Tax Credits: Opportunities to Improve Oversight of the Low-Income Housing
Program (Chapter Report, 03/28/97, GAO/GGD/RCED-97-55).

The low-income housing tax credit is now the largest federal program
used 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 may be
taken annually for 10 years by investors in qualified low-income housing
projects to offset federal income taxes. 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 more than $3
billion. This report discusses the characteristics of the residents and
properties that have benefited from tax credits and assesses the
controls the Internal Revenue Service and the states have in place 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
summarized this report in testimony before Congress; see: Tax Credits:
Opportunities to Improve Oversight of the Low-Income Housing Program, by
James R. White, Associate Director for Tax Policy and Administration
Issues, before the Subcommittee on Oversight, House Committee on Ways
and Means (GAO/T-GGD/RCED-97-149, Apr. 23).

--------------------------- Indexing Terms -----------------------------

 REPORTNUM:  GGD/RCED-97-55
     TITLE:  Tax Credits: Opportunities to Improve Oversight of the 
             Low-Income Housing Program
      DATE:  03/28/97
   SUBJECT:  Low income housing
             Rental housing
             Tax credit
             Disadvantaged persons
             Federal/state relations
             Housing programs
             Monitoring
             State-administered programs
             Cost control
             Tax law
IDENTIFIER:  Community Development Block Grant
             HUD Home Investment Partnership Program
             HUD Low Income Housing Tax Credit Program
             
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Cover
================================================================ COVER


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

Low-Income Housing Tax Credit

(268750)


Abbreviations
=============================================================== ABBREV

  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

Letter
=============================================================== LETTER


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
============================================================ Chapter 0


   PURPOSE
---------------------------------------------------------- Chapter 0:1

The low-income housing tax credit is currently the largest federal
program 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. 


   BACKGROUND
---------------------------------------------------------- Chapter 0:2

Congress established the low-income housing tax credit program as an
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 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. 

IRS is 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 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. 


   RESULTS IN BRIEF
---------------------------------------------------------- Chapter 0:3

Given the results of its random sample, GAO estimates that about
4,100 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 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 IRS regulations, 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 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. 

IRS recently 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
---------------------------------------------------------- Chapter 0:4


      LOW-INCOME HOUSING TAX
      CREDIT PROJECTS VARY IN
      TENANT CHARACTERISTICS,
      PROPERTY CHARACTERISTICS,
      AND COSTS
-------------------------------------------------------- Chapter 0:4.1

From its sample, GAO estimates that about 4,100 low- income housing
projects containing about 172,000 tax credit supported units were
placed in service during the period 1992 through 1994.  About an
estimated three-quarters of the households had incomes in 1996 that
were at or below 50 percent of their area's median income, which the
Department of 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 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
      ALLOCATING CREDITS TO
      HOUSING NEEDS VARY
-------------------------------------------------------- Chapter 0:4.2

The Internal Revenue Code gives state agencies wide latitude in
determining which projects should receive tax credits.  The Code
requires 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 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 IMPROVING
      STATES' CONTROLS OVER
      PROJECT COSTS
-------------------------------------------------------- Chapter 0:4.3

In order to limit the federal share of housing development project
costs, states are to provide no more tax credits to projects than
necessary for 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

  -- 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, 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 MADE IN
      STATE AND IRS OVERSIGHT
      ACTIVITIES
-------------------------------------------------------- Chapter 0:4.4

Not all states fulfilled the requirements of their compliance
monitoring programs, and, although IRS has been developing oversight
programs, it did 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. 

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
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. 


   RECOMMENDATIONS
---------------------------------------------------------- Chapter 0:5

The low-income housing tax credit program has stimulated low-income
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. 


   FEDERAL AGENCY AND STATE
   ASSOCIATION COMMENTS
---------------------------------------------------------- Chapter 0:6

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

  -- 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. 


INTRODUCTION
============================================================ Chapter 1

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. 


   BACKGROUND
---------------------------------------------------------- Chapter 1:1

In establishing the tax credit incentive, Congress recognized that a
private 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 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. 


   TRANSFERRING TAX CREDITS FROM
   THE FEDERAL GOVERNMENT TO THE
   PRIVATE SECTOR
---------------------------------------------------------- Chapter 1:2

To manage the transfer of federal tax credits to the private sector,
Congress established a multistep federal/state process, which is
depicted in figure 1.1 and described in the accompanying narrative. 

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

   (See figure in printed
   edition.)

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

   (See figure in printed
   edition.)

(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 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

(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 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 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. 


--------------------
\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. 

\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. 


   OVERSEEING COMPLIANCE WITH THE
   TAX CREDIT PROGRAM'S
   REQUIREMENTS
---------------------------------------------------------- Chapter 1:3

To promote compliance with the tax credit program's requirements, the
Internal Revenue Code establishes a joint federal/state oversight
system.  In summary, the states are the governmental entities
responsible for determining whether housing projects qualify for tax
credits, allocating credits to qualifying projects, and overseeing
the compliance by the 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. 

   Figure 1.2:  Tax Credit
   Oversight System

   (See figure in printed
   edition.)

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

   (See figure in printed
   edition.)

(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 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. 


   OBJECTIVES, SCOPE, AND
   METHODOLOGY
---------------------------------------------------------- Chapter 1:4

The Chairman, House Committee on Ways and Means, asked us to study
the controls established by the states and IRS for implementing the
tax 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 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 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. 


--------------------
\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. 

\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. 


      CHARACTERISTICS OF PROJECTS
      AND THEIR TENANTS
-------------------------------------------------------- Chapter 1:4.1

To determine the characteristics of low-income housing tax credit
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
      STATE PRIORITY HOUSING NEEDS
-------------------------------------------------------- Chapter 1:4.2

To determine whether state agencies had established controls for
appropriately allocating credits to state needs, we used data from
the state 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 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
      PROJECT COSTS AND TAX
      CREDITS
-------------------------------------------------------- Chapter 1:4.3

To evaluate the controls state agencies used to determine the
reasonableness of project costs and tax credit awards, we analyzed
the 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
      ACTIVITIES
-------------------------------------------------------- Chapter 1:4.4

To evaluate state oversight activities, we analyzed data from both
the 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 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. 


   STATE ASSOCIATION COMMENTS AND
   OUR EVALUATION
---------------------------------------------------------- Chapter 1:5

NCSHA had comments on our methodology in two respects:  (1) the
number of large developments we included in our sample, and (2) the
composition of the projects we included in appendix IV, "Results of
Site Visits to GAO 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 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. 


LOW-INCOME HOUSING TAX CREDIT
PROPERTIES:  THEIR RESIDENTS,
CHARACTERISTICS, AND COSTS
============================================================ Chapter 2

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. 


   REPORTED INCOMES FOR MOST TAX
   CREDIT HOUSEHOLDS WERE VERY LOW
---------------------------------------------------------- Chapter 2:1

As noted in chapter 1, to participate in the tax credit program, an
owner must reserve a specific proportion of the units in the property
for lower income households.  At a minimum, the owner must set aside
either (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 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.)

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

   (See figure in printed
   edition.)

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

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

   (See figure in printed
   edition.)

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
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 Additional Rental
                   Assistance Residing in Tax Credit
                 Properties Placed in Service, 1992-94

                                                        Average income
                                                                  as a
                                             Average    percent of the
                            Percent of       current            area's
Type of Household           households        income    median income\
------------------------  ------------  ------------  ----------------
Received additional                 39        $7,858                25
 rental assistance\a
Did not receive                     61        16,709                45
 additional rental
 assistance\a
======================================================================
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. 


   TAX CREDIT HOUSEHOLDS WERE
   GENERALLY SMALL AND PROJECTS
   HAD DIVERSE RESIDENT
   POPULATIONS
---------------------------------------------------------- Chapter 2:2

Data we obtained from tax credit property managers indicated that the
tax credit program primarily served small households.  We estimate
that about 67 percent of the households included one or two people
and the average household consisted of 2.2 persons.  Figure 2.3 shows
the distribution of households by size. 

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

   (See figure in printed
   edition.)

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 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. 


--------------------
\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. 

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


   PROPERTIES WERE WIDESPREAD,
   UNITS WERE GENERALLY SMALL, AND
   RENTS WERE RESTRICTED
---------------------------------------------------------- Chapter 2:3

On the basis of our sample, we estimate that about 4,100 properties
developed under the tax credit program were placed in service between
1992 and 1994 in the continental United states.  These data also
indicate 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.  Appendix III provides further details on all properties
placed in service between 1992 and 1994, as well as additional
information on those we sampled. 


      PROPERTIES WERE WIDESPREAD
-------------------------------------------------------- Chapter 2:3.1

From our sample, we estimate that approximately 53 percent of the
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.)

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

   (See figure in printed
   edition.)

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


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


      PROPERTY STYLES VARIED AND
      SMALL UNITS WERE COMMON
-------------------------------------------------------- Chapter 2:3.2

Our data indicate that the most common type of tax credit property
placed 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 BELOW
      ALLOWABLE MAXIMUMS
-------------------------------------------------------- Chapter 2:3.3

For units that are eligible for tax credits, rents are generally
limited by the set-aside standard selected by the developer--that is,
rents are usually 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 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 a month.  (See ch.  4 for further discussion of how rental
assistance affects the federal cost of the tax credit program.)


--------------------
\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. 


      MOST OWNERS WERE LIMITED
      PARTNERS
-------------------------------------------------------- Chapter 2:3.4

Most--an estimated 82 percent--of the tax credit properties placed in
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. 


   TAX CREDIT AND DEVELOPMENT
   COSTS VARIED WIDELY
---------------------------------------------------------- Chapter 2:4

When tax credit property owners use their tax credits, taxpayers
subsidize the development costs of tax credit properties.  However,
total federal cost for tax credit properties includes the costs not
only of the tax credits but 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
      WIDELY
-------------------------------------------------------- Chapter 2:4.1

For tax credit properties placed in service between 1992 and 1994, we
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. 

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

   (See figure in printed
   edition.)

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. 


      PROPERTIES' PHYSICAL
      CHARACTERISTICS, COMMUNITY
      DEVELOPMENT NEEDS, AND
      CONTROLS AFFECT DEVELOPMENT
      COSTS
-------------------------------------------------------- Chapter 2:4.2

Project development costs, including land acquisition outlays,
building acquisition and/or construction costs, builders' overhead
and profit, and financing costs, varied widely across tax credit
properties.  We estimate that the average cost of developing the
units placed in service between 1992 and 1994 was about $60,000.\7
About two-thirds of these units cost less 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

   (See figure in printed
   edition.)

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. 

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. 

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

   (See figure in printed
   edition.)

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 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. 


--------------------
\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. 


   OBSERVATIONS
---------------------------------------------------------- Chapter 2:5

Tax credit allocating agencies target and serve very low-income
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. 


   STATE ASSOCIATION COMMENTS AND
   OUR EVALUATION
---------------------------------------------------------- Chapter 2:6

In commenting on this report, NCSHA noted that although it had
previously expressed concerns about potential bias and prejudgment in
some aspects of our work, the report answered many of those concerns. 

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 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. 


STATES' CONTROLS FOR ALLOCATING
CREDITS TO HOUSING NEEDS VARY
============================================================ Chapter 3

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. 


--------------------
\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. 


   INTERNAL REVENUE CODE GIVES
   AGENCIES WIDE LATITUDE IN
   ALLOCATING TAX CREDITS
---------------------------------------------------------- Chapter 3:1

Section 42 of the Internal Revenue Code requires the housing credit
allocating agencies to develop qualified allocation plans to target
their tax credits to proposed housing projects that meet their
"housing priorities" and that include selection criteria that are
"appropriate to local conditions." In addition, the Code requires the
agencies to "give 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 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. 


   AGENCIES HAVE DEFINED THE
   PROGRAM'S REQUIREMENTS IN
   DIFFERENT WAYS
---------------------------------------------------------- Chapter 3:2

Before developing their qualified allocation plans, the allocating
agencies must define their housing priorities and the terms
"appropriate to local conditions," "lowest-income", and "longest
periods." Our review showed the agencies have defined these program
requirements in different ways and, when evaluating the requirements,
have used varying amounts of information and analysis. 


      AGENCIES PRIMARILY RELIED ON
      CONSOLIDATED PLANS TO DEFINE
      THEIR HOUSING PRIORITIES
-------------------------------------------------------- Chapter 3:2.1

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


--------------------
\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. 


         STATES USED CENSUS DATA
         TO DEVELOP THEIR
         CONSOLIDATED PLANS
------------------------------------------------------ Chapter 3:2.1.1

To develop their consolidated plans, the states rely primarily on
special tabulations of demographic and housing data from the 1990
Census that 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 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. 


--------------------
\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. 


         CENSUS DATA HAVE
         LIMITATIONS
------------------------------------------------------ Chapter 3:2.1.2

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,
         UPDATED, OR FURTHER
         ANALYZED CENSUS DATA
------------------------------------------------------ Chapter 3:2.1.3

To obtain more detailed or more current information, some of the
states whose consolidated plans we reviewed supplemented or updated
their 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, 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 STUDIES
      TO DEFINE APPROPRIATENESS TO
      LOCAL CONDITIONS
-------------------------------------------------------- Chapter 3:2.2

As discussed in the preceding paragraphs, the states have taken
various steps to obtain the data required to identify and rank their
housing needs 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 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. 

Both HUD\4 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: 

  -- 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. 


--------------------
\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. 


      AGENCIES HAVE DEFINED LOWEST
      INCOME AND LONGEST PERIODS
-------------------------------------------------------- Chapter 3:2.3

Using the discretion allowed in the Internal Revenue Code, agencies
differed in defining the terms "lowest income" and "longest periods."
All of 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. 


         LOWEST INCOME
------------------------------------------------------ Chapter 3:2.3.1

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 USE
------------------------------------------------------ Chapter 3:2.3.2

As discussed in chapter 1, the Tax Reform Act of 1986 initially
required tax 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. 


   ALLOCATION PLANS WEIGHT
   SELECTION CRITERIA
---------------------------------------------------------- Chapter 3:3

Defining the tax credit program's broad requirements, including
"housing priorities," "appropriate to local conditions," "lowest
income," and "longest periods," is one step in developing the
required qualified allocation plan.  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
-------------------------------------------------------- Chapter 3:3.1

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


--------------------
\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. 


      WEIGHTING OF SELECTION
      CRITERIA
-------------------------------------------------------- Chapter 3:3.2

The 20 allocation plans that we reviewed weighted the selection
criteria by 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. 


   ALLOCATION PLANS PROVIDED FOR
   TARGETING TAX CREDITS
---------------------------------------------------------- Chapter 3:4

To gain more insight into the allocating agencies' approaches for
weighting selection criteria in their allocation plans, we focused on
the means used to give preference to proposed projects serving the
lowest 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
      PREFERENCE TO LOWEST INCOME
-------------------------------------------------------- Chapter 3:4.1

In responding to our survey, all of the 54 allocating agencies
reported giving preference to proposed projects serving the lowest
income tenants.  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 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. 

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.  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
      PREFERENCE TO EXTENDED USE
-------------------------------------------------------- Chapter 3:4.2

In responding to our survey, 49 of the 54 allocating agencies
reported giving preference to projects with agreements to serve
qualified tenants 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 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 part, on the economics of doing so.  The economic
viability of these projects as long-term low-income housing is
discussed below. 


--------------------
\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. 


   SEVERAL FACTORS MAY AFFECT THE
   HOUSING ACTUALLY DELIVERED OVER
   TIME
---------------------------------------------------------- Chapter 3:5

No matter how carefully the allocating agencies define their housing
priorities or control the allocation of tax credits through their
allocation plans, several factors have the potential to affect the
housing actually delivered over time.  First, nearly all of the
agencies reserve some discretion for amending or bypassing the
process.  Second, a significant 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
      ALLOCATION PROCESS TO BE
      BYPASSED
-------------------------------------------------------- Chapter 3:5.1

Seventeen of the 20 qualified allocation plans that we reviewed
provide flexibility for overriding or bypassing the allocation
process.  This 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,

  -- 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 ALLOCATED
      CREDITS THAN ARE PLACED IN
      SERVICE
-------------------------------------------------------- Chapter 3:5.2

Our analysis of data--from the states, IRS, and a study contracted by
HUD--suggests that the states may not be fully using their tax credit
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, 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 difficulties of
monitoring reallocated tax credits are discussed in chapter 5. 


      EXTENDED-USE COMMITMENTS
      HAVE NOT BEEN TESTED
-------------------------------------------------------- Chapter 3:5.3

Because no tax credit properties are old enough to have outlived
their tax credits, the economic viability of these projects as
long-term high-quality 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. 


   CONCLUSIONS
---------------------------------------------------------- Chapter 3:6

All the states had developed qualified tax credit allocation plans,
required 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 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. 


OPPORTUNITIES FOR IMPROVING
STATES' CONTROLS OVER PROJECT
COSTS
============================================================ Chapter 4

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. 


   TAX CODE REQUIREMENTS
---------------------------------------------------------- Chapter 4:1

The Internal Revenue Code directs that allocating agencies shall not
award tax credits to a qualified low-income housing project in excess
of the 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 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 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. 

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

   (See figure in printed
   edition.)

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. 


--------------------
\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. 

\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. 


   ALLOCATING AGENCY PRACTICES FOR
   ENSURING REASONABLE DEVELOPMENT
   COSTS
---------------------------------------------------------- Chapter 4:2

Section 42 of the Internal Revenue Code directs the states to
consider the "reasonableness" of housing project development costs
when determining the amount of tax credits necessary for project
feasibility, but it does not specify how "reasonableness" should be
determined.  Rather, Congress provided the states with the
flexibility to respond to their unique and 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. 

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
      OVERALL DEVELOPMENT COSTS
-------------------------------------------------------- Chapter 4:2.1

In its 1993 report, NCSHA recognized that public support for the tax
credit 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. 

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. 

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. 


--------------------
\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. 


      STANDARDS FOR EVALUATING
      COMPONENTS OF OVERALL COSTS
-------------------------------------------------------- Chapter 4:2.2

In addition to advocating the adoption of a standard for controlling
overall development costs, NCSHA recommended that the allocating
agencies adopt 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
------------------------------------------------------ Chapter 4:2.2.1

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 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. 


--------------------
\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. 

\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. 


      FEES TO BUILDERS AND RELATED
      PARTIES
-------------------------------------------------------- Chapter 4:2.3

NCSHA recommended that the allocating agencies set limits on the fees
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. 

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. 


--------------------
\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. 


         CONSULTANT AND
         PROFESSIONAL FEES
------------------------------------------------------ Chapter 4:2.3.1

To control consulting fees, NCSHA recommended that the states (1)
identify 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
------------------------------------------------------ Chapter 4:2.3.2

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 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. 


--------------------
\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. 


      COMPETITION AS A CONTROL
      OVER PROJECT COSTS
-------------------------------------------------------- Chapter 4:2.4

Competition among developers for tax credits is another control over
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. 

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. 


   ALLOCATING AGENCY PRACTICES FOR
   DETERMINING PROJECT EQUITY
   NEEDS
---------------------------------------------------------- Chapter 4:3

After giving consideration to the reasonableness of a project's
development costs, allocating agencies are to determine a project's
financing deficit, i.e., the amount of development costs that a
project is not 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 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;

  -- 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. 


--------------------
\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. 


      AGENCY PROCEDURES FOR
      ASSESSING PROJECT INCOME
-------------------------------------------------------- Chapter 4:3.1

All of the 54 allocating agencies reported checking the
reasonableness of a 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
      ASSESSING PRIVATE FINANCING
-------------------------------------------------------- Chapter 4:3.2

All but 8 of the 54 allocating agencies reported having written
guidelines to assist their staffs in determining the reasonableness
of a project's private financing and the amount of such financing
that a project can support.  The 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 Service Coverage
                    Ratios and Amortization Periods

                                           Amortization period
                                    ----------------------------------
                      Debt service
                          coverage
Interest rate                ratio    30 years    20 years    15 years
--------------------  ------------  ----------  ----------  ----------
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. 

  -- 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. 


--------------------
\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. 


      REVIEWS OF OTHER PUBLIC
      SUBSIDIES
-------------------------------------------------------- Chapter 4:3.3

The Code directs the allocating agencies to evaluate the total
financing for 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 award\10 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. 



                               Table 4.2
                
                   Estimated Sources of Financing for
                Projects Requiring Subsidies in Addition
                             to Tax Credits

                                                            Percentage
                                                                    of
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. 

  -- 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. 


--------------------
\10 See footnote 1, page 74. 

\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. 

\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. 


   STATE CONTROLS OVER TAX CREDIT
   PRICING
---------------------------------------------------------- Chapter 4:4

After determining a project's financing deficit, allocating agencies
are to calculate the amount of the tax credit award.  The award may
not exceed 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 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 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. 


--------------------
\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. 


      TAX CREDIT PRICE EXPERIENCE
-------------------------------------------------------- Chapter 4:4.1

Even though allocating agencies and syndicators refer to equity
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 Placed In
                           Service, 1992-1994

                                                               Overall
                                                    distribution 1992-
Equity price                                                      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. 

  -- 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. 


   EFFECTIVENESS OF COST CONTROLS
   DEPENDS ON ACCURACY OF COST
   DATA
---------------------------------------------------------- Chapter 4:5

In controlling federal 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 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 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. 

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. 


--------------------
\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. 

\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. 


   CONCLUSION
---------------------------------------------------------- Chapter 4:6

In implementing their responsibilities for controlling the amount of
tax 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 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. 

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. 


   RECOMMENDATION TO THE
   COMMISSIONER OF INTERNAL
   REVENUE
---------------------------------------------------------- Chapter 4:7

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


   FEDERAL AGENCY AND STATE
   ASSOCIATION COMMENTS AND OUR
   EVALUATION
---------------------------------------------------------- Chapter 4:8

In commenting on this report, IRS advised us that it agreed with the
recommendation and would proceed to determine how best to implement
it. 

NCSHA, in commenting on the report, expressed concern about "bias and
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. 


OPPORTUNITIES EXIST TO IMPROVE
STATE AND FEDERAL COMPLIANCE
OVERSIGHT ACTIVITIES
============================================================ Chapter 5

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. 

   Figure 5.1:  Tax Form Flow and
   Oversight

   (See figure in printed
   edition.)

   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.

   (See figure in printed
   edition.)

   Source:  GAO discussions with
   IRS.

   (See figure in printed
   edition.)

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
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. 


   OPPORTUNITIES TO IMPROVE STATE
   OVERSIGHT
---------------------------------------------------------- Chapter 5:1

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

IRS allowed 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 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
      MONITORING PROCEDURES THAT
      MET IRS REQUIREMENTS, BUT
      SOME STATES DID NOT FOLLOW
      THEIR PROCEDURES
-------------------------------------------------------- Chapter 5:1.1

Since June 30, 1992, for state agencies to have a qualified
allocation plan, they must include a procedure for monitoring tax
credit projects to determine if the projects are in compliance with
tax credit program requirements.  IRS regulations require state
agencies to annually review project owners' certifications that their
projects met all low-income housing statutory requirements, such as
serving the minimum number of 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. 

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                    Did fewer        Total
                        either desk or  Conducted both      reviews       number
                               on-site    desk and on-         than     of state
Option                       reviews\a    site 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 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 RECOMMENDED STATES
      DO MORE ON-SITE INSPECTIONS
-------------------------------------------------------- Chapter 5:1.2

Although IRS has established minimum monitoring requirements, NCSHA
has recommended that state agencies do more than required.  For the
most 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 Did Not
                 Meet NCSHA's Monitoring Guidelines in
                                  1995

                                                             Number of
                                                                 state
NCSHA guideline                                               agencies
--------------------------------------------------------  ------------
On-site visit made within 1 year of placed in service                8
 date
On-site visit made at least once every 3 years                      11
On-site visit made both within 1 year of placed in                22\a
 service date and once every 3 years
Did not make on-site visits either within 1 year of                 13
 placed in service date or every 3 years.
======================================================================
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. 

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 Reviews and On-Site
                  Inspections That Found At Least One
                       Incident of Noncompliance

                                                            Percent of
                                            Percent of    time type of
                                          time type of   noncompliance
                                         noncompliance   found through
                                         found through         on-site
Type of noncompliance                    desk review\a    inspection\a
--------------------------------------  --------------  --------------
Tenant(s) not income eligible                       30              13
Rents too high                                      12               7
Building code violation or other                     0              43
 building condition
Administrative requirement not met\b                35              10
Annual income certification either                  53              34
 submitted late or not received
Improper income certification or                     2              26
 failure to properly verify
 certification
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 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. 


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


      MOST STATE AGENCIES REPORTED
      NONCOMPLIANCE ISSUES TO IRS
-------------------------------------------------------- Chapter 5:1.3

As part of their monitoring responsibilities, state agencies are
required to report to IRS and project owners all instances of owner
noncompliance or 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.  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 1995

                                                          Total number
                                             Number of   of Form 8823s
Number of Form 8823s submitted to IRS   state 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

  -- 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. 


--------------------
\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. 


      ADDITIONAL COMPLIANCE
      ACTIVITIES CARRIED OUT FOR
      PROJECTS THAT ALSO RECEIVE
      STATE FUNDS
-------------------------------------------------------- Chapter 5:1.4

Many states perform more compliance activities for low-income housing
tax credit projects that receive state funding than they do for
projects that do not receive any additional state funding.  Forty of
the 54 tax credit allocating agencies provided state funds as another
source for project 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. 

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
      TO INFORM OWNERS OF
      COMPLIANCE RULES
-------------------------------------------------------- Chapter 5:1.5

Most allocating agencies reported making efforts to help project
owners and managers effectively administer the tax credit program
through 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. 


   OPPORTUNITIES TO IMPROVE IRS'
   OVERSIGHT ACTIVITIES
---------------------------------------------------------- Chapter 5:2

IRS is responsible for ensuring that taxpayers claim only those tax
credits for which they are entitled and for ensuring that states do
not exceed their annual tax credit ceilings.  A 1995 IRS report on
its internal controls, which 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
      KEEP STATES INFORMED ABOUT
      CREDIT REQUIREMENTS
-------------------------------------------------------- Chapter 5:2.1

As a means of helping state tax credit allocating agencies to comply
with low-income housing tax credit requirements, IRS established a
federal/state 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 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 DEVELOPED A
      TAX CREDIT AUDIT PROGRAM,
      BUT FEW AUDITS HAVE BEEN
      COMPLETED
-------------------------------------------------------- Chapter 5:2.2

IRS is responsible for ensuring taxpayer compliance with the Internal
Revenue Code's low-income housing tax credit provisions.  Just
because a housing project received a tax credit allocation from the
state does not automatically mean that the owners may take this
credit amount annually for 10 years.  For example, a housing project
may qualify only for a portion 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 Program\3 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 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. 


--------------------
\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. 


      IRS IS ATTEMPTING TO DEVELOP
      A HOUSING TAX CREDIT
      DOCUMENT MATCHING PROGRAM
-------------------------------------------------------- Chapter 5:2.3

To supplement its tax credit audit initiative, IRS is exploring ways
to make better use of state-reported information on tax credit
awards.  IRS' tax credit database currently contains Form 8609 data
on the tax credits awarded to tax credit projects.  IRS is exploring
the possibility of 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
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. 


--------------------
\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. 

\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). 


      AN ESTIMATE OF HOUSING TAX
      CREDIT COMPLIANCE WOULD HELP
      IRS DETERMINE ITS
      ENFORCEMENT STRATEGY
-------------------------------------------------------- Chapter 5:2.4

IRS does not have an estimate of how many taxpayers may not be
entitled to all of the credits they claim.  IRS is depending on the
results of its tax credit audit program to develop such an estimate. 
According to IRS officials, not enough audit cases have been worked
to determine the 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 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 DOCUMENT
      MATCHING PROGRAM TO
      DETERMINE WHETHER STATES
      EXCEED THEIR TAX CREDIT
      CEILINGS
-------------------------------------------------------- Chapter 5:2.5

The Internal Revenue Code gives IRS responsibility for ensuring that
states do not exceed their tax credit allocation ceilings.  A state's
credit ceiling is 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, (3) credit amounts that were initially
allocated in previous years and were 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. 

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. 


   LITTLE INDEPENDENT OVERSIGHT OF
   STATE HOUSING AGENCIES'
   OPERATIONS
---------------------------------------------------------- Chapter 5:3

Most federal programs operated by state and local governments are
subject to independent oversight of state expenditures of federal
funds.  The Single Audit Act,\8

which is an important accountability tool for the hundreds of
billions of dollars of federal financial assistance administered by
state and local governments and nonprofit organizations, does not
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. 


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


      THIRD-PARTY REVIEWS OF TWO
      STATE AGENCIES FOUND CONTROL
      WEAKNESSES
-------------------------------------------------------- Chapter 5:3.1

According to information provided us by the allocating agencies,
third-party reviews of state agencies' low-income housing credit
operations have uncovered control weaknesses.  Twenty agencies
reported that their operations were audited by either the state or an
independent 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 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 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. 


--------------------
\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. 


      IRS HAS NOT CONDUCTED
      REVIEWS OF STATE ALLOCATING
      AGENCIES' OPERATIONS
-------------------------------------------------------- Chapter 5:3.2

According to an IRS Chief Counsel official, section 42 of the
Internal Revenue Code does not explicitly address what
responsibilities or 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. 


      SINGLE AUDITS MAY BE ONE WAY
      TO PROVIDE OVERSIGHT OF
      ALLOCATING AGENCIES'
      OPERATIONS
-------------------------------------------------------- Chapter 5:3.3

The single audit process is designed to provide systematic audit
coverage of state and local governments and nonprofit organizations
that administer federal programs.  Generally, subject entities that
expend $300,000 or more in federal financial assistance are required
to arrange for an audit of their 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. 


   CONCLUSIONS
---------------------------------------------------------- Chapter 5:4

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

IRS is 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 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. 


   RECOMMENDATIONS TO THE
   COMMISSIONER OF INTERNAL
   REVENUE AND DIRECTOR, OFFICE OF
   MANAGEMENT AND BUDGET
---------------------------------------------------------- Chapter 5:5

The low-income housing tax credit program has stimulated low-income
housing development in the United States and states' implementation
of the allocation process generally meets the requirements of the
Internal Revenue Code.  However, some states' and IRS' procedures for
oversight of general compliance with laws and regulations could be
improved.  Accordingly, we recommend that the Commissioner of
Internal Revenue amend regulations for the tax credit program to (1)
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 (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. 


   FEDERAL AGENCY AND STATE
   ASSOCIATION COMMENTS AND OUR
   EVALUATION
---------------------------------------------------------- Chapter 5:6

IRS, NCSHA, and OMB commented on these recommendations.  IRS agreed
with the recommendations addressed to it and orally advised us that
it had already started to implement a reconciliation procedure. 

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 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. 

  -- 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. 


STATISTICAL METHODOLOGY FOR
EVALUATING THE LOW-INCOME HOUSING
TAX CREDIT PROGRAM
=========================================================== Appendix I

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. 


   SAMPLING METHODOLOGY
--------------------------------------------------------- Appendix I:1

We gathered information on the low-income housing tax credit program
through four structured data collection surveys.  Three of these
required 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 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. 


   SAMPLING ERRORS AND CONFIDENCE
   INTERVALS OF ESTIMATES
--------------------------------------------------------- Appendix I:2

Since we used a sample (called a probability sample) of properties
and tenants to develop our estimates from the project and project
manager questionnaire information, each estimate has a measurable
precision, or 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 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. 

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. 


   CONTROLLING FOR NONSAMPLING
   ERRORS
--------------------------------------------------------- Appendix I:3

In addition to the reported sampling errors, the practical
difficulties of conducting any survey may introduce other types of
errors, commonly 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. 



                                    Table I.1
                     
                        Sampling Errors of Estimates From
                     Information in the Project Questionnaire

                                                                    Confidence
                                                                     interval
                                                                  --------------
                                                        Sampling
Description                                 Estimate       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                88           9      79      97
 median area
 income (40/60)
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

Percentage of properties
--------------------------------------------------------------------------------
Special needs (physically or mentally              1           2       0       3
 disabled)
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

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
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

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                  36           4      32      40
 mortgages (payment required) excluding
 Rural Housing Service (515) loans.

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

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
Other locations                                   \b          \b      \b      \b
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

Percentage of units
--------------------------------------------------------------------------------
Total                                            100
N. units                                     168,934       2,094  166,84  171,02
                                                                       1       8

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  166,84  171,02
                                                                       1       8

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  166,84  171,02
                                                                       1       8

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

Other                                             \b          \b      \b      \b

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

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  133,12
                                                                               5
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

Single-family detached                            \b          \b      \b      \b

Other                                             \b          \b      \b      \b

Percent of units qualified for tax                95           3      92      97
 credits
N. units                                     182,140

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



                                    Table I.2
                     
                      Sampling Errors of Estimates About the
                         Households Occupying LIHTC Units

                                                                    Confidence
                                                                     interval
                                                                  --------------
                                                        Sampling
Description                                 Estimate       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  151,27  163,58
                                                                       3       8

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  148,97  161,48
                                                                       0       1

Gender of head of household
Male                                              36           2      34      38
Female                                            64           2      62      66
Total                                            100
N=                                           154,412       6,282  148,13  160,69
                                                                       0       4

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  124,63  139,86
                                                                       1       3

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  149,98  162,24
                                                                       3       8

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  139,84  153,29
                                                                       0       1

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  153,25  165,41
                                                                       2       1

Is the apartment unit overcrowded?
Yes                                                2           1       2       3
No                                                98           1      97      98
Total                                            100
N=                                           156,689       6,183  150,50  162,87
                                                                       6       2

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

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  148,05  160,74
                                                                       7       4

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  148,07  160,76
                                                                       8       6

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

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

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. 



                                    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
                                                         Average      the area's
                                   Percentage of         current          median
Households                            households        income\a        income\a
--------------------------------  --------------  --------------  --------------
Receive additional rental                 39 + 4    $7,858 + 346          25 + 1
 assistance\b
                                      N = 60,714      N = 59,517      N = 59,426
Do not receive additional rental          61 + 4    16,709 + 525          45 + 1
 assistance\c
                                      N = 94,511      N = 93,829      N = 93,715
================================================================================
Total                                        100   $13,323 + 525          37 + 1

                                   N = 155,226 +  N = 156,116 \d   N = 155,827\e
                                           6,256
--------------------------------------------------------------------------------
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. 



                                    Table I.4
                     
                     Sampling Errors for Income Data on Low-
                       Income Households by Type of Housing
                               Assistance Provided

                                                                         Average
                                      Percent of         Average      percent of
Type of assistance                    households  current income   median income
--------------------------------  --------------  --------------  --------------
Tax credit only                           29 + 4       $17,382 +          47 + 2
                                                            $692
                                      N = 45,433                      N = 44,887
                                                      N = 44,963
Tax credit and other assistance           32 + 4       $16,089 +          42 + 1
 to property only                                           $766
                                      N = 49,079                      N = 48,828
                                                      N = 48,866
Tax credit, rental assistance,            29 + 4   $7,901 + $304          27 + 1
 and other assistance to
 property                             N = 44,280      N = 43,134      N = 43,115
Tax credit and rental assistance          11 + 2   $7,745 + $968          22 + 3
 only
                                      N = 16,434        N=16,383      N = 16,311
================================================================================
Total                                        100       $13,323 +          37 + 1
                                                            $525
                                   N = 155,226 +                   N = 155,827\b
                                           6,256   N = 156,116\a

--------------------------------------------------------------------------------
\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. 



                                    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      Households
                                                            with         with no
                                                      additional      additional
                                  All qualifying          rental          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      Households
                                                            with         with no
                                                      additional      additional
                                  All qualifying          rental          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. 



                               Table I.7
                
                Sampling Errors for Table 5.3--Types of
                 Noncompliance Found By Desk Review and
                         On-Site Inspections\a

                                          Noncomplying properties that
                                                 received only
                                          ----------------------------
                                                Desk           On-site
Type of noncompliance                        reviews       inspections
----------------------------------------  ----------  ----------------
1. Tenant(s) not income eligible            30 + 18%          13 + 10%
2. Rents too high                            12 + 12             7 + 7
3. Building code violation or other                            43 + 33
 building condition
4. Administrative requirement not met\b      35 + 23            10 + 9
5. Annual income certification either        53 + 22           34 + 22
 submitted late or not received
6. Improper income certification or            2 + 4           26 + 17
 failure to properly verify
 certifications
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 Requiring
                  Subsidies in Addition to Tax Credits

Source of development financing                                Percent
----------------------------------------------------------  ----------
Grants/donations and concessionary loans                        37 + 3
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. 


ADDITIONAL DATA ON INCOMES OF TAX
CREDIT HOUSEHOLDS BY TYPE OF OTHER
HOUSING ASSISTANCE RECEIVED
========================================================== Appendix II

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. 



                                    Table II.1
                     
                     Income Estimates for Households Residing
                        in Tax Credit Properties Placed in
                       Service, 1992-94, by Type of Housing
                               Assistance Provided

                                                                         Average
                                      Percent of         Average      percent of
Type of assistance                    households  current income   median income
--------------------------------  --------------  --------------  --------------
Tax credits only                              29         $17,382              47
Tax credits and loan subsidies                32         $16,089              42
 or grants
Tax credits and rental                        11          $7,745              22
 assistance
Tax credits, rental assistance,               29          $7,901              27
 and loan subsidies or grants
================================================================================
Total                                        100       $13,323\a           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. 



                                    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
                                                      households      households
                                                            with         with no
                                  Percent of all      additional      additional
                                      qualifying          rental          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
                                                      households      households
                                                            with         with no
                                  Percent of all      additional      additional
Ratio of household income to          qualifying          rental          rental
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. 


TAX CREDIT PROJECT INFORMATION
REPORTED BY ALLOCATING AGENCIES
AND USED IN THE GAO SAMPLE
========================================================= Appendix III

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. 



                              Table III.1
                
                Summary of Tax Credit Projects Reported
                to GAO by Tax Credit Allocating Agencies
                 as Placed in Service During the Period
                               1992-1994

                                                   Total
                           Total       Total       LIHTC   Total LIHTC
State                   projects       units       units         award
--------------------  ----------  ----------  ----------  ------------
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
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 by Tax Credit
                Allocating Agencies as Placed in Service
                      During the Period 1992--1994

                       Number of
                        projects       Total       LIHTC   Total award
State                   selected       units       units           ($)
----------------  --------------  ----------  ----------  ------------
AK                             0           0           0             0
AL                             9         580         580     1,102,750
AR                             9         866         866     2,656,762
AZ                             6         864         864     3,836,820
CA\b                          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
DC\b                           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
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
NJ\a                           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
OH\b                          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
TX\a,b                        42       7,776       7,776     7,214,387
UT                             4         232         232       942,339
VA\a                          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
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. 


RESULTS OF SITE VISITS TO GAO
SAMPLE PROPERTIES
========================================================== Appendix IV

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
-------------------------------------------------------- Appendix IV:1


      CASTLE SQUARE, BOSTON,
      MASSACHUSETTS
------------------------------------------------------ Appendix IV:1.1

Castle Square is a cluster of elevator high-rise buildings that were
rehabilitated with several federal subsidies, including the
low-income 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
---------------------------------------------------- Appendix IV:1.1.1

9 percent


         TOTAL RESIDENTAL UNITS
---------------------------------------------------- Appendix IV:1.1.2

500


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.1.3

470


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:1.1.4

$52.7 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:1.1.5

$105,400

   Figure IV.1:  Castle Square,
   Boston, MA

   (See figure in printed
   edition.)


      TURK STREET APARTMENTS, SAN
      FRANCISCO, CALIFORNIA
------------------------------------------------------ Appendix IV:1.2

The Turk Street Apartments is an elevator high-rise property that was
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
---------------------------------------------------- Appendix IV:1.2.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:1.2.2

175


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.2.3

175


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:1.2.4

$35.3 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:1.2.5

$201,700

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

   (See figure in printed
   edition.)


      MOUNT MERCY, GRAND RAPIDS,
      MICHIGAN
------------------------------------------------------ Appendix IV:1.3

Mount Mercy is a 1-bedroom rental unit property for elderly
residents.  A 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
---------------------------------------------------- Appendix IV:1.3.1

4 percent and 9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:1.3.2

125


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.3.3

125


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:1.3.4

$6.1 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:1.3.5

$48,800

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

   (See figure in printed
   edition.)


      GRAHAM/TERRY, SEATTLE,
      WASHINGTON
------------------------------------------------------ Appendix IV:1.4

Graham/Terry is an elevator high-rise property that contains both
newly 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
---------------------------------------------------- Appendix IV:1.4.1

4 percent and 9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:1.4.2

121


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.4.3

121


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:1.4.4

$7.6 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:1.4.5

$62,800

   Figure IV.4:  Graham/Terry,
   Seattle WA

   (See figure in printed
   edition.)


         PROVIDENCE SQUARE, NEW
         BRUNSWICK, NEW JERSEY
---------------------------------------------------- Appendix IV:1.4.6

Providence Square is a 1-bedroom rental unit property for elderly
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
---------------------------------------------------- Appendix IV:1.4.7

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:1.4.8

99


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.4.9

99


         TOTAL DEVELOPMENT COST
--------------------------------------------------- Appendix IV:1.4.10

$11.1 million


         AVERAGE COST PER UNIT
--------------------------------------------------- Appendix IV:1.4.11

$112,100

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

   (See figure in printed
   edition.)


      O'HERN HOUSE, ATLANTA,
      GEORGIA
------------------------------------------------------ Appendix IV:1.5

O'Hern House is a home for troubled and homeless residents.  A former
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
---------------------------------------------------- Appendix IV:1.5.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:1.5.2

76


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:1.5.3

76


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:1.5.4

$2.9 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:1.5.5

$38,200

   Figure IV.6:  O'Hern House,
   Atlanta, GA

   (See figure in printed
   edition.)


   SUBURBAN PROJECTS
-------------------------------------------------------- Appendix IV:2


      CASCADE COMMONS, STERLING,
      VIRGINIA
------------------------------------------------------ Appendix IV:2.1

Cascade Commons is composed of multiple garden-style, walk-up
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
---------------------------------------------------- Appendix IV:2.1.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:2.1.2

320


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:2.1.3

320


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:2.1.4

$28.6 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:2.1.5

$89,400

   Figure IV.7:  Cascade Commons,
   Sterling, VA

   (See figure in printed
   edition.)


      RANCHO DEL MAR, TUCSON,
      ARIZONA
------------------------------------------------------ Appendix IV:2.2

Rancho Del Mar is a 1- and 2-bedroom unit rental property for family
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
---------------------------------------------------- Appendix IV:2.2.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:2.2.2

312


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:2.2.3

312


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:2.2.4

$8.8 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:2.2.5

$28,200

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

   (See figure in printed
   edition.)


      COVINGTON COURT, ST.  PAUL,
      MINNESOTA
------------------------------------------------------ Appendix IV:2.3

Covington Court is a family rental property.  It is made up of
multiple 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
---------------------------------------------------- Appendix IV:2.3.1

4 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:2.3.2

160


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:2.3.3

160


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:2.3.4

$3.6 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:2.3.5

$22,500

   Figure IV.9:  Covington Court,
   St.  Paul, MN

   (See figure in printed
   edition.)


      LAKEWOOD TERRACE, LAKELAND,
      FLORIDA
------------------------------------------------------ Appendix IV:2.4

Lakewood Terrace is a collection of garden-style 2-story buildings
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
---------------------------------------------------- Appendix IV:2.4.1

4 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:2.4.2

132


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:2.4.3

132


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:2.4.4

$7.2 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:2.4.5

$54,500

   Figure IV.10:  Lakewood
   Terrace, Lakeland, FL

   (See figure in printed
   edition.)


      MANSFIELD MANOR, MANSFIELD,
      TEXAS
------------------------------------------------------ Appendix IV:2.5

Mansfield Manor is a rental property for special needs elderly and
disabled 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
---------------------------------------------------- Appendix IV:2.5.1

4 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:2.5.2

52


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:2.5.3

52


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:2.5.4

$2.1 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:2.5.5

$40,400

   Figure IV.11:  Mansfield Manor,
   Mansfield, TX

   (See figure in printed
   edition.)


   RURAL PROJECTS
-------------------------------------------------------- Appendix IV:3


      LAKE POINTE, CONWAY,
      ARKANSAS
------------------------------------------------------ Appendix IV:3.1

The Lake Pointe Apartments contain 1- and 2-bedroom rental units for
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
---------------------------------------------------- Appendix IV:3.1.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:3.1.2

132


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:3.1.3

132


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:3.1.4

$5.1 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:3.1.5

$38,600

   Figure IV.12:  Lake Pointe,
   Conway, AR

   (See figure in printed
   edition.)


      POST GLEN, OCEANA, WEST
      VIRGINIA
------------------------------------------------------ Appendix IV:3.2

Post Glen is a 1- and 2-bedroom elevator mid-rise building for
elderly 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
---------------------------------------------------- Appendix IV:3.2.1

4 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:3.2.2

41


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:3.2.3

40


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:3.2.4

$1.8 million


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:3.2.5

$43,700

   Figure IV.13:  Post Glen,
   Oceana, WV

   (See figure in printed
   edition.)


      EDGEWOOD APARTMENTS, BELTON,
      SOUTH CAROLINA
------------------------------------------------------ Appendix IV:3.3

Edgewood Apartments is a garden-style, walk-up community for family
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
---------------------------------------------------- Appendix IV:3.3.1

9 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:3.3.2

32


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:3.3.3

32


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:3.3.4

$735,000


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:3.3.5

$23,000

   Figure IV.14:  Edgewood,
   Belton, SC

   (See figure in printed
   edition.)


      HARDWICK, HARDWICK, VERMONT
------------------------------------------------------ Appendix IV:3.4

Hardwick contains seven units of family rental housing in one
garden-style 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
---------------------------------------------------- Appendix IV:3.4.1

4 percent


         TOTAL RESIDENTIAL UNITS
---------------------------------------------------- Appendix IV:3.4.2

7


         TOTAL LOW-INCOME UNITS
---------------------------------------------------- Appendix IV:3.4.3

7


         TOTAL DEVELOPMENT COST
---------------------------------------------------- Appendix IV:3.4.4

$950,000


         AVERAGE COST PER UNIT
---------------------------------------------------- Appendix IV:3.4.5

$135,500

   Figure IV.15:  Hardwick,
   Hardwick VT

   (See figure in printed
   edition.)




(See figure in printed edition.)Appendix V
COMMENTS FROM THE INTERNAL REVENUE
SERVICE
========================================================== Appendix IV




(See figure in printed edition.)Appendix VI
COMMENTS FROM THE NATIONAL COUNCIL
OF STATE HOUSING AGENCIES
========================================================== Appendix IV



(See figure in printed edition.)



(See figure in printed edition.)



(See figure in printed edition.)


MAJOR CONTRIBUTORS TO THIS REPORT
========================================================= Appendix VII

GENERAL GOVERNMENT DIVISION,
WASHINGTON, D.C. 

Ralph T.  Block, Assistant Director, Tax Policy and Administration
Issues
Thomas M.  Richards, Senior Evaluator

RESOURCES, COMMUNITY, AND ECONOMIC
DEVELOPMENT DIVISION, WASHINGTON,
D.C. 

Dennis W.  Fricke, Assistant Director, Housing and Community
Development Issues
William F.  Bley, Senior Evaluator
Andrew E.  Finkel, Senior Evaluator
Diane T.  Brooks, Senior Evaluator

SAN FRANCISCO OFFICE

George A.  Zika, Evaluator-in-Charge
Kathleen E.  Seymour, Senior Evaluator
Arthur L.  Davis, Senior Evaluator
Mary L.  Jankowski, Evaluator
Sharon K.  Caporale, Evaluator
Susan S.  Mak, Evaluator

TECHNICAL SUPPORT

Karen E.  Bracey, Assistant Director, Design, Methodological, and
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

SURVEY TEAM MEMBERS

Joanna M.  Stamatiades, Senior Evaluator-Atlanta Office
Salley P.  Gilley, Evaluator-Atlanta Office
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


*** End of document. ***