures of physical condition include (1) the number of units lacking complete kitchens and
                             plumbing, heating, electricity, and maintenance; (2) the age of the housing; (3) the source of the
                             housing’s water supply; and (4) information on whether the units are boarded up or abandoned.



                             Page 56                                    GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                               Chapter 3
                               States’ Controls for Allocating Credits to
                               Housing Needs Vary




                               of demand include the number of renter households, as well as their size,
                               type, income level, and racial composition. In addition, more extensive
                               tabulations of Census data are available to the states if they wish to
                               conduct more detailed analyses. These tabulations enable the states to
                               analyze certain indicators of their housing needs in areas as small as a
                               neighborhood block.

                               To identify their housing needs, the states can compare their indicators of
                               supply and demand with standards for adequate housing developed by
                               HUD. According to these standards, for example, households should pay no
                               more than 30 percent of their income for rent, units should have one room
                               per person, and apartments should include complete kitchens and
                               plumbing facilities. Comparisons of a state’s indicators with HUD’s
                               standards may show that certain groups in the state have excessive rent
                               burdens, are living in overcrowded conditions, or are living in substandard
                               housing. The states can use their Census data to assess these problems
                               globally or by region, county, city, or even, to a more limited extent,
                               neighborhood.

Census Data Have Limitations   Although the Census is a consistent, national source of demographic and
                               housing data, its information on the physical condition of properties is
                               limited. Furthermore, its statistics may be outdated because it is
                               performed only once every 10 years, and the data are collected well before
                               they are published. To measure the physical condition of their rental
                               housing, many of the states whose consolidated plans we reviewed relied
                               primarily on indicators of age and the existence of kitchen and plumbing
                               facilities. This approach provides little information on whether properties
                               are, in fact, habitable or on whether their internal condition conforms to
                               their external condition. To update the 1990 Census data, the states
                               generally used historical trends to project current conditions. This
                               approach, while reasonable, may not be accurate when major changes
                               have taken place in a state’s housing markets.

Some States Supplemented,      To obtain more detailed or more current information, some of the states
Updated, or Further Analyzed   whose consolidated plans we reviewed supplemented or updated their
Census Data                    Census data. California inventoried its rental properties, Texas surveyed
                               interest groups and residents, and Maryland convened regional advisory
                               groups. New York City asked the Census to perform a special survey to
                               update its data, and Florida hired a contractor to obtain current data.
                               Although efforts such as these cost more than using existing indicators,
                               they can generate a richer database for identifying housing needs and
                               developing strategies to meet those needs. Delaware, for example,



                               Page 57                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                           Chapter 3
                           States’ Controls for Allocating Credits to
                           Housing Needs Vary




                           identified almost 1,400 additional units in substandard condition through a
                           field survey that it commissioned to supplement its Census data.
                           Furthermore, through a review of county code enforcement records, it
                           determined that in one county, where fewer building code violations were
                           recorded, the violations were more serious and more expensive to correct
                           than in other counties. According to the state, such a distinction could not
                           have been made using the Census data alone.

                           Despite their limitations, the Census data can be used to analyze the
                           causes of problems such as high rent burdens and overcrowding. To
                           varying degrees, the states have used their tabulations of Census data to
                           analyze the availability, adequacy, affordability, and accessibility of rental
                           housing. For example, although most states assessed availability by
                           comparing the rate of growth in rental units with the rate of growth in the
                           tenant population, Texas, Vermont, and Ohio performed further analyses
                           to determine whether they had enough affordable units for tenants at
                           different income levels. These additional analyses revealed shortages that
                           the states had not previously detected and might not otherwise have
                           sought to address.


Agencies Used Market       As discussed in the preceding paragraphs, the states have taken various
Studies to Define          steps to obtain the data required to identify and rank their housing needs
Appropriateness to Local   in their consolidated plans. These steps, while sufficient to establish
                           housing priorities for a state as a whole, a region, or even a locality, may
Conditions                 not be adequate to determine whether a particular property will be viable
                           in a particular location. Accordingly, the Internal Revenue Code requires
                           the allocating agencies to determine the appropriateness of a proposed
                           project to local conditions. As noted, the Code does not define the term
                           “appropriate to local conditions,” and it does not establish a procedure for
                           determining appropriateness.

                           In responding to our survey, all of the allocating agencies reported using
                           some procedure(s) to determine appropriateness to local conditions. Most
                           said that they reviewed their consolidated plans, community plans, or
                           neighborhood plans, and most reported taking steps to ensure consistency
                           with local zoning regulations. Some reported requiring, or giving
                           preference to proposals with, letters of support from local officials or local
                           funding commitments. And the vast majority reported requiring market
                           studies or property appraisals, both of which review a market area and
                           assess comparable properties within that area.




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    Both HUD4 and the real estate industry have established general criteria for
    market studies—namely, that they should be comprehensive, independent,
    and timely. A comprehensive study identifies the demographic
    characteristics of the market area, potential tenants, and comparable
    properties, as well as the probable impact of the proposed property on
    rents and vacancy rates in the market area. An independent study is
    performed by a neutral or third party. It is also more likely to be objective
    if it is commissioned by an allocating agency rather than a developer. A
    timely study is both up to date and complete before a project’s application
    for tax credits is reviewed. The costs of market studies vary with their
    complexity.

    Forty-one of the 54 allocating agencies reported relying to some degree on
    market studies. Our review of the qualified allocation plans for 20 agencies
    indicated, however, that these agencies’ requirements for market studies
    varied considerably.5 Whereas some agencies set forth extensive, specific
    criteria, others established very general requirements:

•   Florida’s agency requires that a market study identify and evaluate the
    (1) best comparable and competitive existing and proposed properties;
    (2) project’s dynamics, including rents, designs, and amenities; (3) historic,
    current, and forecasted absorption rates; (4) occupancy and vacancy
    levels in the market; and (5) population growth trends and other
    demographic data.
•   Texas requires an analysis of many of the same factors, as well as an
    overall opinion by the analyst on the adequacy, feasibility, and
    reasonableness of the project’s costs, absorption rates, rent levels, and
    reserves.
•   Nevada’s agency requires “a description of the project substantiating
    community need” and a market or feasibility study that is “acceptable” to
    the state.
•   Virginia does not require a market study but will consider one if it is
    submitted with the application.

    The following cases illustrate the importance of obtaining comprehensive
    information about a market area before investing in a project’s
    development:


    4
     HUD requires independent market studies for all multifamily projects applying for mortgage insurance
    through the Federal Housing Administration.
    5
     We did not attempt to assess whether the agencies’ requirements satisfied HUD’s and the industry’s
    criteria for comprehensiveness, independence, and timeliness. Neither did we try to determine
    whether the studies accepted by the agencies satisfied the agencies’ own requirements for the studies.



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                        •   A market study for a large suburban project analyzed the area’s existing
                            and anticipated rental housing market, demographics, economy, and
                            demand for housing. The study (1) reviewed vacancy rates, (2) analyzed
                            the perceived value of the proposed rent levels within the market and
                            estimated absorption rates with and without tenants using section 8
                            vouchers, and (3) compared proposed rents with existing market-driven
                            rents. The project’s rental agent said the developer was very pleased with
                            the study, which accurately predicted that the property’s units would be
                            rented within 10 months.
                        •   Another market study concluded that the elderly population in a rural area
                            was large enough to support a three-story project for elderly tenants.
                            However, the study did not reveal that many of the elderly were ineligible
                            for the project because their disability benefits raised their incomes above
                            the program’s limits. Furthermore, the study did not determine the housing
                            preferences of the potential tenants. The project has not leased its units as
                            rapidly as scheduled. According to the rental agent, many of the elderly
                            consider an “elevator building” with internal units too confining or “above
                            their station in life.” The developer said that if he had obtained this
                            information before constructing the project, he would have built fewer
                            units in a more open design.

                            The allocating agencies’ requirements for independence and timeliness
                            also varied considerably. New Hampshire, which determines the need for
                            a market study on a case-by-case basis, requires three bids from
                            independent third parties. Although the developer pays for the study, the
                            allocating agency commissions it, thereby controlling the study process.
                            Several other states require that the study be performed by an independent
                            third party according to the state’s guidelines. Some agencies had no
                            requirements for independence. The agencies with a requirement for
                            timeliness generally specified that the market study be no older than 6
                            months (Texas) or 1 year (California and Ohio) when it is submitted with a
                            project’s application for tax credits. Most of the agencies required that the
                            study be submitted with the application.


Agencies Have Defined       Using the discretion allowed in the Internal Revenue Code, agencies
Lowest Income and           differed in defining the terms “lowest income” and “longest periods.” All of
Longest Periods             the 54 allocating agencies reported giving preference to proposed projects
                            serving the lowest income tenants, and 49 of the agencies reported giving
                            preference to proposed projects with agreements to serve qualified
                            tenants for longer periods of time than the federal law requires. Such
                            agreements are commonly referred to as extended use agreements.



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Lowest Income                 The Internal Revenue Code limits tax credit assistance to housing for
                              households with incomes of up to 60 percent of the local area’s median
                              income. Within this limit, the allocating agencies’ definitions of lowest
                              income vary slightly, in part because different agencies rely on the tax
                              credit program to serve different income levels. As noted at the beginning
                              of this chapter, HUD requires the states, in their consolidated plans, to
                              develop strategies for coordinating their available housing resources.
                              Compared with some other housing resources, tax credits can be used to
                              subsidize housing for households with higher incomes. Section 8 subsidies
                              and public housing, for example, must serve a majority of households with
                              incomes at or below 50 percent of the local area’s median income.

                              In reviewing several states’ consolidated plans, we found that different
                              states assigned different roles to the tax credit program. Whereas Texas
                              planned to use its tax credits for households with incomes between 31 and
                              50 percent of their area’s median income, North Carolina targeted its
                              allocation to renters with incomes between 51 and 60 percent of their
                              area’s median income. North Carolina’s consolidated plan specified that
                              renters with incomes between 0 and 50 percent of their area’s median
                              income would not be served through the tax credit program. Florida listed
                              tax credits among the many resources available to the state without
                              specifying what income levels the tax credit program would serve.

                              Our review of the qualified allocation plans for 20 agencies indicated that
                              some of these agencies capped their definition of the lowest income at
                              50 percent of the local area’s median income.

Longest Periods or Extended   As discussed in chapter 1, the Tax Reform Act of 1986 initially required tax
Use                           credit housing to serve low-income households for 15 years. Amendments
                              in 1989 extended that requirement from 15 to 30 years but included a
                              contingency clause that could, in some instances, permit a sale that would
                              result in a property’s conversion to market-rate housing after 15 years. If
                              such a conversion took place, the current low-income tenants would be
                              protected for up to 3 more years.

                              Our review of the qualified allocation plans for 20 agencies indicated that
                              most of the plans gave preference to proposals that (1) commit beyond 30
                              years and/or (2) waive the option of seeking to convert to market rates
                              until some point beyond the fifteenth year.




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                         Defining the tax credit program’s broad requirements, including “housing
Allocation Plans         priorities,” “appropriate to local conditions,” “lowest income,” and “longest
Weight Selection         periods,” is one step in developing the required qualified allocation plan.
Criteria                 Another step in developing a plan is to specify and weight selection
                         criteria that will target tax credit awards in accord with the program’s
                         broad requirements. The Internal Revenue Code lists seven selection
                         criteria that must be included in a qualified allocation plan and allows
                         agencies to use additional criteria. The 20 plans we reviewed weighted the
                         selection criteria by employing thresholds, set-asides, point systems, and
                         rankings.


Selection Criteria       The seven selection criteria listed in the Internal Revenue Code are

                     •   project location,
                     •   housing needs characteristics,
                     •   project characteristics,
                     •   sponsor characteristics,
                     •   participation of local tax-exempt organizations,
                     •   tenant populations with special housing needs, and
                     •   public housing waiting lists.

                         Consistent with the flexibility afforded in the Code, the allocating agencies
                         have defined the selection criteria differently. For example, in the 20
                         allocation plans we reviewed, one criterion—housing needs—stood not
                         only for different types of construction (e.g., new construction, substantial
                         rehabilitation) and different sizes of units (e.g., single room, three or more
                         bedrooms) but also for different types of tenants (e.g., elderly, large
                         families, people with special needs) and several other types of needs.

                         Most of the 20 plans that we reviewed included other criteria, such as
                         indicators of cost efficiency (e.g., low per-unit costs, low developers’
                         costs, low state costs, low per-unit requirements for tax credits, and
                         efficiency in leveraging funds from other sources);6 readiness to proceed
                         with development; and evidence of financial commitments. Many of the
                         plans also treated indicators of appropriateness to local conditions, such
                         as market studies or letters of support from local officials, as selection
                         criteria Finally, many of the plans treated as selection criteria the tax
                         credit program’s requirements for giving preference to proposed projects



                         6
                          As discussed in chapter 4, including some of these indicators of cost efficiency in the allocation plans
                         seems to have helped to control costs in some states.



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                            serving the lowest income tenants and serving qualified tenants for the
                            longest periods.


Weighting of Selection      The 20 allocation plans that we reviewed weighted the selection criteria by
Criteria                    using thresholds, set-asides, points, and rankings. Competition among
                            developers for tax credits encourages developers to propose projects that
                            satisfy more of the selection criteria.

                            The weighting systems had different advantages. Generally, compared to
                            points and rankings, thresholds and set-asides afforded more certainty,
                            while points and rankings provided more flexibility. A threshold virtually
                            ensures that a particular requirement will be met—if a proposal satisfying
                            the threshold is submitted—because a proposal is not to be considered
                            unless it satisfies the requirement. A set-aside, while not as broad in scope
                            as a threshold, nevertheless reserves a portion of an agency’s allocation
                            for projects satisfying a particular requirement. New Jersey, for example,
                            set aside 10 percent of its allocation for projects serving tenants with
                            special needs. Point and ranking systems may allow more flexibility for
                            making trade-offs among multiple selection criteria. The extent to which a
                            scoring or ranking system targets tax credits to projects satisfying a
                            particular requirement depends on the relative weight assigned to the
                            requirement and the level of competition for tax credits.


                            To gain more insight into the allocating agencies’ approaches for
Allocation Plans            weighting selection criteria in their allocation plans, we focused on the
Provided for Targeting      means used to give preference to proposed projects serving the lowest
Tax Credits                 income tenants and serving qualified tenants for the longest periods. Our
                            review found that the allocation plans’ controls provided for selecting
                            proposals designed to satisfy the requirements of the tax credit program
                            requirements. However, we also found that the qualified allocation plans
                            can be bypassed and tax credits awarded on some other bases. This
                            section discusses the selection procedures in the qualified allocation
                            plans. Later we discuss how and when the plans can be bypassed.


Plans Provided for Giving   In responding to our survey, all of the 54 allocating agencies reported
Preference to Lowest        giving preference to proposed projects serving the lowest income tenants.
Income                      Eleven of the agencies reported making this requirement a threshold, and
                            most said that they awarded a higher score or bonus points to proposals
                            satisfying the requirement. Most of the 20 qualified allocation plans that



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    we reviewed treated the requirement as a selection criterion. Two plans
    established income thresholds, and most used points or rankings to
    measure proposals’ commitments to the lowest income tenants.
    California’s plan, for example, set thresholds for income levels for
    different types of projects; thus, projects for large families could not be
    considered for tax credit awards unless they served families with incomes
    at or below 45 percent of the local area’s median income. Among the plans
    that awarded points, the number often increased as the targeted income
    levels decreased. For example:

•   Michigan’s plan increased the number of points—up to 140 out of
    347—with the number of units set aside for households at 50 percent,
    40 percent, 30 percent, and 20 percent of the area’s median income.
•   Florida’s plan awarded up to 90 out of 945 points for projects serving
    low-income households, increasing the number of points with the
    percentage of units targeting lower income levels from 60 percent down to
    35 percent of the area’s median income.
•   Rhode Island’s plan awarded 5 out of 225 points for projects in which at
    least half of the units were reserved for households with incomes below
    45 percent of the area’s median income.

    In comparison, New Jersey’s plan relied primarily on competition,
    assigning priority rankings to the projects serving the households with the
    lowest incomes.

    Several of the allocating agencies whose plans we reviewed used other
    selection criteria to target tax credits to proposed projects serving tenants
    with low or very low incomes:

•   Connecticut, New York, and Rhode Island awarded points under the
    location criterion to projects in areas with high disparities between rent
    and income levels.
•   Illinois applied the project characteristics criterion to award points to
    projects serving the lowest income tenants.
•   Virginia used the housing needs criterion for the same purpose.
•   Maryland created its own selection criterion for leveraging other funds
    and awarded points for projects with long-term subsidies, such as
    project-based rental assistance, which is reserved for very low-income
    households.
•   Vermont developed rankings for projects that had met three thresholds for
    cost efficiency; these rankings were based, in part, on how effectively the
    projects combined resources to enhance affordability.



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    In responding to our survey, all of the 54 allocating agencies reported
    using the public housing waiting list criterion in their allocation plans, as
    the Internal Revenue Code requires. The 20 plans we reviewed reserved
    relatively few points for satisfying this criterion; nevertheless, selecting
    tenants from a public housing authority’s waiting list would generally
    imply serving the lowest income tenants.

•   Illinois awarded 5 percent of its points for a written agreement to give
    preferential treatment to households on a public housing authority’s
    waiting list.
•   Ohio awarded under 1 percent of its points for such an agreement.
•   Michigan deducted 6 percent of its points from proposals that did not
    provide for selecting the tenants for at least six units from a public
    housing authority’s waiting list.

    Several of the plans we reviewed provided multiple opportunities for
    targeting tax credits to proposed projects serving households with low or
    very low incomes. Pennsylvania’s plan, for example, used a set-aside and
    points to give preference to such households under at least five selection
    criteria:

•   The location criterion divided the state into regions and set aside a portion
    of the total allocation for each region. The amount of each region’s
    set-aside was proportional to the number of households with incomes at
    or below 50 percent of the area’s median income.
•   The housing needs criterion provided for awarding up to 22 out of 100
    points for projects reserving at least 50 percent of their units for
    households with incomes at or below 50 percent of the area’s median
    income.
•   The project characteristics criterion provided for awarding up to 19 points
    for projects designed to preserve existing low-income housing.
•   The public housing waiting list criterion made up to 4 points available for
    projects with a letter from a local public housing authority saying that
    tenants on its waiting list would be referred to the tax credit project.
•   The criterion for giving preference to the lowest income tenants made up
    to 14 points available for projects offering support, financial, or other
    services to meet the needs of very low-income households.

    Finally, combining tax credits with funds from other public programs that
    target lower income levels enables tax credit projects to serve tenants at
    these lower levels. In these cases, the more stringent income limits prevail.




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                                Thus, even if an allocation plan does not use controls such as points or
                                rankings to help select projects that combine tax credits with resources
                                from other programs with lower income limits, such combinations ensure
                                that the lower incomes will be targeted.


Plans Provided for Giving       In responding to our survey, 49 of the 54 allocating agencies reported
Preference to Extended          giving preference to projects with agreements to serve qualified tenants
Use                             for longer periods of time than the federal law requires. Seven of these
                                agencies reported making extended use a threshold, and almost all of the
                                others said that they gave higher scores or awarded extra points to
                                projects with extended use commitments. Overall, we estimate that about
                                two-thirds of the projects placed in service between 1992 and 1994 had
                                extended-use commitments exceeding the federal requirements—
                                committing beyond the 30 years or waiving the option of seeking to
                                convert to market rate until some point beyond the fifteenth year.

                                Our review of 20 allocation plans showed that two agencies—California
                                and Massachusetts—established thresholds to ensure that all of their tax
                                credit projects had agreements to serve low-income households for at
                                least 30 years. New Hampshire awarded points for agreements not to seek
                                a market-rate sale for 30 years, while Florida required applicants to waive
                                their right to a sale after 15 years and awarded points for agreements to
                                serve low-income tenants from 31 to 50 years. Other agencies awarded
                                points or higher rankings to projects with extended use commitments.
                                Those that awarded points generally increased the number for each year
                                over the federal requirement. For example:

                            •   Michigan awarded 1 point for each year over 15 years up to 45 years, or 35
                                points for low-income use in perpetuity; and
                            •   Massachusetts added points to its 30-year threshold, awarding 10 points
                                for a 40-year commitment and 15 points for a 50-year commitment.

                                New Jersey used a priority ranking system for the projects competing in a
                                particular round, assigning the highest rank to the project with the longest
                                commitment to low-income use.

                                Giving consideration to sponsor characteristics also seems to support the
                                requirement for giving preference to extended use, much as considering
                                the public housing waiting list criterion reinforces the requirement for
                                giving preference to the lowest income tenants. For example, 22 percent of
                                the properties placed in service from 1992 through 1994 had nonprofit



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sponsors or were tied to nonprofit organizations. According to syndicators
that work primarily with nonprofit sponsors, when investors invest in tax
credit projects through their organization, there is an informal agreement
to sell the properties to nonprofit entities after the initial period of
compliance with the program’s requirements has expired.7 It is assumed
that the nonprofit entity will then operate the property for low-income
households indefinitely.

Combining tax credits with funds from another public program can
increase a project’s commitment to extended-use as well as to the lowest
income tenants. Again, the more stringent requirement prevails. We
estimate that 32 percent of the properties placed in service from 1992
through 1994 received section 515 loans through the Rural Housing
Service. Because these 50-year loans do not include a prepayment option,
the projects are required to serve low-income tenants for at least 50 years.
Similarly, an estimated 5 percent of the projects received financing
through the HOME Investment Partnership. When new construction is
involved, the HOME program carries a 20-year commitment to low-income
use. Nonurban projects with loans from the housing finance agencies in
New Jersey and projects in New York City are required to serve
low-income households for 30 years.

In several states, competition seems to have lengthened extended-use
requirements. California, for example, increased its threshold for extended
use from 30 years in the 1995 allocation cycle to 55 years in the 1996 cycle
because developers, responding to competition, were routinely offering
55-year commitments. During the 1996 allocation cycle, Virginia gave
higher scores and bonus points for extended-use commitments. All 71
qualifying proposals provided either for extended use or for tenants to
purchase their units at the end of the compliance period. Many of the
allocation plans we reviewed offered a comparatively high percentage of
their total points (from 8 to 15 percent) or a relatively high priority ranking
(the third out of seven steps for Vermont) for extended use, making this
criterion comparatively sensitive to the effects of competition.

Whether housing projects subject to extended-use requirements actually
provide housing to low-income tenants on a long-term basis depends, in



7
 The use of informal agreements arises because a nonprofit organization may not negotiate a
below-market purchase option with investors during a project’s initial development. Apparently, there
was concern that giving a nonprofit organization such an option would result in the investors losing
ownership of the property and the accompanying tax benefits of ownership, such as depreciation and
the tax credit.



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                           part, on the economics of doing so. The economic viability of these
                           projects as long-term low-income housing is discussed below.


                           No matter how carefully the allocating agencies define their housing
Several Factors May        priorities or control the allocation of tax credits through their allocation
Affect the Housing         plans, several factors have the potential to affect the housing actually
Actually Delivered         delivered over time. First, nearly all of the agencies reserve some
                           discretion for amending or bypassing the process. Second, a significant
Over Time                  proportion of the tax credits that have been allocated appear not to have
                           been used as planned, according to our analyses of data from several
                           sources. Finally, the long-term economic viability of tax credit projects as
                           housing for low-income tenants has not been tested.


Some Plans Allow the       Seventeen of the 20 qualified allocation plans that we reviewed provide
Allocation Process to Be   flexibility for overriding or bypassing the allocation process. This
Bypassed                   flexibility includes removing certain restrictions, such as set-asides, at the
                           end of the year; reserving a portion of the allocation for discretionary
                           awards; and giving designated officials open-ended discretion.

                           Flexibility can help target needs missed during the allocation process or
                           needs resulting from unforeseen circumstances. For example, in a state
                           where a natural disaster has occurred and housing priorities have changed
                           dramatically, previous allocations may reflect outdated priorities and
                           reallocation at the end of the year may be in order. Even when priorities
                           have not changed, end-of-the-year awards to projects that meet identified
                           needs may be appropriate. Similarly, giving the governor or head of the
                           allocating agency control over a set-aside or other discretionary authority
                           may allow for meeting unforeseen needs.

                           Unless discretionary awards are reserved for unforeseen needs, are
                           well-documented, and are made public, they may undermine the credibility
                           of the allocation process. Recognizing this potential problem, New York’s
                           allocating agency, in August 1996, eliminated a clause in its allocation plan
                           giving the head of the agency the discretion to award over 20 percent of
                           the annual allocation, or $4.5 million.

                           Texas’ 1995 allocation plan gave senior managers considerable discretion
                           in ranking properties to allocate tax credits. Senior managers could
                           override the staffs’ recommendations and award credits to applications
                           with lower scores in order to provide for “geographic dispersion.” In all,



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                                      •   29 of the 46 projects that received credits originally received lower scores
                                          than other projects that did not receive credits, and
                                      •   12 of the projects that received credits were originally classified by the
                                          state’s underwriters as economically unfeasible.

                                          At management’s request, the underwriters subsequently granted
                                          “conditional approval” to the project applications, but the applications
                                          were never returned to the underwriters for verification that the
                                          conditions had been met. Moreover, the managers provided no
                                          documentation to show, as required, how their discretionary awards were
                                          consistent with state and federal requirements to provide housing to low
                                          and very low-income households.


More Projects Are                         Our analysis of data—from the states, IRS, and a study contracted by
Allocated Credits Than Are                HUD—suggests that the states may not be fully using their tax credit

Placed in Service                         allocations. Under the Internal Revenue Code, the states may award tax
                                          credits to projects contingent on their timely completion, i.e., placed in
                                          service within two years after the year of the initial tax credit allocation.
                                          Available data show a significant gap between the tax credits that have
                                          been allocated by the states to proposed projects and the tax credits that
                                          have been awarded to projects that have been placed in service.

                                          Our analysis of data from the states shows that for each year from 1992
                                          through 1994, the value of the tax credits awarded to projects placed in
                                          service fell substantially short of the total annual per capita allocations.
                                          Table 3.1 shows the tax credits the allocating agencies reported as
                                          awarded to projects that were placed in service in the continental United
                                          States from 1992 through 1994.

Table 3.1: Tax Credits Awarded to
Projects Placed in Service, 1992-94                                                           Total tax credits awarded to projects
                                                                                                        placed in service each year
                                          Year                                                                          ($ millions)
                                          1992                                                                                 $158
                                          1993                                                                                  223
                                          1994                                                                                  229
                                          Source: GAO’s analysis of allocating agency data.



                                          The annual per capita allocations total about $315 million each year. Thus,
                                          if all of the credits were awarded to projects that were placed in service,




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the value of the credits for projects placed in service should, over time,
approximate the per capita allocations. Although the value of the credits
awarded to projects placed in service may vary from year to year, it
should, on average, come close to the annual per capita allocation if all
credits awarded were placed in service. However, as table 3.1 indicates,
the value of the credits awarded to projects placed in service fell more
than $80 million short of the annual $315 million per capita allocation in
each of the 3 years. We have not analyzed the reasons for this difference;
possible reasons include developers returning their allocations for
proposed projects to the states for reallocation in subsequent years or the
states awarding less than their full allocation to projects placed in service
each year.

To supplement the data presented in table 3.1, IRS performed an analysis
for us of the cohort of projects proposed in 1992. The analysis compared
the value of the tax credits allocated to projects proposed in 1992 with the
value of the tax credits subsequently awarded when projects proposed in
1992 were placed in service. According to IRS’ analysis, the 1992 allocations
totaled about $322 million, but only about $161 million in credits—or
about one-half of the total—were actually placed in service as of the end
of calendar year 1994.

HUD’s contractor also discussed the apparent shortfall in the production of
tax credit housing. In a study published by HUD in July 1996, the contractor
estimated that from 1987 through 1992, the annual production represented
the use of about 60 percent of the available allocation. Because of the
potential 2-year lag attributable to construction, the study concluded that
the actual “drop out” rate was probably lower than 40 percent, but how
much lower was unknown.

These data raise the question of whether the allocating agencies produced
the housing that the federal government was prepared to fund. If tax
credits have been allocated to proposed projects that are not completed
within 2 years as the program requires, the credits can be returned to the
allocating agency and reallocated before the end of the second year. The
agency then has 2 more years to award the reallocated credits. But if the
agency does not reallocate the credits before the end of the second year,
the credits would lapse and the agency cannot use them. From the
available data, we cannot determine how much of the total federal
allocation that has not been awarded may have lapsed and how much may
have been reallocated for future use. Unawarded allocations that lapsed
would represent lost opportunities to create low-income housing. The



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                       difficulties of monitoring reallocated tax credits are discussed in chapter
                       5.


Extended-Use           Because no tax credit properties are old enough to have outlived their tax
Commitments Have Not   credits, the economic viability of these projects as long-term high-quality
Been Tested            housing for low-income tenants has not been tested. As discussed earlier,
                       projects receiving tax credits are now required to have an extended-use
                       agreement requiring that the property serve low-income tenants for 30
                       years. A contingency clause allows conversion to market-rate housing
                       after 15 years if states cannot find a buyer at a price specified in the
                       Internal Revenue Code willing to keep the property in low-income
                       housing. However, states may impose more stringent extended-use
                       requirements. Indeed, about two-thirds of the projects placed in service
                       from 1992 through 1994 had extended-use commitments that would
                       preclude the possibility of conversion to market-rate housing after 15
                       years.

                       Within the next decade, the first properties subsidized with tax credits will
                       enter the period covered by extended-use agreements. Whether these
                       properties convert to market-rate housing, continue to provide high-quality
                       housing for low-income tenants, or gradually deteriorate will depend on
                       the economics of the alternative uses and states’ ability to find buyers
                       willing to keep the properties in low-income use.

                       Some have questioned the economic viability of these properties as
                       low-income housing after the tax credits expire. For example, several
                       experts told us that in their view, the replacement reserves required by RHS
                       will be insufficient to meet future needs for basic maintenance or
                       rehabilitation. According to these experts, the tax credit properties and
                       other multifamily properties financed with RHS loans will need to obtain
                       additional subsidies if they are to remain high-quality, affordable housing
                       units.


                       All the states had developed qualified tax credit allocation plans, required
Conclusions            by the Internal Revenue Code to direct tax credit awards to meet priority
                       housing needs. The plans generally targeted the credits to the priority
                       housing needs identified by the states. Consistent with the latitude given
                       them in the Code, the states had defined and weighted the selection
                       criteria for awarding credits in different ways. There was also
                       considerable variation in their plans in the data and analyses used in



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assessing housing needs. NCSHA has established a commission to identify
ways to improve various aspects of the credit program, including the way
allocation plans allocate tax credits.

Although all states had qualified allocation plans, we identified three
additional factors that could affect the housing actually delivered over
time. First, some states used discretionary judgment in addition to the
criteria in the allocation plans in making final credit allocation decisions.
Second, IRS and state data indicate that many tax credits that were initially
allocated may not have been used. Finally, the economic viability of tax
credit projects as long-term, low-income housing has not been tested
because projects have not yet been operational beyond the credit period.
Determining whether, or how, these factors affect the long-term delivery
of low-income housing that meets state housing priorities was beyond the
scope of this report.




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                   In order to limit the federal share of housing project development costs,
                   the Internal Revenue Code directs the state tax credit allocating agencies
                   to award no more tax credits to projects than necessary for their financial
                   viability. The Code provides some broad guidance on how to limit awards
                   but leaves to the state allocating agencies the responsibility for
                   establishing specific standards and controls.

                   Our review of tax credit allocating agency implementation of their
                   responsibilities showed that the agencies have established a variety of
                   controls for helping ensure appropriate tax credit awards. These controls
                   vary in their coverage and stringency. For example, some agencies control
                   awards by using cost standards, competition among developers, and
                   independently certified data on projects’ sources and uses of funds. On the
                   other hand, some project files that we reviewed lacked complete or
                   independently certified information on the sources and uses of project
                   funds. This is a control weakness that may make allocating agencies
                   vulnerable to over overawarding or underawarding tax credits to housing
                   projects.

                   The variations in controls established by the allocating agencies may
                   provide opportunities for the agencies to learn from each other’s
                   experiences about the effectiveness of alternative practices. The state
                   allocating agencies, through their national association (National
                   Association of State Housing Agencies) have periodically reviewed state
                   practices to identify appropriate standards and best practices. They have
                   recently convened a Commission that, among other responsibilities, is to
                   consider ways to improve tax credit administration, including matters
                   discussed in this report.


                   The Internal Revenue Code directs that allocating agencies shall not award
Tax Code           tax credits to a qualified low-income housing project in excess of the
Requirements       amount determined necessary for housing project financial feasibility and
                   viability as a qualified low-income housing project throughout the tax
                   credit period. The Code specifies the types of information to be
                   considered in making such a determination and the timing of the
                   determinations.

               •   With respect to information requirements, the Code requires the allocating
                   agencies to consider (1) the sources and uses of funds and total financing
                   planned for the project, (2) any proceeds or receipts expected to be
                   generated as a result of tax benefits, (3) the percentage of the housing



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    credit dollar amount used for project costs other than the cost of
    intermediaries, and (4) the reasonableness of the development and
    operational costs of the project.
•   With respect to timing, the Code requires the allocating agencies to
    consider the required information at the following times: (1) when a
    project’s application is received, (2) when an agency makes a preliminary
    allocation of tax credits, and (3) when a low-income building is placed in
    service.

    As a practical matter, as discussed with allocating agency officials, the
    Internal Revenue Code requirements translate into the following
    three-step tax credit determination process that the states generally
    should follow in order to help ensure that no more credits are provided to
    low-income housing projects than necessary.

•   First, allocating agencies should make a judgment on the reasonableness
    of a project’s development cost because (1) development cost is a
    determinant of the financing needs of a housing project, and (2) the
    maximum tax credit award is based on development cost.1
•   Second, allocating agencies should make a judgment on a housing
    project’s income-producing potential and non-tax credit financing
    arrangements because decisions on the amount of private financing that a
    housing project is capable of supporting affect decisions on the amount of
    tax credit equity investment (or other public assistance) needed by a
    project to overcome any deficits in project financing.
•   Third, allocating agencies should make a judgment on the investment yield
    (i.e., the amount of equity investment a project could raise for each tax
    credit dollar received) obtainable from a project’s tax credit award in
    order to convert tax credits into an equity investment commensurate with
    a project’s financing deficit.

    Also, within the rather broad federal directive of providing housing
    projects with no more tax credits than needed, the allocating agencies are
    responsible for establishing specific implementing controls, such as
    standards for determining the reasonableness of project development cost.
    The use of such standards may enable the agencies to limit the federal tax
    credits per project and finance more projects out of their tax credit


    1
     The Internal Revenue Code limits tax credit awards to an annual amount equal to a specified
    percentage of a project’s qualifying development costs that were determined to be reasonable by the
    allocating agency. The Code originally limited an award to 9 percent of the approved costs of
    substantial rehabilitation and construction of buildings that are not federally subsidized or 4 percent of
    the approved costs of acquisition or construction of projects receiving other federal subsidies. IRS is
    required to periodically revise the rates to reflect current interest rates.



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allotment. To assist the states in making such evaluations, NCSHA has
recommended the adoption of a number of cost control standards.

Figure 4.1 provides an overview of the costs that the allocating agencies
reported were associated with developing and financing the tax credit
supported low-income housing placed in service during 1992 through 1994.
On the basis of our sample, we estimate that these projects cost about
$10.7 billion to develop: about $5.8 billion in construction expenses; about
$2.7 billion in construction-related fees, such as those paid to developers
and builders; and about $2.2 billion in other costs, including the costs of
acquiring the property. The projects were financed with approximately
$3.1 billion of equity investment raised through the award of tax credits
and the remainder largely through commercial loans (mortgages) and
publicly supported concessionary financing, such as CDBG loans.2 Given the
yield of the tax credit awards at the time (averaging an estimated $0.53 of
equity investment for each $1 of tax credits made available to project
equity investors over a 10-year period), the states awarded about
$6.1 billion in tax credits to the projects. These awards amounted to an
estimated 97 percent of what the allocating agencies determined were the
maximum allowable credits that could be awarded to the projects, on a
per project basis.

The following three sections describe the controls and standards
employed by the states in each phase of the three-step tax credit final
award determination process; a process established to help ensure that no
more credits are awarded to low-income housing projects than necessary.
Recently, NCSHA convened a Commission that, among other
responsibilities, is to consider ways to improve tax credit administration,
including matters discussed in this report.




2
 In addition, the projects received an estimated $229 million in rent payments subsidized by various
rental assistance programs, such as those financed by HUD and RHS.



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Figure 4.1: Estimates on Housing
Project Sources and Uses of Funds
                                    Dollars in billions

                                    12
                                                           10.7                                     10.7

                                    10



                                     8



                                     6



                                     4



                                     2



                                     0
                                                     Sources of funds to                       Uses of funds to
                                                      balance projects                         develop projects

                                                            Equity investments raised                 Construction expenses
                                                            through the award of tax credits
                                                            Commercial mortgage loans                 Construction-related fees
                                                            Concessionary financing                   Other
                                                            (e.g., CDBG loans) and other              (e.g., acquisition of property)

                                    Source: GAO analysis of tax credit allocating agency data on sampled projects with adjustments
                                    to account for 14 percent of the projects with incomplete financing information.



                                    Section 42 of the Internal Revenue Code directs the states to consider the
Allocating Agency                   “reasonableness” of housing project development costs when determining
Practices for Ensuring              the amount of tax credits necessary for project feasibility, but it does not
Reasonable                          specify how “reasonableness” should be determined. Rather, Congress
                                    provided the states with the flexibility to respond to their unique and
Development Costs                   varied low-income housing needs. As expressed by the congressional
                                    conferees in establishing the provision, the states were expected to set
                                    standards of reasonableness reflecting the applicable facts and
                                    circumstances, including the location of projects and uses for which the
                                    projects are built. The conferees also indicated that the provision was not
                                    intended to create a national standard of reasonableness.




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                            To assist the states in their administration of the tax credit, in a June 1993
                            report NCSHA recommended a number of cost control standards for the
                            allocating agencies to consider adopting. The cost control areas covered
                            by NCSHA’s recommendations address overall housing unit costs and
                            certain components of overall costs, such as developer fee and consultant
                            fee limits. In October 1995, NCSHA also issued a pamphlet listing a number
                            of tax credit administration “best practices,” some of which relate to cost
                            control standards.

                            In turn, the states have adopted a number of practices to directly control
                            costs (both overall costs and certain components) and to manage
                            competition in a way intended to promote cost control. But the rigor of the
                            controls and the formalized documentation of the controls used by the
                            states vary—in some cases they are more stringent than NCSHA
                            recommended, and in some instances less.


Standards for Evaluating    In its 1993 report, NCSHA recognized that public support for the tax credit
Overall Development Costs   program could be “imperiled by projects, however meritorious, the cost of
                            which exceeds an accepted standard of reasonableness.” Accordingly, it
                            recommended that each state develop a per unit cost standard either for
                            the entire state or different standards within the state to account for
                            variations in construction and other costs.

                            NCSHA’s report also pointed out that the baseline standard(s) states develop
                            should, for many areas, be within the limits established for HUD’s section
                            221(d)(3) mortgage insurance program. This program is designed to
                            establish maximum per unit cost limits equivalent to the costs of
                            constructing nonluxury multifamily housing projects for different areas
                            within each state.3 For market areas and/or project types with higher or
                            lower development costs, NCSHA suggested that the allocation agencies
                            might choose to modify HUD’s 221(d)(3) standards, but it recommended
                            that the agencies fully document the reasons for these higher costs in
                            establishing a higher standard. NCSHA further recommended that once a
                            state had adopted or modified the 221(d)(3) cost standards, any proposed
                            project with costs above its standard should be required to fully document
                            the reasons for these costs and subject them to further review and
                            scrutiny.



                            3
                             These limits were initially set by Congress in legislation and adjusted annually by HUD to reflect
                            changes in construction costs. The limits provide different maximums according to housing
                            characteristics, e.g., elevator and nonelevator buildings.



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    Of the 54 allocating agencies we surveyed, 48 agencies reported that they
    have established guidelines for controlling overall project construction
    costs. Of these 48 agencies,

•   22 said they employed the dollar-specific limits contained in HUD’s
    221(d)(3) guidelines,
•   11 said they established their own dollar-specific per unit or per square
    foot cost limits, and
•   15 said they made reviews without dollar-specific per unit or per square
    foot limits.

    The six allocating agencies that reported not having guidelines said that
    they relied either on the competition of the application process or on staff
    expertise as a means of evaluating cost reasonableness.

    Allocation agency officials from California said that adopting HUD’s
    221(d)(3) limits helped them to reduce housing project costs. According to
    their analysis, the development costs of projects receiving tax credits in
    1996—the first year California made use of the 221(d)(3) limits—were
    12 percent lower than the development costs of projects receiving credits
    the year before. The officials attributed this improvement primarily to
    reductions in “soft costs” (e.g., construction financing and various
    professional fees), which had escalated before the agency adopted the
    221(d)(3) standards.

    Other allocating agency officials said that using their own standards was
    more cost effective than relying on HUD’s 221(d)(3) limits. Mississippi
    allocating agency officials reported, for example, that the agency had
    developed a maximum per unit cost standard that is lower than HUD’s
    limits. This standard is based on the costs of construction and land in the
    state and is adjusted to reflect variations in these costs within the state. In
    addition, the officials said they examined cost data on existing tax credit
    projects and compared these data with cost data for other nonluxury
    multifamily buildings in the same geographic areas.

    New Jersey relied on its own database to determine the reasonableness of
    project costs. According to allocating agency officials, the costs of
    proposed projects are compared with the costs of comparable projects
    included in the state’s database of over 40,000 housing units, and any
    out-of-line costs must be justified.




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                           Iowa relied on the experience of its staff in evaluating the reasonableness
                           of project costs. According to allocating agency officials, the wide
                           variations in project types, unit sizes, and geographic areas make setting
                           specific dollar limits impractical.

                           Whether the allocating agencies relied on specified cost limits or less
                           specific criteria such as database analysis, most said they allowed
                           construction costs to exceed their guidelines. Both the instances in which
                           exceptions were allowed and the size of the permitted exceptions varied
                           among the agencies. South Carolina, for example, required no justification
                           for costs that exceeded the state’s limits by up to 10 percent but required
                           justification for differences of more than 10 percent. In California, projects
                           were eligible for a 15-percent increase if they had special features, such as
                           linkages with mass transit, facilities for tenants with special needs, or
                           significant seismic upgrading.


Standards for Evaluating   In addition to advocating the adoption of a standard for controlling overall
Components of Overall      development costs, NCSHA recommended that the allocating agencies adopt
Costs                      limits for certain components of overall costs, such as fees for developers,
                           builders, and consultants. Most of the agencies reported that they
                           generally followed NCSHA’s recommended limits, while others reported
                           adopting limits that were more or less stringent. Regardless of the
                           standards adopted by the individual agencies, comparisons among
                           agencies are difficult because of differences in how these standards are
                           either defined or computed.

Developer Fees             A developer’s fee is meant to compensate a developer for the staff time,
                           entrepreneurial effort, work, and risk involved in the development of a
                           project. NCSHA recommended that the fee should be limited to no more
                           than 15 percent of a project’s total development cost unless an agency
                           specified criteria for justifying a higher fee. For example, a larger fee might
                           be justified to induce the development of low-income housing in an area
                           that otherwise would not be served.

                           All but one agency reported that it had set limits on the developer’s fee.4
                           For the most part, these limits ranged from 10 to 23 percent—most were
                           15 percent—but comparisons among the agencies were difficult because
                           of differences in the definition of the cost base on which the limits were


                           4
                            According to officials from the agency that has not set limits on the developer’s fee, this fee is
                           reviewed for reasonableness and, when it is considered excessive, the agency has the authority to
                           reduce the project’s tax credit award.



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                           computed and in the variable nature of some agencies’ limits. For
                           example:

                       •   With respect to adopting different cost bases, (1) New Jersey limited the
                           developer’s fee to 15 percent of a project’s total development costs
                           excluding the costs of land, working capital, marketing expenses,
                           operating deficit reserves, and the syndication costs incurred by the
                           developer; (2) Nevada and North Dakota limited the developer’s fee to
                           15 percent of a project’s “eligible basis”;5 (3) Missouri limited the
                           developer’s fee to 18 percent of a project’s adjusted basis; and (4) West
                           Virginia limited the developer’s fee to 20 percent of a project’s “adjusted
                           basis,” excluding the developer’s fee.
                       •   With respect to adopting variable fee limits, North Carolina’s agency took
                           project size into account by limiting the fee to 15 percent of the overall
                           development costs for projects with up to 60 units, to 12.5 percent for
                           projects with between 61 and 100 units, and to 10 percent for projects with
                           over 100 units. Other allocating agencies varied the fee to account for
                           other project characteristics, such as setting one limit for construction and
                           another for acquisition, while other states adjusted the limit to account for
                           the attainment of specified objectives, such as the amount of equity
                           investment realized from the tax credit award.


Fees to Builders and       NCSHA recommended that the allocating agencies set limits on the fees
Related Parties            generally charged by builders or general contractors for their work in
                           constructing or rehabilitating housing projects. NCSHA recommended, for
                           example, that unless otherwise justified, the builder’s total fee should not
                           exceed 14 percent of a project’s construction costs (including 6 percent
                           for profit, 2 percent for overhead, and 6 percent for general requirements).

                           NCSHA  also recommended that the allocating agencies require a developer
                           to disclose any “identity of interest” with any other party to the project and
                           take such interest into consideration in determining the maximum fees.
                           This control could prevent the double payment of some fees, such as
                           overhead charges, to essentially the same party.




                           5
                            “Eligible basis” refers to a project’s development costs that are chargeable to a capital account for
                           determining depreciation expenses for tax purposes (i.e., “adjusted basis”), with certain modifications
                           as defined in section 42 of the Internal Revenue Code.



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                              The responses to our survey indicate that almost all of the agencies have
                              set limits on the builder’s fee.6 About half of the agencies reported
                              following NCSHA’s recommended standards fairly closely, and others
                              introduced variations. For example, Maryland’s allocating agency took the
                              characteristics of individual projects into account. Instead of capping the
                              total builder’s fee at 14 percent, the agency established a range of fees
                              from 12 to 23, percent depending on a project’s construction costs. In
                              contrast, New Jersey had set no fixed standards for the builder’s profit,
                              overhead, and general requirements. The allocating agency required
                              review of these costs only if there was an identity of interest between the
                              developer and the builder.

                              Only one state allocating agency reported that it did not require the
                              identification of an identity of interest. The absence of this information
                              negates the potential for closer scrutiny of costs to ensure they are fully
                              justified and reasonable. But, as a matter of practice, nine state allocating
                              agencies advised us that they did not consider identity of interest when
                              determining maximum fees. For example, District of Columbia officials
                              advised us that the limit is the same regardless of whether the parties are
                              related.

Consultant and Professional   To control consulting fees, NCSHA recommended that the states (1) identify
Fees                          professional fees, such as architect and engineer fees, that could be
                              reimbursed from the financing raised by tax credits; and (2) include other
                              consultant fees within the developer fee limit.

                              All of the allocating agencies reported that in evaluating projects, they
                              require the identification of professional fees. But 11 of the agencies did
                              not require that such fees always be contained within the limit on
                              developer fees.

Syndication Fees              As part of the evaluation process used to determine the amount of tax
                              credits needed by projects, the Code requires states to consider the
                              amount of funds (proceeds) to be generated by tax benefits and the
                              portion that is used for project costs other than for intermediaries, e.g.,
                              syndicators who raise equity capital for housing projects.

                              Typically, most of the expenses of syndication are paid by investors to an
                              investment syndicate in the form of a syndication fee, similar to a “load
                              fee” paid to a mutual fund manager. This fee would cover such syndication

                              6
                               Agencies that have not set limits may review the builder’s fee for reasonableness. According to
                              officials from one agency, if the fee is found to be excessive, the tax credit award may be reduced.



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                           expenses as the marketing of funds contributed to a syndicate, associated
                           legal and accounting costs, management of syndicate funds, monitoring of
                           housing project operations, and funding reserves. Information we obtained
                           from syndicators indicates that syndication fees may consume about 10 to
                           27 percent of the funds contributed by investors to the syndicate,7 leaving
                           about 90 to 73 percent available for investment in housing projects.

                           Syndication expenses may also be paid by housing project developers.
                           These may include legal and accounting fees and other expenses
                           associated with arranging for the equity investment. Typically, these costs
                           would be minor compared to syndication fees.

                           Although much of the syndication expenses would be passed on to
                           housing projects in the form of reductions in the amount of equity
                           investment available to the project, NCSHA has not established a
                           recommended cost limit for those syndication expenses. NCSHA has,
                           however, recommended that if costs that are properly payable by a
                           syndicator (such as those associated with securities registration and sales
                           commissions) appear as development costs of a project, the costs should
                           be disallowed. In turn, the agencies have tended to focus on housing
                           project development costs and, as discussed later, the results of the
                           syndication process (see section on tax credit pricing). More specifically,
                           although 38 agencies advised us that they reviewed syndication costs that
                           were an expense of the housing project, only 11 advised us that they
                           reviewed fees the syndicators charge their investors. As explained by one
                           allocating agency, it reviews the sources and uses of funds for the project
                           (a review required of all allocating agencies by the Code) but not the
                           sources and uses of funds of the syndicators.


Competition as a Control   Competition among developers for tax credits is another control over
Over Project Costs         project costs. Of the 51 allocating agencies that could provide data on the
                           number of housing project developers that applied for tax credits in 1995,
                           all reported turning down applicants. Overall, about 54 percent of the
                           applicants were not successful in competing for tax credits in 1995. But
                           this competition is not uniform among the states; a few allocating agencies
                           turned down less than 20 percent of the 1995 applicants.



                           7
                            Syndication fees are affected by the manner in which the capital is raised. In general, syndication
                           costs are higher for capital raised through public offerings to individuals than for capital raised
                           through private placements with large corporations. According to syndicators, the costs of registration
                           with the Securities and Exchange Commission and brokerage commissions make public offerings
                           more expensive than private placements.



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                          Our review of 20 state allocation plans showed that most adopted
                          procedures for managing this competition in a way that supplements cost
                          control limits. They adopted scoring formulas for ranking housing projects
                          based in part on cost considerations. For example, out of a possible score
                          of 164 points in one state’s ranking system, 20 points were to be awarded
                          to the project determined to be the least costly in terms of per unit
                          development cost and tax credits sought. Other more costly projects were
                          to receive less than 20 points. Overall, the higher the total points earned by
                          a project, the greater the likelihood of receiving a tax credit award.

                          Allocation officials in New Jersey said that they obtained benefits by
                          incorporating cost considerations into their scoring formula. The officials
                          told us that even though the state had established a 15-percent limit on
                          developer fees, since the state started awarding points for lower fees, the
                          developer fees have dropped to an average of about 8 percent of allowable
                          development costs.


                          After giving consideration to the reasonableness of a project’s
Allocating Agency         development costs, allocating agencies are to determine a project’s
Practices for             financing deficit, i.e., the amount of development costs that a project is not
Determining Project       capable of financing through its own operating revenues. The subsequent
                          tax credit award should be no greater than an amount needed to attract an
Equity Needs              equity investment commensurate with the financing deficit.

                          In making judgments on a project’s financing deficit, the Internal Revenue
                          Code requires the allocating agencies to evaluate both the sources and
                          uses of funds (including the reasonableness of a project’s operating costs)
                          and the total financing planned for the project. However, the Code does
                          not specify how the evaluation is to be done, nor has NCSHA recommended
                          standards to be followed.8 Hence, the agencies are responsible for
                          developing their own procedures and practices for implementing the
                          Code’s requirements.

                          In general, the allocating agency officials told us that their staffs

                      •   reviewed the reasonableness of a project’s estimated revenues (e.g., rent)
                          and operating expenses (e.g., maintenance) to determine how much
                          income should be available to cover the project’s private financing;

                          8
                           Although it did not promulgate standards, NCSHA recommended, in its 1995 pamphlet on best
                          practices, that the allocating agencies develop a database on project development and operating costs
                          for use in evaluating proposals for financial feasibility and determining the tax credit awards that
                          projects are eligible to receive.



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                           •   assessed the reasonableness of the private financing arrangements relative
                               to the terms (e.g., interest rate charged) of that financing and to the
                               income anticipated from the project to carry the private financing; and
                           •   reviewed the total financing for the project, including tax credits and any
                               other public subsidies needed to supplement the private financing in order
                               to make the project financially feasible.

                               As the following sections indicate, the allocating agencies used different
                               standards and practices to assess reasonableness, and not all of the
                               agencies assessed all aspects of reasonableness.


Agency Procedures for          All of the 54 allocating agencies reported checking the reasonableness of a
Assessing Project Income       project’s rental income. The most common means of checking were as
                               follows:

                           •   53 agencies said they reviewed the expected vacancy rate over the 15 year
                               tax credit period;
                           •   48 agencies said they reviewed the anticipated rate of increase in rental
                               income over the 15 year tax credit period; and
                           •   31 agencies said they reviewed the estimated absorption rate (number of
                               months needed to lease all of the units in the project).

                               The most common sources of data for these checks were market studies
                               done by the developer (44 agencies), agencies’ databases (34 agencies),
                               property appraisals (24 agencies), and market studies done by the
                               allocating agency or another governmental agency (21 agencies).

                               All but 5 of the 54 allocating agencies reported that they maintained data
                               for use in assessing the reasonableness of a project’s operating costs.
                               Two-thirds maintained their own database on multifamily housing, and the
                               others relied primarily on state or regional cost indexes or other
                               specifically developed data such as that developed by lenders. For the
                               most part, the agencies reported using these data to establish a cost
                               standard based on a specified dollar per unit per month (or per year) or
                               calculated as a percentage of operating revenues. But these standards
                               were not necessarily rigid limits. Almost all of the agencies allowed a
                               project’s operating costs to exceed the standards, if warranted.


Agency Standards for           All but 8 of the 54 allocating agencies reported having written guidelines to
Assessing Private              assist their staffs in determining the reasonableness of a project’s private
Financing                      financing and the amount of such financing that a project can support. The


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                                         most common procedures adopted by the agencies for checking
                                         reasonableness, regardless of whether they were written or not, were the
                                         following:

                                     •   Forty-nine agencies said they reviewed a project’s debt service coverage
                                         ratio. This commonly accepted measure for evaluating a rental project’s
                                         financing is computed by dividing the project’s net income (e.g., rental
                                         revenue less operating expenses) by the mortgage payment. The higher the
                                         ratio, the less the project’s income is committed to financing the project
                                         through its mortgage loan. Conversely, the lower the ratio, the more the
                                         project’s income is committed to the financing and is unavailable for other
                                         purposes. Most of the responding agencies reported that they had set a
                                         maximum rate (ranging between 1.15 and 1.50) and a minimum rate
                                         (ranging between 1.05 and 1.20) for this ratio.
                                     •   Forty-eight agencies said they reviewed the interest rate charged on a
                                         project’s mortgage loan. In general, the higher the interest rate, the lower
                                         the debt that a project can support and, therefore, the greater the project’s
                                         need for tax credit equity investment. Because interest rates change
                                         periodically, we did not ask the agencies for information about their limits
                                         on them.
                                     •   Forty agencies said they reviewed a project’s mortgage loan amortization
                                         period (i.e., the period over which a loan is scheduled to be repaid). In
                                         general, the shorter the amortization period, the higher the periodic loan
                                         payment. Higher payments reduce the amount of debt that a project can
                                         carry over the short term and, therefore, increase the project’s need for tax
                                         credit equity investment. Most of the agencies with limits on the
                                         amortization period set them for between 15 and 30 years.9

Table 4.1: Size of Mortgage Deemed
Supportable Under Alternative Debt                                 Debt service                       Amortization period
Service Coverage Ratios and              Interest rate           coverage ratio              30 years             20 years             15 years
Amortization Periods
                                         10 percent                          1.10         $1,338,000           $1,217,000           $1,093,000
                                                                             1.25         $1,177,000           $1,071,000            $ 962,000
                                                                             1.40         $1,051,000             $ 956,000           $ 856,000
                                         Note: The analysis is based on the following assumptions: a 50-unit property that costs $3 million
                                         to develop and generates $155,000 in annual operating income. Dollar amounts are rounded to
                                         thousands.

                                         Source: GAO analysis.



                                         9
                                          To illustrate the impact of differences in debt service coverage ratios and amortization periods, we
                                         performed a sensitivity analysis showing the effects of alternative ratios and periods on the size of a
                                         mortgage. As table 4.1 shows, changes in these variables can significantly affect the mortgage amount
                                         that net operating income may be deemed sufficient to support.



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                          •   Twenty-six agencies said they reviewed a project’s mortgage loan balloon
                              payment period (i.e., the period over which the loan principal may become
                              due, which would occur before the end of the amortization period). In
                              general, balloon payments add to the long-term financial uncertainty of a
                              project because they require future refinancing. Most of the responding
                              agencies reported that they had set limits on the balloon payment period
                              at 3 to 15 years. As a best practice, however, NCSHA discouraged balloon
                              payments, recommending that the allocating agencies give priority to
                              developments with mortgage commitments of at least 15 years.


Reviews of Other Public       The Code directs the allocating agencies to evaluate the total financing for
Subsidies                     a project, including all of the public subsidies as well as the private
                              financing. This evaluation is necessary because public subsidies may affect
                              the size of the tax credit award10 and also because the maximum allowable
                              tax credit award may not be sufficient to cover a project’s financing
                              deficit. Additional subsidies from federal, state, or local sources may be
                              needed, for example, when a project’s rents have been set very low to
                              serve households with very low incomes or when costly features have
                              been included in a project to meet special needs. The Code’s requirement
                              for an evaluation of all subsidies is designed to prevent both overfunding
                              and underfunding of the assisted projects.

                              All the allocating agencies told us that they considered the reasonableness
                              of the overall sources of funds committed to a housing project. The data
                              on the tax credit projects placed in service between 1992 and 1994 showed
                              that the majority benefited considerably from subsidies in addition to tax
                              credits. On the basis of our sample, we estimate that about 69 percent of
                              these projects received about $3 billion in concessionary loans (e.g., below
                              market interest rate loans) or grants. Table 4.2 sets forth the sources of
                              financing for these projects.




                              10
                                See footnote 1, page 74.



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Table 4.2: Estimated Sources of
Financing for Projects Requiring                                                                                            Percentage of
Subsidies in Addition to Tax Credits   Source of financing                                                                      financing
                                       Concessionary loans/grants                                                                          37
                                       Tax credit equity                                                                                   27
                                       Mortgage loans (commercial)                                                                         29
                                       Other                                                                                                6
                                       Total                                                                                             100
                                       Note: Total does not add because of rounding.

                                       Source: GAO analysis of allocating agency reported data.



                                       Much of the concessionary assistance provided to tax credit projects is
                                       federal—such as loans through RHS, CDBG, and HOME. These types of
                                       housing assistance, some of which are administered by the states, have
                                       their own requirements for evaluating all public and private financing
                                       sources to ensure that no more assistance is provided than necessary. For
                                       financing provided through HUD, the required evaluation is called a
                                       “subsidy layering review.”11

                                       Besides concessionary loans and grants, tax credit projects may receive
                                       funds through rental assistance programs. Rental assistance may be
                                       project based (generally provided under a long-term contract between HUD
                                       or RHS and a housing project) or tenant based (provided through a
                                       certificate or voucher for a qualifying household). On the basis of our
                                       sample, we estimate that the tax credit projects placed in service during
                                       1992 to 1994 received about $229 million a year in project-based and
                                       tenant-based rental assistance payments, increasing the total proportion of
                                       housing projects receiving assistance beyond tax credits to 86 percent.12

                                       We did not review the controls established by the other federal housing
                                       assistance programs for limiting their subsidies to tax credit projects. But,
                                       as indicated by the following two examples, the information we obtained
                                       from the allocating agencies suggests that allocating agencies have
                                       adopted varying practices in integrating the other assistance into the tax
                                       credit review process.



                                       11
                                        Congress originally established the subsidy layering review requirement in the HUD Reform Act of
                                       1989. Although we discussed this requirement with officials from HUD and the allocating agencies, the
                                       scope of our review did not include the implementation of these requirements.
                                       12
                                        This estimate is based on the monthly rental charges for 1996 reported by the projects in our sample.
                                       A property is included in the estimate if at least one tenant received a rental subsidy.



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                      •   First, a tax credit project may attract tenants who qualify for federally
                          financed tenant-based rental assistance. As indicated in chapter 2, rents
                          charged in accordance with the assistance program rules may exceed the
                          tax credit rents charged unassisted tenants. According to our survey of
                          allocating agencies, 12 of the 54 agencies have taken steps to preclude this
                          from happening. Thus, more assistance could be made available for other
                          households. The remaining 42 agencies may either (1) allow affected
                          projects to retain the differential; or (2) require the project to return the
                          differential to the state by, for example, using it to help retire a
                          concessionary loan from the state. The relative frequency of each outcome
                          was not measurable from the data obtained from the housing projects.
                      •   Second, the Code authorizes the states to provide tax credits to housing
                          projects that are financed through the issuance of tax-exempt bonds. For
                          projects that receive at least 50 percent of their financing in this way, the
                          Code authorizes the awards to be made outside of state tax credit
                          allotments.13 In other words, the bond projects do not have to compete
                          against the projects vying for a portion of the annual $1.25 per capita tax
                          credit allotment. A total of about $10 million in tax credits was awarded
                          outside the tax credit ceiling in 1995. Although the projects receiving these
                          awards are subject to other requirements under the Code—for example,
                          they are eligible for no more tax credits than are necessary for their
                          financial feasibility subject to the limits established for federally
                          subsidized projects—their finances may not always be evaluated with the
                          same rigor as those of projects competing for a portion of the per capita
                          allocation. Officials in New Jersey told us, for example, that for
                          tax-exempt bond projects, the developer’s fee is typically the full
                          15 percent allowed by the allocating agency. For other tax credit projects,
                          the developer’s fee has been reduced through competition to 8 percent.


                          After determining a project’s financing deficit, allocating agencies are to
State Controls Over       calculate the amount of the tax credit award. The award may not exceed
Tax Credit Pricing        an amount that would produce an equity investment equal to a project’s
                          financing deficit or the statutory limit, whichever is less.14 Because the
                          equity investment yield of tax credits may vary, the allocating agencies
                          need to have assurance that the appropriate yield figure is used in
                          computing the amount needed to produce an equity investment

                          13
                           Also, for projects receiving less than 50 percent bond financing, the Code authorizes the states to
                          provide tax credits outside of the tax credit ceiling on the bond financed portion of the housing
                          projects.
                          14
                            As discussed earlier, the limit is based on a percentage of qualifying development costs. The
                          percentage may vary depending on the type of development (acquisition or construction-
                          rehabilitation) and the presence of federal subsidies.



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commensurate with the financing deficit. In short, the higher the equity
investment yield of tax credits, the lower the amount of tax credits that
would need to be awarded to a project.

Neither the Code nor NCSHA provides standards for evaluating tax credit
yield. The general measure used by the allocating agencies to quantify
yield is “tax credit price” defined as the total amount of equity investment
made in a project in relation to the tax credits awarded to the projects, i.e.,
the sum of credits allowable over the 10 year credit period. The price is
expressed as the number of cents of equity investment produced by each
$1 of tax credits awarded to a project. The difference provides the
investors with a risk-based rate of return financed over 10 years as well as
compensation for housing project evaluation and monitoring.

All the housing credit agencies reported that they generally use one or
more evaluation techniques to determine the reasonableness of tax credit
prices. They indicated that they mostly rely on market competition to set
the price; 53 of the agencies require housing projects to show evidence of
multiple competitive bids from investment syndicators or other investors.
Additionally, 45 allocating agencies indicated that they use a price
benchmark, an evaluation standard generally based on periodic surveys of
syndicators or analysis of prior year experience.

Although we did not evaluate how well the agencies applied their
evaluation techniques to determine the reasonableness of tax credit prices,
our discussions with allocating agency officials and their advisors
identified limitations to using tax credit price as a measure of tax credit
yield. The timing of the actual capital infusion into a housing project has a
material effect on yield, but this may not be taken into account in the way
tax credit price is computed. Accordingly, the tax credit price may not
provide an ideal measure for states to use for evaluating the equity
investment alternatives available to a project.

In addition to the timing of the equity contribution, which may affect the
price of the credit, industry experts identified a number of other
conditions that could influence tax credit price. For example, given the
differences in the cost of raising investment capital, a project receiving its
equity investment from a private placement with a sole corporate investor
should receive a higher price than that offered by an investment
syndication through a public offering. Also, properties generating
substantial tax losses (tax deductions to the investors) in addition to the
tax credit may command a higher equity price. On the other hand, the



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                                            experts indicated that real estate risks, such as locating a property in an
                                            unstable neighborhood or having an unproven developer, may reduce the
                                            price.

                                            Despite the limitations of using price as an indicator of tax credit yield, at
                                            the present time, no other overall measure exists to evaluate tax credit
                                            yield, make comparisons among projects, or assess developments in the
                                            tax credit market.


Tax Credit Price                            Even though allocating agencies and syndicators refer to equity
Experience                                  investment in terms of “price,” no published data sources provide a
                                            comprehensive record of tax credit pricing over the life of the tax credit
                                            program. Based on our sample of properties placed in service from 1992
                                            through 1994, we estimate that the average price was about $0.53, with
                                            significant variation among the projects. (See table 4.3.)

Table 4.3: Estimated Distribution of
Equity Prices Received for Properties                                                                                    Overall distribution
Placed in Service, 1992-1994                Equity price                                                                          1992-1994
                                            less than $0.40                                                                                      9
                                            $0.40 to $0.49                                                                                      39
                                            $0.50 to $0.59                                                                                      32
                                            $0.60 to $0.69                                                                                      10
                                            $0.70 or more                                                                                        8
                                            Source: GAO analysis of tax credit allocating agency reported data on 86 percent of the projects,
                                            i.e., those with complete information.



                                            In discussions with several major investment syndicators and allocating
                                            agency officials, we were told that tax credit prices have been increasing.
                                            These sources, and recent surveys of tax credit prices, indicated that for
                                            each dollar of tax credits awarded, the average price increased from
                                            around $0.45 in 1987 to over $0.60 in 1996. They attributed the increase to
                                            the following factors:

                                        •   The types of investors have changed, from individuals to corporations.
                                            Because large publicly traded corporations are not subject to the passive
                                            investment loss rules that limit individual investors’ and closely held
                                            corporations’ deductions, tax credit properties represent a relatively more
                                            attractive investment option for corporations.




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                        •   The types of corporations purchasing tax credits have changed from
                            manufacturing corporations to corporate investors that better understand,
                            and are therefore in a better position to value, the risk of a tax credit
                            investment.
                        •   The types and structures of syndications have changed from public
                            offerings characterized by sales to individuals to private placements
                            characterized by sales to a small number of corporations. These changes
                            have reduced the costs of raising capital.
                        •   The tax credit program was made permanent in 1993, reducing investors’
                            uncertainty over the future of tax credit investments.
                        •   States and localities have established their own equity funds to raise
                            investment capital for low-income housing projects. This has helped to
                            increase competition in the syndication process.
                        •   Growth in the economy and in corporate profitability has increased the
                            taxable income that could be sheltered by tax credits.


                            In controlling federal costs—that is, in evaluating the reasonableness of a
Effectiveness of Cost       project’s development costs, financing deficit, and tax credit
Controls Depends on         proceeds—allocating agencies are largely dependent on information
Accuracy of Cost Data       submitted by developers on their sources and uses of funds. In summary,
                            allocating agencies need information on the amount of a project’s (1) total
                            development costs so that an agency can make informed decisions on the
                            reasonableness of the costs and the amount of financing a project will
                            need; (2) development costs that qualify for inclusion in the tax credit cost
                            base—defined as eligible basis by the Code—so that an agency can
                            compute a maximum tax credit award; (3) financing arrangements,
                            together with the terms of the financing, so that an agency can determine a
                            project’s financing deficit; and (4) tax credit proceeds so that an agency
                            can ensure that no more credits are awarded than necessary to cover a
                            project’s financing deficit. If the agencies do not have complete
                            information on these sources and uses of funds, they cannot be assured
                            that their controls are effective at controlling federal costs.

                            In addition, the allocating agencies need assurance about the reliability of
                            that information. Engaging a public accounting firm to validate financial
                            information is a generally recognized practice for ascertaining financial
                            information reliability. When contracting with an independent public
                            accountant, allocating agencies have several options concerning the extent
                            of the work to be performed. These options include (1) an examination or
                            audit, which would provide a reasonable basis for an independent public
                            accountant to issue an opinion on the overall reliability of a project’s



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    financial information taken as a whole; (2) a review, which consists of
    inquiries and application of analytical procedures that may bring to the
    accountant’s attention significant matters affecting a project’s financial
    information but does not provide assurance that the accountant will
    become aware of all significant matters that would be disclosed in an
    audit; and (3) agreed-upon procedures, which would provide an
    accountant with a basis to issue a report of findings based on the specified
    procedures but not a basis to issue an opinion on the reliability of the
    financial information.

    Given the importance of having reliable information as a basis for
    decisionmaking, NCSHA recommended that before finalizing a project’s tax
    credit award, an allocating agency should require a verification of the
    project’s costs by an independent public accountant (or other third-party
    qualified professional).15 NCSHA did not, however, specifically recommend
    the type of public accountant engagement or independent third-party
    verification of a project’s funding sources and tax credit proceeds. But in
    its 1995 pamphlet on best practices, NCSHA indicated that although the
    Code does not specifically require the verification of financing sources,
    allocating agencies should require that the provider and the amount of all
    financing sources or terms be certified by the housing project owners.

    All but 1 of the 54 allocating agencies reported requiring independent cost
    verifications. To determine (1) who performed the reviews and (2) how
    much work was done to validate the projects’ development costs, we
    randomly selected a subsample of 48 projects. We found the following:

•   For 41 of the 48 projects, the development costs were verified by third
    parties: 35 by independent public accountants and 6 by state, county, or
    federal agencies. For the remainder, three were not required by the agency
    to submit verified cost statements, and four were certified by the
    developer or general partner instead of verified by independent third
    parties.
•   For the 35 projects that were reviewed by independent public accountants,
    the costs were validated to varying degrees. The cost verifications for 18
    projects were based on an examination engagement, and the verifications
    for 10 projects were based on more limited but agreed-upon procedures.
    For seven projects the independent public accountant performed other
    services.

    15
      In its 1993 publication on cost control standards, NCSHA recommended that independent third-party
    cost certifications be required for projects with 25 or more units. In its 1995 pamphlet on best
    practices, NCSHA recommended that the allocating agencies require certifications for projects of all
    sizes.



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             With respect to the overall information needs of the allocating agencies,
             we could not clearly discern the extent to which the independent public
             accountants’ reports fully addressed those needs. Although the 35 reports
             required by the allocating agencies that we reviewed had a cost focus, only
             19 indicated work directed at validating the costs that qualify for inclusion
             in the tax credit cost base, i.e., eligible basis. Also, 13 of the 35 reports
             appeared to cover additional aspects of project financing, such as loan
             information and syndication agreements.

             To test the reliability of the financial data available to the allocating
             agencies, we reviewed information that they had obtained for our random
             sample of 423 housing projects placed in service from 1992 through 1994.16
             Extrapolating from our sample, we estimate that 14 percent of the housing
             projects received tax credits on the basis of inadequate financial data, i.e.,
             the allocating agency records showed that project financing was out of
             balance with project cost by 5 percent or more. The principal reason for
             this imbalance was the lack of information in allocating agency records on
             the equity investment raised through tax credit awards.

             Accordingly, given the range of third-party validation practices required by
             the allocating agencies and the variations in the types of information
             obtained by the allocating agencies, agencies did not necessarily have
             assurance as to the reliability of the information needed to make tax credit
             decisions. According to an accounting firm with a tax credit specialty, the
             cost for tax credit certifications (opinion on total costs, eligible basis, and
             tax credit amount) prepared on the basis of an audit done in accordance
             with AICPA audit standards would be in the $5,000 to $7,500 range per
             engagement, even for projects costing upwards of $5 million to
             $10 million.



             In implementing their responsibilities for controlling the amount of tax
Conclusion   credits provided to low-income housing projects, allocating agencies need
             to make three critical judgments. First, they need to make a judgment
             concerning the reasonableness of development costs because they are to
             award no more credits to a project than a specified percentage of certain
             agency-approved project development costs as defined by the Code.
             Second, given their cost reasonableness decisions, agencies need to make
             a judgment on the financing arrangements made by a housing project

             16
               We asked the allocating agencies to provide the final data on costs and financing used to complete
             their evaluation of the placed-in-service projects.



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    because the agencies are required to base a tax credit award on the
    financial need of a project subject to the limit computed on
    agency-approved development costs. And third, they need to make a
    judgment on the pricing of the credit, i.e., use an appropriate rate to
    convert credits into an equity investment amount.

    Our review of the controls established by the allocating agencies to make
    these judgments showed that the agencies have adopted a variety of
    measures. These variations in agency controls may provide opportunities
    for the agencies to learn from each other’s experiences about the
    effectiveness of alternative practices. To this end, the state tax credit
    allocating agencies, through their national association (National
    Association of State Housing Agencies), have periodically reviewed state
    practices to identify appropriate standards and best practices. They have
    recently convened a Commission that, among other responsibilities, is to
    consider ways to improve tax credit administration, including matters
    discussed in this report.

    Nevertheless, in controlling costs—that is, in evaluating the
    reasonableness of a project’s development costs, financing deficit, and tax
    credit proceeds—allocating agencies are largely dependent on information
    submitted by developers. If the agencies do not have complete or accurate
    information, they cannot be assured that their controls are effective.
    Although our study was not designed to produce estimates of overfunding
    or underfunding of housing projects, we did identify areas where the
    allocating agencies may be vulnerable to making misjudgments given the
    information available to them in terms of completeness and reliability.

•   First, with respect to cost-related decisions, we found that the range of
    independent cost verification practices varied, and the resulting reports
    did not always address the amount of project development costs that may
    qualify, subject to allocating agency approval, for inclusion in the base for
    computing the maximum tax credit award.
•   Second, with respect to financing decisions, we found that there was no
    independent verification requirement for reconciling sources of project
    funds with project costs, and, for an estimated 14 percent of the housing
    projects, the allocating agency information on project sources and uses of
    funds was out of balance by 5 percent or more.
•   Third, with respect to tax credit pricing decisions, we found that the
    principal reason for the sources and uses of funds imbalance was that the
    allocating agencies lacked information on the equity investment raised
    through tax credit awards.



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                      Without assurance of reliable and complete cost and financing
                      information, the allocating agencies are vulnerable to providing more (or
                      fewer) tax credits to projects than are actually needed.



                      To ensure reliable and complete information for making decisions on tax
Recommendation to     credit awards, we recommend that the Commissioner of Internal Revenue
the Commissioner of   amend tax credit regulations to establish clear requirements to ensure
Internal Revenue      independent verification of key information on sources and uses of funds
                      submitted to states by developers.


                      In commenting on this report, IRS advised us that it agreed with the
Federal Agency and    recommendation and would proceed to determine how best to implement
State Association     it.
Comments and Our
                      NCSHA, in commenting on the report, expressed concern about “bias and
Evaluation            prejudgment” because the report implies that state deviations from
                      Council-recommended best practices are deficiencies. In response, we
                      note that the report repeatedly points out that the states were given
                      flexibility in the administration of the program. The introduction to the
                      chapter specifically states that “The Code provides some broad guidance
                      on how to limit awards but leaves to the state allocating agencies the
                      responsibility for establishing specific standards and controls.” Moreover,
                      with respect to our recommendation for IRS to develop regulations
                      requiring the verification of sources and uses of funds, we made this
                      recommendation to better enable the states to comply with the statutory
                      requirement that they consider the sources and uses of funds before
                      awarding tax credits—a check that had not always taken place.

                      Also, NCSHA indicated that our recommendation did not take
                      cost-effectiveness into account. We disagree. We recognize that costs
                      associated with implementing our recommendations should always be a
                      concern, and we developed the recommendation with that in mind. In
                      recommending that IRS establish requirements for ensuring independent
                      verification of information on sources and uses of funds, we considered a
                      range of options and estimated costs for obtaining such verification.




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Chapter 5

Opportunities Exist to Improve State and
Federal Compliance Oversight Activities

               The Internal Revenue Code provides for dual oversight of the tax credit
               between tax credit allocating agencies and IRS. In general, we found that
               not all allocating agencies fulfilled the requirements of their compliance
               monitoring programs; and, although IRS has been developing programs, it
               did not have sufficient information to determine state or taxpayer
               compliance.

               In general, states are responsible for monitoring project compliance with
               rent, income, and habitability requirements after the projects are placed in
               service and for reporting any incidence of noncompliance found to IRS. IRS
               is responsible for issuing tax credit regulations establishing state
               monitoring procedures and for ensuring that the states include valid
               monitoring procedures in their qualified allocation plans. It is also
               responsible for ensuring that taxpayers claim only those housing credits to
               which they are entitled and that states do not exceed their annual tax
               credit allocation ceilings.

               Figure 5.1 shows the interrelated nature of the federal/state oversight
               responsibilities and the reporting mechanisms that are in place to support
               the effort.




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                                                 Opportunities Exist to Improve State and
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Figure 5.1: Tax Form Flow and Oversight

                                                                 1065, Schedule K,
                                                                 and Schedule K-1's



                                                                                                       Investors
                                                                                                                             F1120
                                                                                Schedule K-1s        (Corporations)
                                                          Syndicator
                                                     (General partner of an
                                                    investment partnership)
                                                                                Schedule K-1s

                                                                                                       Investors             F1040
                                                                                                      (Individual)
                                             Schedule K-1s




                              F8609, and F8823                                                       State housing
                                                                                                        agency



                                                                                                             F8609, F8610,
                                                                                                             and F8823

                                                                         F1065, Schedule K
                                                                         and K-1s, F8609


                                                                         F1065, F8609,                    IRS
                                                                         Schedule K, and
                                                                         K-1s
                      Developer
           (General partner/managing owner
                     of the project)


                                                                                                                        (Figure notes on next page)




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Legend:

Schedule K - Partners’ Shares of Income, Credits, Deductions, etc: The partnership uses
Schedule K to report the partnership’s income, credits, deductions, etc.

Schedule K-1 (Form 1065) - Partner’s Share of Income, Credits, Deductions, etc: The
partnership uses Schedule K-1 to report the partners’ share of the partnership’s income, credits,
deductions, etc.

Form 1040 - U.S. Individual Income Tax Return: Form 1040 is used by individuals to file their
annual tax returns.

Form 1065 - U.S. Partnership Return of Income: Form 1065 is used by taxpayers to file their
partnership income tax returns.

Form 1120 - U.S. Corporation Income Tax Return: Form 1120 is used by corporations to file
their income tax returns.

Form 8609 - Low-Income Housing Credit Allocation Certification: Form 8609 is used by
allocating agencies to notify IRS and a project owner of a tax credit award. A copy is also
attached to a project owner’s tax return.

Form 8610, Annual Low-Income Housing Credit Agencies Report: Form 8610 is used by
allocating agencies to transmit Form(s) 8609 to IRS and to report the dollar amount of housing
credit allocations issued during the calendar year.

Form 8823 - Low-Income Housing Credit Agencies Report of Noncompliance: Form 8823 is
used by allocating agencies to notify IRS of a building that is not in compliance (or returns to
compliance) with low-income housing tax credit regulations.

Source: GAO discussions with IRS.




All states reported to us that they had adopted compliance monitoring
procedures that met or exceeded the requirements established by IRS.
However, in 1995, several states did not do as many desk reviews or
on-site inspections as they reported were included in their qualified
allocation plans. IRS regulations do not require states to report on all their
monitoring activities, so IRS has no means for determining whether
agencies are meeting their monitoring requirements. Also, IRS’ monitoring
regulations do not require states to make on-site inspections of projects or
obtain building code violation reports from local government units.
Therefore, states that do not make on-site inspections or get local building
code violation reports are unlikely to detect building code violations that
affect project habitability.

Most states had reported instances of noncompliance to IRS, but IRS’
proposed revision to the noncompliance form does not provide for the
states to indicate the number of units that were out of compliance by
specific types of noncompliance, such as tenant income exceeding




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                   eligibility requirements. Without this information, IRS cannot determine
                   whether the noncompliance warrants recapturing tax credits from project
                   owners.

                   IRS recently initiated tax credit compliance activities to detect
                   noncompliant taxpayers. IRS does not know the extent of taxpayer
                   noncompliance with the housing credit but believes that its audit program,
                   which began in 1995, will provide IRS with sufficient data to make an
                   estimate. At the time of our review, few audits had been completed; thus,
                   it was too early to assess the audit program’s effectiveness. Also, IRS’
                   computerized program to match state tax credit information to credits
                   reported on partnership returns was still under development at the time of
                   our review. Similarly, IRS was still developing a computerized system for
                   monitoring allocating agencies’ compliance with Internal Revenue Code
                   restrictions on the total number of credits that may be used in one year.

                   Although both states and IRS conduct various tax credit oversight
                   activities, there is no federally required oversight on the adequacy of state
                   agencies’ controls for meeting tax credit requirements. Recently
                   completed state audits of two state credit agencies found several
                   weaknesses in the agencies’ controls that indicate that there may be a
                   need for some sort of independent oversight. One option to improve
                   oversight would be to include the tax credit program within the scope of
                   the Single Audit Act Amendments of 1996 (Single Audit Act). The single
                   audit process is an important accountability tool for the federal
                   government in providing oversight for hundreds of billions of dollars of
                   federal financial assistance provided annually to state and local
                   governments and nonprofit organizations. A single audit involves, among
                   other things, tests of the audited entity’s controls over compliance with
                   federal laws and regulations. However, neither the Single Audit Act nor
                   implementing guidance issued by OMB includes tax credits in the definition
                   of federal financial assistance.


                   All states reported to us that they had established monitoring procedures
Opportunities to   in their qualified allocation plans that were in compliance with IRS’ project
Improve State      monitoring regulations. However, several states reported that they did not
Oversight          meet the requirements of IRS’ monitoring regulations in 1995.

                   IRSallowed states to adopt monitoring procedures that did not call for
                   making on-site inspections of projects or for obtaining reports of building
                   code violations from local government agencies that perform building



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                         inspections. On-site inspections or local building inspection reports are
                         necessary for states to determine whether the projects meet the
                         habitability requirements in the Internal Revenue Code.

                         Most states reported to us that they were complying with IRS requirements
                         to submit reports on noncompliance that they found during their
                         monitoring. However, many states indicated that IRS did not provide
                         sufficient guidance on the types of noncompliance that are reportable.
                         Also, many states reported that they go beyond federal monitoring
                         requirements when state funds are involved in the projects. Also, in
                         addition to monitoring for project compliance, most states said they try to
                         educate owners on how to stay in compliance with tax credit rules.


All State Agencies Had   Since June 30, 1992, for state agencies to have a qualified allocation plan,
Monitoring Procedures    they must include a procedure for monitoring tax credit projects to
That Met IRS             determine if the projects are in compliance with tax credit program
                         requirements. IRS regulations require state agencies to annually review
Requirements, but Some   project owners’ certifications that their projects met all low-income
States Did Not Follow    housing statutory requirements, such as serving the minimum number of
Their Procedures         low-income residents; ensuring project habitability in terms of local
                         health, safety, and building codes; and ensuring that each low-income unit
                         was rent-restricted. In addition to reviewing all owner certifications, state
                         agencies were required, at a minimum, to review tenant income
                         certifications and rent charges of projects under their jurisdiction using
                         one of the following three monitoring options:

                         Option 1: Obtain from owners and review the annual income certifications
                         for at least 50 percent of the projects, including the documentation
                         supporting the certifications and tenant rent records in at least 20 percent
                         of the low-income units in these projects.

                         Option 2: Make annual on-site inspections of at least 20 percent of the
                         projects, and review the low-income certifications, the documentation
                         supporting the certifications, and rent records for each tenant in at least
                         20 percent of the low-income units in those projects.

                         Option 3: Obtain from all project owners tenant income and rent records
                         for each low-income unit and, for at least 20 percent of the projects,
                         review annual tenant income certifications, backup income
                         documentation, and rent records for each low-income tenant in at least
                         20 percent of the low-income units in those projects.



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                                          In the information the 54 state agencies provided us, all reported they had
                                          project monitoring programs that complied with IRS regulations. As shown
                                          in table 5.1, 48 of the 54 state agencies (about 90 percent) reported that in
                                          1995 they met or exceeded the minimum monitoring requirements; the
                                          remaining 6 agencies reported they did not do as many on-site or desk
                                          reviews as required by the monitoring option they reported that they used.


Table 5.1: Number of State Agencies That Either Met, Exceeded, or Failed to Meet IRS’ Monitoring Requirements in 1995
                                                  Conducted either        Conducted both           Did fewer    Total number
                                                     desk or on-site      desk and on-site      reviews than          of state
Option                                                     reviewsa                reviews          required        agencies
1                                                                                                1                                     1
2                                                                     6                          28                  5                39
3                                                                     3                          10                  1                14
Totals                                                                9                          39                  6                54
                                          a
                                           The state agencies using option 2 conducted only on-site reviews, and the agencies using
                                          option 3 conducted only desk reviews.

                                          Source: GAO analysis of state agency questionnaires.



                                          IRS’monitoring regulations require states to submit reports on any
                                          noncompliance found during desk reviews or site visits. However, IRS does
                                          not require states to submit reports on their monitoring activities that
                                          show the number of projects and units inspected each year. This
                                          information is important because, under the Internal Revenue Code, in
                                          order for a state to have a qualified allocation plan it must include a
                                          monitoring procedure that satisfies IRS’ monitoring regulations. Further,
                                          under the Code, a state cannot allocate credits unless it has a qualified
                                          allocation plan.

                                          Just having a monitoring procedure in the qualified allocation plan does
                                          not necessarily mean that a state follows that procedure. As noted earlier,
                                          we found that six states did not follow their monitoring procedures in
                                          1995. Congress enacted the monitoring requirement as a means of
                                          ensuring that tax credits were going to projects that qualified for the credit
                                          throughout the 15 year tax credit compliance period. One way for states to
                                          know whether projects remain qualified for tax credits is for the states to
                                          carry out their monitoring procedures. Similarly, for IRS to know whether a
                                          state meets IRS’ monitoring requirements, it needs some sort of report from
                                          the state on the number of monitoring inspections made. IRS could then




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                                           compare these numbers with the number of inspections that should be
                                           made under a state’s monitoring procedure in its qualified allocation plan.

                                           An annual report on state monitoring activities that simply shows the
                                           number and types of inspections made (i.e., desk reviews and on-site
                                           inspections) should not be costly for the states to complete. States
                                           evidently have these types of records because they were able to provide us
                                           with this type of data for 1995 when we asked for it.


NCSHA Has                                  Although IRS has established minimum monitoring requirements, NCSHA has
Recommended States Do                      recommended that state agencies do more than required. For the most
More On-Site Inspections                   part, state agencies met or exceeded IRS’ monitoring requirements.
                                           However, in 1995 some of the agencies that did on-site inspections fell
                                           short of meeting the minimum on-site monitoring reviews recommended
                                           by NCSHA in 1993. NCSHA believed that IRS’ compliance monitoring rules
                                           were inadequate for preventing the abuse and physical deterioration that
                                           plagued many subsidized housing projects in the past.1 Consequently, in its
                                           Standards for Tax Credit Administration, NCSHA recommended that on-site
                                           inspections be made to each project (1) within 1 year of its being placed in
                                           service and (2) at least once every 3 years thereafter.

                                           On the basis of data state agencies provided us, we found that 22, or about
                                           41 percent, of the 54 state agencies had adopted both NCSHA site visit
                                           recommendations. Table 5.2 shows the number of agencies that fully met,
                                           partially met, or did not meet NCSHA monitoring guidelines.

Table 5.2: Number of State Agencies
That Either Fully Met, Partially Met, or                                                                                          Number of state
Did Not Meet NCSHA’s Monitoring            NCSHA guideline                                                                             agencies
Guidelines in 1995                         On-site visit made within 1 year of placed in service date                                            8
                                           On-site visit made at least once every 3 years                                                       11
                                           On-site visit made both within 1 year of placed in service date and
                                           once every 3 years                                                                                   22a
                                           Did not make on-site visits either within 1 year of placed in service
                                           date or every 3 years.                                                                               13
                                           Total number of state agencies                                                                       54
                                           a
                                               Thirteen of the 22 agencies also performed on-site visits prior to the placed in service date.

                                           Source: GAO analysis of state agency questionnaires.




                                           1
                                           “Standards For State Tax Credit Administration,” adopted by the National Council of State Housing
                                           Agencies (1993).



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                                       On the basis of our analysis of state-provided data on sampled properties,
                                       we estimate that as of June 1996, 75 percent had received an on-site
                                       monitoring visit. We estimate that the average time between when a
                                       project was placed in service and when the first site visit was made was 21
                                       months, which was 9 months more than the 12 months recommended by
                                       NCSHA.


                                       Making site visits can allow state agencies to directly assess the
                                       compliance status of projects and the physical condition of buildings.
                                       Table 5.3 shows by type of monitoring review the types and frequency of
                                       noncompliance found by the states’ desk reviews and on-site inspections.

Table 5.3: Estimates on the Types of
Noncompliance Identified by Desk                                                          Percent of time type        Percent of time type
Reviews and On-Site Inspections That                                                        of noncompliance            of noncompliance
Found at Least One Incident of                                                            found through desk                found through
Noncompliance                          Type of noncompliance                                           reviewa         on-site inspectiona
                                       Tenant(s) not income eligible                                             30                           13
                                       Rents too high                                                            12                            7
                                       Building code violation or other
                                        building condition                                                        0                           43
                                                                               b
                                       Administrative requirement not met                                        35                           10
                                       Annual income certification either
                                        submitted late or not received                                           53                           34
                                       Improper income certification or failure
                                         to properly verify certification                                         2                           26
                                       Other                                                                     16                            7
                                       a
                                        Noncompliance was identified through desk audits for 37 projects and through on-site
                                       inspections for 94 projects. In some cases, more than one type of noncompliance was found
                                       during a review.
                                       b
                                        This category includes forms not filed on time, forms filed with incomplete information, or failure
                                       to meet other administrative requirements.

                                       Source: GAO’s analysis of sampled project questionnaires.



                                       As shown in table 5.3, we estimate that in 43 percent of the instances when
                                       on-site inspections found noncompliance, the inspection identified a
                                       compliance problem involving the condition of the building. But, we
                                       estimate that no such violations were found during desk reviews. Building
                                       violations would generally not be detectable through a desk review of the
                                       owners’ records unless the records showed the violations or the state also
                                       obtained such information as building code inspection reports that were




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                         performed by the local government unit responsible for making these
                         inspections.

                         Since states have the responsibility for ensuring that projects are
                         habitable, it is unlikely that they can fully meet this responsibility unless
                         they make site visits or obtain local building inspection reports. This
                         points out a potential weakness in IRS’ monitoring requirements, since two
                         of the three monitoring options do not require states to make on-site visits
                         or obtain local building inspection reports. Although NCSHA’s monitoring
                         guidelines recommend on-site visits, the states have no legal requirement
                         to follow these guidelines. States currently doing site visits could cease
                         making them and still be in compliance with IRS requirements.

                         According to IRS officials, IRS did not mandate on-site inspections, because
                         some allocating agencies indicated that such a requirement would be
                         burdensome. We would make two points in this regard. First, states had
                         made on-site visits to 75 percent of our sampled properties. Thus, many
                         states obviously consider this to be a best practice that is worth the cost.
                         Second, there are less costly or less burdensome ways to obtain
                         information on the physical condition of the housing projects. For
                         example, states could contact local government units to obtain
                         information on building inspections that may have been done on the
                         properties. However, IRS regulations do not cite this as a requirement or as
                         an option.


Most State Agencies      As part of their monitoring responsibilities, state agencies are required to
Reported Noncompliance   report to IRS and project owners all instances of owner noncompliance or
Issues to IRS            the failure of owners to certify that projects meet statutory requirements.2
                         For each building affected by the noncompliance, the states are to file
                         Form 8823, Low-Income Housing Credit Agencies Report of
                         Noncompliance, to meet this reporting requirement. Agencies are to
                         explain on the form the nature of the noncompliance or failure to certify
                         and indicate whether the owner has corrected the problem.

                         According to compliance data states provided us, noncompliance
                         reporting to IRS by the state agencies varied in amount and significance.



                         2
                          State agencies also have to notify owners, in writing, about the noncompliance and failure to certify.
                         Owners may be given up to 90 days to correct any noncompliance or certification. The state agencies
                         then have 45 days after the correction period to notify IRS of the infraction regardless of whether the
                         infraction has been corrected. The correction period may be extended for up to 6 months if the agency
                         determines that there is good cause for granting an extension.



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                                            Table 5.4 shows the number of Form 8823s state agencies reported to us
                                            that they submitted to IRS as a result of their 1995 monitoring activities.

Table 5.4: Number of Form 8823s
Submitted by State Agencies to IRS in                                                                                       Total number of
1995                                        Number of Form 8823s submitted to                    Number of state                Form 8823s
                                            IRS                                                       agencies                    submitted
                                            None                                                                   6                     0
                                            1 to 10                                                                6                    33
                                            11 to 25                                                               7                   127
                                            26 to 50                                                             12                    422
                                            51 to 100                                                              7                   479
                                            101 to 1,000                                                         14                   4,172
                                            over 1,000                                                             2                  4,401
                                            Total                                                                54                   9,634
                                            Source: GAO’s analysis of state agencies reported monitoring results from state agency
                                            questionnaire.



                                            As shown in table 5.4, six agencies said they did not report any
                                            noncompliance to IRS, and two others reported over 1,000 Form 8823s.
                                            Since IRS’ guidance to the agencies has been to report all noncompliance,
                                            no matter how insignificant it may seem, noncompliance reported can
                                            range from a serious infraction, such as failure to properly screen tenants
                                            for program eligibility, to an infraction such as a loose electrical outlet
                                            cover. According to state agency officials, about 31 percent, or 3,029, of
                                            the 9,634 Form 8823s submitted in 1995 had infractions that warranted IRS
                                            enforcement action.

                                            Although most state agencies filed Form 8823s, several questioned the
                                            need to report noncompliance issues that have been corrected. According
                                            to IRS officials, all noncompliance, whether corrected or not corrected,
                                            needs to be reported because the tax consequences may be dependent on
                                            the timing of the correction of the noncompliance.

                                            Some states also reported that they needed clarification on various issues
                                            dealing with project compliance. For example, additional clarification was
                                            requested by

                                        •   32 states on the types of noncompliance that should be reported on Form
                                            8823,
                                        •   26 states on circumstances prompting recapture of tax benefits, and




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                             •   28 states on IRS’ authority to enforce project-specific requirements
                                 established by the states.

                                 At the time of our review, IRS was in the process of revising Form 8823.
                                 The proposed revisions may resolve some of the states’ concerns about
                                 the types of noncompliance that should be reported. For example, the
                                 current Form 8823 requires the allocating agency to indicate the date of
                                 noncompliance, provide a description of the noncompliance, and indicate
                                 whether the violation has been corrected. On the other hand, the proposed
                                 form includes a “check block” system for allocating agencies to check
                                 which of 10 categories describe the noncompliance being reported. These
                                 categories include violations for building disposition; income
                                 requirements; health, safety, and building codes; and changes to the
                                 eligible basis or number of low-income units or rent-restricted units. The
                                 proposed form also asks for summary information, including the total
                                 number of residential rental units in the building, the total number of
                                 low-income units, the total number of units reviewed by the state during
                                 the compliance check, and the total units determined to be out of
                                 compliance.

                                 Although we believe the proposed form is an improvement over the
                                 current form because it lists the 10 types of noncompliance that should be
                                 reported, two other changes to the proposed form might allow IRS to better
                                 determine the severity of specific noncompliance categories. For example,
                                 for each category checked, it would be useful to know the number of units
                                 out of compliance and the date the noncompliance was corrected so that
                                 IRS could better determine whether the noncompliance has a tax
                                 consequence for the project owners.


Additional Compliance            Many states perform more compliance activities for low-income housing
Activities Carried Out for       tax credit projects that receive state funding than they do for projects that
Projects That Also Receive       do not receive any additional state funding. Forty of the 54 tax credit
                                 allocating agencies provided state funds as another source for project
State Funds                      financing, and 23 of these agencies did more monitoring of state-funded
                                 projects than of projects with no state funding. Some activities carried out
                                 for state-funded projects were:

                             •   monitoring revenue and operating statements,
                             •   reviewing funding of reserve accounts, and
                             •   conducting more physical inspections of units.




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                              These activities are to allow the state to assess the financial health of the
                              project or the physical condition of the buildings, and therefore the
                              long-term viability of the project as housing for low-income tenants.
                              Thirteen allocating agencies that provide state funds reviewed monthly
                              revenue and operating statements, and 25 agencies required annual
                              revenue and operating statements. By comparison, only seven agencies
                              reviewed either of these statements for projects not receiving any state
                              financing.

                              Similarly, 24 agencies reviewed funding of replacement and operating
                              account reserves for projects receiving state funds, and 5 reviewed such
                              reserves for projects funded only with federal tax credits. We do not know
                              whether projects in states with no reserve requirements are funding such
                              reserves or not. However, if reserves are not available when the housing
                              starts to age, the financial viability of the project could be in jeopardy
                              because funds may not be available to make needed repairs.

                              In addition to requiring financial reports and reserve funding, states were
                              more likely to physically inspect sample units in projects if there was state
                              funding involved. Ninety-five percent made unit inspections when the
                              project had received state funds, and 80 percent made unit inspections
                              when no state funds had been provided to the project. Again, the physical
                              condition of the housing has an impact on the viability of the project and
                              the likelihood that it will continue to provide either low-income or market
                              rate units after the 15 year tax credit compliance period.



Allocating Agencies Efforts   Most allocating agencies reported making efforts to help project owners
to Inform Owners of           and managers effectively administer the tax credit program through
Compliance Rules              providing information or training. Since the program is administered at the
                              most basic level by the project owners and managers who set rents and
                              accept tenants into qualified units these efforts would seem useful.
                              Although not required by IRS to do so, 45 allocating agencies reported that
                              they either provide project owners and managers with optional training on
                              compliance or require such training. Forty-eight allocating agencies also
                              provided compliance manuals that set out tax credit rules with which a
                              project must comply. All allocating agencies reported providing either
                              manuals or training, or both, to project owners and managers.




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                            IRS is responsible for ensuring that taxpayers claim only those tax credits
Opportunities to            for which they are entitled and for ensuring that states do not exceed their
Improve IRS’                annual tax credit ceilings. A 1995 IRS report on its internal controls, which
Oversight Activities        was done under the Federal Managers’ Financial Integrity Act (FMFIA),
                            identified the low-income housing tax credit program operations as a
                            material weakness. The report noted that IRS was vulnerable to a loss of
                            tax revenues due to taxpayer noncompliance, fraud, and abuse because it
                            did not have systems in place to detect the noncompliance.

                            Given the FMFIA report and other internal findings, IRS adopted a
                            low-income housing tax credit compliance strategy consisting of outreach
                            activities aimed at keeping state allocating agency officials informed about
                            program requirements and traditional enforcement tools (audits and
                            document matching) aimed at detecting potential noncompliant states and
                            taxpayers.

                            To verify that taxpayers do not claim more credits than they are entitled to
                            claim, IRS has established a program to audit the returns of the key project
                            owners, which are generally partnerships. IRS was using state
                            noncompliance reports to develop potential audit leads, but as of
                            September 30, 1996, few audits had been completed. IRS was also
                            developing a computerized program that would match state tax credits
                            awarded to projects to owners’ tax returns to determine whether owners
                            properly reported credit awards. We simulated this match on a sample of
                            projects and found little noncompliance. To determine the level of
                            compliance with the tax credit rules, IRS needs to develop an estimate of
                            taxpayer compliance. To verify that state allocating agencies do not
                            exceed their tax credit ceilings, IRS was developing a document matching
                            program using state credit allocation reports to make this check.


IRS’ Outreach Efforts to    As a means of helping state tax credit allocating agencies to comply with
Keep States Informed        low-income housing tax credit requirements, IRS established a federal/state
About Credit Requirements   advisory group in November 1995 consisting of representatives from IRS,
                            HUD, the National Park Service, and NCSHA. This group has met periodically
                            to discuss outreach efforts, information exchange, and legislative activity.
                            In addition, staff from IRS’ low-income housing compliance unit, chief
                            counsel, and national office have attended seminars sponsored by NCSHA.
                            Representatives from the state allocating agencies also attended these
                            seminars. According to IRS officials, during these seminars, state agencies
                            were provided information on such subjects as the tax credit law, filing
                            requirements, and property qualifications. Further, according to



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                         representatives of IRS’ chief counsel office, they receive daily telephone
                         calls from state allocating agency officials concerning technical aspects of
                         the low-income housing tax credit law.


IRS Has Recently         IRS is responsible for ensuring taxpayer compliance with the Internal
Developed a Tax Credit   Revenue Code’s low-income housing tax credit provisions. Just because a
Audit Program, but Few   housing project received a tax credit allocation from the state does not
                         automatically mean that the owners may take this credit amount annually
Audits Have Been         for 10 years. For example, a housing project may qualify only for a portion
Completed                of the allocation based on the number of housing units or floor area of
                         units occupied by qualified tenants at the end of the tax year, so the annual
                         tax credit amount may vary. Also, as discussed in chapter 4, states have
                         awarded tax credits without obtaining audited construction and
                         development cost certifications from independent third parties. Therefore,
                         IRS may not be able to rely on cost certifications submitted by project
                         developers to the state agency when it conducts its tax credit audits. IRS
                         would need to audit these costs to ensure that nonqualifying items are not
                         included in a project’s qualified basis, which is supposed to include costs
                         incurred by the developer only for valid rehabilitation, new construction,
                         and acquisition costs. Conducting these audits requires specialized
                         knowledge of the tax credit law.

                         In 1995, IRS established a national examination program under the
                         leadership of IRS’ Market Segment Specialization Program3 with a core
                         examination group in Philadelphia. The purpose of this program was to
                         have a national coordinated approach for addressing tax credit
                         compliance and to train agents on the intricacies of the tax credit laws.
                         Each district office was requested to designate a coordinator to examine
                         and monitor tax credit audits in its district. To facilitate this audit
                         initiative, a training program was developed. By April 1996, revenue agents
                         in 31 of the 33 IRS district offices had been trained and were assigned 180
                         potential audit cases. The potential audit cases were developed from
                         reports of noncompliance made by the states. The Philadelphia group was
                         to oversee the audit effort and accumulate data on which to assess
                         compliance.

                         As of the end of fiscal year 1996, IRS had completed work on 35 audit cases
                         (31 of the 180 assigned cases and 4 additional cases developed by District
                         Offices). IRS found 12 to be in noncompliance with the tax laws and

                         3
                          The Market Segment Specialization Program seeks to improve voluntary compliance by identifying
                         compliance problems within market segments (taxpayers with common characteristics and tax
                         situations) and prescribe appropriate treatments.



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                           assessed taxes and penalties of about $500,000 for reasons ranging from
                           noncompliance with housing requirements to incorrect determination of
                           eligible basis. A set of earlier audits related to a fraudulent tax credit
                           scheme (a scheme that helped to prompt the tax credit audit initiative) and
                           had resulted in tax adjustments totaling about $5 million.


IRS Is Attempting to       To supplement its tax credit audit initiative, IRS is exploring ways to make
Develop a Housing Tax      better use of state-reported information on tax credit awards. IRS’ tax
Credit Document Matching   credit database currently contains Form 8609 data on the tax credits
                           awarded to tax credit projects. IRS is exploring the possibility of
Program                    computer-matching tax credit awards reported on Form 8609s against tax
                           credit amounts reported on housing project tax returns, i.e., the overall
                           amount of tax credits that the project is distributing to its investors.4 The
                           first step toward resolving any significant discrepancies uncovered
                           through the match would be through correspondence with the owners.

                           To test the results that could be obtained from such a matching program,
                           we requested tax year 1995 tax returns from IRS for our 423 sample
                           projects to see if we could manually match state tax credit awards to the
                           returns. As of January 31, 1997, we received and reviewed 253 project
                           returns that had been awarded $83.3 million in tax credits and found that 3
                           projects, awarded annual tax credits totaling $930,000, overreported the
                           credits by almost $50,000.

                           Although our match did not uncover significant overreporting of the
                           credit, we did find what could be a significant nonfiling problem. Our
                           match of state data to IRS records found that 37 projects, awarded
                           $28.3 million in tax credits, did not file their 1995 tax returns.5 Five of the
                           projects had filed tax year 1994 returns and would have been detected by
                           IRS as 1995 nonfilers in IRS’ stop filer program, which identifies businesses
                           that file one year but not the next. However, since IRS’ records showed that
                           the other 32 projects had not filed 1994 returns, these projects would not
                           have been detected in the stop filer program. Matching state allocation


                           4
                            IRS currently has a computer matching program to identify individual taxpayers who potentially
                           underreported their taxable income, overreported certain deductions, or failed to file tax returns.
                           Third parties, such as banks and other businesses, are required to file information returns to report
                           various payments made to or by individuals. IRS matches amounts on information returns against
                           amounts reported on individual tax returns to identify unreported income, overstated deductions, and
                           nonfilers.
                           5
                            In addition to the 37 nonfilers, 12 projects, awarded $5.1 million tax credits, had not filed their returns
                           but had received a filing extension from IRS; and 121 projects, awarded tax credits of $51.3 million,
                           had filed returns, but IRS did not retrieve them in time for our review.



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                           documents to IRS’ records might be the only way IRS could readily detect
                           such nonfilers.6

                           Although matching state allocation documents to housing project
                           partnership tax returns can uncover overreported credits or nonfiling, this
                           match would not detect noncompliance at the partner level. But
                           overreporting of tax credits by partners could be detected by matching tax
                           credits reported on the Schedule K-1s to the partners’ tax returns. In a
                           June 1995 report on partnership compliance, we recommended that IRS
                           match Schedule K-1 to tax returns.7 However, resource constraints have
                           prevented IRS from transcribing all the Schedule K-1s reporting tax credits
                           it receives so that it could have an effective matching program.


An Estimate of Housing     IRS does not have an estimate of how many taxpayers may not be entitled
Tax Credit Compliance      to all of the credits they claim. IRS is depending on the results of its tax
Would Help IRS Determine   credit audit program to develop such an estimate. According to IRS
                           officials, not enough audit cases have been worked to determine the
Its Enforcement Strategy   extent of noncompliance. However, even after IRS completes a significant
                           number of audits under its current approach, the results will not
                           necessarily be a reliable measure of noncompliance. For the most part, IRS’
                           audit efforts have been directed at targeting housing projects where states
                           have filed reports of noncompliance to IRS as a result of the states’
                           monitoring efforts. Thus, potentially noncompliant taxpayers whose
                           projects the states did not find noncompliant would not be routinely
                           picked up in IRS’ current tax credit audit program. According to data we
                           received from the state agencies, no compliance problems were found at
                           about 75 percent of the projects inspected in 1995.

                           Without more information on tax credit compliance issues, IRS is not in a
                           position to know how many or what type of compliance resources (audits
                           or document matching) it needs to effectively address the issues. One way
                           to develop a valid estimate of the degree of taxpayer noncompliance
                           would be to audit a statistical sample of first-tier partnership returns on
                           which the credit was claimed. The results of these audits could provide IRS
                           with a measure of the compliance level as well as the types of tax credit

                           6
                            Since these nonfilers were partnerships, failure to file partnership returns (Form 1065, U.S.
                           Partnership Return of Income, Credits and Deductions, etc.) would not necessarily mean that the
                           partners had not claimed the tax credits on their individual or corporate tax returns. The partnerships
                           could have issued the partners’ Schedule K-1, Partner’s Share of Income, Credits and Deductions, etc.,
                           which shows each partner’s separate share of the total partnership business activity, including the tax
                           credit.
                           7
                            Tax Administration: IRS’ Partnership Compliance Activities Could be Improved (GAO/GGD 95-151,
                           June 16, 1995).



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                            noncompliance, such as nonqualifying items in projects’ qualified basis.
                            These types of data might also enable IRS to better target its low-income
                            housing tax credit audit resources.

                            In determining whether to do such a study, IRS would need to weigh the
                            costs and benefits of doing the study versus relying primarily on the
                            results of its audit program to obtain data on the degree and types of tax
                            credit noncompliance. For example, on the benefit side, IRS should
                            consider the potential for recapturing tax credits since the tax credit
                            program involves billions of tax dollars and complex tax law issues.


IRS Is Developing a         The Internal Revenue Code gives IRS responsibility for ensuring that states
Document Matching           do not exceed their tax credit allocation ceilings. A state’s credit ceiling is
Program to Determine        composed of (1) annual per capita credit allotment, (2) unused per capita
                            credits from the previous year’s allotment that the state did not allocate,
Whether States Exceed       (3) credit amounts that were initially allocated in previous years and were
Their Tax Credit Ceilings   returned in the current year, and (4) credits given the state from the
                            national pool of credits not used by other states. State agencies are to
                            report this information annually to IRS on Form 8610, Annual Low-Income
                            Housing Credit Agencies Report. This form also shows the dollar amount
                            of the state’s tax credit ceiling that was allocated during the calendar year.

                            The Code also requires states to annually report to IRS the amounts finally
                            awarded to individual projects on a building-by-building basis. States are
                            to report this information to IRS on Form 8609, Low-Income Housing
                            Credit Allocation Certification, which is not issued until the project is
                            placed in service. The form shows both the placed in service date and the
                            allocation date. The year that a project is placed in service can be different
                            from the allocation year because, in certain cases, developers have until
                            the end of the second year after the credit is allocated to put the project in
                            service. For example, a developer that received a 1992 allocation has until
                            the end of 1994 to place the project in service.

                            To determine whether tax credit awards were within statutory ceilings, at
                            the time of our review, IRS was developing plans to track both credit
                            allocations and placed in service awards on a building-by-building basis.
                            Since the Form 8609 shows the allocation date, it would appear that IRS
                            could determine whether states exceeded their credit ceiling by totaling all
                            the Form 8609s with the same allocation year and comparing this total to
                            the total allocations shown on the Form 8610s for that year.




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                           As part of the analysis that would need to be done to make this
                           reconciliation, IRS would need to adjust each year’s credit ceiling by the
                           amount of tax credits that were returned by developers in subsequent
                           years. These returned credits may be substantial. For example, in 1994 the
                           states returned about $80 million tax credits for reallocation, according to
                           their Form 8610 filings. However, although the Form 8610 shows the total
                           amount of credits that were returned from prior years’ allocations, it does
                           not identify them by allocation year. Therefore, unless IRS collects data on
                           the allocation year of returned credits, it would not have an amount to
                           compare Form 8609 totals against. Thus, IRS would not have a clear basis
                           for determining whether states stay within their tax credit ceilings.

                           Collecting this additional data on returned credits would also allow IRS to
                           determine whether the states are fully using their tax credit allocations. As
                           discussed in chapter 3, a significant gap exists between the amount of tax
                           credits that have been allocated by states and the amount of credits that
                           states and IRS records show were awarded to projects that were placed in
                           service.


                           Most federal programs operated by state and local governments are
Little Independent         subject to independent oversight of state expenditures of federal funds.
Oversight of State         The Single Audit Act,8 which is an important accountability tool for the
Housing Agencies’          hundreds of billions of dollars of federal financial assistance administered
                           by state and local governments and nonprofit organizations, does not
Operations                 apply to tax credits because credits are not considered federal financial
                           assistance under the Single Audit Act or OMB implementing guidance. Two
                           state agencies have recently been audited by third parties, and weaknesses
                           were found in the states’ controls over the tax credit allocation process.
                           Although section 42 of the Internal Revenue Code is silent on IRS’ authority
                           to oversee state agencies’ operations, other sections of the Code implicitly
                           give IRS the authority to audit state agencies’ records. However, subjecting
                           the low-income housing tax credit program to the single audit process may
                           be a more efficient, effective, and less federally intrusive way of
                           monitoring state agency controls over the program.


Third-Party Reviews of     According to information provided us by the allocating agencies,
Two State Agencies Found   third-party reviews of state agencies’ low-income housing credit
Control Weaknesses         operations have uncovered control weaknesses. Twenty agencies reported
                           that their operations were audited by either the state or an independent

                           8
                            The Single Audit Act was amended by the Single Audit Act Amendments of 1996.



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    third-party audit organization. Financial audits were performed on 17
    agencies, and performance audits (e.g. assessing compliance with tax laws
    and regulations) were conducted on the remaining 3 agencies. One of the
    performance audit reports was published in 1991, and therefore it
    addressed problems that the state might have had early in program
    implementation. However, the other two performance audit reports, based
    on work performed in Texas and in New York State, were published in
    1996 and described several internal control problems that raised questions
    about the possible need for ongoing oversight of state allocating agencies’
    operations. These two states ranked third and second, respectively, among
    state agencies in terms of tax credit allocations awarded to them by IRS in
    1994 and accounted for about 14 percent of the total tax credits available
    nationwide in 1994.

    The Texas audit was conducted by the Texas Office of the State Auditor.
    The following are several problems cited in the audit report.

•   As discussed in chapter 3, agency management overrode staff
    recommendations on credit allocations in 29 of 46 projects that were
    evaluated for tax credits during one tax credit allocation cycle in 1995. The
    staff’s recommendations were appropriately documented and based on
    applicable threshold and selection criteria.
•   In contrast to staff recommendations, agency management decisions were
    not well documented and failed to include Underwriting Department
    recommendations to the agency’s Board of Directors, which was
    customary for projects funded by other state and federal housing
    programs.
•   Board members were in frequent contact with tax credit program staff.
    Since several of these Board members were actively involved in housing
    and real estate activities, this raised concerns of at least an appearance of
    a conflict of interest.
•   Several projects that initially were rejected by the Underwriting
    Department were given conditional approval at the request of the Program
    Manager. However, there was no documentation that the agency’s Board
    of Directors was informed of these conditions nor that these projects were
    returned to the Underwriting Department to ensure that the conditions
    had been met.

    On June 14, 1996, the New York Office of the State Comptroller released a
    performance audit report of the New York State tax credit program




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administered by the Division of Housing and Community Renewal (DHCR).9
It also included a written response by DHCR to each of the major audit
findings. In general, the audit found that DHCR had not established
adequate procedures to ensure that all tax credit allocations are
reasonable and appropriate. Set forth below are summaries of two specific
audit findings concerning federal tax credit requirements and DHCR’s
response to each finding.

1. Project costs were not evaluated for reasonableness through the use of
established formal criteria or in a manner similar to other state housing
programs, which used cost guidelines limiting the cost per housing unit for
specific project types by geographic region. Overall, the state audit found
that total development costs for tax credit projects with 8,768 units placed
in service between January 1990 and February 1995 ranged between 11
percent to 43 percent higher than other DHCR-funded projects that did not
receive tax credit funding. Had the average cost per unit for the tax credit
units been kept within state guidelines, total development costs would
have been reduced by about $146 million. This reduction in development
costs would have resulted in tax credit allocations being reduced by
$105 million over the 10-year life of the tax credits.

DHCR’s response to the audit findings was that cost guidelines were used
for many tax credit projects, particularly those that were also funded by
government agencies. DHCR maintained that if another government entity,
such as the City of New York, was responsible for a project then that
agency should be responsible for limiting development costs. DHCR
believed that the state auditor’s recommendation to apply state housing
cost limitations to other governmental jurisdictions is not a reasonable
approach.

2. The auditor reported that projects had purposely been granted credits in
excess of amounts needed without the underwriting staff performing the
necessary funding gap analysis. A pool of 20 housing projects that were
originally going to be funded by state housing trust funds was allocated
over $100 million in tax credits over 10 years without DHCR “ensuring that
the credit allocations were limited to the amount needed.” The audit also
found that the cost certifications for each of these 20 projects were based
on estimated, rather than actual, development costs because the


9
 We reviewed the state audit report and most of the audit work papers. We also discussed these
findings with state auditors, senior DHCR officials, and the syndicator for the 20 project syndication
pool. Although we requested DHCR officials to provide us with additional documentation and
clarification to support DHCR’s position, none was provided.



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                              developers were not required to provide actual cost data to the cost
                              certifiers.

                              DHCR’s response was that it performed the necessary funding gap analysis
                              for each project. The net equity raised by the tax credits was used to
                              reduce the permanent loan amounts and to reduce the interest rate on
                              state bonds issued by the state housing agency.


IRS Has Not Conducted         According to an IRS Chief Counsel official, section 42 of the Internal
Reviews of State Allocating   Revenue Code does not explicitly address what responsibilities or
Agencies’ Operations          authority IRS has for ensuring that allocating agencies fulfill their tax credit
                              responsibilities under that statute. However, the official noted that under
                              the Code, IRS has the authority to make broad inquiries regarding the
                              correctness of returns filed with IRS, including the authority to summons
                              and examine the books and records supporting the returns. According to
                              the IRS Chief Counsel official, since the Code requires allocating agencies
                              to report tax credit allocation information to IRS, IRS can examine the
                              agencies’ records that support these information returns.

                              The Chief Counsel official stated that if, in the course of an examination of
                              a state’s information return, IRS determines that a state was not in
                              compliance with its qualified allocation plan it could ultimately disallow a
                              state’s entire credit allocation amount for the period of noncompliance.
                              Use of this authority, however, is of concern to IRS compliance officials
                              because the impact would be on taxpayers who received credits from a
                              noncompliant agency, but who may not be responsible for the
                              noncompliant activity. The Code does not give IRS authority to levy
                              sanctions against state agencies that would not affect taxpayers who have
                              already received credits.

                              According to IRS compliance officials, any oversight reviews of allocating
                              agencies’ operations activities would be based on reviews of allocating
                              agencies’ compliance with tax credit allocation and monitoring reporting
                              requirements and on tax credit audit findings for indications of
                              shortcomings in state implementation of responsibilities. However, IRS
                              currently does not have plans to undertake such examinations and said it
                              would be reluctant to do so without congressional direction.




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Single Audits May Be One   The single audit process is designed to provide systematic audit coverage
Way to Provide Oversight   of state and local governments and nonprofit organizations that administer
of Allocating Agencies’    federal programs. Generally, subject entities that expend $300,000 or more
                           in federal financial assistance are required to arrange for an audit of their
Operations                 financial statements and additional testing of federal programs. Auditors
                           are generally required to use a risk-based approach in selecting federal
                           programs for audit. However, neither the Single Audit Act nor
                           implementing guidance issued by OMB includes tax credits in the definition
                           of federal financial assistance.

                           We found that most state tax credit allocating agencies also receive federal
                           financial assistance, such as CDBG and HOME funds. These agencies are
                           covered by the Single Audit Act if the amount of federal financial
                           assistance expenditures equals or exceeds $300,000 annually. Auditors
                           would test controls over federal programs and test for compliance with
                           federal laws and regulations for programs selected for audit. However, OMB
                           implementing guidance for the Single Audit Act does not include the
                           low-income housing tax credit in the definition of federal financial
                           assistance. Therefore, the tax credit program would not be subject to the
                           Single Audit Act.

                           However, since the tax credit program has compliance requirements that
                           could be tested as part of a single audit, the program may be a good
                           candidate for coverage under the single audit process. Since most state
                           agencies are already undergoing single audits for other types of federal
                           assistance they receive, the low-income housing tax credit could be
                           included with the other programs for the auditor to determine whether it
                           is one of the programs that should be tested under the risk-based
                           approach.

                           The Code allows state agencies to charge fees to developers for the costs
                           states incur for processing and evaluating project proposals and for
                           monitoring projects after they are awarded tax credits. The costs of single
                           audits are shared between the auditee and the federal government based
                           upon the relationship between the entity’s expenditure of federal financial
                           assistance and the entity’s total expenditures. Any additional costs the
                           state entity may incur could be incorporated in states’ administration and
                           monitoring fees.


                           State allocating agencies report that they have adopted project monitoring
Conclusions                programs that meet IRS regulations, but some states reported inspecting



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fewer projects than required in 1995. However, IRS had no reporting system
to determine whether states met their agreed-on monitoring levels. For IRS
to determine whether states follow their monitoring procedures, it would
need a report from state allocating agencies on the number and types of
monitoring inspections they made. IRS could then compare these numbers
with the number of inspections that should be made under states’
monitoring procedures in their qualified allocation plans.

IRS’monitoring regulations do not require states to make on-site project
inspections or other reviews, such as reviews of local government reports
on building code violations, that would allow states to detect violations of
the Internal Revenue Code’s habitability requirements. For IRS to better
ensure that habitability problems are identified during state monitoring
reviews, states would have to do on-site inspections or obtain information
from other sources, such as local government reports on building
inspections results.

IRSis revising the form states use to report projects that are not in
compliance with Internal Revenue Code requirements. These revisions
should help clear up some of the problems states had in determining what
types of noncompliance they should report. However, IRS will still not be
able to easily determine whether the noncompliance reported by states
warrants recapturing credits from project owners because the revised
form we reviewed did not include information on the number of units that
were not in compliance and the date the noncompliance was resolved.

IRS is relying on the results of its audit initiative to provide estimates on the
extent and types of noncompliance that exist in the tax credit program. It
is important for IRS to have this information so that it can determine how
many resources to apply to tax credit compliance problems. However, IRS’
current audit program is not based on a random sample of returns and will
not provide statistically reliable compliance data. If cost-effective, a better
estimate of noncompliance could be obtained from audits of a statistically
valid random sample of partnership returns claiming the tax credit. There
may also be other cost-effective ways to obtain reliable compliance data.
Also, IRS is not in the best position to determine whether states exceed
their tax credit ceilings because it lacks key information on the amount of
tax credits that were initially allocated to projects and later returned for
reallocation.

There is no third-party oversight of state allocating agencies’ low-income
housing tax credit program operations. Unlike other state programs that



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                       are federally funded, the tax credit program is not subject to single audits
                       because neither the Single Audit Act nor implementing guidance issued by
                       OMB includes tax credits in the definition of federal financial assistance.
                       Including low-income housing tax credits in the definition of federal
                       financial assistance so that the tax credit program could be subject to the
                       Single Audit Act would be one way of promoting state compliance with tax
                       credit laws and regulations.


                       The low-income housing tax credit program has stimulated low-income
Recommendations to     housing development in the United States and states’ implementation of
the Commissioner of    the allocation process generally meets the requirements of the Internal
Internal Revenue and   Revenue Code. However, some states’ and IRS’ procedures for oversight of
                       general compliance with laws and regulations could be improved.
Director, Office of    Accordingly, we recommend that the Commissioner of Internal Revenue
Management and         amend regulations for the tax credit program to (1) require that states
                       report sufficient information about monitoring inspections or reviews,
Budget                 including the number and types of inspections made, so that IRS can
                       determine whether states have complied with their monitoring plans; and
                       (2) require that states’ monitoring plans include specific steps, such as site
                       visits, that will provide information to permit IRS to more effectively ensure
                       that the Code’s habitability requirements are met. We also recommend that
                       the Commissioner explore alternative ways to obtain better information to
                       verify that states’ allocations do not exceed tax credit authorizations and
                       to evaluate compliance with the requirements of the Code by taxpayers
                       and housing projects.

                       Finally, to help ensure appropriate oversight of state allocating agencies’
                       overall compliance with tax credit laws and regulations, we recommend
                       that the Director, Office of Management and Budget, incorporate the
                       low-income housing tax credit program in the definition of federal
                       financial assistance included in implementing guidance for the Single
                       Audit Act, as amended, so that the program would be subject to audits
                       conducted under the Single Audit Act.


                       IRS, NCSHA, and OMB commented on these recommendations. IRS agreed
Federal Agency and     with the recommendations addressed to it and orally advised us that it had
State Association      already started to implement a reconciliation procedure.
Comments and Our
                       OMB advised GAO that it did not take exception to strengthening
Evaluation             accountability over the low-income housing tax credit program by building



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    on an existing accountability mechanism such as the single audit concept.
    However, OMB said that incorporating the low-income housing tax credit in
    the definition of federal financial assistance included in implementing
    guidance for the Single Audit Act would likely require a broader evaluation
    of accountability for tax credit programs in general, and the application of
    the single audit concept in particular. Also, OMB indicated that any changes
    in tax credit accountability might be accomplished more appropriately
    through legislation than through administrative initiative.

    We do not object to OMB’s premise about an approach for considering how
    to make the low-income housing tax credit program subject to audits
    conducted under the Single Audit Act. We also note that an evaluation
    along the lines suggested by OMB could also include an assessment of
    whether and, if so, what legislation might be most appropriate.

    NCSHA commented on a number of points with respect to the information in
    this chapter.

•   First, NCSHA raised concerns about bias and prejudgment in the report
    because it believed the report implied that a housing agency was deficient
    if it did not adopt a NCSHA best practice and that the report omitted some
    unspecified corrective actions taken in Texas and New York. In response,
    we note that the report repeatedly points out that the states were given
    flexibility in the administration of the program. The report states that
    allocating agencies have no legal requirement to follow Council best
    practices, such as making site visits. With respect to agency corrective
    actions, we reported on the actions that we found at the time of our visits
    to the states. For example, with respect to the issue of discretionary
    awards, we reported that New York’s allocating agency, in August 1996,
    eliminated a clause in its allocation plan giving the head of the agency the
    discretion to award over 20 percent of the annual allocation, or
    $4.5 million. We also reported on actions taken by California to introduce
    a new system of cost controls and the benefits California cited as a result
    of the change. NCSHA’s mention of New York and Texas seem to refer to the
    results of the two internal audit reports discussed in this chapter. The New
    York state tax credit allocating agency disagreed with the state audit
    report’s findings and recommendations. In Texas, the Executive Director
    of the State Housing Department, which includes the state tax credit
    allocating agency, concurred with the recommendations in the state audit
    report and stated that corrective actions would be taken. Actions to
    address the issues in the reports had not, to our knowledge, been taken at
    the time of our visits to the states.



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•   Second, NCSHA raised a concern about the cost effectiveness and burden of
    some of the recommendations. NCSHA said the recommendation involving a
    requirement for the states to report monitoring information to IRS should
    be limited to information that is both pertinent and useful. NCSHA also said
    that the Single Audit Act should not interfere with the appropriate exercise
    of state responsibilities. We agree with the general thrust of these issues
    and, in fact, considered them as we developed our recommendations. For
    example, in making our recommendation to use the Single Audit Act to
    strengthen federal oversight of the tax credit program, we point out the
    fact that the act was established to eliminate potentially duplicative and
    burdensome federal oversight reviews.
•   Third, NCSHA commented that the report offers little evidence on the extent
    of tax credit overallocations or property owner noncompliance but
    recommends that IRS explore ways to obtain better information to verify
    that state allocations do not exceed their authorizations and evaluate
    taxpayer compliance. Our recommendations were developed with the
    intent to better position IRS to carry out its responsibilities for ensuring
    compliance.




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Appendix I

Statistical Methodology for Evaluating the
Low-Income Housing Tax Credit Program

               This appendix describes the sampling methodology and statistical
               precision of the samples we used in our review of the low-income housing
               tax credit program.


               We gathered information on the low-income housing tax credit program
Sampling       through four structured data collection surveys. Three of these required
Methodology    samples of their respective populations. These three were (1) tax credit
               allocating agency survey, (2) low-income housing project survey, and
               (3) project manager survey. The fourth survey dealt with third-party cost
               certifications.

               The first data collection survey gathered information about tax credit
               allocating agencies’ policies, procedures, and controls. We gathered this
               information using a questionnaire from the entire population of 54
               allocating agencies, which included 50 state agencies, the District of
               Columbia, two suballocating agencies in New York state, and a
               suballocating agency in Chicago. All of the 54 agencies responded to the
               questionnaire and thus provided the 100 percent response rate.

               The second data collection survey collected information from tax credit
               allocating agencies on the characteristics of their sample tax credit
               projects. We collected this information using a questionnaire from a
               probability sample of 423 low-income housing projects to represent the
               total estimated population of 4,121 projects in the continental United
               States. We excluded Alaska and Hawaii projects from our sample because
               of cost considerations, since we would be unable to visit these agencies to
               verify project data. The remaining 52 allocating agencies initially provided
               us with a list with 4,225 projects. After removing four duplicates, a total of
               4,221 projects remained in the list. After sampling and accounting for
               erroneously provided data (see app. III), our sample of 423 projects
               represent our total study universe of an estimated 4,121 projects with
               172,151 low-income units that were authorized for tax credits and were
               placed in service in the 48 contiguous states and the District of Columbia
               from January 1, 1992, through December 31, 1994.

               The representative probability sample of 423 projects was drawn from two
               strata, a large project stratum and a small project stratum. The large
               project stratum consists of 29 projects with more than 300 units in each
               project. All 29 of these projects were included in the sample. The
               remaining small project stratum of the study population consists of an
               estimated total of 4,092 projects containing 161,066 units. A sample of 394



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                       projects represents this stratum. We drew these 394 projects into the
                       sample with probabilities proportionate to their size, as measured by their
                       numbers of low-income housing tax credit units. Our sample of 423 has
                       been properly weighted to represent the estimated population of 4,121
                       projects for all results presented in the report. For example, although each
                       of the projects from the large project stratum represents only itself in the
                       analysis, the smallest project in the small project stratum represents over
                       150 projects. Data were received for everyone of the 423 sampled projects
                       for a response rate of 100 percent.

                       The third data collection survey gathered data directly from the sample
                       projects on tenant and unit characteristics particular to their properties to
                       represent the same estimated population of 4,121 projects. The project
                       managers for the 423 sampled projects were sent a questionnaire
                       requesting information about their projects and all of the units contained
                       in their projects. Questionnaires were returned for 380 of the projects, for
                       a project response rate of 90 percent. We compensated for the three
                       nonresponding projects in the large project sample stratum by increasing
                       the weight for the 26 responding projects’ answers to represent the
                       population of 29 large projects. Similarly, we compensated for the 40
                       nonresponding projects in the small project stratum by weighting the 354
                       respondents’ answers to represent the population of 4,192 small-size
                       projects.

                       The fourth data collection survey gathered data on third-party cost
                       certification procedures for a probability sample of 48 projects. These 48
                       projects were sampled from the 423 previously sampled projects. The
                       projects were drawn with probabilities proportionate to the number of
                       units. As a result, each sampled project represents approximately the same
                       number of housing units in the total population of 172,151 housing units.
                       The sample was again drawn from two strata—three selections from the
                       large project stratum and 45 selections from the small project stratum. We
                       obtained data for all 48 projects for a response rate of 100 percent.


                       Since we used a sample (called a probability sample) of properties and
Sampling Errors and    tenants to develop our estimates from the project and project manager
Confidence Intervals   questionnaire information, each estimate has a measurable precision, or
of Estimates           sampling error, which may be expressed as a plus/minus figure. A
                       sampling error indicates how closely we can reproduce from a sample the
                       results that we would obtain if we were to take a complete count of the
                       universe using the same measurement methods. By adding the sampling



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error to and subtracting it from the estimate, we can develop upper and
lower bounds for each estimate. This range is called a confidence interval.
Sampling errors and confidence intervals are stated at a certain
confidence level—in this case, 95 percent. For example, a confidence
interval at the 95 percent confidence level means that in 95 out of 100
instances, the sampling procedure we used would produce a confidence
interval containing the universe value we are estimating.

This section provides the sampling errors of estimates, referred to in this
report, that were made from these questionnaires. The sampling errors are
provided in a series of tables.

Table I.1 provides sampling errors for estimates made from the
information in the project questionnaire. Table I.1 first provides
information on estimates about properties, followed by information on
estimates about apartment units. Within each of these two main sections,
estimated percentages are given first, followed by estimated means, totals,
and ratios.

Table I.2 provides sampling errors for estimates that use information from
the project manager questionnaire. All the estimates in this table relate to
tenants occupying low-income units. Percentage estimates are provided
first, followed by estimates of means, totals, and ratios.

Table I.3 provides sampling errors for table 2.1 containing economic data
on low-income households with and without additional rental assistance.

Table I.4 provides sampling errors for income data on low-income
households by type of housing assistance provided.

Table I.5 provides sampling errors for current incomes by type of
qualifying household reported by property managers in 1996.

Table I.6 provides sampling errors for the ratio of household current
income to applicable area median income by type of qualifying household.

Table I.7 provides sampling errors for table 5.3 on types of noncompliance
reported from the project questionnaire.

Table I.8 provides sampling errors for figure 4.1 on sources of
development financing for projects receiving grants/donations,
concessionary loans, or Rural Housing Service (515) loans.



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                     Statistical Methodology for Evaluating the
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                     Estimates in these tables do not always represent the entire population
                     because some questions on the questionnaires were not always answered.
                     The size of the population represented by each estimate is also given in the
                     sampling error tables when the entire population is not represented.


                     In addition to the reported sampling errors, the practical difficulties of
Controlling for      conducting any survey may introduce other types of errors, commonly
Nonsampling Errors   referred to as nonsampling errors. For example, differences in how
                     questions are interpreted, errors in entering data, incomplete sampling
                     lists, and the types of people who do not respond can all introduce
                     unwanted variability into the survey results. We included steps in both the
                     data collection and data analysis stages for the purpose of minimizing such
                     nonsampling errors. Some of these steps included pretesting
                     questionnaires with property managers, reviewing answers during
                     follow-up visits to agencies, double-keying and verifying all data during
                     data entry, and checking all computer analyses with a second analyst.

                     Based on the data available, the effect of nonresponses on the
                     representativeness of our project manager sample appears to have been
                     small. To obtain information about the possible effect of nonresponses, we
                     compared five characteristics of the 90 percent of the projects that
                     responded to our housing unit questionnaire with the 10 percent that did
                     not. The greatest difference between the respondent and nonrespondent
                     groups was in the extent of location in urban and rural areas. Lesser
                     differences were found for the following four other items that were
                     examined: the absence of project reevaluations if the numbers of housing
                     units changed after the original tax credit reservation, the primary project
                     goal (serving the elderly or not), ever having been inspected and identified
                     as noncompliant, and being noncompliant because the annual income
                     certification had been submitted late or not received. In order to assess
                     the implications of these differences for our reported results, we estimated
                     the values of the 5 characteristics based on our total sample of 423 and
                     also for our 380 respondents. After weighting to the population, we
                     compared the total sample with the respondents. For the 5 characteristics
                     that we examined, the combined effect of the 90 percent response rate and
                     the nonresponse weighting was that there was no more than a 2.3-percent
                     difference between the weighted totals for the 380 respondents and the
                     totals for the entire sample of 423 projects.




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                                                Statistical Methodology for Evaluating the
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Table I.1: Sampling Errors of Estimates From Information in the Project Questionnaire
                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From              To
Percentage of properties


What is the legal ownership of this property?
  General partnership                                                                        2            1           0              3
  Limited partnership                                                                        82          12          70             94
  Individual                                                                                 12          12           0             24
  S-Corp                                                                                     1            1           0              2
  C-Corp                                                                                     0            0           0              1
  Limited liability company                                                                  1            1           0              2
  Other                                                                                      2            2           (1)            4


Is the project sponsor either an organization or a for-profit subsidiary of a
nonprofit organization?
  Yes                                                                                        22           6          15             28
  No                                                                                         78           6          72             85
  Not answered                                                                               0            0           0              1


What minimum set-aside requirement did this project select?
  20% of rental residential units at 50% of median area income (20/50)
                                                                                             4            2           2              6
  40% of rental residential units at median area
  income (40/60)                                                                             88           9          79             97
  Other (i.e., deep-rent skewing)                                                            8            9           (1)           17


What types of buildings comprise this project? a
  Elevator/high-rise                                                                         10           3           7             13
  Walk-up/garden                                                                             57          11          46             68
  Townhouse/rowhouse                                                                         18           5          12             23
  Single-family detached                                                                     4            3           1              7
  Other                                                                                      19          14           6             33


Which of the following populations is this project primarily intended to
serve?
  Family                                                                                     70           7          62             77
  Elderly                                                                                    26           7          19             32
                                                                                                                            (continued)




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                                               Statistical Methodology for Evaluating the
                                               Low-Income Housing Tax Credit Program




                                                                                                              Confidence interval
Description                                                                        Estimate Sampling error       From              To
Percentage of properties
  Special needs (physically or mentally disabled)                                           1            2           0              3
  Previously homeless                                                                       1            1           0              1
  Other                                                                                     3            2           1              4


In what type of geographic area is this project located?
  Urban                                                                                     36           9          27             45
  Suburban                                                                                  10           3           7             14
  Rural                                                                                     53          10          44             63
  Other                                                                                     0            0           0              1


As indicated on the IRS Forms 8609, what type of construction is this
project? a


  Newly constructed:
     With federal subsidies                                                                 35          10          26             45
     Without federal subsidies                                                              38          11          27             49
  Existing building                                                                         12           4           7             16
  Sec 42(e) rehabilitation expenditure:
     With federal subsidies                                                                 7            4           3             11
     Without federal subsidies                                                              20           6          14             25


Did the sources and uses of funds differ by 5% or more?
  Yes                                                                                       14           9           5             23
  No                                                                                        86           9          77             95


Did the property receive a grant or donation or a soft loan from CDBG,
HOME, AHP, state government, local government, or other nonrural
(non-RHS 515) source?
  Yes                                                                                       37          10          27             46
  No                                                                                        63          10          54             73


Distribution of net equity prices
  Less than $0.40                                                                           9           11           (2)           20
  $0.40 to $0.49                                                                            39           9          31             48
  $0.50 to $0.59                                                                            32          10          23             42
  $0.60 to $0.69                                                                            10           5           5             16
                                                                                                                           (continued)




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                                              Statistical Methodology for Evaluating the
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                                                                                                             Confidence interval
Description                                                                       Estimate Sampling error       From            To
Percentage of properties
  $0.70 or more                                                                            8            4           4           13
              N. proj.                                                                3,605           642       2,963        4,247


For the property, were the amounts known for both the tax credits
awarded and the tax credit equity raised?
  Yes                                                                                      86           9          76           95
  No                                                                                       14           9           5           24


Were any on-site inspections performed?
  Yes                                                                                      75           7          69           82
  No                                                                                       25           7          18           31


Projects with extended use commitments exceeding program
requirements.
  Yes                                                                                      69          11          58           80
  No                                                                                       31          11          20           42


Projects with Section 515 RHS loans (50-year commitment to low-income
use).
  Yes                                                                                      32           8          24           40
  No                                                                                       68           8          60           76


Projects with HOME financing (20-year commitment to low-income use).
  Yes                                                                                      5            4           1              8
  No                                                                                       95           4          92           99


Did project development cost include the cost of land?
  Yes                                                                                      91           4          87           95
  No                                                                                       9            4           5           13


Did property receive grants/donations or concessionary loans (soft
mortgages or Rural Housing Service (515) loans), or did at least one
tenant receive rental assistance?
  Yes                                                                                      86          12          73           98
  No                                                                                       14          12           2           27
                                                                                                                        (continued)




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                                               Statistical Methodology for Evaluating the
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                                                                                                              Confidence interval
Description                                                                        Estimate Sampling error       From            To
              N. proj.                                                                 4,082           746       3,335        4,828
Means for properties


Total number of units in project, including any apartments reserved for
management.
              Mean                                                                          43           8          35           50
              N. proj.                                                                 4,212


Total number of tax credit units.
              Mean                                                                          40           7          33           47
              N. proj.                                                                 4,212


Time in months between when the project was placed in service and the
first on-site inspection of the project.
              Mean                                                                          21           2          19           23
              N. proj.                                                                 3,179


Totals for properties


Tax credit awards in millions of dollars (annual amounts per line 1b,
Form 8609).
              Total                                                                     607             49         558          656
              N. proj.                                                                 4,212


Development cost in millions of dollars.
              Total                                                                  10,669          1,697       8,972       12,366
              N. proj.                                                                 4,212


Total grants/donations, soft mortgages, and Rural Housing Service (515)
loans in millions of dollars.
              Total                                                                    2,946           574       2,372        3,520
              N. proj.                                                                 4,212
Ratios for properties


Tax credit award at placed in service date in relation to the Maximum
Potential Tax Credit Award based on qualified basis.
              Percent                                                                       97           1          96           98
                                                                                                                         (continued)




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                                                Statistical Methodology for Evaluating the
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                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From            To
Ratios for properties
               N. proj.                                                                 4,212
Average equity price in cents.
               Mean                                                                          53           1          51           54
               N. proj.                                                                 3,605


Percent of total development cost:
  Construction expenses                                                                      55           4          50           59
  Construction-related fees                                                                  25           1          24           26
  Other (e.g., acquisition of property)                                                      21           5          16           25
               Total                                                                     100
               N. proj.                                                                 4,212


Percent of total funds for properties where sources and uses of funds did
not differ by 5 percent or more.
  Tax credit equity                                                                          29           5          24           33


  Commercial lender and other hard mortgages (payment required)
  excluding Rural Housing Service (515) loans.                                               36           4          32           40


  Rural Housing Service (515) loans, total soft mortgage,
  grant/donations, equity other than tax credit equity, and other sources.                   36           4          32           40
               Total                                                                     100
               N. proj.                                                                 3,616


Percent of grants/donations, total soft mortgages, and Rural Housing
Service (515) loans that are federally funded (i.e., CDBG, HOME, AHP,
or Rural Housing Service (515) loans).
               Percent                                                                       50          10          40           61
               N. proj.                                                                 2,919


Percentage of units


Percent of total units at placed in service (Note: total does not always
equal sum of bedroom categories.)
  Efficiency                                                                                 6            2           4              8
  1 bedroom                                                                                  36           3          32           39
  2 bedroom                                                                                  41           3          38           44
  3 bedroom                                                                                  16           2          14           18
                                                                                                                          (continued)



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                                                Statistical Methodology for Evaluating the
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                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From             To
Percentage of units


  4 or more bedrooms                                                                         1            0           1              2
  Other                                                                                      0            0           0              1
              N. units                                                               175,100


Percent of total units in:
  Urban locations                                                                            48           5          43            53
  Suburban locations                                                                         23           4          19            27
  Rural locations                                                                            28           4          24            33
                                                                                              b            b           b             b
  Other locations
              Total                                                                      100
              N. units                                                               179,171


Percent of total units with unit costs:
  Less than $20,000                                                                          10           3           7            13
  $20,000 to $39,999                                                                         21           4          17            25
  $40,000 to $59,999                                                                         36           5          31            40
  $60,000 to $79,999                                                                         14           4          11            18
  $80,000 to $99,999                                                                         8            2           6            11
  $100,000 to $119,999                                                                       4            2           2              6
  $120,000 to $139,999                                                                       2            1           0              3
  $140,000 to $160,000                                                                       2            2           0              4
  Over $160,000                                                                              3            2           0              5
              Total                                                                      100
              N. units                                                               179,171


Percent of tax credit units with tax credit cost per unit (present valued at
6.7%) of:
  Less than $10,000                                                                          20           4          17            24
  $10,000 to $19,999                                                                         26           4          22            30
  $20,000 to $29,999                                                                         19           4          15            22
  $30,000 to $39,999                                                                         16           3          13            20
  $40,000 to $49,999                                                                         7            2           5            10
  $50,000 to $59,999                                                                         3            2           1              4
  $60,000 to $69,999                                                                         3            2           1              5
  $70,000 or more                                                                            6            2           4              8
                                                                                                                           (continued)




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                                                Statistical Methodology for Evaluating the
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                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From             To
Percentage of units
              Total                                                                      100
              N. units                                                               168,934          2,094     166,841       171,028


Tax credit costs per tax credit unit (present valued at 6.7%) is less than
or equal to $27,310.
  Yes                                                                                        60           5          56            65
  No                                                                                         40           5          35            44
              Total                                                                      100
              N. units                                                               168,934          2,094     166,841       171,028


Tax credit costs per tax credit unit (present valued at 6.7%) is greater
than $100,000.
  Yes                                                                                        2            1           1              3
  No                                                                                         98           1          97            99
              Total                                                                      100
              N. units                                                               168,934          2,094     166,841       171,028
Means and ratios for units


Total certified development cost per unit
  Urban                                                                               66,651         16,080      50,572        82,731
              N. units                                                                85,893


  Suburban                                                                            57,489          5,543      51,946        63,032
              N. units                                                                41,625


  Rural                                                                               49,478          3,637      45,840        53,115
              N. units                                                                50,835

                                                                                              b            b           b             b
  Other


  Total                                                                               59,545          8,069      51,476        67,614


Total certified development cost per unit
  Land cost known?
  Yes                                                                                 59,720          9,033      50,687        68,753
              N. units                                                               158,297
                                                                                                                           (continued)




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                                                Statistical Methodology for Evaluating the
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                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From             To
Means and ratios for units
  No                                                                                  58,216         10,081      48,135        68,296
              N. units                                                                20,874


  Total                                                                               59,545          8,069      51,476        67,614
              N. units                                                               179,171


Total certified development cost per unit in properties:
  With new construction                                                               67,513         12,613      54,900        80,126
              N. units                                                               107,833


  Without new construction                                                            47,501          5,190      42,311        52,691
              N. units                                                                71,338


Total certified development cost per unit in properties:
  With rehabilitation                                                                 48,250          5,191      43,059        53,441
              N. units                                                                71,800


  Without rehabilitation                                                              67,098         12,685      54,413        79,783
              N. units                                                               107,371


Total certified development cost per unit in properties of following
building type:
  Elevator/high-rise                                                                  97,874         35,251      62,622       133,125
              N. units                                                                34,230


  Walk-up/garden                                                                      49,303          2,974      46,329        52,277
              N. units                                                               117,349


  Townhouse/rowhouse                                                                  60,901          7,277      53,625        68,178
              N. units                                                                30,033

                                                                                              b            b           b             b
  Single-family detached

                                                                                              b            b           b             b
  Other


Percent of units qualified for tax credits                                                   95           3          92            97
                                                                                                                           (continued)




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                                             Statistical Methodology for Evaluating the
                                             Low-Income Housing Tax Credit Program




                                                                                                                        Confidence interval
Description                                                                          Estimate Sampling error                 From              To
              N. units                                                                182,140


Tax credit amount per unit (present valued at 6.7%)                                     27,310                2,138         25,172        29,448
              N. units                                                                168,934


                                             Note 1: Sampling errors and confidence intervals are calculated at the 95-percent level of
                                             confidence.

                                             Note 2: Unless otherwise stated, these estimates apply to the estimated 4,212 + 746 properties.

                                             Note 3: “N. proj.” provides the number of projects to which the estimate applies.

                                             Note 4: “N. units” provides the number of apartment units to which the estimate applies.
                                             a
                                              The sum of the percentages should not equal 100 percent because respondents were asked to
                                             check more than one item, if appropriate.
                                             b
                                              Too few occurrences (fewer than 30 properties) in sample to make estimate.

                                             Source: GAO’s analysis of project questionnaire.




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                                             Statistical Methodology for Evaluating the
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Table I.2: Sampling Errors of Estimates About the Households Occupying LIHTC Units
                                                                                                            Confidence interval
Description                                                                      Estimate Sampling error       From            To
Percentage of households


Number of people living in household
  1 Person                                                                                43           3          39           46
  2 Persons                                                                               24           1          23           26
  3 Persons                                                                               17           1          16           18
  4 Persons                                                                               11           1          10           12
  5 or More persons                                                                       6            1           5              7
              Total                                                                   100
              N=                                                                  157,430          6,157     151,273      163,588


Is anyone in household receiving a rental subsidy?
  Yes                                                                                     39           4          35           43
  No                                                                                      61           4          57           65
              Total                                                                   100
              N=                                                                  155,226          6,256     148,970      161,481


Gender of head of household
  Male                                                                                    36           2          34           38
  Female                                                                                  64           2          62           66
              Total                                                                   100
              N=                                                                  154,412          6,282     148,130      160,694


Race of head of household
  White                                                                                   53           4          49           57
  Black                                                                                   33           4          29           37
  Hispanic (not black)                                                                    11           2           9           13
  Other                                                                                   4            1           3              5
              Total                                                                   100
              N=                                                                  132,247          7,616     124,631      139,863
                                                                                                                       (continued)




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                                                                                                             Confidence interval
Description                                                                       Estimate Sampling error       From            To
Percentage of households


Current annual household income
  <$5,000                                                                                  10           2           8           11
  $5,000-$9,999                                                                            29           3          26           31
  $10,000-$14,999                                                                          23           2          22           25
  $15,000-$19,999                                                                          20           2          19           22
  $20,000-$24,999                                                                          11           1          10           12
  $25,000 or more                                                                          7            1           6              8
               Total                                                                   100
               N=                                                                  156,116          6,132     149,983      162,248


Head of household’s age
  <= 34                                                                                    44           3          42           47
  35 - 54                                                                                  26           2          25           28
  >= 55                                                                                    29           4          25           33
               Total                                                                   100
               N=                                                                  146,565          6,725     139,840      153,291


Household income as a percent of median income
  30% and under                                                                            39           3          36           41
  31-50%                                                                                   39           2          37           40
  51-60%                                                                                   16           2          15           18
  61% and over                                                                             6            1           5              7
               Total                                                                   100
               N=                                                                  159,331          6,079     153,252      165,411


Is the apartment unit overcrowded?
  Yes                                                                                      2            1           2              3
  No                                                                                       98           1          97           98
               Total                                                                   100
               N=                                                                  156,689          6,183     150,506      162,872


If the apartment unit is overcrowded, what is the apartment size?
  Efficiency                                                                               10           5           5           16
  1 bedroom                                                                                51           8          43           58
  2 bedrooms                                                                               31           7          24           37
  3 bedrooms                                                                               8            4           4           12
                                                                                                                        (continued)


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                                                                                                               Confidence interval
Description                                                                         Estimate Sampling error       From            To
Percentage of households


  4 bedrooms                                                                                 1            1           0              1
              Total                                                                      100
              N=                                                                        3,621         1,005       2,615        4,626


For households receiving subsidies, is total current monthly rent
charged, including utility allowance and rental subsidy, greater than the
maximum tax credit allowable rent (including utilities), as of April 1, 1996?
  Yes                                                                                        25           6          19           31
  No                                                                                         75           6          69           81
              Total                                                                      100
              N=                                                                      60,714          6,686      54,028       67,400



For households receiving subsidies, is total current monthly rent
charged, including utility allowance and rental subsidy, 121 percent or
more of the maximum tax credit allowable rent (including utilities), as of
April 1, 1996?
  Yes                                                                                        7            3           3           10
  No                                                                                         93           3          90           97
              Total                                                                      100
              N=                                                                      60,714          6,686      54,028       67,400


Is the household receiving subsidies, and is the total current monthly
rent charged, including utility allowance and rental subsidy, greater than
the maximum tax credit allowable rent (including utilities), as of April 1,
1996?
  Yes                                                                                        10           3           7           13
  No                                                                                         90           3          87           93
              Total                                                                      100
              N=                                                                     154,401          6,344     148,057      160,744


Is the household receiving subsidies, and is the total current monthly
rent charged, including utility allowance and rental subsidy, 121 percent
or more of the maximum tax credit allowable rent (including utilities), as
of April 1, 1996?
  Yes                                                                                        3            1           1              4
  No                                                                                         97           1          96           99
              Total                                                                      100
              N=                                                                     154,422          6,344     148,078      160,766
                                                                                                                          (continued)


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                                               Appendix I
                                               Statistical Methodology for Evaluating the
                                               Low-Income Housing Tax Credit Program




                                                                                                              Confidence interval
Description                                                                        Estimate Sampling error       From              To
Percentage of households
For households receiving subsidies and living in apartments where the
total current monthly rent charged, including utility allowance and rental
subsidy, is more than the maximum tax credit allowable rent (including
utilities), as of April 1, 1996, the rental subsidy is
  Property based                                                                            43          15          29             58
  Tenant based                                                                              15           9           6             24
  Rural Housing Service                                                                     42          15          27             57
               Total                                                                    100
               N=                                                                    15,114          4,298      10,816         19,413


For households receiving subsidies and living in apartments where the
total current monthly rent charged, including utility allowance and rental
subsidy, is more than 120 percent of the maximum tax credit allowable
rent (including utilities), as of April 1, 1996, the rental subsidy is
  Property based                                                                            74          24          50             98
  Tenant based                                                                              7            7           (0)           14
  Rural Housing Service                                                                     19          24           (5)           43
               Total                                                                    100
               N=                                                                      4,209         2,190       2,019          6,399


Means for households


Number of people living in household
               Mean                                                                     2.15          0.08         2.07          2.23
               N=                                                                   157,472


Annual household income
               Mean                                                                  13,323            525      12,797         13,848
               N=                                                                   156,116


What is the average total current monthly rent charged, including utility
allowance and rental subsidy, of low-income units by bedroom type?
  Efficiency
               Mean                                                                     342             40         302            382
               N=                                                                      8,846
  1 bedroom
               Mean                                                                     385             15         370            400
               N=                                                                    57,582
                                                                                                                           (continued)



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                                               Appendix I
                                               Statistical Methodology for Evaluating the
                                               Low-Income Housing Tax Credit Program




                                                                                                              Confidence interval
Description                                                                        Estimate Sampling error       From            To
Means for households


  2 bedroom
              Mean                                                                      474             14         460          488
              N=                                                                     61,487
  3 bedroom
              Mean                                                                      576             27         550          603
              N=                                                                     26,338
  4 or more bedrooms
              Mean                                                                      623             64         560          687
              N=                                                                       2,109
  Total (overall average)
              Mean                                                                      453             13         441          466
              N=                                                                    157,079


Totals for households


Annual rental subsidy amount in millions of dollars (12 times the
difference between total current monthly rent, including utility allowance
and rental subsidy, and the amount the tenant paid, when the tenant
received a rent subsidy)
  Total                                                                                 229             28         201          257
              N=                                                                    152,658


Number of households receiving rent subsidies and living in apartments
where the total current monthly rent charged, including utility allowance
and rental subsidy, is more than the maximum tax credit allowable rent
(including utilities), as of April 1, 1996, and the rental subsidy is
  Property based                                                                       6,568         2,874       3,693        9,442
  Tenant based                                                                         2,216         1,414         802        3,629
  Rural Housing Service                                                                6,331         3,075       3,256        9,406
              N=                                                                     15,114          4,298      10,816       19,413
                                                                                                                         (continued)




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                                                Appendix I
                                                Statistical Methodology for Evaluating the
                                                Low-Income Housing Tax Credit Program




                                                                                                                           Confidence interval
Description                                                                             Estimate Sampling error                From               To
Ratios for households


Ratio of total current monthly rent charged, including utility allowance
and rental subsidy, to monthly maximum tax credit allowable rent
(including utilities), as of April 1, 1996.


  Efficiency                                                                                 0.77                 0.07           0.70        0.84
               N=                                                                           8,739


  1 bedroom                                                                                  0.86                 0.03           0.83        0.89
               N=                                                                         54,888


  2 bedrooms                                                                                 0.85                 0.02           0.83        0.87
               N=                                                                         59,462


  3 bedrooms                                                                                 0.87                 0.04           0.83        0.92
               N=                                                                         25,686


  4 or more bedrooms                                                                         0.84                 0.08           0.76        0.93
               N=                                                                           2,038


  Total                                                                                      0.85                 0.02           0.83        0.87
               N=                                                                        150,813


                                                Note 1: Sampling errors and confidence intervals are calculated at the 95-percent level of
                                                confidence.

                                                Note 2: Unless otherwise indicated, estimates represent approximately 158,975 + 6,160 occupied
                                                LIHTC apartments.

                                                Note 3: “N=” indicates the number of households occupying LIHTC units included in the analysis.

                                                Source: GAO’s analysis of project and project manager questionnaires.




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                                              Appendix I
                                              Statistical Methodology for Evaluating the
                                              Low-Income Housing Tax Credit Program




Table I.3: Sampling Errors for Table 2.1—Economic Data on Low-Income Households With and Without Additional Rental
Assistance
                                                                                                   Average income as a
                                                                                                        percentage of the
                                                                  Percentage of    Average current         area’s median
Households                                                          households            incomea                incomea
Receive additional rental assistanceb                                                   39 + 4            $7,858 + 346                      25 + 1

                                                                                  N = 60,714                 N = 59,517                N = 59,426
                                          c
Do not receive additional rental assistance                                             61 + 4            16,709 + 525                      45 + 1

                                                                                  N = 94,511                 N = 93,829                N = 93,715
Total                                                                                      100           $13,323 + 525                      37 + 1

                                                                        N = 155,226 + 6,256                N = 156,116 d              N = 155,827e
                                              Note: The sampling errors of the estimates, at the 95-percent level of confidence, are provided
                                              following the “+. “ The number of households represented in the estimate is provided following the
                                              “N=.” When information was available from all of our sampled respondents, the number of
                                              households was 158,975 + 6,160.
                                              a
                                               In our analyses, we used current incomes reported to us by property managers in 1996. HUD’s
                                              definitions of low income, which apply to the housing credit program, are based on adjusted
                                              incomes (gross incomes less certain expenses). Consequently, our economic data will indicate
                                              that households are better off economically to the extent that the current incomes reported to us
                                              exceed the adjusted incomes.
                                              b
                                               About 73 + 6 percent of 60,714 + 6,686 households with additional housing assistance also
                                              benefit indirectly from other government loans, loan subsidies, or grants.
                                              c
                                               About 52 + 6 percent of 94,511 + 7,473 households without additional rental assistance benefit
                                              indirectly from other government loans, loan subsidies, or grants.
                                              d
                                                  Includes 2,770 households with missing rental assistance data.
                                              e
                                              Inclues 2,687 with missing data on rent subsidy.

                                              Source: GAO’s analysis of data from property managers.




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                                               Appendix I
                                               Statistical Methodology for Evaluating the
                                               Low-Income Housing Tax Credit Program




Table I.4: Sampling Errors for Income Data on Low-Income Households by Type of Housing Assistance Provided
                                                                     Percent of     Average current    Average percent of
Type of assistance                                                 households               income        median income
Tax credit only                                                                          29 + 4          $17,382 + $692             47 + 2

                                                                                   N = 45,433                 N = 44,963       N = 44,887
Tax credit and other assistance to property only                                         32 + 4          $16,089 + $766             42 + 1

                                                                                   N = 49,079                 N = 48,866       N = 48,828
Tax credit, rental assistance, and other assistance to property                          29 + 4           $7,901 + $304             27 + 1

                                                                                   N = 44,280                 N = 43,134       N = 43,115
Tax credit and rental assistance only                                                    11 + 2           $7,745 + $968             22 + 3

                                                                                   N = 16,434                  N=16,383        N = 16,311
Total                                                                                       100          $13,323 + $525             37 + 1

                                                                         N = 155,226 + 6,256                 N = 156,116a     N = 155,827b

                                               a
                                               Includes 2,770 households with missing rental assistance data.
                                               b
                                                   Includes 2,686 households with missing rental assistance data.

                                               Source: GAO analysis of property manager questionnaire.




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                                          Appendix I
                                          Statistical Methodology for Evaluating the
                                          Low-Income Housing Tax Credit Program




Table I.5: Sampling Errors for Table 2.1—Current Incomes by Type of Qualifying Household Reported by Property
Managers in 1996 (Properties Placed in Service 1992 Through 1994)
                                                                                     Households with Households with no
                                                                    All qualifying    additional rental    additional rental
Annual household gross income                                        households             assistance           assistance
Less than $5,000                                                               10 + 2                   22 + 3             2+1

                                                                          N = 15,178               N = 12,857          N = 2,321
$5,000-$9,999                                                                  29 + 3                   54 + 4            13 + 2

                                                                          N = 44,506               N = 32,175        N = 12,331
$10,000-$14,499                                                                23 + 2                   17 + 2            27 + 2

                                                                          N = 35,954               N = 10,217        N = 25,738
$15,000-$19,999                                                                20 + 2                    5+1              30 + 2

                                                                          N = 31,095                N = 3,093        N = 28,002
More than $20,000                                                              17 + 2                    2+1              27 + 3

                                                                          N = 26,613                N = 1,176        N = 25,437
                                          Note: Columns may not add to 100 due to rounding.

                                          Source: GAO analysis of data from low-income housing property managers.




Table I.6: Sampling Errors for the Ratio of Household Current Income to Applicable Area Median Income by Type of
Qualifying Household—Properties Placed in Service 1992-1994
                                                                                       Households with Households with no
                                                                     All qualifying     additional rental   additional rental
Applicable area median income                                         households              assistance          assistance
30 percent and under                                                           38 + 3                   68 + 4            19 + 2

                                                                          N = 59,019               N = 41,115        N = 17,904
31 to 50 percent                                                               39 + 2                   28 + 3            46 + 2

                                                                          N = 60,667               N = 16,782        N = 43,884
51 to 60 percent                                                               17 + 2                    4+1              25 + 2

                                                                          N = 25,881                N = 2,231        N = 23, 651
61 and above                                                                    6+1                      1+0              10 + 1

                                                                           N = 9,659                  N = 586          N = 9,072
                                          Note: Columns may not add to 100 due to rounding.

                                          Source: GAO analysis of data from property managers.




                                          Page 143                              GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                         Appendix I
                                         Statistical Methodology for Evaluating the
                                         Low-Income Housing Tax Credit Program




Table I.7: Sampling Errors for Table
5.3—Types of Noncompliance Found         Type of noncompliance                                   Desk reviews            On-site inspections
by Desk Review and On-Site               1. Tenant(s) not income eligible                                30 + 18%                       13 + 10%
Inspectionsa
                                         2. Rents too high                                               12 + 12                           7+7
                                         3. Building code violation or other building
                                         condition                                                                                      43 + 33
                                         4. Administrative requirement not metb                          35 + 23                          10 + 9
                                         5. Annual income certification either
                                         submitted late or not received                                  53 + 22                        34 + 22
                                         6. Improper income certification or failure to
                                         properly verify certifications                                     2+4                         26 + 17
                                         7. Other                                                        16 + 14                           7+6

                                         a
                                          This analysis is limited to properties that were found to be in noncompliance at any time. It was
                                         further limited to properties that received only desk audits (37 sampled properties) or only on-site
                                         inspections (94 sampled properties)—about 8 and 18 percent of the properties, respectively.
                                         Since the number of sampled cases available for analysis was relatively small, the sampling
                                         errors of these estimates are relatively large.
                                         b
                                          This category includes forms not filed on time, forms filed with incomplete information, or failure
                                         to meet other federal or administrative requirements.

                                         Source: GAO analysis of sampled project questionnaires.



Table I.8: Sampling Errors for Table
4.2—Sources of Financing for Projects    Source of development financing                                                                Percent
Requiring Subsidies in Addition to Tax   Grants/donations and concessionary loans                                                         37 + 3
Credits
                                         Tax credit equity                                                                                27 + 6
                                         Commercial and other hard mortgages (payment required)                                           29 + 5
                                         Other                                                                                            06 + 3
                                         Total                                                                                                  100
                                         Note: An estimated 69 percent (+ 11 percent) of the properties received grants/donations and
                                         concessionary loans. However, this table is based on only the 84 percent (+ 13 percent) of the
                                         69 percent of properties where reported sources and uses of funds did not differ by 5 percent or
                                         more—i.e., 58 percent (+ 11 percent) of all properties.

                                         Source: GAO’s analysis of project questionnaire.




                                         Page 144                                  GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix II

Additional Data on Incomes of Tax Credit
Households by Type of Other Housing
Assistance Received
               The data in this appendix provide additional detail on the incomes of tax
               credit households presented in chapter 2. These data further demonstrate
               how direct rental assistance enables the tax credit program to serve those
               tax credit households with the lowest incomes.

               As discussed in chapter 2, in 1996 an estimated 71 percent of the qualifying
               households in tax credit properties placed in service between 1992 and
               1994 benefited directly or indirectly from one or more types of additional
               housing assistance. This assistance is provided either directly as rental
               assistance, or indirectly through loan subsidies or grants to property
               owners. Because such indirect assistance may reduce operating expenses
               or debt service costs, it can support lower rents. As table 2.1 indicated (see
               ch. 2), in 1996, the estimated average annual income of households in tax
               credit properties with additional rental assistance was $7,858; the
               estimated average income of households without additional rental
               assistance was $16,709.

               However, many of the households—an estimated 73 percent—with
               additional rental assistance lived in units that also benefited indirectly
               from loan subsidies and grants. In addition, an estimated 52 percent of the
               households without rental assistance benefited indirectly from loan
               subsidies or grants. To isolate the impact of loan subsidies and grants on
               tax credit residents, we divided the households into four categories:
               (1) those with tax credit assistance only; (2) those with tax credit
               assistance and loan subsidies or grants; (3) those with tax credit and rental
               assistance; and (4) those with all three types of assistance—tax credit,
               rental, and loan subsidies or grants.

               This analysis confirmed the significant role of direct rental assistance in
               serving households with the lowest incomes. Table II.1 shows that the
               average incomes of tax credit households with rental assistance were
               similar regardless of whether the property received loan subsidies or
               grants—an estimated $8,000 in either case. The table also shows that when
               households were not receiving rental assistance, other assistance to tax
               credit properties—loan subsidies or grants—had only an incremental
               impact on the incomes of tax credit households.




               Page 145                       GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                               Appendix II
                                               Additional Data on Incomes of Tax Credit
                                               Households by Type of Other Housing
                                               Assistance Received




Table II.1: Income Estimates for Households Residing in Tax Credit Properties Placed in Service, 1992-94, by Type of
Housing Assistance Provided
                                                                       Percent of       Average current     Average percent of
Type of assistance                                                    households                  income        median income
Tax credits only                                                                             29                     $17,382            47
Tax credits and loan subsidies or grants                                                     32                     $16,089            42
Tax credits and rental assistance                                                            11                      $7,745            22
Tax credits, rental assistance, and loan subsidies or grants                                 29                      $7,901            27
Total                                                                                       100                     $13,323a           37 b
                                               a
                                               Includes 2,770 households with missing rental assistance data.
                                               b
                                                   Includes 2,686 households with missing rental assistance data.

                                               Source: GAO’s analysis of data provided by tax credit property managers.



                                               Tables II.2 and II.3 provide information on the incomes of households
                                               residing in tax credit properties that were placed in service between 1992
                                               and 1994. The data, which are arrayed by the rental assistance status of the
                                               household, augment the information on incomes presented in figure 2.1
                                               (see ch. 2). The data show that a large majority of tax credit households
                                               with rental assistance were at the lower end of the income distribution,
                                               whereas only a small proportion of tax credit households without rental
                                               assistance were at these low income levels. Table II.2 shows estimates for
                                               the income received by tax credit households, and table II.3 shows
                                               estimates for the incomes of tax credit households relative to the incomes
                                               of others in the same geographical area.

                                               As noted in chapter 2, the small percentage of households whose incomes
                                               exceeded the tax credit program’s limit of 60 percent of area median
                                               income does not necessarily indicate noncompliance with the income
                                               limits for two reasons. First, in our analyses, we used current incomes
                                               reported to us by tax credit property managers in 1996. HUD’s definitions of
                                               low income, which apply to the tax credit program, are based on adjusted
                                               incomes (annual incomes less certain expenses). Consequently, our
                                               income data may place households in higher area median income
                                               categories to the extent that the current incomes reported to us exceed the
                                               adjusted incomes. Second, under the Internal Revenue Code, households
                                               whose incomes increased while they resided in tax credit units may
                                               remain in those units even if their incomes exceed the program’s
                                               qualifying limits.




                                               Page 146                                   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                          Appendix II
                                          Additional Data on Incomes of Tax Credit
                                          Households by Type of Other Housing
                                          Assistance Received




Table II.2: Current Income Estimates by Type of Qualifying Household Reported by Property Managers in 1996 for
Properties Placed in Service, 1992-94
                                                                                            Percent of            Percent of
                                                                    Percent of all   households with households with no
                                                                       qualifying     additional rental     additional rental
Annual household income                                              households             assistance            assistance
Less than $5,000                                                                    10                        22               2
$5,000 - $9,999                                                                     29                        54              13
$10,000 - $14,499                                                                   23                        17              27
$15,000 - $19,999                                                                   20                          5             29
More than $20,000                                                                   17                          2             27
                                          Note: Percentages may not add to 100 because of rounding.

                                          Source: GAO’s analysis of data provided by tax credit property managers.




Table II.3: Ratio of Household Current Income Estimates to Applicable Area Median Income by Type of Qualifying
Household for Properties Placed in Service, 1992-94
                                                                                            Percent of             Percent of
                                                                     Percent of all   households with households with no
                                                                        qualifying    additional rental      additional rental
Ratio of household income to area median income                       households            assistance             assistance
30 percent and under                                                                38                        68              19
31 to 50 percent                                                                    39                        28              46
51 to 60 percent                                                                    17                          4             25
61 and above                                                                          6                         1             10
                                          Note: Percentages may not add to 100 because of rounding.

                                          Source: GAO’s analysis of data provided by tax credit property managers.




                                          Page 147                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix III

Tax Credit Project Information Reported by
Allocating Agencies and Used in the GAO
Sample
               The tables in this appendix present summary tax credit project universe
               and sample data. Universe data is the information we received from tax
               credit allocating agencies on tax credit projects placed in service from
               1992 through 1994. Sample data identifies the information we used from
               sampling universe data.

               Table III.1 shows that 52 tax credit allocating agencies located in 48 states
               and Washington, D.C., placed 4,221 projects in service between 1992 and
               1994. We excluded tax credit project information for Alaska and Hawaii
               because we never intended to visit these locations to verify
               project-specific information. The 52 allocating agencies initially reported
               that they placed 4,225 tax credit projects in service during the subject
               period, but subsequent verification efforts disclosed that 4 of these
               projects contained redundant information.

               Table III.2 presents the 431 tax credit projects that we sampled from the
               4,225 projects initially reported by allocating agencies as placed in service
               between 1992 and 1994. Our original sample was 435 projects, but, again, 4
               sample projects contained redundant information. Moreover, eight other
               sample projects had to be excluded from our analysis because we
               subsequently determined they either had not been placed in service during
               the subject period or their owners had never received an IRS Form 8609,
               which would have made them eligible to claim tax credits. As a result, the
               435 tax credit projects and 48,725 tax credit-supported units contained in
               our original sample were ultimately reduced for review purposes to 423
               tax credit projects containing 45,886 tax credit-supported units. These 423
               sample tax credit projects represent an estimated population of 4,121 tax
               credit projects in our study universe.




               Page 148                       GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                         Appendix III
                                         Tax Credit Project Information Reported by
                                         Allocating Agencies and Used in the GAO
                                         Sample




Table III.1: Summary of Tax Credit
Projects Reported to GAO by Tax                                                                Total LIHTC      Total LIHTC
Credit Allocating Agencies as Placed     State            Total projects       Total units            units           award
in Service During the Period 1992-1994   AK                             0                 0              0               $0
                                         AL                          105               3,716         3,716         8,743,153
                                         AR                           70               3,737         3,733         9,826,063
                                         AZ                           34               2,386         2,211         9,114,966
                                         CA                          247              15,417        13,884      103,634,201
                                         Chicago                      30               2,325         2,306         8,771,563
                                         CO                           57               1,986         1,882         8,321,805
                                         CT                           25                962            806         6,060,180
                                         DC                             6               903            903         2,023,739
                                         DE                           15                788            783         2,838,575
                                         FL                          112              11,312        11,237       40,426,449
                                         GA                          104               5,110         4,881         9,458,009
                                         HI                             0                 0              0                0
                                         IA                           90               2,933         2,927         7,299,461
                                         ID                           34               1,504         1,258         4,357,173
                                         IL                          125               3,661         3,504       10,077,651
                                         IN                          100               4,037         3,992       12,917,791
                                         KS                           43               2,224         2,224         4,387,379
                                         KY                          125               3,232         3,180         8,394,802
                                         LA                           81               3,559         3,471         6,880,774
                                         MA                           56               3,067         2,960       15,306,892
                                         MD                           73               5,951         4,936       15,688,562
                                         ME                           31                941            780         2,039,661
                                         MI                          167               7,860         7,007       22,608,020
                                         MN                          118               4,083         4,083       11,500,964
                                         MO                          221               4,368         4,124       12,065,205
                                         MT                           15                528            528         1,646,851
                                         MS                           80               3,490         3,470         3,532,221
                                         NC                          330               4,629         4,620       12,123,726
                                         ND                           30                668            668         1,805,829
                                         NE                           59               1,310         1,303         4,290,501
                                         NH                           12                296            292          680,178
                                         NJ                           69               4,196         3,957       21,660,341
                                         NM                           22                791            791         2,033,536
                                         NV                           13                701            701         3,279,838
                                         NY                          109               5,293         4,327       29,676,233
                                         NYC                          68               3,589         3,108       18,942,931
                                                                                                                 (continued)


                                         Page 149                           GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                        Appendix III
                                        Tax Credit Project Information Reported by
                                        Allocating Agencies and Used in the GAO
                                        Sample




                                                                                                 Total LIHTC       Total LIHTC
                                        State              Total projects          Total units          units            award
                                        NY(other)                         8               824            639          1,516,850
                                        OH                             193               8,661         8,661        25,824,095
                                        OK                               54              2,157         2,015          2,817,924
                                        OR                               41              2,776         2,765        10,747,481
                                        PA                             190               5,024         4,878        25,808,479
                                        RI                               19               712            648          1,585,291
                                        SC                               81              2,598         2,598          5,142,650
                                        SD                               42              1,078         1,053          2,631,716
                                        TN                               76              2,106         2,106          6,307,471
                                        TX                             209              17,370        17,110        18,855,782
                                        UT                               46              1,850         1,760          5,871,045
                                        VA                               88              7,138         6,764        21,659,829
                                        VT                               23               463            421          1,428,283
                                        WA                               76              4,211         4,058        20,389,416
                                        WI                             154               4,908         4,422        15,278,902
                                        WV                               42              1,064         1,064          1,581,439
                                        WY                                3                78             78           169,483
                                        Total                        4,221             184,571       175,593      $610,031,359

                                        Source: GAO analysis of state-reported data.



Table III.2: Summary of GAO Sample of
Tax Credit Projects Reported to GAO                  Number of projects
by Tax Credit Allocating Agencies as    State                  selected            Total units   LIHTC units    Total award ($)
Placed in Service During the Period     AK                                0                 0              0                 0
1992—1994
                                        AL                                9               580            580          1,102,750
                                        AR                                9               866            866          2,656,762
                                        AZ                                6               864            864          3,836,820
                                        CAb                              34              3,702         3,526        25,327,649
                                        Chicago                           4               835            835          3,053,554
                                        CO                                5               349            345          1,353,127
                                        CT                                2               117            117           888,571
                                        DCb                               2               728            728          1,391,334
                                        DE                                2               211            210           767,639
                                        FL                               28              5,480         5,457        22,851,867
                                        GA                               12              1,174         1,161          2,318,473
                                        HI                                0                 0              0                 0
                                        IA                                7               440            434          1,001,549
                                                                                                                    (continued)



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Appendix III
Tax Credit Project Information Reported by
Allocating Agencies and Used in the GAO
Sample




            Number of projects
State                 selected        Total units    LIHTC units    Total award ($)
ID                             3              161           144            436,543
IL                           10               964           884           2,459,569
IN                           10               752           752           2,024,089
KS                             5              427           427            561,368
KY                             8              495           460           1,221,270
LA                             9              852           852           1,531,635
MA                             7             1,082         1,048          3,500,349
MD                           12              2,564         1,905          4,383,360
ME                             2               98            70            144,281
MI                           17              1,938         1,938          5,934,180
MN                           10               784           784           1,905,029
MO                           10               529           492           1,159,253
MS                             9             1,129         1,114           787,320
MT                             1               60            60            284,159
NC                           11               458           457           1,282,690
ND                             2               42            42            126,927
NE                             3              102           102            400,596
NH                             1               27            27             53,634
     a
NJ                             9             1,907         1,899          5,949,373
NM                             2              134           134            826,167
NV                             1               60            60            273,749
NY                             9             1,013          880           3,520,673
NYC                          10               707           673           3,705,513
NY(other)                      1              394           394            730,000
     b
OH                           21              1,909         1,909          5,089,694
OK                             5              394           368            465,512
OR                             7              707           696           3,000,342
PA                           12               651           541           4,101,084
RI                             2              137           131            210,071
SC                             6              540           540            790,251
SD                             3              100           100            386,856
TN                             5              512           512           1,062,144
TXa,b                        42              7,776         7,776          7,214,387
UT                             4              232           232            942,339
     a
VA                           17              2,418         2,318          8,546,293
VT                             2               55            47             92,815
WA                             9              802           777           4,157,702
WI                           11               573           488           1,818,957
                                                                        (continued)


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Appendix III
Tax Credit Project Information Reported by
Allocating Agencies and Used in the GAO
Sample




              Number of projects
State                   selected            Total units        LIHTC units         Total award ($)
WV                                 3                  88                   88               139,003
WY                                 0                    0                   0                         0
Total                            431             48,919               47,244          $147,769,272

a
 We excluded from our analysis one project in each of these states because project owners never
received an IRS Form 8609.
b
 We excluded from our analysis one project in each of these states and two projects in the District
of Columbia because these projects were never placed in service during our 1992-1994 review
period.

Source: GAO analysis of state-reported data.




Page 152                                 GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix IV

Results of Site Visits to GAO Sample
Properties

                         As part of our review, GAO evaluator teams from offices across the country
                         visited 92 low-income housing tax credit projects in 37 states, New York
                         City, Chicago, and Washington, D.C. As discussed in the Objectives, Scope
                         and Methodology section of chapter 1, the projects were judgmentally
                         selected, on the basis of cost considerations, from our stratified random
                         sample of 423 projects. During the visits, the teams interviewed on-site
                         management agents and project owners who frequently were on hand for
                         our visits; generally reviewed tenant and project management records;
                         walked through exterior grounds, residential units, and common areas;
                         took photographs; and, for nearly all projects, reviewed the files of the five
                         tenants who had most recently moved into the project. We reviewed each
                         tenant file for evidence of (1) current annual household income;
                         (2) income verification; (3) rent calculations, including utilities and
                         allowances; and (4) tenant rent payments. Finally, we compared the total
                         number of LIHTC units (according to bedroom size) reported by the
                         on-site property manager with the number of units reported by the
                         allocating agency in our project data collection instrument.

                         In the 431 tenant files we reviewed, we found almost no evidence of
                         ineligible tenant incomes or excessive rent charges. In all but four tenant
                         case files at four different properties, tenant data showed that property
                         managers consistently adhered to program monitoring requirements by
                         gathering and verifying household income data. Tenant file data also
                         showed total rents charged for rental units and proportional tenant rent
                         payments to be accurate. Further, the total number of units by bedroom
                         size as reported by property managers and allocating agencies compared
                         favorably.

                         The projects we visited had a wide variety of building types and floor plans
                         in urban, suburban and rural settings. Many projects included the types of
                         amenities found in market rate rental housing, such as swimming pools,
                         laundry areas, covered parking garages, activity rooms, and playgrounds.
                         What follows is a series of photographs and project descriptions that
                         illustrate the diverse types of affordable housing we encountered in our
                         review.



Urban Projects

Castle Square, Boston,   Castle Square is a cluster of elevator high-rise buildings that were
Massachusetts            rehabilitated with several federal subsidies, including the low-income



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                                         Appendix IV
                                         Results of Site Visits to GAO Sample
                                         Properties




                                         housing tax credit program. The property has a mix of 1-, 2-, 3-, and
                                         4-bedroom family rental units. The average annual income of the typical
                                         2-person household is about $13,600, compared with an area median
                                         income of $56,500. Monthly rents including utilities at Castle Square vary
                                         from $814 for a 1-bedroom unit to $1,359 for a 4-bedroom unit. However,
                                         the average monthly rent paid by resident households is about $300
                                         because all low-income rental units have section 8 project-based rental
                                         assistance attached to them. Castle Square had an average occupancy rate
                                         of 99 percent during 1995.

Tax Credit Award                         9 percent

Total Residental Units                   500

Total Low-Income Units                   470

Total Development Cost                   $52.7 million

Average Cost Per Unit                    $105,400


Figure IV.1: Castle Square, Boston, MA




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                                       Appendix IV
                                       Results of Site Visits to GAO Sample
                                       Properties




Turk Street Apartments,                The Turk Street Apartments is an elevator high-rise property that was
San Francisco, California              newly constructed without the use of federal subsidies other than the
                                       low-income housing tax credit program. The property has a mix of
                                       efficiencies and 1-, 2-, and 3-bedroom family rental units. The average
                                       annual income of the typical 2-person household is about $16,300,
                                       compared with an area median income of $61,300. Monthly rents including
                                       utilities at Turk Street vary from $483 for an efficiency unit to $657 for a
                                       3-bedroom unit. Although most low-income residents in this property pay
                                       unsubsidized rents, households with rental assistance pay as little as $155
                                       for an efficiency and $218 for a 2-bedroom apartment. Turk Street was
                                       fully occupied during 1995.

Tax Credit Award                       9 percent

Total Residential Units                175

Total Low-Income Units                 175

Total Development Cost                 $35.3 million

Average Cost Per Unit                  $201,700


Figure IV.2: Turk Street Apartments,
San Francisco, CA




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                                  Appendix IV
                                  Results of Site Visits to GAO Sample
                                  Properties




Mount Mercy, Grand                Mount Mercy is a 1-bedroom rental unit property for elderly residents. A
Rapids, Michigan                  former Catholic girls school, this property contains one elevator high-rise
                                  building that was purchased and rehabilitated without the use of federal
                                  subsidies other than the low-income housing tax credit program. The
                                  average annual income of the typical resident 1-person household is about
                                  $12,400, compared with an area median income of $45,100. Monthly rents
                                  are $295 including utilities, and no resident receives rental assistance.
                                  Mount Mercy had a 98 percent occupancy rate during 1995.

Tax Credit Award                  4 percent and 9 percent

Total Residential Units           125

Total Low-Income Units            125

Total Development Cost            $6.1 million

Average Cost Per Unit             $48,800


Figure IV.3: Mount Mercy, Grand
Rapids, MI




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                                        Properties




Graham/Terry, Seattle,                  Graham/Terry is an elevator high-rise property that contains both newly
Washington                              constructed and rehabilitated buildings that were developed without
                                        federal subsidies other than the low-income housing tax credit program.
                                        The buildings are nearly 75 percent efficiency units, and the average
                                        annual income of the typical single-resident household is about $10,700,
                                        compared with an area median income of $52,800. Monthly rent for an
                                        efficiency unit is $280 including utilities, and all but a few residents (less
                                        than 10) pay full rent without benefit of rental assistance. Graham/Terry
                                        had a 95 percent occupancy rate during 1995.

Tax Credit Award                        4 percent and 9 percent

Total Residential Units                 121

Total Low-Income Units                  121

Total Development Cost                  $7.6 million

Average Cost Per Unit                   $62,800


Figure IV.4: Graham/Terry, Seattle WA




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                                      Properties




Providence Square, New                Providence Square is a 1-bedroom rental unit property for elderly
Brunswick, New Jersey                 residents. A former cigar factory, this property comprises one elevator
                                      high-rise building that was rehabilitated without the use of federal
                                      subsidies other than the low-income housing tax credit program. The
                                      average annual income of the typical resident 1-person household is about
                                      $16,200, compared with an area median income of $67,400. Average
                                      monthly rents are $438 including utilities, and no household receives
                                      rental assistance. Providence Square was fully occupied during 1995.

Tax Credit Award                      9 percent

Total Residential Units               99

Total Low-Income Units                99

Total Development Cost                $11.1 million

Average Cost Per Unit                 $112,100


Figure IV.5: Providence Square, New
Brunswick, NJ




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                                         Properties




O’hern House, Atlanta,                   O’Hern House is a home for troubled and homeless residents. A former
Georgia                                  shoe factory, this property contains only efficiency rental units in a 4-story
                                         elevator high-rise building that was gutted and completely renovated using
                                         historic preservation and low-income housing tax credit program
                                         subsidies. The average annual income of the single resident population is
                                         about $4,283, compared with an area median income of $52,100. Monthly
                                         rent is about $150 including utilities. The rent level is set at 30 percent of a
                                         resident’s monthly income, which typically comes from supplemental
                                         (SSI) and disability (SSDI) Social Security income sources. No resident
                                         receives state or federal rental assistance. As a special needs project,
                                         O’Hern House contains many amenities and services, such as (1) a
                                         cafeteria that provides three meals a day at no charge, (2) maid service at
                                         no charge 2 days a week, (3) full building security, (4) laundry facilities
                                         and recreation rooms on every floor, (5) an in-house newsletter and tenant
                                         association, and (6) psychological and medical professionals available to
                                         residents who are mentally challenged and previously homeless. These
                                         features are provided in part through a $1.3 million annual operating
                                         subsidy from the Georgia Department of Human Resources. O’Hern House
                                         had a 97 percent occupancy rate during 1995.

Tax Credit Award                         9 percent

Total Residential Units                  76

Total Low-Income Units                   76

Total Development Cost                   $2.9 million

Average Cost Per Unit                    $38,200


Figure IV.6: O’hern House, Atlanta, GA




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                          Appendix IV
                          Results of Site Visits to GAO Sample
                          Properties




Suburban Projects

Cascade Commons,          Cascade Commons is composed of multiple garden-style, walk-up
Sterling, Virginia        buildings for family residents in 2- and 3-bedroom units. It was newly
                          constructed without federal subsidies other than the low-income housing
                          tax credit program. About 75 percent of the units are 2-bedroom
                          apartments where the average 2-person household has an annual income
                          of nearly $27,000, compared to an area median income of $68,300. Average
                          monthly rent and all utility charges for a 2-bedroom unit at Cascade
                          Commons amount to about $835, and no household receives rental
                          assistance. Although this property reported a 43 percent average vacancy
                          rate in 1995, it currently has a 93 percent occupancy rate, and it reported
                          achieving a 90 percent occupancy rate within 3 months of being placed in
                          service.

Tax Credit Award          9 percent

Total Residential Units   320

Total Low-Income Units    320

Total Development Cost    $28.6 million

Average Cost Per Unit     $89,400




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                                Properties




Figure IV.7: Cascade Commons,
Sterling, VA




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                                       Properties




Rancho Del Mar, Tucson,                Rancho Del Mar is a 1- and 2-bedroom unit rental property for family
Arizona                                residents. It is made up of multiple garden-style buildings, newly
                                       constructed without the use of federal subsidies from other than the
                                       low-income housing credit program. The average annual income of the
                                       typical resident 2-person household is $12,300; $14,600 for the typical
                                       resident 3-person household, compared to an area median income of
                                       $37,800. Average monthly rents including utilities at Rancho Del Mar vary
                                       from $390 for a 1-bedroom unit to $452 for a 2-bedroom unit. Although
                                       most low-income residents in this property pay unsubsidized rents,
                                       households with rental assistance pay an average of $26 a month for a
                                       1-bedroom unit and $55 a month for a 2-bedroom unit. Rancho Del Mar
                                       had a 94 percent occupancy rate during 1995.

Tax Credit Award                       9 percent

Total Residential Units                312

Total Low-Income Units                 312

Total Development Cost                 $8.8 million

Average Cost Per Unit                  $28,200


Figure IV.8: Rancho Del Mar, Tucson,
AZ




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                                          Results of Site Visits to GAO Sample
                                          Properties




Covington Court, St. Paul,                Covington Court is a family rental property. It is made up of multiple
Minnesota                                 3-story mid-rise buildings that were rehabilitated with federal subsidies.
                                          The property has a mix of 1- and 2-bedroom units but is predominantly
                                          1-bedroom. The average annual income of the typical 1-person household
                                          living in a 1-bedroom unit is $14,100, compared to an area median income
                                          of $54,600. Monthly rent including utilities for a 1-bedroom unit is $434.
                                          About one-third of the households occupying 1-bedroom units receive
                                          rental assistance and pay, on average, only $123 a month for rent.
                                          Covington Court had a 98 percent occupancy rate during 1995.

Tax Credit Award                          4 percent

Total Residential Units                   160

Total Low-Income Units                    160

Total Development Cost                    $3.6 million

Average Cost Per Unit                     $22,500


Figure IV.9: Covington Court, St. Paul,
MN




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                                  Appendix IV
                                  Results of Site Visits to GAO Sample
                                  Properties




Lakewood Terrace,                 Lakewood Terrace is a collection of garden-style 2-story buildings
Lakeland, Florida                 containing rental units for family residents. These buildings were
                                  purchased and rehabilitated with federal subsidies, including the
                                  low-income housing tax credit program. Mostly 2- and 3-bedroom units,
                                  Lakewood Terrace also offers some 1-bedroom and 4-bedroom units. The
                                  average annual income of the typical 4-person household occupying a
                                  3-bedroom unit is $6,372, compared with an area median income of
                                  $35,900. Average monthly rent including utilities for the 3-bedroom unit is
                                  $429. However, since all rental units in this property have section 8
                                  project-based assistance attached to them, the average rent paid by a
                                  low-income family in a 3-bedroom unit, for example, is about $77 a month.
                                  Lakewood Terrace had a 95 percent occupancy rate during 1995.

Tax Credit Award                  4 percent

Total Residential Units           132

Total Low-Income Units            132

Total Development Cost            $7.2 million

Average Cost Per Unit             $54,500


Figure IV.10: Lakewood Terrace,
Lakeland, FL




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                                 Appendix IV
                                 Results of Site Visits to GAO Sample
                                 Properties




Mansfield Manor,                 Mansfield Manor is a rental property for special needs elderly and disabled
Mansfield, Texas                 residents. It is made up of 1- and 2-bedroom townhouses that were newly
                                 constructed using multiple federal subsidies. About half of its units are
                                 2-bedroom apartments in which the average 2.3-person household has an
                                 average annual income of $9,211, compared to an area median income of
                                 $47,500. Monthly rent including utilities for these units is $284, but most
                                 resident households have rental assistance and pay, on average, $81 a
                                 month in rent. Mansfield Manor was fully occupied in 1995.

Tax Credit Award                 4 percent

Total Residential Units          52

Total Low-Income Units           52

Total Development Cost           $2.1 million

Average Cost Per Unit            $40,400


Figure IV.11: Mansfield Manor,
Mansfield, TX




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                                        Appendix IV
                                        Results of Site Visits to GAO Sample
                                        Properties




Rural Projects

Lake Pointe, Conway,                    The Lake Pointe Apartments contain 1- and 2-bedroom rental units for
Arkansas                                family residents. This walk-up, garden-style building community was
                                        newly constructed without the use of federal subsidies other than the
                                        low-income housing tax credit. The average annual income of the typical
                                        2-person household living in a 2-bedroom unit is about $14,210, compared
                                        with an area median income of $39,000. Average monthly rent including
                                        utilities for these 2-bedroom units is $375, and no households receive
                                        rental assistance. Lake Pointe had a 98 percent occupancy rate during
                                        1995.

Tax Credit Award                        9 percent

Total Residential Units                 132

Total Low-Income Units                  132

Total Development Cost                  $5.1 million

Average Cost Per Unit                   $38,600


Figure IV.12: Lake Pointe, Conway, AR




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                                      Appendix IV
                                      Results of Site Visits to GAO Sample
                                      Properties




Post Glen, Oceana, West               Post Glen is a 1- and 2-bedroom elevator mid-rise building for elderly
Virginia                              residents. It was newly constructed using federal subsidies, including the
                                      low-income housing tax credit program. The average annual income of the
                                      typical single-resident household is about $5,788, compared with an area
                                      median income of $24,400. Monthly rent including utilities is $355, but
                                      almost all households receive rental assistance and pay, on average, only
                                      $94 of this monthly rent amount. Post Glen was 70-percent occupied in
                                      1995.

Tax Credit Award                      4 percent

Total Residential Units               41

Total Low-Income Units                40

Total Development Cost                $1.8 million

Average Cost Per Unit                 $43,700


Figure IV.13: Post Glen, Oceana, WV




                                      Page 167                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                     Appendix IV
                                     Results of Site Visits to GAO Sample
                                     Properties




Edgewood Apartments,                 Edgewood Apartments is a garden-style, walk-up community for family
Belton, South Carolina               residents. Its predominantly 2-bedroom rental unit buildings were
                                     rehabilitated without using federal subsidies, other than the low-income
                                     housing tax credit program. The average annual income of the typical
                                     2-person household is $10,675, compared to an area median income of
                                     $40,300. Monthly rent including utilities is $322. Only a few families receive
                                     rental assistance, and these households pay, on average, about $54 in rent.
                                     About half of Edgewood’s rental units were vacant during 1995.

Tax Credit Award                     9 percent

Total Residential Units              32

Total Low-Income Units               32

Total Development Cost               $735,000

Average Cost Per Unit                $23,000


Figure IV.14: Edgewood, Belton, SC




                                     Page 168                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
                                      Appendix IV
                                      Results of Site Visits to GAO Sample
                                      Properties




Hardwick, Hardwick,                   Hardwick contains seven units of family rental housing in one garden-style
Vermont                               walk-up building. It was newly constructed with federal subsidies,
                                      including the low-income housing tax credit program. Six of the seven
                                      rental units are 2-bedroom apartments, in which the typical household
                                      contains two people whose average annual income is less than the average
                                      of the other 2-bedroom, 2-person households in this appendix and less
                                      than half of the area median income where this property is located.
                                      Monthly rent including utilities for these 2-bedroom units is $386, but half
                                      of the six households receive rental assistance and pay, on average, only
                                      $160 in rent. Hardwick had an 86 percent occupancy rate (one vacancy)
                                      during 1995.

Tax Credit Award                      4 percent

Total Residential Units               7

Total Low-Income Units                7

Total Development Cost                $950,000

Average Cost Per Unit                 $135,500


Figure IV.15: Hardwick, Hardwick VT




                                      Page 169                               GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix V

Comments From the Internal Revenue
Service




              Page 170   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix VI

Comments From the National Council of
State Housing Agencies




              Page 171   GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix VI
Comments From the National Council of
State Housing Agencies




Page 172                          GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix VI
Comments From the National Council of
State Housing Agencies




Page 173                          GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix VI
Comments From the National Council of
State Housing Agencies




Page 174                          GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
Appendix VII

Major Contributors to This Report


                        Ralph T. Block, Assistant Director, Tax Policy and Administration Issues
General Government      Thomas M. Richards, Senior Evaluator
Division, Washington,
D.C.
                        Dennis W. Fricke, Assistant Director, Housing and Community
Resources,              Development Issues
Community, and          William F. Bley, Senior Evaluator
Economic                Andrew E. Finkel, Senior Evaluator
                        Diane T. Brooks, Senior Evaluator
Development
Division, Washington,
D.C.
                        George A. Zika, Evaluator-in-Charge
San Francisco Office    Kathleen E. Seymour, Senior Evaluator
                        Arthur L. Davis, Senior Evaluator
                        Mary L. Jankowski, Evaluator
                        Sharon K. Caporale, Evaluator
                        Susan S. Mak, Evaluator


                        Karen E. Bracey, Assistant Director, Design, Methodological, and
Technical Support       Technical Group
                        Patrick B. Doerning, Senior Operations Research Analyst
                        Luann M. Moy, Senior Social Science Analyst
                        Elizabeth R. Eisenstadt, Communication Analyst
                        Samuel H. Scrutchins, Technical Advisor
                        Donna M. Leiss, Communications Analyst


                        Joanna M. Stamatiades, Senior Evaluator-Atlanta Office
Survey Team             Salley P. Gilley, Evaluator-Atlanta Office
Members                 Nancy S. Barry, Senior Evaluator-Boston Office
                        Frank M. Taliaferro, Senior Evaluator-Chicago Office
                        Marvin G. McGill, Evaluator-Kansas City Office
                        Margarita A. Vallazzo, Evaluator-Kansas City Office
                        Jennie B. Davis, Senior Evaluator-Dallas Office
                        Willie D. Watson, Senior Evaluator-Dallas Office




(268750)                Page 175                      GAO/GGD/RCED-97-55 Low-Income Housing Tax Credit
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