    District of Columbia: Structural Imbalance and Management Issues
    (22-MAY-03, GAO-03-666).

    District officials have recently reported both a budget gap and a
    more permanent structural imbalance between costs and revenue
    raising capacity. They maintain that the structural imbalance
    largely stems from the federal government's presence and
    restrictions on the District's tax base. Accordingly, at various
    times District officials have asked the Congress for additional
    funds and other measures to enhance revenues. In a preliminary
    September 2002 report, GAO concluded that the District had not
    provided sufficient data and analysis to discern whether, or to
    what extent, it is facing a structural imbalance. At that time,
    GAO also agreed to perform a more comprehensive analysis and was
    asked to (1) determine whether, or to what extent, the District
    faces a structural imbalance between its revenue capacity and its
    public service responsibilities, (2) identify any significant
    constraints on the District's revenue capacity, (3) discuss
    factors beyond the control of District officials that influence
    the District's spending in key program areas as well as factors
    within its control, such as management problems, and (4) report
    on the District's deferred infrastructure projects and
    outstanding debt service and related expenses that might be
    affected by a structural imbalance. The District concurred with
    our key findings.
    -------------------------Indexing Terms-------------------------
    REPORTNUM:   GAO-03-666
        ACCNO:   A06932
      TITLE:     District of Columbia: Structural Imbalance and Management
    Issues
         DATE:   05/22/2003
      SUBJECT:   Balanced budgets
    	     Economic analysis
    	     Financial management
    	     Fiscal policies
    	     Intergovernmental fiscal relations
    	     Internal controls

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    GAO-03-666

                                           A

    Report to Congressional Requesters

    May 2003 DISTRICT OF COLUMBIA Structural Imbalance and Management Issues

    GAO- 03- 666

    Transmittal Letter 1 Executive Summary 2

    Purpose 2 Background 2 Results in Brief 7 Principal Findings 10 Concluding
    Observations 14 District of Columbia Comments 16

    Chapter 1 18

    Introduction Characteristics of the District 18

    The District*s Fiscal Relationship with the Federal Government 19 Reports
    on the District*s Unique Circumstances, Fiscal Health, and

    Management Problems 21 The Economic Slowdown and the District*s Finances
    22 Scope and Methodology 24

    Chapter 2 31

    The District*s Cost of The Spending Necessary to Fund an Average Basket of
    Public Services Exceeds That of All State Fiscal Systems 32

    Meeting Its Public The District*s Per Capita Total and Own- Source Revenue
    Capacities

    Service Are High Relative to Those of State Fiscal Systems 36

    Responsibilities The District*s Structural Deficit Results from a High
    Cost of Funding

    an Average Level of Services 39 Exceeds Its Revenue

    The District*s High Tax Burden Yields Revenues That Could Only Capacity,
    Resulting in a

    Support an Average Level of Services 41 Structural Deficit

    Chapter 3 43

    The District*s Revenue The Federal Prohibition against a District Tax on
    the Income of

    Nonresidents Is Unique 43 Capacity Would Be

    The District*s Property Tax Base Is Relatively Large despite the Even
    Higher in the

    Disproportionate Presence of Properties Owned by the Federal Absence of
    Several

    and Foreign Governments 46 District Officials Believe That the Federally
    Imposed Height

    Constraints on Its Restriction on Buildings Also Limits the District*s
    Property Tax

    Taxing Authority Base 48

    Other Nationwide Restrictions on Taxing Authority Are Likely to Affect the
    District Disproportionately 48

    Chapter 4 50

    The District Faces High Special Circumstances and Management Problems
    Influence High

    Medicaid Costs in the District 50 Cost Conditions and

    Special Circumstances and Management Problems May Result in Significant
    Increased Education Costs and Below Average Services 57

    Management Problems The District Faces Significant Public Safety Demands
    due to the

    Federal Presence, but Related Costs Are Not Adequately Tracked 63 Chapter
    5

    71 The District Continues

    District Infrastructure Continues to Be Deferred 72 District Debt
    Pressures Remain 76 to Defer Infrastructure

    Selected District Debt Statistics Compared to Other Projects While Debt
    Jurisdictions 85

    Pressures Remain Appendixes

    Appendix I: Methodology for Calculating the Cost of Providing a
    Representative Basket of Public Services 89 Defining a Representative
    Basket of Public Services: The Rafuse/

    ACIR Method 89 Limitations to the Interpretation of the Representative
    Expenditure

    Model 94 Modifications to the Rafuse Methodology 95

    Appendix II: Revenue Capacity Analysis: Methodology and Detailed Estimates
    114 Estimating Grants Associated with Average Services 114 Estimating Own-
    Source Revenue Capacity 114 Details on Individual Taxes 118 Resulting
    Estimates of the District*s Own- Source Revenue Capacity 128

    Appendix III: Computation of the District*s Structural Deficit 130 The
    Structural Deficit Computation 130 Deficit as a Percentage of Own- Source
    Revenue Capacity 131

    Appendix IV: The District*s Deferred Maintenance and Acquisitions Projects
    133

    Appendix V: Information Related to the District*s Debt 138

    Appendix VI: Comments from the District of Columbia 140

    Appendix VII: GAO Contacts and Staff Acknowledgments 145 Tables Table 1:
    Demographic Characteristics of the District Compared to

    National Averages, 2000 19 Table 2: Significant Statutes or Actions That
    Affected the District*s Fiscal Relationship with the Federal Government
    since

    Home Rule 20 Table 3: Recent Reports on the District*s Fiscal and
    Management

    Problems 21 Table 4: Changes in the District*s Local Source Revenues since

    Fiscal Year 2000 (Revenues in Millions of Real Dollars) 24 Table 5: The
    District*s Estimated Per Capita Cost of Funding an

    Average Basket of Public Services, Fiscal Year 2000 34 Table 6: Estimated
    Size of the District*s Structural Deficit in Fiscal

    Year 2000, Using Alternative Measures and Estimation Approaches 40 Table
    7: The District*s Capital Improvement Program: Deferred Maintenance
    Projects and Costs for Fiscal Year 2003 and

    Fiscal Years 2003 through 2008 73 Table 8: Overview of the District*s
    Capital Improvement Program: Planned Funding and Expenditures for Fiscal
    Year 2003 through Fiscal Year 2008 74

    Table 9: Total Costs of the District*s Approved and Unapproved Capital
    Projects for Fiscal Year 2003 and Fiscal Years 2003 through 2008 75 Table
    10: The District*s Capital Improvement Program: Other

    Deferred Infrastructure and Acquisition Costs for Fiscal Year 2003 and
    Fiscal Years 2003 through 2008 75 Table 11: Source of Capital Funds for
    Fiscal Years 2003 through 2008 77

    Table 12: U. S. Census Bureau Data on Debt Per Capita by State and as a
    Percentage of Own- Source Revenue Capacity 86 Table 13: Fiscal Year 1987
    Weights Associated with the National

    Average Basket of Public Services 92 Table 14: RES Workload Indicators and
    Weights by Expenditure

    Category 93 Table 15: Modifications of Workload Indicators 107

    Table 16: RTS Estimates of the District*s Own- Source Revenue Capacity 129
    Table 17: Computation of the District*s Structural Deficit under

    Alternative Estimation Approaches, Using Fiscal Year 2000 Data 131 Table
    18: The District*s Capital Improvement Program: Deferred

    Maintenance Projects and Costs for Fiscal Year 2003 and Fiscal Years 2003
    through 2008 133 Table 19: The District*s Capital Improvement Program:
    Deferred

    Acquisitions Projects for Fiscal Year 2003 and Fiscal Years 2003 through
    2008 136 Table 20: The District*s Total Outstanding General Obligation
    Debt 138

    Table 21: The District*s Debt Per Capita for Fiscal Years 1995 through
    2002 (Actual) 138 Table 22: The District*s Percentage of Debt Service to
    General Fund

    Expenditures for Fiscal Years 1995 through 2002 (Actual) and 2003 through
    2006 (Projected) 138 Table 23: The District*s Percentage of Debt Service
    Costs to General

    Fund Revenues for Fiscal Years 1995 through 2002 (Actual) and 2003 through
    2006 (Projected) 139

    Figures Figure 1: Per Capita Spending Necessary to Fund an Average Basket
    of Public Services for Selected State Fiscal

    Systems (Percentage of Average State Fiscal System) 33 Figure 2: Total
    Revenue Capacity Per Capita for the

    Highest- Capacity Fiscal Systems (Percentage of Average State Fiscal
    System) 39 Figure 3: Fiscal Systems with the Largest Structural Deficits
    Per

    Capita 41 Figure 4: The District*s Tax Burden and Cost- Adjusted Spending
    42 Figure 5: The District*s Total Outstanding General Obligation Debt

    for Fiscal Years 1995 through 2002 79 Figure 6: The District*s Debt Per
    Capita for 1995 through 2002 80 Figure 7: The District*s Percentage of
    Debt Service Costs to Total

    General Fund Expenditures for 1995 through 2002 (Actual) 81 Figure 8: The
    District*s Percentage of Debt Service Expenditures to

    General Fund Revenues for Fiscal Years 1995 through 2002 (Actual) and 2003
    through 2006 (Projected) 82 Figure 9: Bond Ratings of 35 Largest U. S.
    Cities (Based on Revenue) 84

    Figure 10: Fiscal Systems with the Largest Structural Deficits as a
    Percentage of Own- Source Revenue Capacity 132

    Abbreviations

    ACIR Advisory Commission on Intergovernmental Relations BEA Bureau of
    Economic Analysis CAFR comprehesive annual financial report CBO
    Congressional Budget Office CFO chief financial officer CFSA Child and
    Family Services Agency CIP Capital Improvement Plan CMS Centers for
    Medicare & Medicaid Services DCPS District of Columbia Public Schools DHS
    Department of Homeland Security DMH Department of Mental Health FEMS Fire
    and Emergency Medical Services FMAP Federal Medical Assistance Percentage
    GSE government- sponsored enterprise IDEA Individuals with Disabilities
    Education Act IEP individualized education plan IG inspector general IMF
    International Monetary Fund IRS Internal Revenue Service MAA Medicaid
    Assistance Administration MPD Metropolitan Police Department OFT Office of
    Finance and Treasury RES representative expenditure system RTS
    representative tax system SEO State Education Office TTR total taxable
    resources USDA Department of Agriculture USPP United States Park Police
    WASA Water and Sewer Authority WMATA Washington Metropolitan Area Transit
    Authority YYPL years of productive life lost

    This is a work of the U. S. Government and is not subject to copyright
    protection in the United States. It may be reproduced and distributed in
    its entirety without further permission from GAO. It may contain
    copyrighted graphics, images or other materials. Permission from the
    copyright holder may be necessary should you wish to reproduce copyrighted
    materials separately from GAO*s product.

    Executive Summary Purpose District of Columbia officials have reported
    that, in addition to facing the

    prospect of their budget falling into deficit over the next several years,
    they face a more permanent imbalance between the District*s revenue-
    raising capacity and the cost of meeting its public service
    responsibilities. They maintain that this more permanent imbalance is not
    related to their current budgetary imbalance, but rather is based on
    structural conditions that are beyond their ability to control, such as
    public service costs imposed on the District by the federal government,
    federal restrictions on its revenue capacity, and issues associated with
    having both state and local responsibilities. In response, at various
    times District officials have asked the Congress for additional funds and
    other measures to enhance revenues. To help inform the debate, GAO was
    asked to

    1. assess whether, or to what extent, the District faces a structural
    imbalance between its revenue capacity and the cost of providing residents
    and visitors with average levels of public services, 2. identify
    significant constraints on the District*s revenue capacity, 3. examine
    cost conditions and management problems in key program

    areas, and 4. study the effects of the District*s fiscal situation on its
    ability to fund

    infrastructure projects and repay related debt. Background Defining
    Structural

    Although there is no uniform definition of structural imbalance, there are
    Imbalance

    two concepts that can be used to measure it* current services and
    representative services imbalances. A current services imbalance addresses
    this question: If a jurisdiction were to maintain its current level

    of services into the future, would it be able to raise the revenues
    necessary to maintain that level of service under its current taxing
    policies? This type of longitudinal analysis compares a jurisdiction*s
    projected fiscal position

    with its current position and is independent of other similarly situated
    jurisdictions.

    In contrast, a representative services imbalance addresses this question:
    If a jurisdiction were to provide a representative basket of public
    services with average efficiency, would it be able to generate sufficient
    revenues from its own taxable resources and federal grants to fund a
    representative basket of services if its resources were taxed at
    representative rates? This type of analysis uses a basket of services and
    tax structure typical of other

    jurisdictions with similar public service responsibilities as a benchmark
    against which to compare imbalances between the cost of providing public
    services and revenue- raising capacity. The approach attempts to compare
    differences in jurisdictions* fiscal positions under a common set of
    policies regarding levels of services and taxation. As noted below, GAO
    employed a representative services approach in performing this engagement.

    When analyzing a representative services imbalance, the choice of a
    benchmark for a representative level of public services and taxation is a
    critical decision. In fact, the appropriate level of services and taxation
    is a matter of perennial debate in every jurisdiction in the nation. For
    this reason, GAO used as a benchmark national average levels of spending
    and taxation because they are independent of individual jurisdictions
    particular preferences, policy choices, and efficiency of service
    provision. National averages provide benchmarks that are *representative*
    of the level of services and taxation that a typical state fiscal system
    (the collections of a state, its counties, its cities, and its myriad
    special purpose district governments) employs. A fiscal system is said to
    have a structural imbalance if it is unable to finance an average (or
    representative) level of

    services by taxing its funding capacity at average (or representative)
    rates. Because GAO defines structural imbalance in terms of comparisons to
    national averages, for any given period a significant proportion of all
    fiscal systems will have structural deficits.

    The District*s Estimates of a The District has reported both a current
    services and a more permanent

    Structural Imbalance structural imbalance between its costs and revenue-
    raising capacity.

    According to recent projections by the District*s Chief Financial Office,
    a continuation of the District*s current spending and taxing policies
    would result in budget gaps, peaking at $372 million by fiscal year 2006
    before declining to $325 million in fiscal year 2007. 1 District officials
    have demonstrated their resolve to maintain fiscal discipline by taking
    the steps needed to balance their budgets for fiscal years 2003 and 2004.
    However, those officials claim that the District faces a more permanent
    structural

    imbalance between its revenue- raising capacity and the cost of meeting
    its public service responsibilities that are the result of many factors,
    several stemming from the federal government*s presence in the District
    and the restrictions on the District*s tax base. District officials claim
    the structural imbalance may amount to $1 billion annually. 2

    Last year, GAO examined issues related to the District*s reported
    structural imbalance and, in September 2002, concluded that the District
    had not provided sufficient data and analysis to determine whether, or to
    what extent, the District is in fact facing a structural imbalance between
    its revenue capacity and the cost of meeting its public service
    responsibilities. To help inform the debate on this issue, GAO also
    committed to perform a more comprehensive analysis of the District*s
    fiscal situation. GAO*s Estimation

    GAO used a representative services analysis to determine whether and to
    Methodology*

    what extent the District has a structural imbalance. This approach allowed
    Representative Services

    GAO to compare the District*s fiscal circumstances against a benchmark
    based on services and taxation that is typical of jurisdictions with
    similar fiscal responsibilities, which is different from a current
    services approach, which would be based on the District*s historical
    spending and tax choices. The methodologies for all elements of this study
    are described in chapter 1.

    Appendixes I, II, and III provide additional detail about GAO*s
    quantitative methodology.

    Determining empirically whether the District has a structural imbalance is
    a complex task that involves making judgments about (1) the appropriate

    1 The District*s approved fiscal year 2003 budget was $5. 6 billion. 2 See
    the District*s comments in U. S. General Accounting Office, District of
    Columbia: Fiscal Structural Balance Issues, GAO- 02- 1001 (Washington, D.
    C.: Sept. 4, 2002), 33.

    set of governments to use when developing benchmarks for the District*s
    spending and revenue capacity, (2) the influence that various workload and
    cost factors, such as the number of school- age children and number of
    vehicle miles traveled, have on the cost of public services, and (3) the
    best way to measure revenue capacity.

    Given the lack of professional consensus and a limited empirical basis for
    many of the assumptions underlying GAO*s methodology, GAO performed
    several sensitivity analyses to show how its estimates changed as it
    varied specific judgments and choices regarding key assumptions. In
    addition, the

    precision of GAO*s estimates is adversely affected by data limitations for
    various cost and tax bases. Consequently, uncertainty surrounds the
    specific numerical estimates GAO presents. Nevertheless, GAO believes that
    the consistency of its basic result over a broad range of alternative
    assumptions and approaches provides sufficient support for the concluding
    observations offered in this report.

    Moreover, GAO supplemented its quantitative analysis with a programmatic
    review of the District*s three highest cost program areas to provide
    additional insights into the level of services, costs, management, and
    financing. GAO also reviewed the District*s infrastructure and debt
    management experience. GAO*s methodology was vetted among key experts,
    including individuals who designed the underlying methodology and District
    economists.

    Choosing a Benchmark of Determining the appropriate benchmarks for the
    District*s spending is

    Services complicated by the fact that the District is a unique
    governmental entity. It

    has all of the fiscal responsibilities generally shared by state, city,
    county, and special district governments; however, it is a relatively
    small and densely populated area in comparison to the 50 states. No peer
    group of governments has both the same fiscal responsibilities and the
    same

    geographic and demographic characteristics as the District. For this
    reason, GAO computed two separate sets of benchmarks* one based on a
    *state* services baskets, the mix of services typically provided by state
    fiscal systems (each state and all of its local governments), and a

    second based on an *urban* services basket, the mix of services typically
    provided by governments in more densely populated areas. The scope of
    services included is the same for both baskets; what differs is the

    proportion of total spending that is allocated to each service. For
    example, the *urban* basket of services gives greater weight to public
    safety

    functions and less weight to higher education than does the state basket
    of services.

    Calculating the Average Cost of To calculate the cost of providing a
    representative level of public services,

    Representative Services GAO used the national average per capita spending
    for each expenditure

    function as a benchmark. For example, when using the state services
    basket, the national average per capita spending for elementary and
    secondary education was $1, 338 per capita. GAO used this figure as a
    benchmark indicator of an average level of educational services. However,
    each benchmark had to be adjusted to account for the fact that an average

    level of spending does not support the same level of service in each
    fiscal system. For this reason, GAO adjusted for differences in workloads
    (e. g., number of school- age children) across states. GAO also adjusted
    for the

    fact that the private sector wage rate varies across states because that
    means the cost of hiring a given number of public employees also varies.
    These factors for which GAO adjusted represent circumstances beyond the

    governments* control. GAO did not adjust for differences in preferences or
    policy decisions across states, nor did it adjust for differing degrees of
    efficiency in providing services. Rather, GAO*s cost estimates were made
    on the

    presumption that services are delivered to residents with average
    efficiency. Therefore, governments that are relatively inefficient would
    have to spend more than the average amount to provide an average level of
    services. In addition, GAO made no adjustments for the unique public

    service costs associated with the District being the nation*s capital.
    Although GAO*s quantitative analysis did not reflect these service
    inefficiencies and unique costs, its programmatic work does provide
    insights about the extent and nature of these issues.

    Estimating Revenue Capacity To estimate the total revenue capacity of each
    state fiscal system, GAO combined estimates for the two principal sources
    from which those systems finance their expenditures: (1) revenues that
    could be raised from each system*s own economic base (own- source revenue)
    and (2) the federal grants that each system would receive if it provided
    an average basket of services.

    In the past, two basic approaches have been employed to estimate the
    ownsource revenue capacity of states: (1) those that use income to measure
    the ability of governments to fund public services and (2) those that
    attempt to measure the amount of revenue that could be raised in each
    state if an

    average set of tax rates were applied to a specified set of statutory tax

    bases *typically* used to fund public services. Total taxable resources
    (TTR), developed by the U. S. Department of the Treasury (Treasury), is a
    leading example of the first type of measure; and the representative tax
    system (RTS), developed by the Advisory Commission on Intergovernmental
    Relations, is a leading example of the second. Because experts disagree as
    to which approach is superior, GAO computed

    separate results using both methodologies. Both the RTS and TTR take into
    account the restrictions placed on the District*s taxing authority. GAO
    generally used the actual amounts that state fiscal systems received from
    the federal government as proxies for the actual amounts that each system
    would receive if it provided an average basket of services. However, GAO
    made special adjustments in the case of Medicaid grants because the
    current amount that each fiscal system receives would be significantly
    different if it were to provide average Medicaid coverage and benefits.

    Calculating the Structural GAO estimated the size of the District*s
    structural imbalance as the

    Imbalance difference between its cost of providing an average level of
    services and its

    total revenue capacity* the amount of revenue the District would have
    (including federal grants) if it applied average tax rates to its taxable
    resources. The average level of services and average tax rates that GAO
    used should not be interpreted as the levels of spending and taxation that
    jurisdictions should seek to provide. Each jurisdiction is an autonomous
    governmental entity responsible for providing the package of services and

    level of taxation desired by its citizens. Depending on the preferences of
    local citizens and their representatives, levels of taxation and services
    may be higher in some jurisdictions and lower in others. The use of
    average levels in GAO*s analysis should only be thought of as a convenient
    benchmark against which to gauge relative differences in the cost of

    providing public services over which local officials have little direct
    control and as providing an indication of the potential availability of
    revenue sources from which to finance those costs. Results in Brief No
    consensus exists regarding the *best* approach to estimating structural

    imbalance, and the empirical basis for many of the assumptions underlying
    GAO*s methodology is limited. Consequently, GAO performed several
    sensitivity analyses to show how its estimates changed as it varied
    specific judgments and choices regarding key assumptions. The consistency
    of

    GAO*s basic result over a broad range of alternative assumptions and
    approaches led GAO to conclude that the District does have a substantial

    structural imbalance, even though considerable uncertainty exists
    regarding its exact size.

    The existence of this structural deficit means that, even if the
    District*s services were managed efficiently, the District would have to
    impose above- average tax burdens just to provide an average level of
    services. To the extent that services are delivered inefficiently, the
    District*s high tax burden would likely not support even average service
    levels. GAO*s programmatic review of three key areas (Medicaid, elementary
    and secondary education, and public safety) indicated that, in fact,
    significant management inefficiencies exist, totaling tens of millions of
    dollars annually. Consequently, the District*s high tax burden is likely
    providing an actual level of services below the national average.

    GAO estimated the size of the District*s structural imbalance as the
    difference between its cost of providing an average level of services and
    its total revenue capacity* the total amount of revenue it would have
    (including federal grants) if it applied average tax rates to its taxable
    resources. Based on GAO*s use of a state fiscal system basket of services
    as a benchmark, GAO*s analysis indicated that the cost of providing an
    average level of services per capita in the District exceeds that of the

    average state fiscal system by approximately 75 percent, or $2.3 billion
    more annually than if it faced average cost circumstances. If state fiscal
    systems were to provide a basket of services typically provided in more
    densely populated urban areas, GAO estimated that the District would have
    to spend over 85 percent, or $2.6 billion more annually to fund an average
    level of services.

    GAO*s analysis also indicated that the District*s per capita total revenue
    capacity is higher than those of all state fiscal systems due to its large
    tax bases and federal grant funding that is over two and one half times
    higher than the national average. Depending on which estimation approach
    GAO used, the District*s total revenue capacity ranged from 47 percent
    above the national average (based on a conservative version of the RTS
    approach) to 60 percent above (based on the TTR approach). Using fiscal
    year 2000 information, GAO obtained its lowest estimate of the District*s
    structural deficit*$ 470 million* by combining the District*s cost of
    providing the average state basket of services with GAO*s highest estimate
    of the District*s revenue capacity. All other combinations led to higher
    estimates of the structural imbalance* up to more than $1.1 billion.

    While the District*s revenue capacity per capita is large relative to
    those of most state fiscal systems, it would be even larger in the absence
    of several existing constraints on the District*s tax authority. These
    constraints include the prohibition against taxation of income earned by
    nonresidents working in the District and the relatively large proportion
    of the District*s property tax base that is not taxable because it is
    either owned or

    specifically exempted by the federal government. Despite these revenue
    constraints, the per capita revenue capacities of the District*s income
    and property taxes are higher than those for all but a few state fiscal
    systems, partly reflecting the indirect benefits of the federal presence
    for the

    District*s economy. In contrast, the District may have a relatively low
    sales tax capacity due, in part, to a disproportionate share of sales to
    the federal government and other exempt purchasers.

    GAO*s review of three key program areas (Medicaid, elementary and
    secondary education, and public safety, particulary police and fire
    services) revealed that the District faces high cost conditions. GAO found
    that the District*s spending for Medicaid and elementary and secondary
    education may be slightly above what it would take to provide an average
    level of services, if delivered with average efficiency, while police
    spending may be significantly below the average level. However, GAO*s
    quantitative analysis was not able to account for all special
    circumstances beyond the control of

    the District, such as the high cost of special education services, and
    extra police and fire services associated with the federal presence,
    including those for political demonstrations. In recognition of the
    District*s high- cost

    environment, the federal government provides certain supplemental
    financial support to the District, such as an enhanced federal share of
    the District*s spending on Medicaid.

    Significant and costly management problems* mostly under the District*s
    authority to control* further increase spending unnecessarily in Medicaid,
    elementary and secondary education, and police and fire protection. These
    problems, documented in GAO*s work and in that of others, include
    inadequate financial management, billing systems, and internal controls
    that result in unnecessary spending, drawing resources away from program
    services. Various reports have estimated wasted resources to be at least
    in the tens of millions of dollars. For example, serious management
    problems exist, such as poor financial and program management in education
    as well as inadequate compliance with the requirements of federal programs
    like Medicaid and the Individuals with Disabilities Education Act. The
    District has taken some actions to correct management inefficiencies, such
    as

    creating an Office of Medicaid Public Provider Operations Reform; however,
    more improvements are needed. By addressing such management challenges,
    the District could free up local

    funds and possibly gain additional federal funds for use in increasing the
    levels of services to its residents and closing its current budget gap.
    However, addressing these management problems will not offset the
    District*s underlying structural imbalance, which is due to factors
    outside its direct control. In recognition of the District*s management
    problems, the federal government provides the District with special
    technical assistance.

    While capital spending has increased in recent years, the District
    continues to defer infrastructure improvements because of constraints in
    its operating budget. Most of the District*s infrastructure and capital
    improvement projects are financed by using general obligation bonds. The

    interest and principal payments (debt service) on those bonds are paid
    from the District*s operating budget. Although the District is not close
    to its legal debt limit, it cannot take on additional debt without cutting
    services or raising taxes that are already higher than other
    jurisdictions. Contributing to the District*s difficulties is its legacy
    of deteriorated

    infrastructure and its responsibility for funding its 40 percent share of
    the metropolitan area*s mass transit system. However, the District is
    attempting to address its backlog of infrastructure projects through

    increased capital expenditures (estimated at roughly $371 million in
    fiscal year 2003). Nevertheless, the District continues to defer major
    infrastructure and capital investment in part because of its structural
    imbalance.

    Principal Findings The District*s Public Service

    Using other state fiscal systems as a benchmark, GAO*s analysis indicates
    Costs Are the Highest in the

    that the cost of delivering an average level of services per capita in the
    Nation

    District exceeds that of the average state fiscal system by approximately
    75 percent (or a total of $2. 3 billion more annually than if it faced
    average cost circumstances) and is over a third more than the second
    highest cost fiscal system, New York. If state fiscal systems were to
    provide a basket of

    services typically provided in more densely populated urban areas, GAO
    estimated that the District would have to spend over 85 percent more (or a

    total of $2.6 billion more annually) than average to fund an average level
    of services.

    The District faces high cost circumstances, largely beyond its control, in
    key program areas, including Medicaid, elementary and secondary education,
    and police and fire services, that increase the fiscal burdens on its
    budget. For Medicaid, GAO estimated that high cost circumstances, such as
    its large low- income population, would require the District to spend well
    over twice the national average per capita. Consequently, to provide an
    average level of services the District would have to spend a total of $437
    million more than if it faced average cost circumstances. Similarly, GAO
    estimated that the District*s per capita cost of elementary and

    secondary education is 18 percent above the average state fiscal system,
    due to circumstances such as the District*s disproportionately high
    percentage of low- income children. As a result, to provide an average
    level of services the District would have to spend a total of about $136
    million more than if it faced average cost circumstances. Likewise, for
    police and fire services, the District*s per capita costs of providing an
    average level of services are well over twice the national average due to
    circumstances such as its relatively young population, especially its high
    crime rates, its dense living conditions. As a result, to provide an
    average level of services the District would have to spend about $480
    million more than if it faced

    average cost circumstances. Further, GAO*s cost estimates did not
    explicitly account for the various public safety demands and costs
    associated with the federal government*s presence, although GAO*s
    programmatic work does provide insights about this issue.

    The District*s Revenue GAO*s analysis indicated that the District*s per
    capita total revenue and

    Capacity Is among the own- source revenue capacities are higher than those
    of all but a few state

    Highest in the Nation, fiscal systems. Its capacity is high even though
    the District faces some

    despite Some Constraints significant constraints on its taxing authority,
    such as the inability to tax

    federal property or the income of nonresidents who work in the District.
    on Its Taxing Authority As noted earlier, the District*s total revenue
    capacity equals the sum of its own- source revenue capacity (the revenue
    that it could raise by applying average tax rates to its own economic
    base), plus the amount of federal grants that the District would receive
    if it provided a representative level of services. The two estimation
    approaches (RTS and TTR) GAO used to measure the

    District*s revenue capacity yielded the same basic result: The District*s
    own- source revenue capacity per capita ranked among the top five when

    compared to those of the 50 state fiscal systems. This high own- source
    revenue capacity, combined with the fact that its federal grant funding is
    over two and one- half times the national average, gives the District a
    higher total revenue capacity than any other state fiscal system.

    Depending on which estimation approach GAO used, the District*s total
    revenue capacity ranged from 47 percent above the national average (based
    on a conservative version of the RTS approach) to 60 percent above (based

    on the TTR approach). However, the distance between the District*s revenue
    capacity and that of the next highest systems* capacity is not as extreme
    as is the case with the cost of funding an average service level. The
    District Faces a

    Using a representative services analysis (which compares the District*s
    Structural Deficit circumstances to a benchmark based on average spending
    and tax policies of state fiscal systems), GAO found that the District
    faces a structural deficit in the sense that the cost of providing an
    average level of public services exceeds the amount of revenue it could
    raise by applying average

    tax rates. As previously discussed, data limitations and uncertainties
    surrounding key assumptions in GAO*s analysis made it difficult to
    determine the exact size of the District*s structural deficit.
    Nevertheless, using a broad range of alternative assumptions and
    approaches, GAO obtained the same basic result* the District faces a
    substantial structural deficit.

    GAO obtained its lowest deficit estimate of about $470 million per year by
    combining its lowest estimate of the District*s costs (the one based on
    the state basket of services) with its highest estimate of the District*s
    total revenue capacity (TTR). In contrast, GAO obtained its highest
    deficit estimate of over $1.1 billion per year by combining its highest
    estimate of the District*s costs (the one based on the urban basket of
    services) with its lowest estimate of the District*s total revenue
    capacity (RTS). Among the contributing factors to the structural imbalance
    are high cost conditions largely beyond the District*s control, such as
    high poverty rates.

    Despite a High Tax Burden, In addition to having a high revenue capacity,
    the District also imposes

    the District*s Revenues Are above- average tax rates; however, high taxes
    are only sufficient to fund an

    Only Sufficient to Fund an average level of services. Because of its high
    tax rates, actual revenues

    Average Level of Services collected by the District exceeded GAO*s lower
    estimate of its own- source revenue capacity by 33 percent and exceeded
    GAO*s higher estimate of that capacity by 18 percent. However, the
    District*s actual fiscal year 2000

    spending was only equal to the cost of an average level of public
    services, based on the basket of services provided by the average state
    fiscal system. Using the basket of services typically provided by urban
    governments as a benchmark, the District*s spending is 5 percent below
    that needed to fund an average level of services. GAO*s cost estimates
    presume services are provided with average efficiency. To the extent that
    the District does not

    deliver services with average efficiency, its actual level of services may
    be below average. Management Problems The District*s long- standing
    management problems waste resources that it Result in Unnecessary

    cannot afford to lose and draw resources away from providing even an
    Spending That

    average level of services. In three key program areas (Medicaid,
    Compromises the District*s elementary and secondary education, and police
    and fire services), GAO

    identified significant management problems, such as inadequate financial
    Ability to Provide an management, billing systems, and internal controls.
    While the District has Average Level of Public

    taken some actions to correct management inefficiencies, more Services

    improvements are needed. In the case of Medicaid, in fiscal year 2001 the
    District wrote off over $78 million for several years worth of
    unreimbursed claims for federal Medicaid matching funds. The District was
    not able to claim this reimbursement because of late submission of
    reimbursement requests, incomplete documentation, inadequate computerized
    billing systems, services provided to individuals not eligible for
    Medicaid at the time of delivery, and billing for services not allowable
    under Medicaid. The extent of these management problems suggests that the
    District bears more of the

    burden of Medicaid costs than necessary. In the case of education,
    District officials were not able to track either the total number of
    employees or whether particular positions were still available or had been
    filled. For example, in March 2003, District officials acknowledged that
    the school system had hired 640 more employees than its budget authorized,
    resulting in the District exceeding its personnel budget by a projected
    $31.5 million over the entire fiscal year. Also, in

    December 2002, District officials announced that the school system paid $5
    million for employee insurance benefits and contributions to tax- free
    retirement accounts for employees who no longer worked for the District.
    In another example, the District*s lack of internal control for
    procurement practices in its public school system resulted in $10 million
    in unauthorized purchases. While GAO*s cost analysis showed that the
    District is spending an amount that could provide an average level of
    services, the extent of

    these management problems suggests that the District provides less than
    the national average level of education services.

    In the case of police and fire services, the District does not adequately
    track the costs it incurs to support the federal presence, for example, in
    areas such as providing protection to federal officials and key
    dignitaries and dealing with an array of special events and
    demonstrations. This hinders its ability to make a case for additional
    federal reimbursement,

    requiring it to spend more of its own resources to support the federal
    presence.

    The District Continues to Although the District is making some attempts to
    address its backlog of Defer Improvements to Its

    infrastructure projects, it has nonetheless continued to defer significant
    Infrastructure While Debt

    amounts of infrastructure projects because of constraints in its operating
    Pressures Remain

    budget. The Chief Financial Officer (CFO) is also taking steps to reduce
    the city*s debt servicing costs, such as refinancing some bonds at lower
    rates. However, the District cannot take on additional debt without
    cutting services or raising taxes that are already higher than other
    jurisdictions. As

    a result, it has chosen to put off needed repairs to streets and schools
    and postponed new construction that would improve the District*s
    infrastructure (estimated at $371 million in fiscal year 2003).

    From 1995 to 2002, the District*s outstanding general obligation debt
    changed little, totaling $2.67 billion as of September 30, 2002. Debt per
    capita has also remained fairly constant except for a dip due to debt
    retirement that was made possible by an influx of funds resulting from the
    1998 tobacco settlement. As a percentage of local general fund revenues,
    debt service costs, which were 7.3 percent of revenue for fiscal year
    2002, are expected to climb to approximately 10 percent by 2006. The
    District*s projections assume that debt service costs will increase at a
    higher rate

    than local revenues. Furthermore, when compared to combined state and
    local debt across the 50 states, the District*s debt ranks as the highest
    in the nation both per capita and as a percentage of own- source revenue.

    Concluding Due to a combination of its significant management problems and
    its

    Observations substantial structural deficit, the District is likely
    providing a belowaverage

    level of services even though its tax burden is among the highest in the
    nation. By addressing these management problems, in the long term the
    District could reduce future budget shortfalls. However, management

    improvements will not offset the underlying structural imbalance because
    it is caused by factors beyond the direct control of District officials.
    As a consequence, District officials may face more difficult policy
    choices than most other jurisdictions in addressing a budget gap between
    spending and revenues based on current policies. For example, given its
    existing high tax burdens, further raising taxes would likely worsen its
    competitive

    advantage in attracting new businesses and residents to locate in the
    District.

    Since the District may not be providing an average level of services, it
    could also be difficult to cut services further. GAO*s site visits and
    past studies identified myriad management problems that led GAO to
    conclude that the level of services provided to District residents is
    likely below the national norm. Therefore, cutting services means, in all
    likelihood, cutting an already low level of services to residents as well
    as businesses and visitors,

    which could also have undesirable consequences for the District*s economy.
    An alternative option to raising taxes or cutting services would be for
    District officials to continue deferring improvements to its capital
    infrastructure. While the rate of investment has picked up in recent
    years, GAO*s analysis of its capital improvement plan reveals that the
    District

    continues to defer many improvements to its aging stock of infrastructure
    assets as a means of dealing with both a structural deficit and continuing
    budgetary pressures. However, this strategy also is not viable in the long
    run because deteriorating infrastructure would of necessity lead to
    further reductions in the levels and types of services provided and
    ultimately would necessitate either higher taxes or cuts in services.

    Although it would be difficult, District officials could address a budget
    gap by taking actions such as cutting spending, raising taxes, and
    improving management efficiencies. In contrast, a structural imbalance is
    largely beyond District officials* direct control. Without changes in the
    underlying factors driving expenses and revenue capacity, the structural
    imbalance will remain. If this imbalance is to be addressed, in the near
    term it may be necessary to change federal policies to expand the
    District*s tax base or to provide additional financial support. However,
    given the existence of

    structural imbalances in other jurisdictions and the District*s
    significant management problems, federal policymakers face difficult
    choices regarding what changes, if any, they should make in their
    financial relationship with the District.

    Federal policymakers could choose not to address the District*s structural
    imbalance and require local officials to deal with the difficult choices
    it faces to meet its obligations. This approach recognizes that other
    jurisdictions also face substantial structural deficits and local
    officials are in the best position to decide for themselves the most
    effective means of balancing trade- offs between high tax burdens and
    reduced levels of public services for local residents and visitors to the
    nation*s capital.

    Alternatively, additional federal assistance (beyond the high level
    already provided) for the District could compensate for its structural
    imbalance. However, this assistance might suggest that officials of other
    fiscal systems, also with sizable structural imbalances, would have
    equally sound claims on additional federal assistance. Nevertheless, by
    virtue of the District being the nation*s capital, justification may exist
    for a greater role by the federal government to help the District maintain
    fiscal balance. However, this strategy is not without its own risks. For
    example,

    significant management problems in the District mean that the aid
    provided, if not used wisely, could result in more wasteful spending or in
    the District simply postponing many management reforms. Given its
    management challenges, it is important that the District achieve basic
    management performance and accountability standards to ensure an efficient
    use of any resources.

    District of Columbia GAO provided copies of a draft of this report to the
    Mayor and CFO of the

    Comments District of Columbia for their review and comment. The CFO, in
    consultation with the Mayor, provided written comments agreeing with all

    key findings in the draft report. The District*s letter is reprinted in
    appendix VI. Specifically, District officials commented on what they saw
    as the report*s three major themes. First, they concur with the existence
    of a structural deficit. Second, they concur with the four fundamental
    features of the District*s fiscal problems, mainly that the District*s
    expenditure requirements for providing an average level of services are
    far higher than any state fiscal system; the District taxes itself very
    heavily; even with high taxes, the District may not be providing an
    average level of services to residents, commuters, and visitors; and the
    District has a serious infrastructure problem. Third, the District agrees
    that GAO provides a constructive analysis of several issues about the
    District*s finances and acknowledges that significant opportunities exist
    for addressing serious management inefficiencies. In addition, District
    officials state that spending and revenue

    adjustments taken to maintain a balanced budget do not resolve the
    underlying structural deficit.

    District officials stated their belief that, given the District*s unique
    relationship with the federal government, a strong case exists for the
    federal government to assist it in addressing its structural deficit. They
    also presented four technical suggestions with respect to the content of
    the draft report. Specifically, they asked and GAO agreed to highlight in
    the executive summary that the District is taking some measures to address

    management inefficiencies and that the District has maintained balanced
    budgets, but these year- to- year adjustments do not address the
    underlying structural deficit. Although District officials also requested
    that GAO further emphasize that solving management inefficiencies alone
    will not resolve the District*s structural deficit, GAO believes this
    discussion is adequately captured throughout the report. Similarly,
    District officials asked GAO to emphasize the unique situation involved in
    the District*s fiscal deficit; GAO believes the report adequately
    addresses this issue as

    well.

    Chapt er 1

    Introduction A perennial issue for federal and District of Columbia
    officials has been determining the proper level of federal assistance to
    the District. Federal assistance historically has helped the District
    offset costs associated with its unique status and position. However,
    according to District officials, this assistance is inadequate.

    Based on the District*s most recent budget analysis, District officials
    claim that they will be unable to maintain the District*s current level of
    services into the future under its current revenue policies. District
    officials also point to a deeper structural imbalance, stating that they
    do not have

    sufficient revenue capacity to meet the high cost of providing residents
    and visitors with adequate public services. In addition, the District has
    experienced serious and longstanding management problems.

    In September 2002, we published an interim report that concluded that the
    District had not provided sufficient data and analysis for us to determine
    whether, or to what extent, the District is, in fact, facing a fiscal
    structural imbalance. 1 To help inform this debate about the proper level
    of federal assistance, this report (1) assesses whether, or to what
    extent, the District faces a structural imbalance between its revenue
    capacity and the cost of

    providing residents and visitors with average levels of public services,
    (2) identifies significant constraints on the District*s revenue capacity,
    (3) examines cost conditions and management problems in key program areas,
    and (4) studies the effects of the District*s fiscal situation on its
    ability to fund infrastructure projects and repay related debt.

    Characteristics of the While the District serves as the seat of the
    federal government, it also

    District serves as home to over a half million people. The District is 61
    square miles

    and had 9,316 residents per square mile in 2000. The District*s primary
    industry after the federal government is tourism. Other important
    industries include trade associations, as the District is home to more
    associations than any other U. S. city. Table 1 describes some of the

    demographic characteristics of the District and compares them to national
    averages in 2000.

    1 GAO- 02- 1001.

    Tabl e 1: Demographic Characteristics of the District Compared to National
    Averages, 2000

    District of Characteristics Columbia United States

    Percentage of population under 19 years 24 29 Percentage of population 65
    years and older 12 12 Percentage of population by race: White 31 75
    Black or African- American 60 12 Estimated median household income $40,926
    $41, 486 Percentage of individuals below poverty 18 12 Source: U. S.
    Census Bureau.

    The District*s Fiscal The fiscal relationship between the federal
    government and the District has

    Relationship with the been a subject of perennial debate. Although the U.
    S. Constitution gives

    the Congress exclusive legislative authority and control over the District
    as Federal Government the seat of the federal government, 2 the
    Constitution did not specifically define the fiscal relationship between
    the District and the federal government. Accordingly, tension has existed
    between maintaining some degree of federal control over the District and
    the desire to grant District residents a say in how they are governed. As
    a result, local autonomy and

    federal fiscal support for the District have evolved throughout the last
    200 years.

    Through the 1870s to the present, the federal government has made
    financial contributions to the District*s operations. Table 2 briefly
    describes the evolution of this fiscal relationship by highlighting the
    important milestones since home rule in 1973.

    2 U. S. Constitution., art. I, S: 8, cl. 17.

    Tabl e 2: Significant Statutes or Actions That Affected the District*s
    Fiscal Relationship with the Federal Government since Home Rule

    Federal statutes or actions a Purpose of statute or action Implementation
    of statute or action

    The District of Columbia Provided for an elected mayor and city council.
    However, the

    In recognition of the constraints on the Self- Government

    District cannot obligate or spend funds unless appropriated by District*s
    revenue capacity, such as its Reorganization Act of

    an act of the Congress. The act also continued the annual inability to tax
    the income of nonresidents, 1973 b (subsequently

    payment to the District, but the actual amount appropriated was the act
    required the District to estimate the renamed the District of

    within the discretion of the Congress. budgetary impact of these
    limitations each Columbia Home Rule Act)

    year and to include in its budget submission a request for a federal
    payment.

    The District of Columbia Intended to restore the city to financial
    solvency and improve its

    The control board was responsible for Financial Responsibility

    management in response to a serious financial and helping the District
    recover its financial and Management management crisis. The act created a
    federal control board

    solvency and improve management Assistance Act of 1995

    whose authority supplanted that of the elected mayor and city
    effectiveness. The CFO was charged with council; it also created a chief
    financial officer (CFO). The act developing long- term financial plans and
    also extended the powers of the District Inspector General (IG). enforcing
    budget discipline among

    agencies. The IG was charged with performing annual audits and
    investigating allegations of waste, fraud, and abuse of city funds or
    procedures.

    The National Capital Enacted to provide key structural changes to the
    District*s The federal government assumed the Revitalization and
    SelfGovernment finances and to repeal the annual federal payment. The act

    District*s unfunded pension liabilities and a Improvement

    also repealed the provision in the Home Rule Act requiring the larger
    share of its Medicaid expenditures. Act of 1997 District to submit an
    annual federal payment request as part of The act authorized a federal
    financial its budget. contribution, but did not specify an amount. The act
    also shifted to the federal

    government certain financial and administrative responsibilities for
    justice, including the court system, corrections,

    offender supervision, and crime victim compensation.

    In September 2001, the The control board certified that the provisions of
    the Financial

    The last of the preconditions for control board suspended

    Responsibility and Management Assistance Act had been met. suspension of
    the control board was its oversight

    However, under the law the control board will return if any one of
    achieved in February 2001 when the responsibilities. seven events occur,
    such as if the District fails to meet its payroll

    fourth consecutive balanced budget for the or if it has a cash deficit at
    the end of any quarter. District was certified based on the Fiscal Year
    2000 Comprehensive Annual

    Financial Report (CAFR). Source: GAO.

    Note: GAO analysis of the federal actions and statutes described in this
    table. a Pub. L. No. 93- 198.

    b For a comprehensive discussion of the history of District*s relationship
    with the federal government, see Congressional Research Service, The
    Evolution of District of Columbia Governance, Order Code RL 30897
    (Washington, D. C.: November 2001).

    Reports on the Several recent reports address some of the unique
    challenges the District District*s Unique

    faces as the nation*s capital, the status of its fiscal health, and the
    management inefficiencies that continue to affect its programs, costs, and
    Circumstances, Fiscal service delivery. While these studies reach similar
    conclusions about the Health, and

    District*s unique costs associated with the federal presence, as well as
    its Management Problems

    high demand for services, these studies also recognize that the District
    needs continued management improvements. Table 3 highlights the
    conclusions reached in several recent reports about the District.

    Tabl e 3: Recent Reports on the District*s Fiscal and Management Problems
    Report Conclusions

    GAO*s interim September 2002 This report provided our preliminary
    assessment of several elements of the District*s reported fiscal report on
    the District*s fiscal structural imbalance. The report concluded that the
    District had not provided sufficient data or analysis structural imbalance
    a

    to determine whether, and to what extent, a fiscal structural imbalance
    exists. Instead, we committed to perform a more comprehensive analysis to
    address this issue.

    Brookings Institution*s October Federal restrictions on the District and
    the burdens associated with the federal presence prevent it from 2002
    report b reaching its potential as a great capital city. The report
    concludes that the federal government should make a continuing payment to
    the District in the range of $300 million to $500 million per year. Three
    arguments are made to support a federal payment.

    1. Restrictions on the District*s revenue capacity prevent it from
    obtaining reimbursement for services provided to commuters, tax- exempt
    property owners, and national and international officials. 2. The District
    plays a unique jurisdictional role, including providing many services
    typically provided

    by state governments, but without the fiscal tools available to pay for
    these services. 3. The federal government has a responsibility to address
    the neglected state of the District*s

    infrastructure and to help it become a showcase capital city. While the
    report recognizes that some management inefficiencies contribute to the
    budget shortfalls, it concludes that no one knows the extent of its
    contribution to the shortfall or the effects improvements would have on
    its underlying fiscal crisis. The report presents a variety of options for
    providing federal support that range from payments in lieu of taxes, to
    restoring the federal payment as a per capita grant, to providing state-
    like aid to elementary and secondary education.

    (Continued From Previous Page)

    Report Conclusions

    Federal City Council report, The report concludes that the District is on
    a path that will lead to a budget deficit of $500 million

    Assessing the District of annually by 2005. Factors contributing to the
    projected deficit include the economic downturn and

    Columbia*s Financial Position unbudgeted spending increasing in several
    areas, including public schools, Medicaid, the Washington (conducted by
    McKinsey and Metropolitan Area Transit Authority, and the constraints the
    District is faced with due to the presence of Company 2002 ) c

    the federal government. The report calls for three actions. 1. Improve
    management efficiency, which could result in annual cost savings from $110
    to $160 million by 2005. 2. Defer planned individual tax rate cuts from
    2002 through 2004, which would add $150 million to

    2005 revenue. 3. Seek additional financial relief from the federal
    government for costs associated with the burdens it

    faces by virtue of its status as the nation*s capital* the report
    estimates that these annual costs are in the range of $500 million to $650
    million. Source: GAO.

    Note: GAO analysis of the reports described in this table. a GAO- 02-
    1001.

    b Carol O*Cleireacain and Alice Rivlin, A Sound Fiscal Footing For The
    Nation*s Capital (Washington, D. C.: Brookings Institution, 2002). c
    McKinsey and Company, Assessing the District of Columbia*s Financial
    Position (Washington, D. C.:

    2002). The Federal City Council commissioned this report. This council is
    a non profit, non partisan organization dedicated to the improvement of
    the nation*s capital. It is composed of and financed by 170 of the
    region's top business, professional, educational, and civic leaders.

    The Economic After the economic boom of the 1990s, all levels of
    government are now

    Slowdown and the experiencing serious fiscal challenges and are likely to
    face even more

    fundamental ones in the future. The federal budget has moved from
    District*s Finances

    unprecedented federal surpluses in the late 1990s to deficits, with the
    Congressional Budget Office (CBO) now projecting the federal government to
    run deficits of $246 billion in fiscal year 2003 and $200 billion in
    fiscal year 2004. 3 At the same time, spending demands are also on the
    rise, as the federal government deals with funding entitlement programs,
    such as Medicaid, Medicare, and Social Security, along with new and
    rapidly increasing health care costs and recent defense and homeland
    security needs.

    3 CBO*s adjusted baseline assumes discretionary budget authority for 2003
    will total $751 billion and grow with inflation thereafter. See CBO, An
    Analysis of the President*s Budgetary Proposals for Fiscal Year 2004: An
    Interim Report, March 2003 (Washington, D. C.: March 2003).

    Similarly, states are experiencing significant, recurring revenue
    declines* estimates show state budget shortfalls of about $80 billion by
    2004. 4 States are not only facing a major decline in revenues* attributed
    to the recession, steep stock market declines and other factors* but also
    increased spending in areas like Medicaid due to increased enrollment and
    health care costs. This shortfall translated into reductions in aid to
    local governments, hiring and salary freezes, cuts in infrastructure
    projects and discretionary programs aimed at low- income individuals and
    families and even across the board spending reductions. Many states have
    also taken other actions like tapping *rainy day funds* or tobacco
    settlement money, or raising *sin* taxes. Like those of other state and
    local governments, the District*s finances have

    been adversely affected by the recent economic slowdown. The CFO*s office
    projects that total local source revenues for fiscal year 2003 will be
    $53.5 million (or 1.5 percent) lower in inflation- adjusted terms than
    they were in fiscal year 2000. The principal reason for this decline is a
    significant deterioration in individual income tax revenue. In fact, the
    decline of $214.1 million in the individual income tax far exceeds the
    decline in overall revenues. The CFO*s office attributes much of this
    decline to a steep drop- off in capital gains earned by residents,
    although the office does not have sufficiently detailed data to quantify
    the decline in this specific source of income.

    Sales tax and business franchise tax revenues have also declined, but in
    smaller absolute amounts compared to the individual income tax. In
    contrast, revenues from property taxes (the District*s second most
    important revenue source after the income tax), gross receipts, other
    taxes, and nontax sources have increased since fiscal year 2000. Table 4
    shows the change in revenue from each principal source from fiscal year
    2000 through fiscal year 2003. 5

    4 National Associate of State Budget Officers. 5 The projected fiscal year
    2003 total local source revenues are higher than actual fiscal year 2002
    revenues, but by less than 0.2 percent in inflation- adjusted terms.

    Table 4: Changes in the District*s Local Source Revenues since Fiscal Year
    2000 (Revenues in Millions of Real Dollars) Fiscal year 2003 projected
    Fiscal year

    (as of February Change in Percentage Revenue source 2000 actual 2003) real
    dollars change

    Property taxes $732.0 $897. 1 $165. 1 22.6 Sales and use taxes 738.5 708.
    6 -29.9 -4.0 Individual income taxes 1,138.3 924. 2 -214. 1 -18.8
    Franchise taxes 276.0 200. 9 -75.1 -27.2 Gross receipts taxes 224.0 250. 7
    26. 7 11.9 Other taxes 149.6 204. 9 55. 3 37.0 Nontax revenue a 266.7 285.
    3 18. 5 6.9

    Total local source revenue $3, 525.2 $3, 471. 7 -53.5 -1.5

    Sources: District*s Fiscal Year 2000 Comprehensive Annual Financial Report
    and CFO. Note: Fiscal year 2000 dollars were adjusted to constant fiscal
    year 2003 values by using the Bureau of Economic Analysis* price index for
    gross domestic product. a Excludes lottery revenue.

    The District*s approved fiscal year 2003 budget was $5.6 billion. As of
    April 2003, District officials projected that over the long term,
    continuing current spending and tax policies would lead to increasingly
    large deficits, growing to $325 million dollars annually by 2007.

    Scope and The Ranking Minority Member of the Subcommittee on the District
    of

    Methodology Columbia, Committee on Appropriations, United States Senate,
    and the

    Honorable Eleanor Holmes Norton, House of Representatives, asked us to
    study the District*s fiscal position, including whether, or to what
    extent, the District faces a structural imbalance. To address our
    requesters* questions, we used a body of evidence approach that combined
    quantitative and programmatic analyses to identify any possible structural
    imbalance.

    Our approach was not intended to provide a definitive point estimate of
    any imbalance, rather, it was expected to show whether the District*s
    ability to provide an average level of services with its given revenue
    capacity is substantially different from that of most jurisdictions. The
    approach was

    also designed to examine cost conditions in key program areas and to
    identify management problems that could lead to wasted resources. In
    addition, we attempted to identify the effects of the District*s fiscal

    situation on deferred infrastructure projects and debt capacity. Our
    methodology was vetted among key experts, including individuals who
    designed the underlying methodology and District economists. We revised
    our methodology based on expert consultation as appropriate. (See apps. I,
    II, and III for more detail on our overall approach.)

    Our methodology was based on previous efforts to define an objective
    measure of a fiscal system*s structural balance. No consensus exists
    regarding the appropriate level of services and taxation, and this issue
    has been a matter of perennial debate in every state. For this reason,
    when public finance analysts have, in the past, compared the underlying or
    *structural* fiscal position of jurisdictions, they have attempted to
    estimate

    objective measures of each jurisdiction*s spending that are independent of
    that jurisdiction*s particular preferences and policies. Similarly,
    analysts have estimated measures of revenue capacity that are independent
    of each jurisdiction*s decisions regarding tax rates and other tax policy
    choices. As we explain in more detail below, these objective benchmarks
    for levels

    of service and for revenue capacity are based on the national average
    spending and the national average tax rates for state fiscal systems.
    Consequently, the benchmarks are *representative* of the level of services
    that a typical fiscal system provides and the tax rates that it imposes on
    its

    tax bases. A fiscal system is said to be in structural balance if it is
    able to finance a representative basket of services by taxing its funding
    capacity at representative rates. Our use of an average level of services
    and average tax rates should not be

    interpreted as an indication that these are the levels of spending and
    taxation that jurisdictions should seek to provide. Each jurisdiction is
    an autonomous governmental entity responsible for providing the package of
    services and level of taxation desired by its citizens. Depending on the
    preferences of local citizens and their representatives, levels of
    taxation and the services they support may be higher in some jurisdictions
    and

    lower in others. The use of average levels in our analysis should only be
    thought of as a convenient benchmark against which to gauge relative
    differences in the cost of providing public services over which local
    officials have little direct control and as providing an indication of the
    potential availability of revenue sources from which to finance those
    costs.

    Because the District has all the fiscal responsibilities generally shared
    by state, city, county, and special district governments, we used two
    baskets of services as benchmarks. The first is a basket of services
    typically provided by state fiscal systems (the state and all of its local
    governments), and the second is a basket of services typically provided in
    more densely populated urban areas. Both baskets include such functions as
    elementary and secondary education, higher education, public welfare,
    health and hospitals, surface transportation, public safety, and other
    public service functions. 6 For the basket of services provided by state
    fiscal systems, we combined our separate estimates by weighting each
    spending function by its

    proportionate share of total spending of the average state fiscal system.
    For the second basket of services provided by governments serving densely
    populated urban areas, we combined our separate estimates by weighting
    each spending function by its proportionate share of total spending of the
    average urban areas.

    To calculate the cost of providing an average, or representative, basket
    of public services, we used the national average per capita spending for
    each expenditure function as a benchmark for an average service level. For
    example, the national average per capita spending for elementary and
    secondary education was $1, 338 per capita. We used this figure as a
    benchmark indicator of an average level of educational services. However,
    this benchmark has to be adjusted to account for the fact that an average

    level of spending does not support the same level of service in each
    fiscal system. To estimate the cost of an average level of services for
    each state fiscal

    system, we adjusted our benchmark by cost drivers that reflect specific
    demographic, economic, and physical characteristics that are beyond the
    direct control of government officials to affect. For example, we used the

    number of school- age children (excluding children attending private
    schools) rather than actual school enrollments to represent the overall
    scope of government responsibility for elementary and secondary education
    since actual enrollments can be affected by the decisions of policymakers.
    Similarly, we used the average wage rate in private sector

    6 Functions not explicitly listed, such as housing and environmental
    services, and other comparatively small spending functions were aggregated
    into an all other spending category.

    employment to measure the personnel cost of delivering public services
    rather than using actual government labor compensation rates since these
    too are affected by negotiations with public employees and, therefore,
    reflect government policy choices.

    Our estimates of the cost of providing an average level of services are
    likely to understate to some unknown extent the District*s cost of an
    average service level for a number of reasons. First, by using the average
    per capita spending of all state fiscal systems as our benchmark of an
    average service level, by necessity the benchmark excludes any unique
    public service costs associated with being the nation*s capital. Such
    unique costs would include, for example, above average costs for crowd
    control for political demonstrations and increased public safety and
    sanitation costs based on

    the disproportionate number of visitors. In addition, data for the various
    cost drivers (e. g., school- age children and low- income residents) are
    limited and may not fully reflect all relevant cost drivers affecting a
    jurisdiction*s cost environment.

    In addition, a degree of uncertainty exists regarding the relative
    importance each should have in the overall cost calculation. In these
    instances, we have generally attempted to choose conservative assumptions
    so as not to overstate the cost impact of factors used in our analysis.
    (See app. I for a more detailed discussion of our methodology and examples
    of instances where conservative assumptions were employed in calculating
    the cost of providing an average level of public services.)

    To estimate total revenue capacity, we combined revenue estimates for the
    two principal sources from which state fiscal systems finance their
    expenditures: (1) revenues that could be raised from a fiscal system*s own
    revenue sources and (2) the federal grants that the system would receive
    if it provided an average basket of services. In the past, two basic
    approaches have been employed to estimate the ownsource

    revenue capacity of states: (1) those that use income to measure the
    ability of governments to fund public services and (2) those that attempt
    to measure the amount of revenue that could be raised in each state if a

    standardized set of tax rates were applied to a specified set of statutory
    tax bases typically used to fund public services. Total taxable resources
    (TTR), developed by the U. S. Department of the Treasury (Treasury), is a
    leading example of the first type of measure and the representative tax
    system (RTS), developed by the Advisory Commission on Intergovernmental
    Relations, is a leading example of the second.

    Because experts disagree as to which approach is superior, we present
    separate results using both methodologies. Both RTS and TTR take into
    account the restrictions placed on the District*s taxing authority. For
    example, they do not include tax- exempt property or the income earned by
    nonresidents who work in the District. However, since other states may tax
    nonresidents* incomes, those incomes are included in their tax bases.

    We generally used the actual amounts that state fiscal systems received
    from the federal government as proxies for the actual amounts that each
    system would receive if it provided an average basket of services. We do
    so because grant amounts generally are not likely to change significantly
    in response to changes in state and local spending choices. However, in
    the case of the Medicaid program, the federal government provides
    openended matching funds to the District and other state fiscal systems
    that automatically adjust to changing state policy choices regarding the
    coverage of their Medicaid programs and the benefits that are provided. In
    this case, we used an estimate of the Medicaid funding amount that state
    fiscal systems would likely receive if average Medicaid services were
    provided. We have not attempted to estimate the extent to which the

    District and state fiscal systems take advantage of all of their
    opportunities to receive federal grants. As a consequence, our grant
    estimates may understate the true potential that these fiscal systems have
    to receive grants. (See app. II for a more detailed description of the
    methodology we

    used to estimate the revenue capacity of state fiscal systems.) To obtain
    information on federally imposed constraints on the District*s revenue
    authority, we interviewed officials from the office of the District*s CFO
    and several local experts on the District*s economy and finances. We also
    reviewed a number of studies prepared by the District, independent

    commissions, and other researchers that contained information,
    evaluations, and estimates relating to these constraints.

    In addition to the quantitative analysis, we conducted a programmatic
    analysis of the District*s reported structural imbalance by evaluating the
    levels of service, costs, management, and financing of three of the
    District*s highest cost program areas: Medicaid; elementary and secondary

    education; and public safety, particularly police, fire, and emergency
    medical services. We also conducted case study work on two similar
    jurisdictions: San Francisco, California and Boston, Massachusetts. These
    jurisdictions were selected based upon a literature search for empirically
    based comparisons of cities; opinions of experts of District finances; and
    a cluster analysis, using demographic and economic variables such as
    populations, measures of poverty, and number of school- age children.
    Cluster analysis is a technique that groups units (in this case, cities)
    into

    clusters based on their closeness on a set of measures. 7 The case study
    work was conducted to assess how the District compares to other
    jurisdictions regarding the types and costs of similar services in
    Medicaid, education, and public safety, as well as to provide contextual
    sophistication to the quantitative analysis. In conducting the
    programmatic work, we collected and analyzed program data and interviewed
    government officials in the District, California, Massachusetts, San
    Francisco and Boston governments and in federal agencies responsible for
    overseeing or providing major funding in these three program areas.
    Finally, we conducted companion work to identify the effects of the

    District*s fiscal situation on deferred infrastructure projects and debt
    structure. To examine the factors involved, we met with officials of the
    District CFO*s office and Capital Improvement Program (CIP). We also
    obtained and reviewed prior- year District budget and financial plans,
    current year expenditure reports for the capital projects, internal
    studies, and statistics and financial information on the current
    expenditures for the

    District*s CIP. Our approach to analyzing the District*s infrastructure
    projects differed from the approaches used to address the other objectives
    in this report. Because of the variety of ways infrastructure projects are
    owned, managed, and reported by other jurisdictions, comparative

    7 We included 100 high- population cities in our cluster analysis, and
    used the following measures to look for clusters: race; ethnicity;
    population size; population density; population change from 1990 to 2000;
    percentage of school age children; percentage of persons over age 65;
    percentage of unemployed; percentage in poverty; violent crime rates;
    property crime rates; average wage rate; percentage of employees in
    retail, food and hotel, manufacturing, and wholesale labor force;
    percentage of institutionalized; and percentage of female headed
    households with children.

    information on infrastructure across states and local jurisdictions was
    not readily available; therefore, we did not do a comparative analysis of
    the District*s infrastructure with states or other jurisdictions. We
    reviewed the data that the District had available in its annual budget and
    financial plans

    and CAFRs, and other documents. To assess the District*s debt service, we
    obtained and analyzed information from the District*s CFO on the
    District*s debt levels and projected infrastructure needs. We also
    compared selected debt service measures for the District to other state
    fiscal systems.

    Our work was performed from August 2002 through May 2003 in accordance
    with generally accepted government auditing standards.

    The District*s Cost of Meeting Its Public Service Responsibilities Exceeds
    Its Revenue

    Chapt er 2

    Capacity, Resulting in a Structural Deficit To determine if a jurisdiction
    has a structural deficit, we estimated, for the District of Columbia and
    the 50 state fiscal systems, the spending needed to provide an average
    level of public services, the revenues that could be raised with average
    tax rates and the amount of grant funding the jurisdiction can expect to
    receive. Our analysis indicated that the District*s cost of delivering an
    average level of services per capita is the highest in the

    nation due to factors such as high poverty, crime, and a high cost of
    living. Our analysis also indicated that the District*s total revenue
    capacity (ownsource revenues plus grants) is higher than all state fiscal
    systems, but not to the same extent that its costs are higher. The
    District*s own- source revenue capacity ranked among the top five when
    compared to those of the 50 state fiscal systems, and its federal grant
    funding is over two and one

    half times the national average. To estimate a structural imbalance, we
    performed several sensitivity analyses to show how our estimates changed
    as we varied specific judgments and assumptions regarding cost
    circumstances and the value of specific tax bases. The consistency of our
    basic result over a broad range of alternative assumptions and approaches
    led us to conclude that the District does have a substantial structural
    deficit, even though considerable uncertainty exists regarding its exact
    size. Using fiscal year 2000 data, our

    lowest estimate was $470 million and our highest estimate was over $1.1
    billion annually. Our analysis did not take into account the unique public
    service costs associated with being the nation*s capital; however, our
    analysis did take into account the significant federal restrictions on the
    District*s taxing authority. The primary reason for the structural deficit
    is high costs due to conditions beyond District officials* direct control.
    To cope with its high cost conditions, the District uses its relatively
    high revenue capacity to a

    greater extent than almost all state fiscal systems. However, this
    relatively high tax burden, in combination with federal grants, is just
    sufficient to fund an average level of public services if delivered with
    average efficiency.

    The Spending Using an average of the 50 state fiscal systems as a
    benchmark, our analysis

    Necessary to Fund an indicates that the per capita cost of funding an
    average level of services in

    the District exceeds that of the average state fiscal system by Average
    Basket of

    approximately 75 percent (and is over a third more than the second highest
    Public Services

    cost fiscal system, New York). In dollar terms, the District would have to
    Exceeds That of All

    spend $2.3 billion more each year to fund an average level of public
    services compared to what it would have to spend if it faced average cost

    State Fiscal Systems circumstances. When we adjusted the basket of
    services to reflect those

    typically provided in more densely populated urban areas, we estimated
    that the District would annually have to spend over 85 percent more than
    the average state fiscal system per capita. As a result, to provide an
    average level of services the District would have to spend $2. 6 billion
    more than if it faced average cost circumstances. 1 Figure 1 compares the
    District*s per capita costs of funding an average level of services with
    those

    of the five state fiscal systems with the highest costs. 1 Urban areas
    included in our analysis were those county areas with populations over
    250,000 and whose population densities exceeded 3,000 persons per square
    mile.

    Figure 1: Per Capita Spending Necessary to Fund an Average Basket of
    Public Services for Selected State Fiscal Systems (Percentage of Average
    State Fiscal System) 200

    Spending (percentage of average) 180 160 140

    U. S. average

    120 100

    80 60 40 20

    0 District of

    New York California Massachusetts Texas New Jersey Columbia State service
    basket

    Urban service basket Source: GAO. Note: GAO analysis based on the
    methodology described in app. I.

    We used the U. S. average per capita spending for each specific
    expenditure function (for example, Medicaid, education, and public safety)
    as a benchmark for an average service level for that function. We then
    adjusted this benchmark to account for differing workloads and costs to
    reflect the fact that an average level of spending does not support the
    same level of services in each fiscal system because cost conditions
    differ across locations. 2 For example, adjustments are necessary to
    reflect the fact that the District

    must compete with a high- wage private sector in attracting public
    employees, and high real estate costs push up the cost of government
    office space, making the provision of public services more expensive than
    in most

    2 We arrived at the cost of funding an average level of public services by
    summing the estimated dollar cost of each spending function separately.
    See app. I for a more detailed discussion of cost estimates for each
    expenditure function.

    states. The adjustments also reflect the fact that the District faces
    unusually high workloads per capita, such as large numbers of low- income
    people and high crime rates that increase the cost of Medicaid and public
    safety.

    The public service functions that contribute most to the District*s high
    cost circumstances are Medical Vendor Payments (Medicaid), health and
    hospitals, and police and corrections. To provide average Medicaid
    coverage and benefits to its low- income population residents, the
    District would have to spend about $1,315 per capita, which is more than
    twice the national average of $551 per capita. (See table 5.) This added
    Medicaid cost accounts for $437 million of the $2.3 billion difference
    between what the District would have to spend to meet its high costs and
    what it would have to spend if it faced only average costs (based on the
    state basket of services). Similarly, we estimated the per capita cost of
    providing police

    services is more than four times the average state fiscal system, adding
    $436 million to the District*s cost of providing an average level of
    services annually. One area of the budget where costs are not as high is
    elementary and secondary education, where, due to a comparatively small
    percentage of school- age children, the estimated per capita cost of an
    average level of services is 18 percent above that of the average state
    fiscal system. The only expenditure function in which the District*s per
    capita cost of an average service level is estimated to be well below the
    national average is

    highways, of which the District has comparatively few miles per capita.
    Table 5 provides information on the District*s costs of funding services
    for all functions.

    Tabl e 5: The District*s Estimated Per Capita Cost of Funding an Average
    Basket of Public Services, Fiscal Year 2000 Average basket of services
    State basket of services Urban basket of services

    Percentage of Percentage of Expenditure function Per capita national
    average Per capita national average

    All functions $9, 216 176 $9, 783 187

    Education

    Elementary & secondary 1,576 118 1,645 118 Higher 836 162 126 162

    Public welfare

    (Continued From Previous Page)

    Average basket of services State basket of services Urban basket of
    services

    Percentage of Percentage of Expenditure function Per capita national
    average Per capita national average

    Medical vendor payments (Medicaid) 1,315 239 1,315 239 Health and
    hospitals 732 162 608 162 Other public welfare 595 214 745 213

    Highways 234 65 119 65

    Public safety

    Pol i ce 964 478 1,718 478 Corrections 765 441 532 441 Fire protection 157
    192 275 192

    Interest on Debt 437 176 520 187

    Administration 436 143 339 136

    All Other 1,168 160 1,842 160 Source: GAO analysis of data from the U. S.
    Census Bureau.

    The cost estimates shown in table 5 are likely to understate to some
    unknown extent the District*s cost of an average level of services for a
    number of reasons. First, by using the average per capita spending of all
    state fiscal systems as our benchmark for an average level of public
    services, the benchmark by necessity, excludes any unique public service

    costs associated with the District being the nation*s capital. Such costs
    would include, for example, crowd control for political demonstrations
    that occur disproportionately in the nation*s capital and a
    disproportionate number of tourists and out of town visitors that impose
    public safety and sanitation costs on the District*s budget. In addition,
    limited data are available for the various indicators of

    workload used in our analysis and there is a degree of uncertainty
    regarding their relative importance in our overall cost estimates. In
    these instances, we generally chose conservative assumptions so as not to
    overstate the cost impact of factors used in our analysis. For example, in
    adjusting for differences in the cost of living, we took into account only
    differences in the cost of housing, but due to data limitations, we were
    unable to take into account other potential sources of such cost
    variation. Such conservative assumptions likely result in an underestimate
    of the

    number of low- income residents in our analysis. For more discussion and
    examples of instances where conservative assumptions were employed in our
    analysis, see appendix I.

    The District*s Per Our analysis indicated that the District*s per capita
    total revenue and ownsource

    Capita Total and OwnSource revenue capacities are higher than those of all
    but a few state fiscal

    systems. As noted earlier, the District*s total revenue capacity equals
    the Revenue

    sum of its own- source revenue capacity (the revenue that it could raise
    Capacities Are High

    from its own economic base), plus the amount of federal grants that the
    Relative to Those of

    District would receive if it provided a representative level of services.
    State Fiscal Systems Experts disagree on the best approach for estimating
    revenue capacity and numerous data limitations exist; thus, in the course
    of our analyses we made a variety of methodological decisions and
    assumptions. For this reason, we present a range of estimates for the
    District*s revenue capacity based on two fundamentally different
    approaches that have been used in

    the past. All of the estimates we present include adjustments designed to
    account for significant constraints on the District*s taxing authority,
    which are discussed in chapter 3.

    For one measure of the District*s own- source revenue capacity we used the
    U. S. Department of the Treasury*s (Treasury) estimates of total taxable
    resources (TTR). TTR is a comprehensive measure of all income either
    received by state residents (from state or out- of- state sources) or
    income produced within the state but received by nonresidents. 3 We also
    developed a second set of estimates of own- source revenue capacity, using
    the representative tax system (RTS) methodology. The RTS methodology
    estimates the amount of revenue that could be raised in each state if a
    standardized set of tax rates were applied to a set of uniformly defined
    statutory tax bases typically used to fund public services.

    Proponents of TTR believe that a measure of revenue capacity should be
    independent of policy decisions and should avoid judgments about the
    administrative or political feasibility of taxing particular bases.
    Proponents of the RTS approach believe that administrative and political
    constraints should be taken into account, even though it may be subjective
    to say what is a constraint and what is a choice.

    3 TTR is a more comprehensive measure of income potentially subject to
    taxation by state fiscal systems than either personal income or gross
    state product, two other potential indicators of revenue capacity. By
    applying the national average effective tax rate, TTR can also be
    expressed in terms of the revenues that could be raised by a state fiscal
    system with an average tax burden.

    In producing our RTS estimates, data limitations compelled us to use a
    variety of assumptions and, in some cases, several different approaches
    when estimating individual tax bases. 4 Rather than present results for
    every possible combination of plausible assumptions, we developed *low*
    and *high* RTS estimates of own- source revenue capacity. The *low*
    estimate is the result we obtained when we used all of the assumptions
    that tended to lower our estimate of the District*s capacity relative to
    those of the states; the reverse holds for our *high* RTS estimate. (See
    app. II for additional details.)

    The two fundamentally different estimation approaches yielded the same
    basic result* the District*s own- source revenue capacity per capita
    ranked among the top five when compared to those of the 50 state fiscal
    systems. According to the Treasury*s TTR estimates, the District*s per
    capita ownsource revenue capacity was 34 percent larger than that of the
    average state fiscal system in fiscal year 2000. According to our RTS
    estimates for that same year, the District*s per capita own- source
    revenue capacity was from 19 percent to 29 percent greater than the
    average. Although we believe it is likely that the District*s actual
    revenue capacity falls within the

    range spanned by both Treasury*s and our estimates, we cannot be
    absolutely certain that it does. 5 The District*s relatively high own-
    source revenue capacity, combined with

    the fact that the District has access to much larger federal grants per
    capita than any of the state fiscal systems, gives the District a higher
    total revenue capacity than any of the state fiscal systems. We estimated
    that, if the

    4 For example, although aggregate data on sales in the retail trade and
    selected services sectors are available from the U. S. Census Bureau every
    year, state- by- state data are available only every 5 years. The last
    disaggregation available was for 1997. To estimate the state- by- state
    distribution of sales in 2000, we had the options of assuming (1) that the
    2000 sales were distributed across states in the same proportions as the
    1997 sales had been or (2) that the sales were distributed in the same
    proportion across states as was year 2000 employment in the retail and
    sales industries. We had no way to determine which assumption was more
    accurate, so we produced estimates using each approach.

    5 Given that our *high* RTS estimate (29 percent above average) falls
    between the other two estimates, we will not present any further results
    based on that estimate in this chapter. Our range of RTS estimates is
    broadly consistent with results produced by Tannenwald, who used a similar
    RTS approach. (See Robert Tannenwald, *Interstate Fiscal Disparity in
    1997,*

    New England Economic Review (Boston, Mass.: Federal Reserve Bank of
    Boston, Third Quarter, 2002).) Tannenwald estimated that the District*s
    per capita own- source revenue capacity was 23 percent greater than that
    of the average state fiscal system in fiscal year 1997.

    District had provided an average level of services in fiscal year 2000,
    its federal grants would have been more than two and one- half times as
    large as the average per capita federal grants received by state fiscal
    systems and over 50 percent more than the second largest recipient of
    federal assistance, Alaska. Adding these grants to the TTR estimate of
    own- source revenue capacity yields an estimated total revenue capacity
    for the District that is 60 percent greater than that of the average state
    fiscal system. The estimated total revenue capacity for the District,
    based on the grants plus our *low* RTS estimate, is 47 percent above the
    national average.

    Figure 2 compares the District*s total revenue capacity to those of the
    five state fiscal systems with the highest total revenue capacities. The
    values in the figure show the extent to which each system*s revenue
    capacity exceeds the national average, which equals 100 percent. Although
    the District had the highest total revenue capacity of any fiscal system,
    the District*s distance from the next highest fiscal systems is not nearly
    as extreme as it was for the representative expenditure estimates
    presented previously in figure 1.

    Figure 2: Total Revenue Capacity Per Capita for the Highest- Capacity
    Fiscal Systems (Percentage of Average State Fiscal System) 200

    Revenue capacity (percentage of average) 180 160 140

    U. S. averaqge

    120 100

    80 60 40 20

    0 District of

    Alaska Connecticut Wyoming Massachusetts Delaware Columbia

    TTR Low RTS Source: GAO.

    Note: GAO analysis based on methodologies described in app. II. Total
    revenue capacity is the sum of own- source revenue capacity plus federal
    grant funding if an average level of services were provided.

    The District*s The District has a structural deficit because its costs of
    providing an Structural Deficit

    average level of services exceed the amount of revenue that it could raise
    by applying average tax rates. This result holds regardless of which range
    Results from a High

    of estimating approaches and assumptions we used. We obtained our Cost of
    Funding an

    lowest deficit estimate of about $470 million by combining our lowest
    Average Level of

    estimate of the District*s costs (the one based on the state basket of
    services) with our highest estimate of the District*s total revenue
    capacity

    Services (the one based on the TTR approach). In contrast, we obtained our
    highest

    deficit estimate of over $1.1 billion by combining our highest estimate of
    the District*s costs (the one based on the urban basket of services) with
    our lowest estimate of the District*s total revenue capacity (the one
    based on the *low* RTS approach). While we cannot be certain that the
    actual size of the District*s structural deficit falls within this range
    of estimates, we

    believe that the District's structural deficit is unlikely lower than our
    most conservative estimate of $470 million for the reasons explained
    earlier.

    To better compare the size of the District*s deficit to those of the state
    fiscal systems, we sought to control for the wide differences in the sizes
    of the fiscal systems by dividing each system*s deficit (or surplus) by
    its population and own- source revenues. Table 6 presents the three

    alternative measures of the deficit and, for each of them, shows how the
    District ranks against the 50 state fiscal systems. The District*s deficit
    is larger in per capita terms than that of any state fiscal system for
    both our higher and lower estimates. The District*s deficit as a
    percentage of ownsource revenue is sixth largest according to our lower
    estimate, and the largest according to our higher estimate. Tabl e 6:
    Estimated Size of the District*s Structural Deficit in Fiscal Year 2000,
    Using

    Alternative Measures and Estimation Approaches Deficit as a percentage of
    Absolute deficit Deficit per

    own- source (in millions) capita revenue

    Estimation approach Value Rank Val ue Rank Value Rank

    State services basket; TTR for revenue capacity $470 18 $821 1 14.4 6
    Urban services basket; Low RTS for revenue capacity $1, 163 8 $2, 032 1
    40.3 1 Source: GAO. Note: GAO analysis based on methodologies described in
    apps. I and II.

    Figures 3 shows how the District*s structural deficit per capita compares
    to the state systems with the largest structural deficits. 6 The figure
    shows that, if the District*s actual structural deficit is close to our
    lower estimate, then it is not much different than the deficits of most of
    the state fiscal systems in the top 10 in per capita terms. However, if
    the District*s actual structural deficit is close to our higher estimate,
    then it is much larger in per capita terms than the deficits of any state
    fiscal system.

    6 The figure includes those fiscal systems whose deficits ranked among the
    top 10 under one estimation approach or the other. Figure 11 in app. III
    shows roughly the same pattern when deficits are compared as a percentage
    of own- source revenue capacity, although in that comparison five states
    have larger deficits than our low estimate for the District.

    Figure 3: Fiscal Systems with the Largest Structural Deficits Per Capita
    2500 Deficit per capita (national average = 0)

    2000 1500 1000

    500 0

    District of Alabama Arizona Arkansas California Georgia Louisiana
    Mississippi New Mexico New York Oklahoma Texas

    Columbia State services, TTR capacity Urban services, RTS *Low* capacity
    Source: GAO.

    Note: GAO analysis based on methodologies described in apps. I and II.

    The District*s High Tax The District*s tax burden (actual revenues
    collected from local resources

    Burden Yields relative to their own- source revenue capacity) is among the
    highest of all

    fiscal systems, but that burden yields revenues that are only sufficient
    to Revenues That Could

    fund an average level of services. The District*s actual tax burden Only
    Support an

    exceeded that of the average state fiscal system by 33 percent, based on
    Average Level of

    our lower estimate of its own- source revenue capacity, and by 18 percent,
    based on our higher estimate of that capacity. (See the first two bars of
    fig. Services 4.)

    The combination of a high revenue capacity and a high tax burden allows
    the District to fund a very high level of actual spending*$ 9,298 per
    capita in fiscal year 2000 compared to a national average of $5, 236.
    However, when the District*s high cost circumstances are taken into
    account, this

    high spending level would only be sufficient to provide an average level
    of services if those services were delivered with average efficiency.
    Specifically, for the state basket of services, the District*s actual
    spending is

    nearly the same as the cost of an average level of public services; for
    the

    urban basket of services, its actual spending is about 5 percent below
    average. (See the last 2 bars of fig. 4.) Moreover, as we discuss in
    chapter 4, the fact that the District*s aggregate spending is
    approximately equal to the aggregate cost of an average level of services,
    suggests that the level of services it actually provides may be below
    average due to inefficient service delivery and other management problems.
    Nevertheless, even if the District were to provide its public services as
    efficiently as a typical state fiscal system, it would still face a
    structural deficit of $470 million or more.

    Figure 4: The District*s Tax Burden and Cost- Adjusted Spending 160

    Percentage of U. S. average 140

    U. S. average

    120 100

    80 60 40 20

    0 Low capacity

    High capacity State service

    Urban service estimate

    estimate basket

    basket Tax

    Cost- adjusted burden spending

    Source: GAO. Note: GAO analysis based on methodologies described in apps.
    I and II.

    The District*s Revenue Capacity Would Be Even Higher in the Absence of
    Several

    Chapt er 3

    Constraints on Its Taxing Authority Although the District of Columbia*s
    (District) own- source revenue capacity per capita appears to be large
    relative to those of most state fiscal systems, it would be even larger in
    the absence of several existing constraints on the District*s taxing
    authority. The most significant constraints are (1) the unique prohibition
    against the taxation of District- source income earned by nonresidents and
    (2) the relatively large proportion of the District*s property tax base
    that is not taxable because it is either owned or

    specifically exempted by the federal government. District officials say
    that building height restrictions also limit the District*s property tax
    base.

    We are not able to estimate the amount of revenue that the District would
    gain if these constraints were removed. However, our quantitative analysis
    indicates that, despite these constraints, the per capita revenue
    capacities of the District*s income and property taxes are higher than
    those of all but a few state fiscal systems. In contrast, the District
    likely has a relatively low

    sales tax capacity due, in part, to a disproportionate share of sales to
    the federal government and other exempt purchasers. The fact that the
    federal government does not pay property or sales taxes to the District
    does not necessarily mean that the federal presence has a net negative
    effect on the District*s finances. A significant portion of the private
    sector activity in the

    District is linked to the presence of the federal government. The Federal
    Unlike that of any state, the District*s government is prohibited by
    federal law from taxing the District- source income of nonresidents. 1 The
    41 states Prohibition against a that have income taxes tax the income of
    residents of at least some other District Tax on the

    states. Fifteen states participate in reciprocal nontaxation agreements,
    but Income of

    no state has an agreement with more than 6 other states. 2 States that
    Nonresidents Is Unique

    impose income taxes also typically provide tax credits to their residents
    for income taxes paid to other states.

    1 Section 602( a) (5) of the District of Columbia Home Rule Act (D. C.
    Official Code, 2001 Edition, Sec. 1- 206.02 (a) (5)) states that the
    District*s council may not *impose any tax on the whole or any portion of
    the personal income, either directly or at the source thereof, of any
    individual not a resident of the District.* 2 This information comes from
    a Commerce Clearinghouse Web site that provides

    information on state tax withholding requirements for multistate
    businesses. We have not independently verified this information.

    In addition, some cities such as Philadelphia, Detroit, Cleveland, and
    several other cities in Ohio, tax the incomes of commuters who work within
    their boundaries. These taxes are typically levied at a low flat rate
    (most of the ones we identified were between 1 and 2 percent) on
    citysource earnings. Other cities are not authorized to levy commuter
    taxes by their state governments. 3 However, in those cases the state
    governments are able, if they choose, to redistribute some of the state
    tax revenues collected from residents of suburbs to central cities in the
    form of grants to the city governments or in the form of direct state
    spending within the cities. 4 Critics of this restriction on the
    District*s income tax base argue that

    commuters increase the demand for city services and, therefore, should
    contribute to defraying the additional costs that they impose. Although no
    data are collected on the amount of money the District spends on
    commuters, we have rough indications of some of the impacts based on our

    own quantitative analysis. For example, we estimated that the cost to the
    District of providing a representative level of police and fire services,
    solid waste management, parking facilities, local libraries, and transit
    subsidies in fiscal year 2000 was from $44 million to $77 million more
    than it would have been if the daily inflow of commuters to the District
    had only equaled the daily outflow. 5 We cannot separate the impact of
    commuters from

    residents on the District's highway costs. Commuters should not have a
    large impact on the District's costs for other services, such as primary
    and secondary education or Medicaid.

    3 The range of tax rates in the cities we identified as levying commuter
    taxes was verified using publicly available tax descriptions drafted by
    the individual jurisdictions. 4 Grants from a state to city government do
    not represent the net fiscal flow between the two jurisdictions. States
    collect significant amounts of tax revenue from individuals, businesses,
    and transactions located in cities. The net fiscal flow would equal state
    grants and direct state spending in a city (excluding any pass- through of
    federal funds), minus all state revenues collected in that city.

    5 These are all services for which we used average daytime population as
    one of the workload factors. We isolated the impact of the large net
    inflow of commuters on representative spending for these services by,
    first, producing estimates based on average daytime population, then
    producing alternative estimates based on resident population, and,
    finally, subtracting the latter from the former. These estimates of the
    commuter impact are subject to the same limitations that affect our other
    representative spending estimates. (See

    app. I for details.)

    Although commuters impose costs, some local economists we interviewed
    noted that commuters already do contribute to the financing of these
    services, even without a tax on their income. Again, no data are collected
    on the amount of taxes paid directly by commuters or the tax revenues
    attributable to jobs supported by them. Some rough indications of the
    revenue contributions are available. One recent study estimated that a
    typical daily commuter to the District pays about $250 per year in sales
    and excise taxes, parking taxes, and purchases of lottery tickets. 6
    Another study indicates that spending by commuters supports jobs for
    District residents who are subject to the District*s income tax. 7 It is
    difficult to estimate the amount of additional revenue that the District

    would gain if it were allowed to tax the income of nonresidents. The
    revenue consequences and the distribution of the ultimate burden of a
    nonresident income tax for the District would depend on how the tax is
    designed and how nonresidents and neighboring governments respond to it.
    Particularly important is the nature of the crediting mechanism that would
    be established under such a tax. For example, if the District*s tax

    were made fully creditable against the federal income tax liabilities of
    the commuters, as was proposed in the *District of Columbia Fair Federal
    Compensation Act of 2002* (H. R. 3923), then the federal government would
    bear the cost and would have to either reduce spending or make up for this
    revenue loss by other means. 8 If the states of Maryland and Virginia
    allowed their residents to fully credit any tax paid to the District
    against their state income tax liabilities, then those two states would
    suffer a revenue loss (relative to the current situation). The two states
    might respond to a District commuter tax by taxing the income of District
    residents who work within their jurisdictions or increasing the tax rates
    on all of their residents. 9

    6 Philip M. Dearborn, Effects of Telecommuting on Central City Tax Bases
    (Washington, D. C.: Brookings Institution, January 2002). The study did
    not attempt to estimate the indirect fiscal contributions that commuters
    may have through taxes on their employers. 7 Stephen S. Fuller, The
    Economic and Fiscal Impacts of the Proposed International Monetary Fund
    Building at 1900 Pennsylvania Avenue, NW on the District of Columbia,
    prepared for the International Monetary Fund, Washington, D. C.: May 2001.

    8 This bill was introduced in the House of Representatives on March 11,
    2002 and referred to the Committee on Government Reform and the Committee
    on Ways and Means. This bill has not been re- introduced this year.

    9 The District currently has a reciprocity agreement with Maryland and
    Virginia under which residents only pay income tax in the jurisdictions
    where they reside.

    If the District*s tax were not fully creditable against either the federal
    or state taxes, then the commuters themselves would bear some of the tax
    burden. 10 Those commuters might try to pass the burden of the tax along
    to their employers by demanding higher compensation, or they might choose
    to work elsewhere. This, in turn, would reduce the amount of revenue the
    District would gain from the tax. Conversely, the higher taxes paid by
    commuters could result in decisions to relocate to the District to avoid
    paying the commuter tax. The difficulty of predicting the magnitudes of
    the various potential policy and behavioral responses makes it difficult
    to estimate the revenue that the District would gain from a typical tax on
    nonresidents.

    The District*s Property Like all state and local governments, the District
    is unable to tax property

    Tax Base Is Relatively owned by the federal government and foreign
    governments. As the nation*s

    capital, the District clearly has a higher percentage of its total
    property Large despite the

    value owned by the federal government and by foreign governments than
    Disproportionate most jurisdictions and, therefore, would benefit more
    than most

    Presence of Properties jurisdictions if the federal government and foreign
    governments paid property taxes or made payments- in- lieu- of- taxes.
    Nevertheless, our

    Owned by the Federal quantitative analysis indicates that the District*s
    per capita property tax

    and Foreign base is already larger than those of all but a few state
    fiscal systems. (See app. II.)

    Governments 10 When a state imposes an income tax on a nonresident, that
    taxpayer typically must report all income, calculate adjustments, and
    compute a tax liability based on his or her total adjusted income. This
    liability is then multiplied by the ratio of income earned by the taxpayer
    in the host state to the taxpayer*s total adjusted income.

    There does not appear to be a strong basis for concluding that the
    District*s commercial property tax base is negatively affected by the
    federal presence. Given that a large portion of the private sector
    activity in the District is linked to the presence of the federal
    government and other exempt entities, it is unclear whether commercial
    property would fill the void left if federally owned property were reduced
    to the hypothetical average level seen in other cities. In fact, a good
    deal of the commercial property tax base locates in the District due to
    the federal presence. For

    example, commercial office buildings in the District are occupied by
    contractors who provide services to the federal government, lawyers who
    need to interact with regulatory agencies, and public relations firms that
    interact with congressional offices, among others. The District of
    Columbia Tax Revision Commission presented a comparison suggesting that,
    even with the large concentration of exempt property, the per capita

    value of the District*s taxable property base is large compared to that of
    other large cities and comparable to the per capita values in surrounding
    jurisdictions. 11 It is difficult to estimate the net fiscal impact of the
    presence of the federal

    government or other tax- exempt entities because of the wide variety of
    indirect contributions that these entities make to District revenues and
    the lack of information on the services they use. Tax- exempt entities do
    generate revenues for the District, even though they do not pay income or
    property taxes directly. For example, employees of the tax- exempt
    entities and employees of businesses that provide services to these
    entities pay sales taxes to the District. We have found no comprehensive
    estimates of these revenue contributions; however, studies of individual
    tax- exempt entities suggest that the amounts could be significant. 12
    Fully taxable properties also generate these indirect revenues and a fully
    taxable property that is similar to a U. S. government property in every
    respect, except for ownership, would contribute more to the District*s
    finances than the government- owned property. However, as noted above, it
    is not clear

    11 The District of Columbia Tax Revision Commission, Taxing Simply, Taxing
    Fairly (Washington, D. C.: June 1998). Although it is possible to compare
    the value of taxable property across jurisdictions, it is difficult to
    compare the value of nontaxable property. Experts within and outside of
    the District government have told us that locally assessed values for
    nontaxable properties are likely to be significantly less accurate than
    those for taxable property.

    12 See Stephen S. Fuller, *The Economic and Fiscal Impacts of the Proposed
    International Monetary Fund Building* and *The Economic Impact of George
    Washington University on the Washington Metropolitan Area.* Greater
    Washington Research Center, July 2000.

    that the District would have more taxable property than it currently has
    if the federal presence were reduced to a level typical of other
    jurisdictions.

    District Officials District officials cite the congressionally imposed
    height restrictions on

    buildings 13 as another factor that constrains the District*s property tax
    Believe That the

    base. Although these restrictions may affect the distribution of
    commercial Federally Imposed

    and residential buildings within the District, it is difficult to
    determine Height Restriction on

    whether, or to what extent, these restrictions affect the aggregate amount
    Buildings Also Limits

    and value of those buildings. the District*s Property Two factors are
    likely to mitigate the potential negative impact on the Tax Base

    District*s tax base. First, the space available for building within the
    District has not been completely used. At least some of the office or
    residence space that would have been supplied on higher floors at certain
    locations, if it were not for the height restrictions, is likely to have
    been shifted to other locations in the District where building would have
    been less intensive otherwise. Second, in the face of a given demand for
    office space, a constraint on the supply of that space will increase its
    value per square foot. In addition, the restriction could have an effect
    on the cost of the District*s services by influencing the District*s
    population density. However, the size of any such effect on service costs
    is unknown. Other Nationwide

    In addition to the restrictions discussed above, the District is unable to
    tax Restrictions on Taxing

    the incomes or most purchases of foreign embassies and diplomats,
    purchases or sales by the federal government, the personal property of the
    Authority Are Likely to

    United States or foreign exempt entities, 14 the income of military
    personnel Affect the District

    who are stationed in the District but claim residence in another
    Disproportionately

    jurisdiction, or the income of federal government sponsored enterprises
    (GSE), such as the Federal National Mortgage Association and the Student
    Loan Marketing Association. All states and localities nationwide are
    potentially subject to these same restrictions on their taxing authority,
    even though some of the restrictions may have a disproportionate effect on
    the District, given the relatively high concentration of these nontaxable
    entities and persons within its boundaries.

    13 D. C. Code, 2001 Ed. Secs. 1- 206.02 (6) and 6- 601. 05. 14 Personal
    property refers to tangible property, such as machinery, equipment, and
    furniture, excluding real property, which refers to land and buildings.

    In contrast to the case with the income and property taxes, where
    nontaxable income and property were already excluded from the data we used
    in our quantitative analysis, the sales data that we used contained some
    sales to the federal government, embassies, and military personnel that
    would be exempt. Given data limitations, we were required to make a range
    of assumptions to estimate the amount of sales that would be exempt (see
    app. II for details). Our lower estimate for the District*s sales tax
    revenue capacity placed it below that of 49 of the state fiscal systems;
    our higher estimate placed it below 31 of the state fiscal systems.

    The District Faces High Cost Conditions and

    Chapt er 4

    Significant Management Problems The District*s high spending on the key
    program areas of Medicaid, elementary and secondary education, as well as
    public safety, particularly police, fire, and emergency medical services,
    is influenced by several cost factors, including high poverty,
    economically disadvantaged children and elderly, and high crime. Our
    quantitative analysis shows that the District*s spending for Medicaid and
    elementary and secondary education is slightly

    above what it would take to provide an average level of services, while
    police spending may be significantly below what it would take to provide
    an average level of services if provided with average efficiency. 1
    However, this analysis does not account for all special circumstances
    beyond the control of the District, such as high demand for Medicaid, high
    demand for

    special education services, and extra police and fire services associated
    with political demonstrations. In addition, in each of the three key
    program areas we identified significant management problems, such as
    inadequate financial management, billing systems and internal controls
    that result in unnecessary spending, which draw scarce resources away from
    program services. In recognition of the District*s high- cost environment
    and management challenges, the federal government provides financial and
    other support to the District, including an enhanced Medicaid match.

    Special Circumstances Medicaid is a large and growing portion of the
    District*s budget, with the

    per capita delivery costs of the program being more than twice the
    national and Management

    average. 2 Certain population and delivery characteristics largely outside
    Problems Influence

    the District*s control influence these high Medicaid costs. These High
    Medicaid Costs in

    characteristics include a high poverty rate that contributes to the large
    the District

    numbers of citizens who lack private health insurance and who meet
    existing Medicaid eligibility criteria, a heavy concentration of Medicaid
    beneficiaries with chronic health conditions that require expensive and
    ongoing care, and high real estate and personnel costs for health and
    longterm care providers. When we adjusted for these high- cost
    characteristics, our analysis revealed that the District spent only
    slightly more than that needed to fund the national average levels of
    coverage and services.

    1 Spending results for Medicaid, elementary and secondary education, and
    police (but not fire services) are similar whether District spending is
    compared to a state service basket or an urban service basket.

    2 See medical vendor payments in table 5 of chapter 2.

    However, management problems, which are under the District*s control, have
    further influenced the local share of Medicaid spending. For example, the
    District has been foregoing millions in available federal matching funds

    due to claims management and billing problems, requiring it to use more
    local funds than necessary in support of the program. If the District
    adequately addressed these problems and continued to actively pursue
    reforms already in place, it could receive more federal matching funds and
    free local funds for other purposes. In recognition of the high costs and
    management challenges, the federal government provides certain
    supplemental financial and other support to the District, such as an
    enhanced federal share of the District*s spending on Medicaid.

    The District*s Spending on The District*s per capita costs of providing
    Medicaid services were more

    Medicaid Is Slightly More than twice the national average. However, when
    we adjusted for the

    Than That Needed to Fund District*s high- cost environment, it spent only
    11 percent more than what it

    Average Levels of Coverage would take to fund the national average
    Medicaid coverage and services.

    Our analysis adjusted for several factors that affect costs but are to a
    large and Services extent beyond the control of District officials,
    including people in poverty, the elderly poor, the high cost of living,
    and real estate and personnel costs for providers. Special Population and

    Special population and service delivery characteristics create a high-
    cost Service Delivery

    environment in the District, requiring it to spend substantially more than
    Characteristics Influence other jurisdictions to fund an average level of
    Medicaid coverage and

    High Medicaid Costs services. The District*s high costs for Medicaid are
    caused by a high

    demand for Medicaid that, in part, can be attributed to its special
    population consisting of people at a very high poverty rate and a high
    proportion of citizens who lack private health insurance because their

    employers do not offer it or they cannot afford it; thus, a large number
    of District residents rely on Medicaid for public health care coverage.
    These factors lead to the District spending disproportionately more to
    fund an average level of Medicaid coverage and services. Specifically, the
    District*s poverty level is the second highest among states, and many
    District

    residents meet income- based coverage criteria. For example, in 1999 the
    District had the highest percentage of individuals under age 65 with
    incomes less than 100 percent of the poverty limit covered by Medicaid
    (based on 1997 through 1999 data). Overall, one in four District residents
    receive Medicaid, which was high in comparison to its neighboring state,
    Maryland. However, when the District*s high poverty rate is taken into
    account, its Medicaid coverage of low- income residents is about average,

    as the District has not elected to provide optional coverage or services
    that are far above the national average. An additional factor influencing
    costs is that District residents* many of whom rely on Medicaid for health
    care coverage* have a disproportionately high number of chronic health
    conditions that require

    expensive, ongoing care. The District ranks near the bottom in many health
    indicators relative to other states, a situation that affects the types
    and levels of services the population needs. For example, among states, it
    has very high rates of low birth weight infants, adult- diagnosed
    diabetes, lung cancer, and human immunodeficiency virus (HIV)/ acquired

    immunodeficiency syndrome (AIDS) infection, which tend to be found
    disproportionately among the poor and in urban areas like the District.
    Further, these chronic health conditions for the most part are costly to

    treat, often requiring expensive institutional care or ongoing outpatient
    treatment, such as drug therapy* all at a time when health care costs,
    particularly prescription drugs, are increasing.

    The HIV/ AIDS epidemic has presented a particular fiscal challenge for the
    District*s Medicaid program. For example, the Centers for Disease Control
    and Prevention reported that the District*s 2001 AIDS prevalence rate was
    152 per 100,000 people whereas the next highest state, New York, was 39
    per 100,000 people. The costs of treating Medicaid beneficiaries with

    HIV/ AIDS are very high and because the District has the highest infection
    rate in the country and a disproportionately large number of Medicaid
    beneficiaries, the fiscal burden of the HIV/ AIDS epidemic on the
    District*s Medicaid program is likely disproportionately larger than most
    states. Another factor influencing the District*s high Medicaid costs
    relates to the

    ways in which health and long- term care services are delivered. Providers
    generally are located in densely populated urban areas with high real
    estate and personnel costs, a situation which drives providers* costs
    upward. Specifically, many providers have high operating costs in the
    District, largely due to the high costs of purchasing or renting office
    space and the

    necessity of paying higher salaries to medical personnel. Moreover,
    according to District officials, many of the District*s provider payment
    rates, particularly for physicians, are below average relative to
    operating costs.

    The combined effects of high operating costs and low payment rates may
    contribute to physicians not accepting beneficiaries of the District
    Medicaid program. This could be a reason why many of the District*s
    Medicaid beneficiaries rely on emergency rooms more so than in other

    jurisdictions. District Medicaid beneficiaries may also not obtain
    preventive care when needed, thus allowing health conditions to worsen,
    which could lead to hospital stays. Use of these more costly forms of
    health care are disproportionately high in the District. One report found
    the District had the highest emergency room visits per 1,000 of the

    population in the country as well as the highest hospital admissions rate.
    3 Management Problems Billing and claims management problems are forcing
    the District to forego Result in the District

    millions in federal matching funds and, as a result, requiring it to use
    more Foregoing Significant

    local funds than necessary to pay for expenditures already incurred. Key
    Federal Matching Funds,

    issues that lead to rejected federal reimbursement claims include but the
    District Is Taking

    incomplete documentation, inadequate computerized billing systems,
    submission of reimbursement requests past federal deadlines, providing
    Steps to Address Them

    services to individuals not eligible for Medicaid at the time of delivery,
    and billing for services not allowable under Medicaid. According to a
    recent report, these problems resulted in the District receiving $40
    million less in expected federal reimbursement during fiscal year 2002
    than it had projected in its budget. 4 District officials and other
    experts told us it would be difficult to make any precise estimate of how
    much the District is

    foregoing in federal funding. These management problems involve the
    weaknesses in the processes and systems that several District agencies use
    to track and process claims for federal Medicaid reimbursement after

    services have already been provided. The difference between costs
    submitted for reimbursement and the costs actually reimbursed based on
    federal criteria result in the use of local, rather than federal money, to
    pay for these costs.

    While many states have experienced similar financial management problems,
    the District*s problems appear to be worse than most states, according to
    a federal official we interviewed. The magnitude of the problem is
    serious: Medicaid financial management was identified as a *material
    weakness* by independent auditors of the District*s fiscal year

    3 AARP, Reforming the Health Care System: State Profiles 2000 (Washington,
    D. C.: 2000). 4 McKinsey and Company, 2002. McKinsey did not audit these
    numbers.

    2001 financial statements. These problems have been addressed in several
    of our reports over the years, as well as in reports by the District
    Inspector General (IG), the District Auditor, and McKinsey and Company.
    According to these reports, less than projected federal reimbursements
    have amounted to millions of dollars across the various agencies, creating
    significant, unexpected pressures on the District*s budget.

    The management problems rest mostly with individual District agencies that
    bill for federal Medicaid reimbursement: Child & Family Services Agency
    (CFSA), Department of Mental Health (DMH), and District of Columbia Public
    Schools (DCPS). 5 For example, DMH, which was removed from federal
    receivership in May 2001, did not have an adequate billing process or
    information management systems in place. District officials told us that
    DMH*s billing system contained system edits that permitted unallowable
    costs to go through undetected and then forwarded these claims to the
    Medical Assistance Administration*s (MAA) fiscal agent for reimbursement,
    6 which would reject them after the services were already provided. As a
    result, Medicaid charges, as well as Medicare, were not properly
    documented and deemed unreimbursable by the federal government. In fact,
    officials said the problems were so severe that DMH voluntarily ceased
    billing for Medicaid federal funds* as well as Medicare* for most of 2001
    to resolve these problems and avoid almost certain disallowances from the
    federal government. DMH did not provide a precise estimate of the federal
    reimbursement that was lost during this period.

    The District also does not have an effective centralized monitoring
    process for Medicaid. Officials of MAA told us they have a limited ability
    to control and monitor CFSA, DMH, and DCPS* unlike the private third
    parties that provide services under the regular Medicaid program. Because
    these public provider agencies are distinct units of the District
    government, the District*s budget makes it clear that MAA does not have
    authority over these agencies in terms of financial management, programs,
    budget, claims for submission or billing, or estimation of federal
    reimbursement. 5 These agencies are eligible to bill the federal
    government for specialized Medicaid

    services* estimated to be $121 million in fiscal year 2003. The District*s
    Department of Human Services (DHS) is expected to start making Medicaid
    claims in the near future.

    6 MAA is the District*s single state Medicaid agency.

    Officials told us that historically individual agencies, such as DMH or
    DCPS, made their own Medicaid projections for inclusion in the District*s
    budget and the projections were almost always highly inflated.

    Accordingly, the baseline of the District*s budget would indicate a large
    influx in federal Medicaid funds that would never materialize due to
    billing and claims management problems. For example, DCPS*s original
    estimate of expected federal reimbursement for fiscal year 2002 was $43
    million, which was later reduced to $15 million by the District chief
    financial officer (CFO). In fiscal year 2001, the District wrote off over
    $78 million of several years worth of such unpaid federal claims, which
    were still in the baseline of its budget. If District agencies adequately
    addressed these problems, they could receive more federal matching funds
    and free local funds for

    other purposes, such as providing an above average level of Medicaid
    coverage or optional services. While the District has taken some positive
    steps to improve management, more improvements are needed. Steps to
    Address Management District officials have acknowledged the severity of
    the District*s Medicaid Problems

    management problems and have taken steps to remedy them. Most
    significantly, improving management could help the District increase its
    share of federal Medicaid reimbursement. Most of these reforms have only
    been implemented within the past year, so it is unclear how effective they
    will be in the long run. Key examples include the following:

     The Office of Medicaid Public Provider Operations Reform, which was
    created in June 2002, has become a needed focal point in the Mayor*s
    office for integrating billing processes across District agencies and
    helping these agencies modify their processes and management systems to
    maximize federal Medicaid reimbursement.

     The District recently created an $87 million Medicaid reserve to
    compensate for the costs of Medicaid reimbursements that may need to be
    covered by local funds and to serve as a cushion for any less than
    expected reimbursement in federal Medicaid funds, Medicare and Title IV-
    E. 7 District officials told us they expect to use at least a portion of
    these funds during the current fiscal year. 7 Title IV- E of the Social
    Security Act (42 U. S. C. Secs. 670 * 679b (2000)) provides federal

    payments to states for foster care and adoption assistance. In the
    District, CFSA receives these payments.

     The District CFO is now responsible for analyzing and clearing any
    Medicaid projections made by CFSA, DCPS, and DMH (and eventually DHS)
    before they are incorporated into the District*s budget. Officials

    told us that the District plans to be more conservative in its projections
    for federal Medicaid funds to avoid the negative effects of less than
    expected federal reimbursement.  DMH has designed and implemented a new
    billing process for Medicare

    and Medicaid, in accordance with the business plan mandated by the court
    as part of its post- receivership agreement. CFSA is implementing a new
    computerized billing system, making changes to its data collection
    process, and working closely with federal Medicaid officials to ensure
    that any changes meet federal requirements.

    The District Receives Recognizing the District*s Medicaid situation, the
    federal government has

    Enhanced Medicaid provided additional funding, as well as technical
    assistance and other

    Matching Support and Other programmatic flexibilities. Most significantly,
    in 1997 Congress provided

    the District with a fixed, enhanced Medicaid federal medical assistance
    Assistance from the Federal percentage (FMAP) of 70 percent, 8 which has
    resulted in an influx of

    Government millions of additional federal Medicaid funds that the District
    was not

    eligible to receive previously. Previously, under the statutory formula
    that establishes the federal matching share of eligible state Medicaid
    expenditures, the District received a 50 percent FMAP* the lowest possible
    under the law. In addition, the District uses programmatic flexibility and
    technical

    assistance from the Centers for Medicare & Medicaid Services (CMS), the
    federal agency within the U. S. Department of Health and Human Services
    that is responsible for Medicaid. CMS officials told us they have more
    frequent contact with the District than with many other states. For
    example, they have reviewed the District*s billing processes and computer
    systems in some cases to ensure they meet federal criteria. 8 The federal
    government*s share of a state*s Medicaid expenditures is called the FMAP;

    states and the District must contribute the remaining portion to qualify
    for federal funds. Determined annually, the FMAP is designed so that the
    federal government pays a larger portion of Medicaid costs in states with
    lower per capita income relative to the national average. In fiscal year
    2003, FMAPs ranged from 50 to 77 percent (the maximum allowable is 83
    percent). Generally, with a federally approved state Medicaid plan,
    federal payments are not limited for Medicaid as long as the state
    contributes its share of matching funds.

    Special Circumstances When we adjusted for the District*s service costs
    and workload factors, our

    and Management cost analysis suggests that the District spent 18 percent
    more than what would be necessary to fund an average level of services.
    However, our

    Problems May Result analysis was not able to take into account all of the
    special circumstances

    in Increased Education facing the District. Specifically, it is likely
    that significant management

    Costs and Below problems and disproportionately high special education
    costs are drawing resources away from elementary and secondary education,
    suggesting that

    Average Services the District provides less than the national average
    level of education

    services. The federal government to some extent has recognized the
    District*s special circumstances and the extent of its management problems
    by providing it with special technical and other assistance. The
    District*s Education

    We estimate that the District*s elementary and secondary education costs
    Spending Is Somewhat

    were 18 percent above what it would take to fund an average level of
    Higher Than What It Would

    services. Our analysis incorporated several workload factors that Take to
    Fund an Average

    represent cost conditions that are largely beyond the control of District
    officials, which include the number of school age children (excluding
    those Level of Services

    enrolled in private schools), and the specific costs of serving elementary
    and secondary students and economically disadvantaged children. Our model
    also took into account the costs of attracting teachers and the
    maintenance of capital facilities, both of which are higher in the
    District. When the District*s costs and these workload factors were
    considered, our analysis showed that the District*s spending is somewhat
    higher than what it would take to fund a national average level of
    services.

    Our analysis, however, probably understated the District*s education costs
    because we were not able to quantify the District*s significant management
    problems or high special education costs due, in part, to court mandated
    services. If these factors could be adequately taken into account, they
    may show that the District is actually spending less than what is needed
    to fund a national average level of education services.

    Significant Management We, along with the District IG, the District
    Auditor, and federal inspectors

    Problems Are Further general have identified* and District officials have
    acknowledged* serious

    Drawing Resources Away management problems throughout DCPS*s programs and
    divisions in areas

    from Educational Services such as financial and program management, as
    well as compliance with the requirements of federal programs, such as
    Medicaid and the Individuals

    with Disabilities Education Act (IDEA). These reports estimate that the
    local costs of management problems could be in the millions of dollars.

    However, our cost analysis did not take into account the costs associated
    with fiscal resources that are wasted due to inefficient management. This
    limitation likely results in significant amounts of DCPS*s fiscal
    resources being lost.

    Many of the management problems at DCPS can be attributed to inadequate
    financial management, including a lack of effective internal controls and
    clearly defined and enforced policies and procedures. For

    example, the independent audit of the District*s financial statements for
    fiscal year 2001 classified DCPS*s accounting and financial reporting as a
    *material weakness.* The auditors found that DCPS did not ensure timely
    loading of budget information into its accounting system, which prevented
    DCPS from monitoring expenditures and having accurate financial

    reports. 9 In another instance, DCPS*s procurement procedures were not
    routinely enforced, as exemplified by capital project purchase orders
    being processed directly through the DCPS CFO instead of through the

    procurement office. Recently, DCPS officials acknowledged that they face
    difficulties in tracking procurement costs, and as a result, individuals
    at schools may purchase goods without completing a purchase order. Often
    through a process known as a *friendly lawsuit,* vendors will deliver
    goods without a purchase order and subsequently notify DCPS of the
    purchase to receive payment. Last year, DCPS set aside $17 million to
    compensate for

    such unauthorized purchases, and spent $10 million of it. DCPS officials
    provided us with other examples of the limitations of DCPS*s electronic
    financial management system. These limitations prevent DCPS from
    adequately tracking personnel costs, which represent approximately 80
    percent of the school district*s budget. The system also does not allow
    DCPS officials to track either the total number of employees

    or whether particular positions are still available or have been filled.
    Recently reported problems with managing personnel expenses further
    highlight DCPS*s financial management problems. In March 2003, DCPS
    officials announced that the school system had hired about 640 more

    employees than its budget authorized, resulting in DCPS exceeding its
    personnel budget by a projected amount of $31.5 million over the entire

    9 As previously noted, the independent auditors also identified DCPS*s
    management of Medicaid school- based services claims as a separate
    *material weakness* because DCPS*s billing processes are not set up to
    adequately distinguish between health- related costs

    (which are reimbursable under Medicaid) and education- related costs
    (which are not reimbursable). This was noted by independent auditors as a
    second, separate material weakness in the District*s fiscal year 2001
    financial statements.

    fiscal year. Also, in December 2002, DCPS officials announced that it paid
    $5 million for employee insurance benefits and contributed to tax- free
    retirement accounts for employees who no longer worked for DCPS. Reports
    have also identified management problems in particular

    educational programs, which influence costs and negatively affect the
    quality and level of service provided to students, particularly in special
    education. For example, a September 2002 investigation by the District
    Auditor found that DCPS paid $1.2 million to vendors for providing special
    education services to individuals whose eligibility could not be
    determined from information on vendors* invoices. In November 2000, the
    District IG reported that DCPS paid more than $175,000 in tuition to
    nonpublic special

    education schools that failed to meet the standards for special education
    programs. The District IG also reported inaccuracies in DCPS*s database
    for special education students, inadequate oversight of special education
    tuition payments, and insufficient monitoring of nonpublic special
    education schools. Finally, the District IG concluded that DCPS lacked
    adequate management controls to ensure that transportation services were
    adequately procured, documented, and paid. The IG concluded that by
    implementing certain cost saving measures DCPS could save at least $2.4

    million annually. In addition, DCPS has longstanding issues regarding its
    ability to comply with the laws and regulations of federal education
    programs, including IDEA, and the U. S. Department of Agriculture*s (USDA)
    food and nutrition programs. The extent of DCPS*s compliance issues with
    IDEA have been

    serious, and by 1998 the U. S. Department of Education (Education) entered
    into a compliance agreement with DCPS that mandated improvements in DCPS*s
    special education program. Further, the District has experienced
    longstanding issues of complying with USDA*s requirements for the National
    School Lunch Program and the School Breakfast Program. DCPS*s poor
    management of USDA*s food and nutrition programs resulted in the Mayor and
    the City Council removing oversight and monitoring responsibilities from
    DCPS and placing them under a new, independent District State Education
    Office (SEO). SEO officials told us that while oversight and monitoring
    have improved, they still face many problems in effectively managing
    USDA*s food and nutrition programs.

    High Special Education Our program review revealed that the District has a
    high demand for

    Costs May Result in Less special education and related costs, which are
    not adequately captured in

    Funding Available for All our quantitative analysis. The District has a
    disproportionately large share

    Other Elementary and of special education due process hearings that often
    result in it having to

    provide more expensive services and pay large legal fees; relies heavily
    on Secondary Education

    costly non- public schools; and operates under an array of court orders
    Services

    springing from class action lawsuits, many of which mandate additional
    types and levels of services.

    Accordingly, our cost analysis does not sufficiently consider a major
    education cost driver for the District because we assumed that the
    District*s special education costs were typical of the average state
    system, which we found is not the case. For example, the number of special
    education students has grown rapidly in recent years. Between the 19981999
    and 2000- 2001 school years, the number of special education students in
    DCPS grew by over 25 percent, while the total number of nonspecial
    education students decreased slightly. Over the same period of time, the

    percentage of special education students attending Boston Public Schools
    and the San Francisco Unified School District declined about 9 percent and
    4 percent respectively. DCPS projects that the number of special education
    students will continue to grow even as the general student population is
    expected to continue declining, which will likely cause the special

    education program to pose an increasingly significant financial burden on
    DCPS. Overall, the size of the special education population as a
    percentage of students attending DCPS exceeds the average size for 100 of
    the largest urban school districts in the United States. Further, evidence
    suggests that DCPS may also pay a higher cost per special education
    student than other urban systems.

    The high costs associated with the District*s large number of due process
    hearings divert resources from other critical education services. As
    required by IDEA, a due process hearing gives parents of special needs
    children the opportunity to present complaints on any matter relating to
    the education of their children and seek remedies to any shortcomings. 10
    Some shortcomings that frequently spur due process hearings in the

    District include a lack of sufficient educational programs, older school
    buildings that are not handicapped accessible, failure to meet deadlines
    for

    10 The intent of IDEA is to provide a free and appropriate education for
    children with disabilities in the least restrictive setting.

    providing services in accordance with students* individualized education
    plans (IEP), and not sufficiently involving parents in the development of
    IEPs. The number of due process hearings held in the District in 2000
    exceeded every state except New York, and DCPS estimates that the number
    of hearings requested will continue to grow as these shortcomings
    continue. DCPS officials also acknowledged that their special education
    program

    suffers from a range of shortcomings, such as a lack of early intervention
    and prevention and underinvestment in program capacity. For example, DCPS
    officials noted that many special education teachers are not certified to
    provide special education.

    According to some officials, due process hearings in the District often
    become forums for parents to advocate moving their child out of public
    schooling and into a private facility* at the District*s expense. Due
    process hearings may result in the placement of a child in a much more
    costly setting, such as the transfer of the student from a public to an
    out- ofDistrict

    private facility at the expense of DCPS, or mandating additional types or
    levels of services. Furthermore, the due process hearings result in legal
    costs to the District because the parents of a student often use a law
    firm to handle their cases, and if the student prevails in the hearing,
    the District must pay the legal fees. DCPS officials and other key
    observers have told us that many parents in the District want their
    children to be moved into private facilities and lawyers respond to
    parents wishes and DCPS*s deficiencies, thereby realizing financial gains.
    For example, DCPS staff informed us that one law firm alone represented
    students in over 900 due process cases between September 2002 and January
    2003 and earned approximately $1 million in fees from the District in 1
    year. Even though

    Congress implemented a cap on legal fees related to special education,
    District officials told us the cap does not appear to have affected the
    incidence of due process hearings, but we did not independently verify
    these claims.

    DCPS officials indicated that DCPS has also incurred additional costs to
    comply with court orders and settlements resulting from class action
    lawsuits. For example, DCPS officials said that the costs of transporting
    special education students doubled after implementing service improvements
    as required by the court in the Petties case. 11 However, DCPS could not
    verify that some of the costs attributed to the Petties case

    were court ordered. DCPS officials stated that even with increased
    spending and greater services, they do not think they will be able to meet
    all of the court ordered service improvements. According to DCPS
    officials, another significant case was the Nelson case, which required
    DCPS to develop emergency evacuation plans for students with mobility
    impairments. 12 DCPS officials said that complying with the court order
    required DCPS to make significant capital expenditures. DCPS also reported
    that it has a high percentage of special education

    students attending nonpublic special education schools because it lacks
    the staff and facilities to adequately serve its special education
    students. DCPS officials acknowledged that the school system historically
    has relied on contracting with non- public education facilities, and DCPS
    has never built up the capacity to deliver sufficient special education
    services within DCPS. Services provided in non- public special facilities
    services are much more costly to DCPS than services provided in public
    institutions, as nonpublic schools charge much more for their services.
    For example, a special education student attending a nonpublic institution
    costs about twice as

    much as one receiving special education within DCPS. Spending on these
    services draws resources away from other public education services, as
    well as helping to build up the capacity to deliver more special education
    services within DCPS.

    11 See e. g., Petties v. District of Columbia, Civ. No. 95- 0148 (D. D.
    C.) (September 15, 1997, Order to comply with deadlines and
    recommendations in the Special Master*s report of August 25, 1997),
    (November 14, 1997, Order regarding acquisition of 150 buses), (December
    22, 1997, Order of approving schedule for partial abatement of the
    imposition of additional fines based on acquisition of additional buses).

    12 See, e. g., Nelson v District of Columbia, Civ. No. 1: 00CV02930 (D. D.
    C.) (December 21, 1997, Order approving consent decree).

    The Federal Government In recognition of the District*s special
    circumstances and management

    Provides Technical problems, the federal government, to some extent, has
    provided technical

    Assistance to the District, assistance to the District. Specifically,
    Education has provided substantial

    Recognizing Its Challenges assistance to DCPS, including, since 1996, a
    dedicated liaison to DCPS to

    help identify opportunities for providing technical assistance. According
    to an Education official, no other school district in the country has such
    a departmentwide liaison. In addition, Education officials told us they
    have provided extensive technical assistance to DCPS, including guidance
    for developing an education plan, as well as help in improving its special
    education program, establishing performance standards for students, and
    developing a new database to track student data to increase DCPS*s
    capacity to comply with the future data requirements of the No Child Left
    Behind Act. 13 Education staff has also hosted conferences to help the

    DCPS leadership better understand their oversight responsibilities for
    federal funding programs. The District Faces

    The District*s costs for the key public safety functions of police and
    fire Significant Public

    protection were far above average, according to our analysis. In fact, the
    District*s costs were higher for police than any other category. However,
    Safety Demands due to our analysis showed that when we adjusted for the
    District*s high- cost

    the Federal Presence, environment, the District spent far less on both
    police and fire than it

    but Related Costs Are would take to fund a national average level of
    services in these areas.

    However, the factors considered for both police and fire do not adequately
    Not Adequately

    capture the demands the District faces. Most significantly, our factors do
    Tracked not include any measures of the various public safety demands and
    costs associated with the federal presence and the District*s status as
    the nation*s capital, such as extra protection for federal officials,
    including the President and Vice President, as well as diplomatic
    personnel and foreign dignitaries who visit the city; nor did they capture
    the police and fire costs

    associated with the multitude of regular special events and political
    demonstrations that often draw thousands of people. As a result, the
    District*s spending on traditional public safety services for residents,
    such as policing neighborhoods, traffic control, and fire and emergency
    medical services, is likely even further below average than our analysis
    would suggest* indicating the District is providing fewer traditional
    police and fire services to its citizens. In addition, the District*s
    current cost tracking processes do not adequately capture the true total
    costs associated with

    13 Pub. L. 107- 110.

    providing police and fire services to support the federal presence,
    putting the District at a disadvantage in recovering more costs related to
    protection, special events, or demonstrations. Finally, while the District
    has received some special federal funding in recognition of the services
    it provides to support the federal presence, it is unlikely this funding
    fully compensates for all related costs* indicating that local dollars are
    being used in support of federal activities.

    Our Analysis Shows the According to our analysis, the District*s costs of
    providing police services

    District*s Police and Fire were very high* at four and one- half times the
    national average* as were

    Spending Is Below Average the costs of providing fire protection services,
    which were nearly double

    When Its High- Cost the national average. However, our analysis indicated
    that when we

    Environment Is Considered adjusted for the District*s high- cost
    environment for both police and fire, it

    was spending below what it would take to fund an average basket of
    services typically associated with police and fire departments.
    Specifically, the District*s spending on police was 66 percent below what
    would be necessary to fund a national average level of services based on
    the urban

    basket of services and 40 percent below using the state basket of
    services. Furthermore, fire protection was 28 percent below using the
    urban basket of services. 14

    Our analysis for police was based on three factors only* murder rates, the
    18- 24 year old population, and the general population. The District*s
    murder rate, which served as an indicator of the prevalence of violent

    behavior, was extremely high at more than seven times the national
    average. Further, we found that the percentage of residents in the 18- 24
    age range* a group prone to commit more crimes than any other age group*

    was disproportionately large in the District. Similarly, our workload
    factors for fire protection* multifamily housing units and older housing
    units built prior to 1939* indicated that the District faced high costs
    related to providing fire protection services. Specifically, the District
    had disproportionately high instances of older housing units, which are
    more prone to fires, and disproportionately high numbers of dense living
    conditions in multifamily units, another indication of the extent of fire
    services a jurisdiction must provide. The workload factors for police and
    fire protection suggested that the District*s costs of providing typical
    14 Alternatively, using the state basket of services, the District*s
    spending for fire protection

    was 25 percent above the national average. These results reflect the fact
    that fire services are a larger share of urban government budgets.

    services in these areas were disproportionately higher than in most other
    jurisdictions.

    For several reasons, our analysis may understate what the District spends
    on police and fire services for residents. First, our factors may not
    fully capture the extent of police and fire demands or related costs in
    the District. Specifically, a great deal of uncertainty exists as to
    whether or not some of our factors adequately measure demand for services
    or cost burdens. In addition, we believe these factors understated the
    District*s expenditure demands because they did not capture any costs
    related to

    services provided to the federal government. For example, the factors do
    not adequately reflect increases in the District*s daily population due to
    tourists, college students and other commuters, as well as services
    related to the federal presence for which it does not receive full
    reimbursement, such as protection for federal officials and dignitaries,
    special events, or demonstrations. Because these costs were not taken into
    account in our

    analysis, we believe the District is likely providing less police or fire
    protection services to residents. The District Provides

    As the nation*s capital, the District is continually faced with paying for
    Significant Public Safety

    expenses to support the federal government's presence, such as extra
    Services to the Federal

    services for federal officials, including the President and Vice
    President, Government, Likely

    and diplomatic personnel and foreign dignitaries who visit the city. It is
    also responsible for paying for services related to an array of special
    events Resulting in Less Spending

    and political demonstrations that often draw thousands of people, on
    Services for Residents

    sometimes with short notice. The federal government routinely provides the
    District with special funding and other forms of assistance; however, it
    is unlikely that the federal government fully compensates the District for
    all expenses associated with the federal presence, meaning many related
    services provided by the District are funded with local money. Assistance
    in Protection of

    Although the 1973 Home Rule Act requires the District, including the
    Federal Officials and Dignitaries

    Metropolitan Police Department (MPD), to support federal agencies in
    providing protection to the President and Vice President as well as
    foreign missions and embassies, the federal government does not routinely
    reimburse the District for these expenditures, which District officials
    say places a financial strain on their budget and could negatively affect
    the operations of public safety agencies. The District*s Fire and
    Emergency Medical Services (FEMS) department also provides similar support
    to the federal government. Although the police and fire departments
    typically receive advanced notification of federal protection needs from
    the U. S.

    Secret Service, they are sometimes notified the day of or hours prior to
    an event, resulting in additional costs by necessitating the shifting of
    employees, calling up employees to back- fill positions, and paying
    overtime to employees. It also makes it difficult to plan or budget for
    federally related expenses. For example, MPD reported to us that in fiscal
    year 2002 it incurred 3,240 hours in police officer overtime hours related
    to providing

    protection to federal officials and dignitaries, at a cost of over
    $101,000. MPD operates a special dignitary protection unit that is solely
    responsible for assisting federal law enforcement agencies, such as the
    Secret Service, by providing police escort and protection for federal
    officials, such as the

    President and Vice President, as well as key foreign dignitaries. For
    example, when the motorcade of a federal official, such as the President
    or a key dignitary, travels anywhere in the District, MPD is responsible
    for closing off streets, sending out scout cars in advance of the
    motorcade, and placing motorcycles beside and in front of the official
    cars; for the President, as many as 100 traffic posts are sometimes
    needed. MPD officials noted that they have no choice but to provide these
    services because the District controls its streets, so MPD must assist the
    federal agencies in providing protective services for motorcades that
    travel upon them, as would be the case in whatever jurisdiction these
    officials visited. Often the magnitude of the required duties exceed the
    capacity of the

    dedicated unit; as a result, other MPD officers must be pulled from their
    regular duties, including policing District neighborhoods. According to
    MPD, the key difference between the District and other jurisdictions is
    the

    extent of the protective duties. For example, District officials told us
    the President often leaves the White House several times a day,
    necessitating police and fire support, whereas he visits other
    jurisdictions, such as San Francisco, with much less frequency. Similarly,
    FEMS regularly uses its resources to provide services to federal

    officials and dignitaries. For example, officials told us that a District
    emergency medical technician (EMT) unit is required to accompany the
    President whenever or wherever he travels within a 50- mile radius of the
    White House, as well as to the presidential retreat, Camp David, in
    Maryland. Further, FEMS is required to pre- inspect any District buildings

    where the President, Vice President, or a key dignitary is scheduled to
    appear.

    Special Events and District officials told us that special events and
    demonstrations also result

    Demonstrations in the District incurring costs funded with local dollars.
    Special events also

    affect police operations by diverting police officers from their normal
    duties as well as incurring costly overtime payments to police officers
    who are called upon during their scheduled time off. In addition, MPD
    staff said that it often does not have enough officers in its special
    events unit to provide all the necessary security for large events,
    meaning it must call up officers on leave or contract with officers from
    other jurisdictions. As the nation*s capital, the District is an
    attractive and preferred venue for

    demonstrations, protest rallies, and other special events as it provides a
    *high profile* venue and potential for media coverage for individuals and
    organizations seeking a mechanism for national publicity and potential

    access to legislators and other government officials. Thus, the District
    frequently hosts numerous planned and unplanned special events that often
    are not fully reimbursed by event organizers or the federal government.

    Although the District receives positive economic benefits generated by an
    influx of visiting demonstrators or protestors and dignitaries, such as
    revenue from sales taxes in restaurants, hotels, and stores, the District
    must also bear a financial burden in providing unbudgeted public safety
    services related to these events. A comparison of the District to our case
    study sites of San Francisco and Boston suggested that the magnitude of
    the District*s expenses related to protection, special events, and
    demonstrations is disproportionately higher than those of San Francisco
    and Boston police departments, which are both major international cities.
    For example, we collected data on overtime hours from several recurring

    special events in the District, Boston, and San Francisco and found that
    the District*s expenditures were roughly four to six times greater than
    those other cities. 15 According to MPD officials, expenditures for the
    demonstrations resulting

    from the International Monetary Fund (IMF)/ World Bank conferences
    represent the largest unreimbursed expenditures. A IMF/ World Bank
    conference* and resulting demonstrations* is scheduled to occur at those
    organizations* headquarters in the District twice in a fiscal year,
    usually during the spring and fall. District officials noted that the
    conference occurs in the District only because it is home to IMF and World
    Bank

    offices. MPD reported incurring over 116,800 in police officer overtime 15
    However, for all three cities this information is neither comprehensive
    nor is it audited, rather the information is self reported.

    hours at a cost of more than $5.7 million during the fall of 2002, and
    this figure did not include the costs of purchasing new equipment, such as
    security fencing, or wear and tear on existing equipment and automobiles.
    MPD officials told us they also had to contract for officers from other

    jurisdictions to provide added security. MPD officials told us they
    estimated that the total costs of IMF/ World Bank conferences could be as
    high as $14.8 million, but did not provide documentation for this figure.

    The national Independence Day celebration on the National Mall serves as a
    key example of a large scale, federally related special event that results
    in significant employee overtime expenses to the District. MPD officials
    told

    us that the U. S. Park Police (USPP)* which has jurisdiction over the
    National Mall, where the event is held* could not handle an event of this
    magnitude on its own. Because the National Mall is within the District*s
    boundaries, it must assist in security and assume any costs. On July 4,

    2002, MPD activated 1,500 officers to work overtime to supplement USPP,
    and MPD brought in officers from other jurisdictions as well. MPD paid
    officers from other jurisdictions for their services, but MPD officials
    told us

    the department received no reimbursement from the federal government. FEMS
    officials also provided extensive services during the Independence Day
    celebrations, including emergency medical technicians. 16 A final example
    of the federal presence*s impact on the District involves

    MPD*s newly constructed state- of- the- art command center that is
    intended to coordinate the law enforcement aspects of special events or
    emergencies, such as the IMF/ World Bank conference. MPD officials told us
    that their previous facilities were not sufficient to effectively manage
    such events, so they felt it necessary to construct a new one at a total
    cost of nearly $7 million* all out of the District*s capital budget. The
    federal government has not provided financial support for constructing or
    maintaining the command center, but federal law enforcement agencies (e.
    g., the U. S. Secret Service, Federal Bureau of Investigation, the U. S.
    Capitol Police, and the USPP) nonetheless rely on the facility to
    coordinate and manage law enforcement responses to emergencies or large-
    scale special events within District boundaries. However, in the past the
    federal

    16 District officials noted that other agencies incur expenses during
    special events or demonstrations. For example, before any large- scale
    event like Independence Day, the Department of Public Works (DPW) must
    board up abandoned houses and clean the streets afterwards.

    government has provided some funding to MPD for other capital improvements
    to MPD facilities. Effects of Increased Terrorist

    District public safety officials told us that in recent years the number
    of Threats special events and demonstrations, along with the potential for
    violence and security threats during them, have increased as have the
    security needs of federal officials and key dignitaries. Accordingly,
    District officials told us that unanticipated and unreimbursed
    expenditures have escalated. In addition, District officials told us that
    after the September 11, 2001, terrorist attacks* and the resulting
    national focus on enhanced homeland security preparedness and increased
    threats of additional terrorist

    attacks* their ongoing costs have escalated even more. Police and fire
    officials told us that since September 11 they have provided permanently
    higher levels of security and additional services to the federal
    government. The events of September 11 have also affected the security
    needs of special

    events and demonstrations, leading to increased costs to the District. For
    example, officials told us that, in 2002, expenses to ensure security were
    even higher for national Independence Day celebrations than in past years
    because of concerns about terrorist attacks on the National Mall. However,
    specific data are not available for this event and others.

    Better Tracking of Costs The District*s current cost tracking processes do
    not provide officials in

    Could Strengthen the MPD or FEMS, or the District CFO, with reliable
    financial information to District*s Case for Federal

    allow them to better estimate and budget for federally related
    Reimbursement

    expenditures, control overtime costs, or strengthen their cases for
    reimbursement from the federal government. In particular, the District is
    not collecting data and tracking all expenditures to determine its true
    total costs associated with its public safety programs and activities,
    putting the District at a disadvantage in capturing and recovering more
    costs related to protection, special events, or demonstrations. MPD and
    FEMS do some tracking of personnel costs associated with large

    events, such as the IMF/ World Bank conference as well as ongoing
    protection, but neither agency routinely tracks data regarding supplies,
    equipment, training, vehicle maintenance, and repair costs, and they are
    likely underestimating the full extent of expenditures related to federal
    protection, special events, and demonstrations. The absence of a rigorous
    cost tracking process in MPD and FEMS appears to have hindered their

    ability to determine the true costs of providing public safety and other
    services in support of the federal presence. For example, MPD data on
    special events related to overtime paid for federal holiday activities,
    such

    as Independence Day, are aggregated with all other holiday overtime. The
    quality, accuracy and completeness of these data are also lacking.

    Recently, MPD and FEMS have attempted to improve tracking of costs
    associated with special events in response to direction from the District
    CFO*s Budget Office. For example, MPD reported that it now tracks special
    event overtime hours and associated costs by the respective police unit,
    and the District CFO*s Budget Office recently established a separate
    account to track actual expenditures for these events.

    The Federal Government Although it is unlikely that the federal government
    fully compensates the Has Provided Some Amount

    District for all related expenses, the federal government has provided the
    of Financial Assistance

    District with special funding and other forms of assistance in recognition
    of the magnitude of public safety demands related to the federal presence.
    For example, the District recently received $16 million to compensate for
    any expenses related to the demonstrations resulting from the IMF/ World
    Bank conferences. However, District officials told us this level of
    funding would not be sufficient to cover many costs incurred by District
    agencies.

    Specifically, District officials claimed that each IMF/ World Bank event
    might result in total costs, including personnel and equipment, of as much
    as $15 million, and two events are scheduled to occur within a fiscal
    year* although the District was unable to provide documentation for this
    figure. The District received an additional $15 million in fiscal year
    2003 for emergency planning and security enhancements. Further, in April
    2003 as part of its urban security initiative, the Department of Homeland
    Security (DHS) awarded the District an additional $18 million; DHS also
    awarded funding to other major cities. Another key example was Congress
    providing over $200 million to the District as part of the Defense
    Appropriations Act for fiscal year 2002 to improve emergency preparedness
    and the capacity of the District to deal with any terrorist attacks. This
    funding, which went to a

    number of District agencies including MPD and FEMS, as well as nonDistrict
    entities, was intended to assist in purchasing equipment to respond to
    chemical or biological weapons, improve its public safety communications
    systems, improve emergency traffic management, and enhance training, among
    other things.

    The District Continues to Defer Infrastructure

    Chapt er 5

    Projects While Debt Pressures Remain When forced to balance the budget
    when a structural imbalance exists, governments often choose to hold down
    debt by deferring capital improvements. The District has thus deferred
    infrastructure maintenance and new capital projects because of constraints
    within its operating budget. Contributing to the District*s difficulties
    is its legacy of an aging and deteriorated infrastructure, particularly in
    the schools, and maintaining its 40 percent share of the funding for the
    area*s metropolitan transit system. The District*s Chief Financial Officer
    (CFO) is actively managing the District*s debt, refinancing some bonds to
    reduce interest and issuing bonds backed by funds from the tobacco
    settlement. Nevertheless, the District cannot take on additional debt
    without cutting an already low level of services or raising taxes that are
    already higher than other jurisdictions, and so it has chosen to put off
    needed repairs to streets and schools and postpone new construction that
    would improve the city*s infrastructure. In fact, our analysis shows that
    the District*s debt per capita ranks the highest when compared to combined
    state and local debt across the 50 states. The District operates with an
    aged and badly deteriorated infrastructure*

    antiquated school buildings, health facilities, and police stations; out-
    ofdate and inadequate computer systems; and aging sewer systems* for which
    the District has been unable to fund the needed improvements. The District
    is, however, attempting to address its backlog of infrastructure needs
    which, as several studies 1 have noted, was long ignored throughout the
    1970s, 1980s, and early 1990s. This legacy continues to exacerbate the
    current situation. The District*s level of spending for infrastructure
    repairs and improvements has increased steadily since 1995 and 1996, when
    virtually all major projects were deferred. The reality is, however, that
    the

    District continues to defer major infrastructure repair and development
    and capital acquisitions due to its budget and debt issues, while the
    legacy from its history of neglected infrastructure needs continues.

    Our approach to analyzing the District*s infrastructure projects differed
    from the approaches used to address the other objectives in this report.
    Because of the variety of ways infrastructure projects are owned, managed,
    and reported by other jurisdictions, comparative information on
    infrastructure across states and local jurisdictions was not readily

    available; therefore, we did not do a comparative analysis of the
    District*s 1 Carol O*Cleireacain and Alice Rivlin and the Commission on
    Budget and Financial Priorities of the District of Columbia, Financing the
    Nation*s Capital (Washington, D. C.: November 1990).

    infrastructure with states or other jurisdictions. We reviewed the data
    that the District has available in its annual budget, financial plans,
    comprehensive annual financial reports, and other documents.

    District Infrastructure The District is deferring significant amounts of
    capital projects by not

    Continues to Be funding or taking action on specific repairs and
    improvements to the

    District*s infrastructure. For the 6- year period fiscal years 2003
    through Deferred

    2008, the total number of projects that were not approved for funding was
    115. These 115 projects represent about 43 percent of the total identified
    capital cost needs for fiscal years 2003 through 2008. Many of these
    capital projects affect the safety and health of citizens. Deferred public
    safety projects include, for example, renovation of the third and sixth
    police district buildings and a disaster vehicle facility. District of
    Columbia Public Schools* (DCPS) fiscal year 2003 deferred projects
    included the replacement of electrical systems and heating and cooling
    plants and the upgrade of fire alarms, intercoms, and master clocks.
    Public health deferred projects include asbestos abatement and lighting
    system

    retrofitting in local facilities. Deferred transportation projects
    included rehabilitating bridges, paving alleys and sidewalks, and
    resurfacing streets. Deferred maintenance 2 project costs for three
    agencies total 79 percent of the total percentage of all deferred
    maintenance projects for fiscal year 2003* DCPS totals about 34 percent,
    Department of Transportation is about 30 percent, and the Metropolitan
    Police Department is about 15 percent. Table 7 lists the agencies and
    their deferred maintenance project costs for fiscal year 2003 and the 6-
    year period fiscal years 2003 through 2008. See appendix IV for a detailed
    list of agency projects and funding requests that the District has
    deferred.

    2 Deferred maintenance is the postponement of regular routine maintenance
    necessary to keep a fixed asset in operating condition for use or
    occupancy. Such maintenance would include, but not be limited to,
    recurring inspections, cleaning, painting, oiling, adjusting, replacing
    moving components, and major overhauls.

    Table 7: The District*s Capital Improvement Program: Deferred Maintenance
    Projects and Costs for Fiscal Year 2003 and Fiscal Years 2003 through 2008
    Deferred

    Deferred maintenance maintenance

    fiscal year 2003, capital fiscal years

    Agency improvement plan

    2003- 08

    District of Columbia Public Schools $126,011,441 $1, 134,102, 956
    Department of Transportation 112,750,000 645,500, 000 Metropolitan Police
    Department 54, 511,420 142,802, 983 Department of Mental Health 23,
    242,000 23,252, 150 Office of Property Management 17, 970,000 32,360, 000
    Department of Parks & Recreation 9,389,000 24,689, 000 Department of
    Public Works 8,235,400 32,805, 400 Department of Health 5,695,000 9,265,
    000 Department of Corrections 4,849,500 12,293, 000 Department of Human
    Services 3,175,000 8,705, 000 University of the District of Columbia
    1,946,000 19,438, 000 Fire and Emergency Medical Services Department
    1,916,103 5,304, 784

    Office of the Chief Financial Officer 1,235,000 9,000, 000 Office of the
    Chief Technology Officer 0 9,900, 000 Office of the Secretary 0 3,386, 000
    Total $370,925,864 $2, 112,804, 273

    Source: District of Columbia, Office of the Chief Financial Officer,
    Office of Budget and Planning. Note: Differences due to rounding.

    The District*s Capital Improvement Plan (CIP) funding for fiscal years
    2003 through 2008 is currently budgeted at $3. 3 billion for a total of
    229 projects. For fiscal year 2003, the amount for planned funding and
    expenditures is $881 million for projects such as school modernization,
    street repairs, roadway reconstruction, Metro bus replacement, equipment
    acquisition or

    leases, fire apparatus, and emergency communication systems. See table 8
    for an overview of the District*s planned funding and expenditures for
    fiscal year 2003 and the period fiscal year 2003 through fiscal year 2008.
    These amounts do not include $371 million in deferred maintenance project
    costs from table 7, as well as an additional $51 million in other deferred
    project costs that were not approved in fiscal year 2003 due to budget
    concerns. In addition, the District estimates that the total amount of
    deferred projects

    not included in the plan for fiscal years 2003 through 2008 total

    approximately $2.5 billion. In many instances, new project requests
    require more financing than the District could afford to repay in future
    years.

    Tabl e 8: Overview of the District*s Capital Improvement Program: Planned
    Funding and Expenditures for Fiscal Year 2003 through Fiscal Year 2008

    Overview Amount

    Total number of projects approved for the 6- year period 229 Number of
    ongoing projects 192 Number of new projects 37 Total fiscal year 2003
    planned funding $881,428, 000 Total fiscal year 2003 planned expenditures
    $881,428, 000 Total fiscal year 2003 to fiscal year 2008 planned funding
    $3, 332,700, 000 Total fiscal year 2003 to fiscal year 2008 planned
    expenditures $3, 332,700, 000 Fiscal year 2003 appropriated budget
    authority request a $639,069, 780 Fiscal year 2003 appropriated budget
    authority (actual) $671,020, 000 Sources: Government of the District of
    Columbia Fiscal Year 2003 Proposed Budget and Financial Plan, June 3,
    2002, and Pub. L. No. 108- 7, 117 Stat. 11, 121 (2003).

    a *Appropriated budget authority* is the spending threshold approved by
    Congress for the District*s Capital Improvement Program. Each year,
    Congress grants the District spending authority to implement a citywide
    capital program.

    As shown in table 9, a total of 115 capital projects with a cost of about
    $422 million were deferred in fiscal year 2003. District officials told us
    that, in an attempt to remain steadfast to spending affordability 3
    limits, they did not recommend these projects for funding even though some
    projects ranked high in priority in the CIP process. Of the $422 million
    in deferred projects for fiscal year 2003, $371 million was deferred
    maintenance, and the remaining $51 million represented other deferred
    projects. These projects will eventually need to be funded, but possibly
    at a higher cost later. Table 9 shows the approximate amount of funding
    that would be required if all requested infrastructure projects had been
    approved for fiscal year 2003 and fiscal years 2003 through 2008.

    3 Spending affordability is determined by the amount of debt service and
    paygo capital funds that can be reasonably afforded by the operating
    budget, given the District*s revenue levels, operating/ service needs, and
    capital infrastructure needs.

    Table 9: Total Costs of the District*s Approved and Unapproved Capital
    Projects for Fiscal Year 2003 and Fiscal Years 2003 through 2008

    Number of Fiscal year Fiscal years Capital projects projects 2003 costs
    2003- 08 costs

    Unapproved projects: Deferred maintenance projects 80 $ 371 million $ 2. 1
    billion Other deferred infrastructure projects 35 51 million 345 million

    Subtotal unapproved projects 115 422 million 2. 5 billion Approved
    projects 229 881 million 3. 3 billion

    Total all projects 344 $1.3 billion $ 5.8 billion

    Unapproved projects as a percentage of total identified needs 32.5% 43. 1%
    Source: District of Columbia, Office of the Chief Financial Officer,
    Office of Budget and Planning. Note: Differences due to rounding.

    The category *other deferred infrastructure and acquisition projects*
    included 35 projects, at a total cost of about $51 million for fiscal year
    2003 and about $345 million over the 6- year period fiscal years 2003
    though 2008. Similar to the financial situation of deferred maintenance,
    these projects

    were not approved because the projects required more financing than the
    District could afford to repay in future years. (See table 10.)

    Table 10: The District*s Capital Improvement Program: Other Deferred
    Infrastructure and Acquisition Costs for Fiscal Year 2003 and Fiscal Years
    2003 through 2008 Agency costs *

    Agency costs * 1- year request

    6- year request fiscal Agency fiscal year 2003

    year 2003- 08

    Deferred Acquisition Projects: Metropolitan Police Department $3, 800,000
    $11,030, 000 Fire and Emergency Medical Services Department 4,500,000
    4,500, 000

    Department of Human Services 4,060,000 8,560, 000 Emergency Management
    Agency 2,302,000 2,302, 000 Department of Public Works 1,315,000 1,315,
    000 Department of Mental Health 1,540,000 3,000, 000 D. C. Public Library
    275,000 2,275, 000

    (Continued From Previous Page)

    Agency costs * Agency costs *

    1- year request 6- year request fiscal

    Agency fiscal year 2003 year 2003- 08

    Subtotal deferred acquisition projects 17, 792,000 32,982, 000

    Other deferred infrastructure and acquisition projects:

    Office of the Chief Financial Officer 14, 250,000 32,350, 000 Commission
    on the Arts and Humanities 1,520,000 3,955, 000

    Office of the Chief Technology Officer 3,700,000 170,580, 000

    Fire and Emergency Medical Services Department 3,193,684 6,645, 256

    Department of Human Services 5,200,000 8,700, 000 Washington Metropolitan
    Area Transit Authority 0 80,800, 000

    Office of Contracts & Procurement 1,500,000 1,500, 000 Department of
    Mental Health 3,500,000 7,500, 000

    Subtotal other deferred projects $32,863,684 $312,030, 256 Total
    $50,655,684 $345,012, 256

    Sources: District of Columbia, Office of the Chief Financial Officer,
    Office of Budget and Planning, and the Government of the District of
    Columbia Fiscal Year 2003 Budget and Financial Plan, June 3, 2002.

    District Debt Pressures There has been little change in the District*s
    outstanding general obligation

    Remain debt, which totaled $2.67 billion as of September 30, 2002, except
    for a drop

    in 2001 attributable to the issuance of bonds backed by funds received
    from a multistate settlement with tobacco companies. Debt per capita has
    also remained fairly constant except for a dip as tobacco bonds were
    issued. In contrast, with expenditures holding steady, debt service costs
    as a percentage of expenditures have increased. As a percentage of local
    general fund revenues, debt service costs, which were 7.3 percent of
    revenue for fiscal year 2002, are expected to climb to approximately 10
    percent by 2006. The District*s annual debt service for the fiscal year
    ended September 30,

    2002, was $272 million, or approximately 7.3 percent of the local portion
    of general fund revenues, and the District*s projected debt service for
    fiscal year 2003 is about $304 million, which represents 8.3 percent of
    the local portion of projected general fund revenues. Although this level
    of debt service is well within the statutory limit of 17 percent of
    general fund

    revenues, the effect of issuing substantially more debt without a
    corresponding increase in general fund revenue or cuts in other areas of
    the budget would adversely affect the District*s debt ratios, its future
    ability

    to service its debt, and, consequently, its credit rating. The primary
    funding source for capital projects is through the issuance of tax- exempt
    bonds. These bonds are issued as general obligations of the District and
    are backed by the full faith and credit of the District. Several sources
    of funding for infrastructure and capital projects are presented in the
    capital budgets for fiscal years 2003 through 2008. However, only general
    obligation bonds and master equipment lease funding sources have an impact
    on the annual operating budget. These funding sources require debt service
    payments, which include principal and interest and are paid from general
    fund revenues. General obligation bonds represent about 52 percent of the
    funding sources for the District*s capital plan for fiscal years 2003
    through 2008. (See table 11.)

    Tabl e 11: Source of Capital Funds for Fiscal Years 2003 through 2008

    Dollars in thousands

    Fiscal years Percentage of total fiscal

    Total fiscal year 2003- 08

    Source 2003 2004 2005 2006 2007 2008 year 2003- 08 funding

    General obligation bonds $587,833 $432,541 $320, 372 $258,719 $118,860
    $349 $1,718, 674 52

    Federal grants 208,440 240,950 218, 859 194,737 146,984 136,615 $1,146,
    585 34 Rights of way fees 36, 940 37, 950 37, 350 37,500 36,133 36, 127
    $222, 000 7

    Highway trust fund 38, 330 43, 544 41, 576 36,639 25,606 24, 447 $210, 142
    6

    Equipment lease 9,885 3,200 0 0 0 0 $13, 085 .4

    Other 0 11, 102 11, 112 0 0 0 $22, 214 .6

    Total funding $881,428 $769,287 $629, 269 $527,595 $327,583 $197,538
    $3,332, 700 100

    Source: Government of the District of Columbia Fiscal Year 2003 Proposed
    Budget and Financial Plan, June 3, 2002.

    Faced with decreasing revenues and a significant backlog of unfunded
    capital projects, the District is taking steps to reduce debt service
    costs. In February 2003, the District*s CFO testified that in the first
    quarter of fiscal

    year 2003, the District issued general obligation bonds to finance capital
    projects through a complex transaction that produced historically low
    interest rates, and refinanced (refunded) outstanding general obligation
    bonds and certificates of participation, at lower interest rates.
    According to the Deputy CFO, Office of Finance and Treasury (OFT), the
    District took advantage of market conditions in October 2002 and used an
    interest- swap mechanism, resulting in an average interest rate of
    approximately 4 percent on a portion of the bonds. Another portion of the
    bonds was issued as variable- rate demand bonds, and the Deputy CFO
    reported that this allowed the District to benefit from extremely low
    interest rates (about 1. 25 percent currently). The Deputy CFO also stated
    that OFT has continued to focus on issuing its bonds based on actual
    capital spending needs (as opposed to its previous approach of planned
    spending levels), reducing the amount of unspent bond proceeds on hand,
    and thereby reducing debt service expenses. District officials testified
    that these actions produced substantial debt service savings totaling
    about $20 million.

    Total Outstanding General There was little change in the District*s total
    outstanding general obligation

    Obligation Debt debt for the period 1995 through 2000, as shown in figure
    5. The drop in outstanding debt in 2001 was attributable to the issuance
    of tobacco

    settlement bonds 4 with the funds used to defease approximately $482.5
    million of the District*s outstanding general obligation bonds. As of
    September 30, 2002, the District*s outstanding general obligation bonds
    totaled $2.67 billion. (See fig. 5.)

    Since fiscal year 1991, the District*s outstanding general obligation
    bonds have included balances related to the $331 million in deficit
    reduction bonds that were issued by the District in 1991 to eliminate the
    operating deficit in its general fund that year. As a result, the
    District*s debt included amounts that were used to cover operating
    expenditures. The District has continued paying debt service on those
    bonds in the intervening years. In fiscal year 2002, $38.9 million of the
    District*s $272.2 million in debt service

    expenditures was to cover principal and interest paymets on the deficit
    reduction bonds that had been issued in 1991. The District anticipates
    that

    4 The tobacco settlement bonds are asset- backed bonds secured by future
    payments from a Master Settlement Agreement with the major U. S. tobacco
    companies. The tobacco settlement bonds are not backed by the credit of
    the District, but by the future cash flows from the tobacco settlement
    agreement.

    it will make the final payment on these bonds in fiscal year 2003, in the
    amount of $39.3 million.

    Figure 5: The District*s Total Outstanding General Obligation Debt for
    Fiscal Years 1995 through 2002 4,000

    Total debt (dollars in thousands) 3,500

    323,172 282,100 303,719 114,122

    107,662 100,147 3,000

    95,296 79,070 2,500

    2,000

    3,157,003 2,965,756 3,084,763 3,091,403 3,098,582 3,109,728 2,582,017
    2,670,573 1,500 1,000

    500 0

    1995 1996 1997 1998 1999 2000 2001 2002 Years

    Water and sewer authority General obligation debt Sources: District of
    Columbia Fiscal Year 2002 Comprehensive Annual Financial Report (January
    27, 2003) and also the Government of the District of Columbia Fiscal Year
    2003 Budget and Financial Plan, June 3, 2002.

    Note: This information includes separately stated amounts for general
    obligation bonds that were issued by the District prior to the creation of
    the Water and Sewer Authority (WASA). Although the WASA debt is serviced
    with funds provided by WASA as required by law, the District is still
    directly liable for the debt.

    Debt Per Capita Debt per capita measures the level of debt burden placed
    on each citizen of a state or city. Since the citizens are ultimately
    responsible for financing the debt through payment of taxes, debt per
    capita is a good way to measure changes in a city*s debt load or compare a
    city*s debt load to that

    of another municipality. The District*s ratio of general obligation debt
    per capita was fairly constant from fiscal years 1995 through 1999. (See
    fig. 6.) The general obligation debt per capita further declined in 2001
    because of the reduction in outstanding general obligation debt through
    the issuance

    of tobacco settlement bonds.

    District officials offered the following explanations for the current
    situation of high debt per capita even while there has been a trend of
    significant deferred capital needs: (1) high funding for education and the

    Washington Metropolitan Area Transit Authority (WMATA), (2) funding
    projects with lifetimes shorter than the terms of the bonds, (3) funding
    enterprise fund activities, and (4) funding services that are now being
    provided by the federal government. The District*s largest authorization
    items over the past 18 years have been public schools (16.8 percent of
    total funding) and WMATA funding (12.0 percent of total funding). District
    officials also explained that the District had funded projects with
    lifetimes shorter than the term of the bonds issued, as well as provided
    funding for the original convention center, WASA, the Washington Aqueduct,
    and public assisted housing. These activities are now operating outside
    the

    District*s general fund. In addition, District officials identified past
    major events and circumstances that contributed to the present levels of
    longterm debt and deferred infrastructure projects, including the issuance
    of bonds in large amounts in fiscal years 1990, 1992, and 2002 for major
    authorization items such as public assisted housing and public education.

    Figure 6: The District*s Debt Per Capita for 1995 through 2002 7,000
    Dollars in thousands

    6,000 5,000 4,000 3,000 2,000 1,000

    0 1995 1996 1997 1998 1999 2000 2001 2002

    Source: District of Columbia Fiscal Year 2002 Comprehensive Financial
    Annual Report (January 27, 2003).

    Expenditures Required to From 1995 through 1998, the District*s debt
    service costs as a percentage of

    Service Outstanding Debt total general fund expenditures increased slowly,
    as shown in figure 7.

    Most of the increase was attributable to a steady increase in outstanding

    debt, while expenditures remained somewhat steady. However, from 1999
    through 2001, the District*s debt service as a percentage of expenditures
    decreased substantially, due primarily to the defeasement of approximately
    $482.5 million in general obligation bonds through the issuance of tobacco
    settlement bonds. This trend was a result of a unique, one- time,
    permanent reduction in the District*s outstanding general obligation debt.
    Figure 7: The District*s Percentage of Debt Service Costs to Total General
    Fund Expenditures for 1995 through 2002 (Actual)

    12 Percentage

    10 8 6 4 2 0

    1995 1996 1997 1998 1999 2000 2001 2002

    Source: District of Columbia Fiscal Year 2002 Comprehensive Financial
    Annual Report (January 27, 2003). Note: This ratio is commonly used by
    local governments to measure the portion of expenditures that are required
    to service outstanding debt.

    Revenue Available to The most recent calculations show that, for 2002, the
    District*s debt service

    Service Outstanding Debt costs amounted to about 7.3 percent of general
    fund revenues, as shown in

    figure 8. Based on the District*s projections, the percentage of debt
    service costs to the local portion of general fund revenues is expected to
    climb steadily to approximately 10 percent by 2006. The District*s
    projections

    assume that debt service costs will increase at a higher rate than local
    revenues.

    Like debt costs as a percentage of expenditures, the District*s debt
    service expenditures as a percentage of revenue remained level through
    1999, then decreased substantially in 2000 and 2001 (see figure 8). The
    decrease was

    due to the issuance of the tobacco settlement bonds mentioned in the debt

    service costs to general fund expenditures discussion, as well as an
    increase in general fund revenues over that same period.

    Figure 8: The District*s Percentage of Debt Service Expenditures to
    General Fund Revenues for Fiscal Years 1995 through 2002 (Actual) and 2003
    through 2006 (Projected) 14

    Percentage 12 10

    8 6 4 2 0

    1995 1996 1997 1998 1999 2000 2001 2002 ** 2003 ** 2004 ** 2005 ** 2006

    Source: District of Columbia Fiscal Year 2002 Comprehensive Financial
    Annual Report (January 27, 2003). Note: Percentage of debt service costs
    to revenues is a common measure used by local governments to measure a
    municipality's capacity to issue debt. a These numbers are estimates.

    Credit Ratings During fiscal year 1995, the District*s general obligation
    debt was downgraded by all three rating agencies to *below- investment-
    grade* or *junk bond* levels. Since 1998, with the District*s financial
    recovery, each

    rating agency has issued a series of upgrades to the District*s bond
    rating. The upgrades that occurred in 1999 raised the District*s ratings
    back to *investment grade* levels. The upgrades in the bond ratings by the
    rating agencies made the District*s bonds more marketable, resulting in a
    lower cost of capital to the District. The District continues to have the
    goal of having its credit rating raised to the *A* level. In October 2002,
    the bond rating agency, Fitch IBCA, Inc., reviewed its rating for the
    District and

    reported that although the BBB+ long- term general obligation bond rating
    reflects the sound financial cushion that the District has built up over
    the last several years and the District*s demonstrated ability to respond
    quickly and effectively to funding shortfalls and unexpected expenditure
    needs while still strengthening reserves, its debt levels remain high and
    capital needs are substantial. 5 While the District has seen significant
    improvement in its credit ratings over the last couple of years, its Baa1
    from Moody*s

    rating places the District in the lowest tier among 35 U. S. cities. (See
    fig. 9.) 5 Fitch Press Release, *Fitch Rates District of Columbia*s $375mm
    GO*s *BBB+ *,* Oct. 4, 2002.

    Figure 9: Bond Ratings of 35 Largest U. S. Cities (Based on Revenue) City
    Revenue

    Moody*s rating

    Dallas 1,487,356,000 Aaa Bonds rated at this level are judged to be of the
    best quality.

    Seattle 1,276,337,000 Aaa They carry the smallest degree of investment
    risk.

    Indianapolis 1,121,129,000 Aaa Interest payments are protected by large or
    stable margins and Columbus 797,579,000 Aaa

    principal is secure. San Diego 1,577,934,000 Aa1

    Denver 1,463,543,000 Aa1 Phoenix 1,372,605,000 Aa1 San Jose 921,473,000
    Aa1 Minneapolis 918,720,000 Aa1 Virginia Beach 801,885,000 Aa1 Los Angeles
    7,631,064,000 Aa2 Boston 2,126,398,000 Aa2 Memphis 2,093,600,000 Aa2

    Bonds rated at this level are judged to be of high quality by all
    Nashville standards.

    1,816,080,000 Aa2 Together with the Aaa group, they constitute what are
    known as San Antonio 1,679,745,000 Aa2

    high- grade bonds. Jacksonville 1,648,966,000 Aa2

    They are rated lower than the best bonds because margins of Austin
    1,366,541,000 Aa2

    protection are not as large. Long Beach 814,618,000 Aa2 Milwaukee
    810,889,000 Aa2 San Francisco 3,765,464,000 Aa3 Houston 1,971,006,000 Aa3
    Honolulu 1,113,601,000 Aa3 Atlanta 876,932,000 Aa3 Anchorage 870,628,000
    Aa3 Richmond 818,935,000 Aa3 Kansas City, Mo. 736,297,000 Aa3 Chicago
    4,731,877,000 A1

    Bonds rated at this level are judged to be of upper- medium grade.
    Baltimore 2,186,376,000 A1

    They possess many favorable investment attributes. Cleveland 813,678,000
    A1

    Security of principal and interest are considered adequate, but New York
    City 47,303,166,000 A2

    susceptible to impairment in the future. Washington, D. C. 5,085,551,000
    Baa1

    Bonds rated at this level are considered medium- grade obligations.
    Philadelphia 4,169,097,000 Baa1

    They are neither highly protected nor poorly secured. Detroit
    2,192,898,000 Baa1

    Such bonds lack outstanding investment characeristics and in fact New
    Orleans 768,944,000 Baa1

    have speculative characteristics. Buffalo 759,268,000 Baa2

    Numerical modifiers are applied in each generic rating classification. 1=
    The obligation ranks in the higher end of its rating category. 2= The
    obligation ranks in the midrange of its rating category. 3= The obligation
    ranks in the lower end of its rating category. Source: Governing. com, The
    Government Performance Project 2000/ Revenue Chart.

    Selected District Debt Our analysis shows that the District*s debt per
    capita ranks the highest

    Statistics Compared to when compared to combined state and local debt
    across the 50 states. The District funds many infrastructure projects that
    in other U. S. cities would

    Other Jurisdictions be financed either in part or in whole by state
    governments. For this

    reason, we have analyzed U. S. Census Bureau (Census) data that combine
    debt issued by the state government and all local governments within that
    state. The resulting debt per capita figure shows a complete picture of
    the debt burden for a state and all cities and municipalities within the
    state. From the Census data, we analyzed the portion of long- term debt 6
    that is backed by the full faith and credit of the government entity
    issuing the debt. 7 This portion of long- term debt is supported solely by
    the taxing authority of the entity issuing the debt.

    Based on the Census data 8 from all 50 states and the District of
    Columbia, the District shows the highest debt per capita level at $6, 501.
    It is important to note that the Census data figures for the District*s
    *full- faith and credit debt outstanding* as of April 2000 is
    significantly higher than the District*s audited balance of general
    obligation debt as of September 30, 2000. 9 Therefore, we also included an
    *adjusted* level of debt to reflect the

    lower, audited general obligation debt level. Even using the audited lower
    level of debt, the District still ranked highest in debt per capita when
    compared to the 50 states. Based on the Census data, debt per capita in
    the other states ranges from a low of $173 (Oklahoma) to the second
    highest debt per capita of $4,348 (for both Hawaii and Connecticut). The
    median debt per capita is $1,462. The average debt per capita is $1, 812.
    (See table

    12.) 6 Long- term debt is typically used to finance capital projects. 7
    Full- faith and credit debt is long- term debt for which the credit of the
    government concerned, implying the power of taxation, is unconditionally
    pledged. In contrast, the nonguaranteed portion of a jurisdiction*s long-
    term debt is not backed by the tax base of the government associated with
    the debt, but is backed by a specific revenue stream or other source; for
    example, earnings of revenue- producing activities, such as municipal
    water and sewer authorities.

    8 Census data are as of April 2000, the most recent Census data available.
    9 The difference is likely due to inclusion of the Washington Convention
    Center bonds. The convention center bonds are backed by a dedicated tax
    revenue stream but are not general obligations of the District.

    We also compared the District*s outstanding debt burden to that of the 50
    state fiscal systems in terms of debt as a percentage of own- source
    revenue capacity for fiscal year 2000, using our own range of estimates of
    that capacity. Our results show that the District*s debt is larger
    relative to the resources it has available to repay it than that of any
    state fiscal system. (See the last two columns of table 12.) We estimated
    that the District*s outstanding debt was equal to between 114 percent and
    129 percent of the

    District*s own- source revenue capacity in fiscal year 2000. 10 Both of
    these percentages were higher than those of any state fiscal system and
    well above the state median of 38 percent.

    Tabl e 12: U. S. Census Bureau Data on Debt Per Capita by State and as a
    Percentage of Own- Source Revenue Capacity Debt as a percentage of own-
    source

    revenue capacity Full faith and

    credit debt outstanding

    Population Debt per State

    ($ 000) (000) capita Low RTS TTR

    District of Columbia $3,718, 838 572 $6, 501 129 114 DC (adjusted) a
    3,209, 876 572 5,611 111 99 Hawaii 5,270, 348 1,212 4,348 104 107
    Connecticut 14,808, 632 3,406 4,348 76 73 Nevada 7,922, 678 1,998 3,965 83
    86 Massachusetts 22,766, 965 6,349 3,586 66 65 Alaska 2,145, 416 627 3,422
    59 69 New York 63,242, 280 18, 976 3,333 71 66 Washington 17,921, 583
    5,894 3,041 66 68 Minnesota 14,075, 859 4,919 2,862 62 64 Illinois 33,822,
    469 12, 419 2,723 60 60 Wisconsin 13,968, 405 5,364 2,604 63 67
    Pennsylvania 28,329, 230 12, 281 2,307 57 58 Oregon 7,542, 569 3,421 2,205
    53 53

    10 The 114 percent is based on our highest estimate of the District*s own-
    source revenue capacity (using the total taxable resources, or TTR,
    approach); the 129 percent is based on our most conservative estimate of
    that capacity (using the representative tax system, or RTS, approach).

    (Continued From Previous Page)

    Debt as a percentage of own- source revenue capacity Full faith and

    credit debt outstanding

    Population Debt per State

    ($ 000) (000) capita Low RTS TTR

    Maryland 11,492, 877 5,296 2,170 50 46 Texas 42,816, 539 20, 852 2,053 53
    51 New Jersey 16,803, 492 8,414 1,997 40 36 Colorado 8,080, 104 4,301
    1,879 38 41 Rhode Island 1,867, 221 1,048 1,782 45 40 Delaware 1,363, 973
    784 1,740 36 32 South Carolina 6,916, 351 4,012 1,724 48 51 Arizona 8,753,
    094 5,131 1,706 45 47 Michigan 16,583, 026 9,938 1,669 40 43 New Hampshire
    1,995, 189 1,236 1,614 34 31 Mississippi 4,520, 007 2,845 1,589 52 56
    Vermont 964, 792 609 1,584 38 42 Kansas 3,928, 589 2,688 1,462 37 37
    Tennessee 8,225, 817 5,689 1,446 38 40 Virginia 10,183, 759 7,079 1,439 33
    32 Maine 1,743, 816 1,275 1,368 36 39 Alabama 6,072, 224 4,447 1,365 39 43
    Utah 3,002, 986 2,233 1,345 37 38 Ohio 15,229, 929 11, 353 1,341 33 35
    Louisiana 5,936, 496 4,469 1,328 38 37 California 44,666, 627 33, 872
    1,319 29 28 Georgia 10,273, 721 8,186 1,255 31 30 North Carolina 9,701,
    264 8,049 1,205 31 30 New Mexico 2,120, 068 1,819 1,166 33 34 Nebraska
    1,711, 133 1,711 1,000 24 25 Iowa 2,919, 449 2,926 998 25 27 Missouri
    5,369, 711 5,595 960 24 25 Florida 13,382, 448 15, 982 837 20 22 North
    Dakota 511, 520 642 797 20 23 South Dakota 587, 876 755 779 18 21 Arkansas
    1,991, 973 2,673 745 23 25 Montana 585, 007 902 649 17 21 Idaho 788, 739
    1,294 610 17 17

    (Continued From Previous Page)

    Debt as a percentage of own- source revenue capacity Full faith and

    credit debt outstanding

    Population Debt per State

    ($ 000) (000) capita Low RTS TTR

    Wyoming 297, 923 494 603 12 12 Kentucky 2,286, 543 4,042 566 16 16 Indiana
    3,271, 379 6,080 538 13 14 West Virginia 710, 606 1,808 393 12 13 Oklahoma
    1,963, 110 11, 353 173 17 18 Sources: U. S. Census Bureau and the District
    of Columbia Fiscal Year 2002 Comprehensive Annual Financial Report
    (January 27, 2003).

    a Based on the District*s audited balance general obligation debt.

    Appendi xes Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Appendi x I

    Services The purpose of this appendix is to describe the methodology of
    previous studies that have employed the representative expenditure system
    to estimate the cost of providing an average (representative) level of
    public services and then describe modifications we have made to adapt it
    to reflect both the public service responsibilities and the relatively
    small

    urban environment faced by District. Dr. Robert W. Rafuse, Jr originally
    developed the representative expenditures system (RES) for the U. S.
    Advisory Commission on Intergovernmental Relations (ACIR). 1 The

    method developed was specifically designed to take into account those
    location- specific cost circumstances that are considered to be beyond the
    direct control of state and local government officials. The resulting
    estimate of a structural imbalance is, therefore, constructed so that it
    does

    not reflect conditions that are the result of discretionary policy choices
    made by local officials. 2 Our estimate of representative expenditures, in
    conjunction with our estimates of revenue- raising capacity, described in

    appendix II, provides the basis for determining the presence or absence of
    a structural imbalance. Defining a

    The RES is designed to compare the cost of providing an average level of
    Representative Basket

    public services by state fiscal systems (a state government and all of its
    local governments). In the following sections of this appendix we describe
    of Public Services: The

    the approach developed by ACIR and the modifications we made to make it
    Rafuse/ ACIR Method more suitable for evaluating the presence of a
    structural imbalance for a small and highly urban jurisdiction like the
    District.

    It would not be appropriate to compare the District to any single type of
    government, because fiscal responsibilities similar to those of the
    District are performed across the nation in varying proportions by state,
    county, municipal, school district, and special district governments. For
    this

    1 Robert W. Rafuse, Jr., Representative Expenditures: Addressing the
    Neglected Dimension of Fiscal Capacity (Washington, D. C.: ACIR, December
    1990). 2 While cleanly separating policy- related variables from cost
    factors beyond the control of government officials would be ideal, this is
    not possible. Dr. Rafuse, for example, acknowledges that private school
    enrollments are a policy related cost factor, and he uses vehicle miles
    traveled and lane miles of roads as an important determinant of highway
    costs, though both reflect a legacy of past policy choices. The best that
    can be hoped for is a degree of policy neutrality in which the effects of
    policy choices are indirect and gradual. In the long run, virtually all
    cost factors are influenced by policy choices; even resident

    population is the result of policies that influence migration and housing
    construction and rehabilitation.

    reason, the RES compares the District to all governments that serve
    geographic areas. That is, our analysis compares the public service
    workloads and costs of the District with those of state areas where public
    services are typically provided by state, county, municipal, educational
    districts, and special districts collectively.

    Ideally, it would be appropriate to compare the District to other
    geographic entities with similar economic and demographic profiles.
    However, this approach was not possible because comparable data for all
    governmental entities serving geographic locations similar to the District
    were not available. For example, expenditures for services provided
    directly by state governments are not typically reported for substate
    geographic

    entities. In addition, the structure of local government is diverse and
    their boundaries often do not coincide, so that, from a practical
    standpoint, it would be very difficult to consistently organize
    information on a comparable basket of public services for geographic
    entities below the level of state boundaries. For example, school district
    boundaries often do not correspond to either municipal or county
    government boundaries. Therefore, the services of a school district whose
    boundaries partly overlap

    that of two or more counties would have to be somehow apportioned among
    them. Imputing the value of these services would be problematic at best.
    The RES approach uses state boundaries to aggregate spending on public
    services provided by the state government and every local

    government within the state. 3 Based on this geographic unit, we defined a
    representative level of public service provided by the average state
    fiscal system. 4 The Representative

    The representative basket of public services developed by ACIR is the sum
    Expenditures System

    of a representative expenditure level for seven categories of public
    Defined

    spending: 1. Elementary and secondary education 2. Higher education 3 We
    made small modifications to this original RES state area benchmark of
    comparison in order to reflect the particular circumstances of the
    District. These are described in detail subsequently in the subsection on
    our modification of the RES expenditure weights. 4 Since we refer to all
    the states and the District here, the public expenditures of the average

    state fiscal system are equal to the national average.

    3. Public welfare 4. Health and hospitals 5. Highways 6. Police and
    corrections 7. All other For a given category of spending, the national
    average per capita spending is used as a benchmark for the spending that
    would be needed to fund an average level of services. A fiscal system*s
    representative expenditures per capita are estimated by multiplying per
    capita expenditures in each expenditure function by two adjustment factors
    to account for differences in the cost of providing an average level of
    services: (1) an index of each jurisdiction*s relative workload
    appropriate to the expenditure function (e. g., school age children in the
    case of education and miles of road in the case of highways) and (2) the
    costs of inputs (such as personnel, buildings, and materials) used to
    provide public services. Once the national average

    per capita expenditure for each expenditure function is adjusted for
    differences in workloads and costs, the representative expenditure amounts
    are aggregated into an overall average per capita amount that represents
    the funding necessary to fund an average level of public

    services. This is accomplished by weighting the per capita representative
    expenditures index of each expenditure function by its share of total
    spending for all functions. Table 13 shows fiscal year 1987 expenditures
    shares for the seven expenditure functions included in the ACIR analysis.

    Table 13: Fiscal Year 1987 Weights Associated with the National Average
    Basket of Public Services

    Expenditure category Weight (percentage)

    Elementary and secondary education 24.0 Higher education 9.2 Public
    welfare 12.3 Health and hospitals 8.7 Highways 8.0 Police and corrections
    6.3 All other 31.4 Source: GAO. Note: GAO analysis based on information in
    Representative Expenditures: Addressing the Neglected Dimension of Fiscal
    Capacity.

    While the RES yields estimates of the expenditures necessary to fund an
    average level of services, this should not be interpreted to mean that
    states that actually spend that amount are providing an average service
    level. If services are delivered with an above average level of
    efficiency, the actual level of services may be above average. And
    similarly, if they are delivered with below average efficiency, the actual
    level of services may be below average.

    Workload Indicators and Workload indicators generally represent the number
    of potential

    Weights consumers of the service, but other indicators of the volume of
    activity are

    used as well. For example, school age children represent the number of
    consumers of educational services and low- income people represent the
    number of consumers of public welfare. However, the scale of activity for
    highway maintenance and repair is indicated by the number of miles driven
    by vehicles using the streets and highways, and also by the miles of roads
    to be maintained. The various workload indicators and the associated
    weights employed under the ACIR methodology are summarized in table 14.

    Table 14: RES Workload Indicators and Weights by Expenditure Category
    Workload Expenditure category Workload indicators factor weights

    Elementary and secondary 1. Children of elementary school age

    1. 0.60 education (5- 13), net of private school enrollment

    2. Children of secondary school age 2. 1.00 (14- 17), net of private
    school enrollment 3. Children under age 18 living in

    3. 0.25 poverty

    Higher education 1. Population 14- 17 1. 1.32% 2. Population 18- 24

    2. 22.44% 3. Population 25- 34

    3. 4.16% 4. Population 35 and over

    4. 0.83% Public welfare 1. Poverty population 1. 100% Health and hospitals
    Percentage shares of

    1. Total population 1. 1/ 3 2. Population below 150% of the

    2. 1/ 3 poverty line 3. Population 16- 64

    3. 1/ 3 Highways Percentage shares of

    1. Vehicle miles traveled 1. 82.5% 2. Lane miles of streets and roads 2.
    17.5%

    Police and corrections Percentage shares of 1. Total population 1. 1/ 3 2.
    Number of murders

    2. 1/ 3 3. Population 18- 24

    3. 1/ 3 All other 1. Total population 1. 100% Source: GAO. Note: GAO
    analysis based on information in Representative Expenditures: Addressing
    the Neglected

    Dimension of Fiscal Capacity, p. 9.

    Unit Cost Adjustments In addition to workload indicators reflecting
    circumstances that typically would require greater expenditure to achieve
    a given level of public service

    outputs, the cost of providing a representative level of expenditures
    depends on the unit cost of services provided. The ACIR RES methodology
    abstracts from unit cost differences other than those related to the cost
    of labor and other inputs used in the provision of services. The only
    specific factor input whose costs are taken into account is labor costs;
    the ACIR methodology assumes nonlabor costs do not systematically differ
    across states.

    The ACIR methodology standardizes labor costs by controlling for
    differences in age, gender, and educational attainment across states.
    Differences in educational attainment are controlled for by using the
    national average percentage distribution of educational attainment to
    calculate an average level of earnings for males ages 45 through 54.
    Average earnings levels are divided by the national average to form an

    index of labor costs across states. A cost index for each category of
    spending is calculated by weighting the indexes of labor costs on the
    basis of the proportion of expenditures in each category of spending
    accounted for by employee compensation.

    Limitations to the Dr. Rafuse discussed a number of limitations to the
    interpretation and

    Interpretation of the understanding of the results of the RES model. This
    section explains that

    these limitations also apply to our modified version of the RES designed
    for Representative

    use in measuring the District*s costs of providing an average level of
    Expenditure Model

    expenditures per capita (adjusted for workload and input cost
    differences.) Rafuse says, *No implications should be drawn that the
    representative outlays are in any sense correct or *needed* in any
    absolute sense. The estimates merely show how much it would cost each
    state to provide the national- average level of each service.* 5 For the
    RES for every function and for the composite RES measure including all
    functions, the RES is a relative measure that employs cost, workload, and
    expenditure measures that, in effect, are indexed to the national average.
    For example, by using national averages as a benchmark, a fiscal system*s
    actual spending may remain unchanged yet its spending relative to that
    average will have fallen.

    Since the national average spending for each function reflects policy and
    political preferences across the nation, it is apparently a more *typical*
    spending level, though there is no reason to suppose that it is more
    sensible or appropriate than the spending level that any individual state
    or the District chooses. Further, state and local policymakers may decide,
    in the process of making

    budget choices for their area, that the policy goals associated with one
    function are best advanced by spending in other functional areas. For
    example, spending more for corrections (probation supervision, juvenile
    detention, etc.) and spending for extracurricular activities and after
    school 5 Rafuse, v.

    programs could be deemed more effective budget choices for purposes of
    reducing crime rates than increased spending for police. Another example
    is transit subsidies, which policymakers may view as a substitute for some
    highway spending.

    Rafuse says that the RES assumes uniform efficiency and thus could not be
    adapted to make conclusions with respect to efficiency and management
    performance. It assumes, he says, that *a given level of spending per
    capita (adjusted for differences in compensation costs) buys the same
    level of service in each state. Hence, no inferences about operating
    efficiency can be drawn from the relationship between actual spending for
    a function and the representative expenditures.* Further, he says,
    *Although we know that public services are not of equal quality per dollar
    spent everywhere in the nation, it is, regrettably, impossible to take
    this into account because credible measures of performance are not
    available.* 6 Finally, for some functions, there are multiple policy
    objectives that the RES would model more accurately if it used a wider
    array of workload measures with appropriate weightings for each. To some
    degree, the workload indicators employed in the RES model are perhaps
    correlated with omitted indicators. For example, the workload factor for
    children in poverty may be correlated with some of the additional costs
    imposed on schools for providing an

    education to those of limited English speaking proficiency. The error
    created by the omission of key workloads in calculating the RES estimates
    is unknown.

    Modifications to the The primary intent of the original RES analysis was
    to compare the fiscal

    Rafuse Methodology circumstances of states without consideration of the
    fact that the District

    has boundaries that are geographically much smaller, demographic
    characteristics that are more urban, and an economy that is far more open
    to cross- border flows than is true of states. In modifying the RES, we
    sought to better reflect these considerations.

    Our modifications to the RES was focused on three main areas: 6 Rafuse, v.

     Workload Indicators: In circumstances where alternative workloads could
    better reflect community and population characteristics that, other things
    being equal, are associated with increased cost for providing a particular
    service outcome, we modified the indicators used in earlier analyses.
    Where this is not possible, we generally used the ACIR methodology as one
    that is conservative and unlikely to overestimate the District*s
    representative expenditure levels. 7  Cost of Inputs Used to Provide
    Public Services: We used Bureau of

    Labor Statistics data to account for differences in labor costs and added
    an indicator of the cost of office space and related building assets used
    to deliver public services.

     Composition of Benchmark Basket of Public Services: In addition to using
    the basket of services typically provided by state fiscal systems, we also
    developed a basket of services typical of that provided by governments
    serving more densely populated urban areas.

    As explained in detail below, with each of these broad types of RES
    modifications we have departed from the ACIR methodology where the
    improvement appears to us to be highly likely. Where there has been a
    choice required between alternative modifications, we have generally
    chosen the more conservative one. That is, we have chosen modifications
    that are likely to underestimate the District*s RES measure and very
    unlikely to overestimate it. Conservative estimates of the District*s
    representative expenditure, in turn, will tend to understate the
    District*s structural imbalance.

    Before discussing modifications by detailed expenditure category, it is
    worth observing that our modified RES workloads and input costs are not
    intended nor designed to capture the effects of a legacy of past problems
    (inefficiencies, poor policy decisions, deferred capital maintenance,
    etc.) that can, at present, be a serious impediment to effective service
    delivery, and the effects of which may take years to reverse. According to
    experts,

    the District*s capital assets reflect many years of deferred maintenance,
    yet 7 Dr. Robert Tannenwald calculated the District*s 1997 RES to equal
    121 essentially using the ACIR methodology. Robert Tannenwald, *Interstate
    Fiscal Disparity in 1997,* New England Economic Review, Federal Reserve
    Bank of Boston (Boston, Mass.: Third Quarter, 2002), 24. Since the
    District*s actual expenditures per capita are typically well above
    average, our

    preference for the use of the Rafuse method is a conservative approach
    toward estimating the District*s RES expenditure levels.

    RES makes the implicit assumption that the District*s plant and equipment
    are of average quality and quantity per capita. To the degree that the
    District suffers from a legacy of undermaintained capital and inefficient
    operations that may take years to return to an average level, this is a
    unique circumstance that RES does not capture and it would thus
    underestimate the District*s RES level compared to one that reflects the
    actual quantity and quality of capital assets.

    Modifications to the In contrast to the 7 expenditure categories used in
    the ACIR report, we

    Workload Indicators used a more detailed set of expenditure functions for
    our benchmark

    baskets of services using data from the U. S. Census Bureau (Census). 8
    Specifically, we have (1) separated public welfare into medical vendor
    payments (largely Medicaid expenditures) and other public welfare; (2)
    separated expenditures for police and corrections into separate functions;
    and (3) disaggregated the other expenditure category into separate
    expenditure categories for fire, mass transit subsidies, sewerage, social
    insurance administration, libraries, parking facilities, solid waste
    management, housing and community development, parks and recreation,
    protective inspections and regulation, government administration, interest
    on debt, and general expenditures not elsewhere classified. Representative
    expenditures were calculated for each of the above expenditure functions
    and aggregated into the 12 expenditure categories shown in table 5 of
    chapter 2.

    As described above, population and the number of people in poverty are
    used as workload indicators for several expenditure functions. Therefore,
    we will discuss our modifications to these factors and then point out
    where these changes occur as we discuss the workload factors for specific
    expenditure functions below. 8 Detailed data from the state by type of
    government * public use format file downloaded on

    11/ 14/ 2002 from www. census. gov/ govs/ www/ estimate. html.

     Adjustment to population for commuting. Using data on the journey to
    work from the 2000 Decennial Census, we summed for each state and the
    District the number of workers who leave and come into another state to
    work. Taking the difference between the inflow of workers and the outflow,
    and adjusting that difference to reflect hours worked, provides us with a
    *daytime* population adjustment for each state and the District. We do not
    include any adjustment for visitors and

    commuting students because of the lack of data, although there is evidence
    to suggest that the District has large numbers of visitors as well.
    Therefore, our adjustment for commuters likely does not fully

    capture the District*s daytime population. 9 9 The District has over three
    times the number of guestrooms per capita than the national average, and
    it ranks fourth among the states after Nevada, Hawaii, and Wyoming
    according to the 1997 Economic Census of Traveler Accommodations. However,
    we lack data on room occupancy.

     Adjustment of Poverty Population for Cost of Living. The poverty data
    used in ACIR*s RES are based on an income threshold that does not account
    for geographic variation in cost of living. We apply a cost- ofliving
    adjustment using a method suggested by the National Research Council (NRC)
    of the National Academy of Sciences: NRC*s suggested index is the sum of
    44 percent of an index of housing cost calculated using the Department of
    Housing and Urban Development*s (HUD) fair market rent data 10 and 56
    percent of an index to represent other factors that affect the cost- of-
    living that are, of necessity, assumed to not vary by location. 11
    Differences in housing costs are identified as the single most important
    source of cost- of- living differences and the NRC says that these cost
    differences represent about 44 percent of a low- income household*s
    budget. For the remaining sources of cost- of- living

    differences, NRC concluded that no reliable sources of data exist. Using
    an index of 1.0 for the nonhousing costs component of the index implies
    that such costs do not vary across geographic areas, an assumption that
    also serves to underestimate the District*s representative expenditures.
    12 Therefore, NRC suggests calculating cost of living differences using
    the formula: cost of living index = 0.56 + 0.44 x (rent index).

    10 The data we used are from fair market rents data collected by HUD for
    the Section 8 Housing Assistance Program. These data are available by
    metropolitan area and nonmetropolitan areas of states. The data were
    aggregated to the state level by weighting each metropolitan area and the
    balance of the state by their respective shares of total population.

    11 Panel on Poverty and Family Assistance [et al], Measuring Poverty: A
    New Approach (Washington, D. C.: National Academy of Sciences, 1995), 197-
    200. 12 The NRC report acknowledges, on p. 199, the assumption that 56
    percent does not vary by region. However, the report views the method *as
    a modest step in the right direction. The procedure only takes account of
    housing cost differences and, even for those differences,

    will assign index values to people in some areas that are considerably in
    error.*

    Elementary and Secondary The ACIR RES applies a weight of 0.25 to the
    workload factor of children in

    Education poverty to reflect the weighting many states apply in their
    school- aid

    formulas, based on fiscal year 1987 information. 13 Based on our 1998
    study, 14 the median weight states accorded low- income children was 0.6.
    While some research suggests that still higher weights would be
    appropriate, 15 we thought that the median was a conservative choice and
    increased the weight accorded poverty to 0. 60. The workload measure for
    the number of school- age children is measured net of children enrolled in
    private schools. Because the District pays for the cost of a private
    school for many special

    education students, this adjustment is also a source of underestimation of
    the District*s education workload. Higher Education The workload
    methodology for the higher education function is unchanged

    from the original ACIR method (though the workload data have been updated
    to rely on the 2000 Decennial Census.)

    Medical Vendor Payments This category includes Medicaid. 16 Since this
    function largely benefits lowincome households, and the cost of serving
    these populations varies substantially by age, we use the experience of
    the Medicaid program to develop age weights for the cost- of- living-
    adjusted poverty population.

    These age weights take into account both differences in the average cost
    per Medicaid recipient by age (children (0- 18), adults (18- 64), and
    elderly (65 and over)) and the different rates of participation in the
    Medicaid program. This procedure assumes that medical vendor payments of
    state and local governments generally reflect the experience of the
    Medicaid program. 13 Rafuse, p. 10, footnote 9.

    14 U. S. General Accounting Office, School Finance: State and Federal
    Efforts to Target Poor Students, GAO/ HEHS- 98- 36 (Washington, D. C.:
    January 1998), 51. 15 Andrew Reschovsky and Jennifer Imazeki, *The
    Development of School Finance Formulas to Guarantee the Provision of
    Adequate Education to Low- Income Students,* in

    Developments in School Finance 1997 (Washington, D. C.: U. S. Department
    of Education, July 1997), 123- 144. 16 This functional category includes
    payments to nongovernmental medical providers. Medicaid payments to
    hospitals, nursing homes, and other institutions owned by state and local
    governments are included in the public welfare and hospitals categories,
    but cannot be separated out.

    Public Welfare For other public welfare expenditures, we use the estimate
    of persons in poverty with the poverty threshold adjusted for cost of
    living using NRC*s suggested method. Health and Hospitals The ACIR method
    used the sum of equally weighted percentage

    distributions of (1) population age 16- 64 with work disabilities, (2)
    population below 150 percent of the poverty threshold, and (3) total
    population. In the case of this expenditure category, we judged that most
    services would be delivered to residents so that the *daytime population*
    adjustment is not used. The poverty threshold is adjusted for cost of
    living using NRC*s suggested method.

    In the roughly 15 years since the ACIR research on workloads, there has
    been a significant amount of work on collecting, analyzing, and improving
    the data providing indicators of public health. Limitations of time and
    resources did not allow us to incorporate information from this literature

    into our RES modifications. However, it appears likely that the approach
    we have taken underestimates the District*s workload levels for this
    function. One of our previous studies, for example, found that an
    indicator of premature mortality called years of productive life lost
    (YPLL) is wellsuited as an indicator of public health workloads, and
    including it would have increased the District*s RES. 17 Highways Vehicle
    miles traveled and lane miles of highways and streets are

    workloads that reflect a legacy of earlier policy decisions with regard to
    how many highways to build and the success of efforts to control the
    volume of traffic through mass transit service provision and fares,
    carpooling, HOV, and other policies and programs. As mentioned earlier, to
    the degree that there has also been a legacy of relative undermaintenance
    of capital stock in this function, the workload measure would be an
    underestimate for the District.

    17 U. S. General Accounting Office, Public Health: A Health Status
    Indicator for Targeting Federal Aid to States, GAO/ HEHS- 97- 13
    (Washington, D. C.: November 1996). YPLL per capita is about 100 percent
    greater in the District than the average for the nation. Using our
    modified RES methodology for this expenditure function, the District*s
    workload per capita is 29 percent greater than the national average.
    Consequently, had YPLL been incorporated into our workload indicators, it
    would have resulted in a higher cost estimate for the District.

    Mass Transit Subsidies The workload factor chosen is the population of the
    urbanized area of the state with the adjustment for commuter population.
    Census* urbanized area definition is based on the population density of
    the geographic area; however, it is still a rather broad population
    measure. The total of state and

    District population in urbanized areas in 2000 is 192 million, which is 68
    percent of the total resident population of 281 million. The 2000
    Decennial Census provides two other pieces of information that are
    relevant in this context: (1) the total number of workers age 16 and over
    who use mass transit is 6 million and (2) the total number of households,
    with householders aged 16 through 65 and no motor vehicle available to the
    household, is 7 million. These data suggest that the chosen workload
    factor of urbanized population is very broad, and thereby, is likely to
    provide an underestimation of the District*s RES spending for this
    function.

    Police and Corrections The workload measure for both police and
    corrections under the ACIR methodology is the equally weighted sum of the
    percent distributions of: (1) resident population, (2) number of murders,
    and (3) population age 18- 24. We applied the *daytime* commuter
    adjustment to the resident population factor for police, but did not
    adjust the population factor for corrections.

    We thought the use of resident population unadjusted for *daytime*
    population was unlikely to risk overestimating the workload for
    corrections. Dr. Rafuse explains that workload factors (2) and (3) are
    connected to the incidence of crime and therefore are appropriate for
    corrections; however, no justification for including resident population
    is stated. The rationale for including (1) resident population is that
    *Many police responsibilities have little to do with crime. They include
    such tasks as accident investigation, traffic control, and enforcement of
    municipal safety and parking ordinances.* 18 Such factors would clearly
    increase with a significant influx of commuters. Regarding corrections,
    Rafuse writes

    *The number of murders and the size of the 18- 24 year population can also
    serve as crude indicators of the relative cost of corrections, on the
    assumption that these costs are directly related to the incidence of
    serious crime.* 19 While the ACIR report is silent on the rationale for
    including population, we have continued with this procedure as a
    conservative approach for measuring the District*s RES for corrections.
    The District*s RES workload for corrections is over three times the
    average per capita and removing the resident population workload factor
    would increase it further. The District*s actual incarceration rates are
    also high but not as

    high compared to the national average, and they have decreased rapidly in
    recent years. 20

    Fire Protection Fire protection services in the ACIR methodology are
    subsumed under the *all other* category and thereby assigned population as
    a workload factor. We assign to fire protection the workload factors of 40
    percent *daytime adjusted* resident population, 50 percent housing units
    in buildings with five or more units, and 10 percent housing units built
    prior to 1940. 21 These variables reflect the characteristics of older,
    densely settled urban areas where the risks of fire are greater and the
    costs of providing a given level of

    18 Rafuse, 15. 19 Rafuse, 15. 20 Ann L. Pastore and Kathleen Maguire,
    eds., Sourcebook of Criminal Justice Statistics [online] available: www.
    albany. edu/ sourcebook/. While actual incarceration rates reflect policy
    choices, in the absence of full understanding of these trends, we think it
    conservative to use this information to influence our choice of workload
    factors. For example, table 6.24 shows a more than 50 percent drop in the
    District*s rate of prisoners per 100,000 resident population from 1998 to
    2000.

    21 These weights were derived from regressing a per capita index of 1997
    fire expenditures by county area on adjusted population, and indexes of
    this housing information from the 2000 Census. All coefficients were
    significant.

    fire safety are magnified by the need to rely on professionals rather than
    volunteers, by the need for more specialized types of equipment and
    apparatus, and other reasons. While our method results in a workload
    measure for the District of 38

    percent above the national average for fire (using the weighted sum of the
    three workloads), there is evidence that suggests it could be higher. Our
    model for fire workloads did not include neighborhood, housing, and
    population characteristics that research has shown to be strongly related
    to the incidence of fire. 22 Though we have not examined all such

    characteristics, these are typical of low- income, urban areas that the
    District has in much higher percentages than the national average. For
    example, 2000 Decennial Census data show that the District*s per capita
    rate of families with a female head of household, no husband present, in
    poverty, is over twice the national average. 23 Sewerage Sewerage in the
    ACIR methodology is subsumed under the *all other*

    category and, thereby, assigned population as a workload factor. Housing
    units in many rural and suburban areas are not connected to a public sewer
    system and instead rely on septic tanks. We use the number of households
    connected to a public sewer system as the workload factor. 24 While this
    is

    only one aspect of the cost of supplying and maintaining sewer lines and
    treatment facilities, we believe it is superior to the use of population.

    Social Insurance Administration Census defines this category to consist of
    state and local spending on the unemployment compensation system and
    related employment search assistance. 25 Thus, we use the number
    unemployed as reported in the 2000 Decennial Census. 26

    22 A review of the literature is contained in National Fire Data Center,
    Socioeconomic Factors and the Incidence of Fire (Washington, D. C.:
    Federal Emergency Management Agency, June 1997). 23 National Fire Data
    Center, p. 18, discusses single- parent households with children present
    as a risk factor. Unfortunately, we do not have a consensus among the
    research studies as to the average impact such added risk factors have on
    the cost of fire services.

    24 These data are only available from the 1990 Decennial Census. 25 See
    www. census. gov/ govs/ www/ classfunc22. html. 26 The District*s
    unemployment rate was 10. 7 percent compared to the national average of
    5.7 percent.

    Libraries, Parking Facilities, and These three categories are subsumed
    under the *all other* expenditure

    Solid Waste Management category and are assigned population as their
    respective workload factors. In that commuters can reasonably be expected
    to use these services, in

    each case, we have assigned them population with the *daytime* adjustment
    for the net flow of commuters discussed above.

    Housing and Community These four categories are discussed together because
    they share common

    Development, Parks and treatment for their workloads. In the ACIR
    methodology, each is subsumed

    Recreation, Protective under the *all other* category and, in effect,
    assigned population as a

    Inspection and Regulation, and workload factor. We have chosen to continue
    using population as the

    Governmental Administration workload factor (without a *daytime*
    population adjustment), though we

    recognize that population may underestimate the workloads in some cases.
    For example, housing and community workloads would ideally reflect those
    blighted neighborhood conditions and lack of affordable housing that are
    more characteristic of urbanized areas than the use of population would
    indicate. Another example is governmental administration. For an area such
    as the District, with particularly high workloads per capita for most of
    its major expenditure functions (e. g., public safety, welfare, health and
    hospitals), it would seem reasonable to expect that more

    administrative expenses per capita would be necessary in order to
    effectively control the larger expenditures and larger numbers of public
    employees per capita that are needed to contend with the overall high
    level of workloads. 27 Thus, the workload for the governmental
    administration category should reflect, to some degree, the overall levels
    of workloads in other functional areas, and our use of population does not
    do that. 27 Of course, as noted earlier, this assumes a given average
    level of administrative efficiency.

    Interest on Debt We assigned a workload factor equal to the average
    workload of all other categories (except that the average excludes this
    category and the *not elsewhere classified* category discussed below). The
    ACIR method assigned the workload of total resident population to this
    category. Our modification reflects the fact that the amount of interest
    owed is directly related to the amount of debt incurred. Everything else
    the same (e. g., time preferences for debt, revenue- raising capacity,
    policy decisions about capital investment for public services), the
    circumstances that ought to determine the amount of debt incurred are the
    workloads for various expenditure functions and the input costs for them.
    Thus, for this category, both the workload and input cost measures of each
    individual state and the District are set equal to the average workload
    and input costs indexes of all its other functions (e. g., education,
    welfare, public safety) in that state/ the District. 28

    General Expenditures, Not This category is assigned a workload measure
    equal to the average Elsewhere Classified

    workload of every category (except the average excludes this category and
    the previous one.) Subsumed under *all other* according to the ACIR
    method, this category was in effect assigned the workload of resident
    population. The category is largely composed of expenditures on multiple
    functions that cannot be allocated to a single one, such as centralized
    purchasing, data processing, and vehicle fleet operations. Our workload
    measure reflects an averaging of the multiple expenditure categories that
    obtain goods and services through expenditures for this type of
    centralized, multifunction expenditure. As with interest on general debt,
    the workload and input cost measures used for each state and the District
    are the average

    workload and input costs index of all its other functions (e. g.,
    education, welfare, public safety). Table 15 summarizes the changes for
    each function and also the rationale for making those changes.

    28 While input costs indexes are discussed later, we mention it here
    because the rationale is the same.

    Table 15: Modifications of Workload Indicators Expenditure category
    Workload modification Rationale

    Elementary and 1. To estimate children in poverty, apply a

    1. The number of low- income people potentially eligible for secondary
    education cost- of- living adjustment to the

    public services, in principle, should be measured by a threshold used for
    determining poverty

    uniform standard independently of differences in costs. status. This
    adjustment allows the low- income population to be measured in real dollar
    terms.

    2. Increase the weight applied to the 2. Update this parameter to reflect
    current median state children in poverty from 0.25 to 0. 60.

    weighting of children in poverty. Higher education No change NA Medical
    vendor payments 1. Adjust the threshold of the poverty

    1. See elementary and secondary education estimate for cost of living. 2.
    Weight children, adults, and elderly

    2. These are superior measures of potential workload and the based on
    historical cost differences cost of serving these populations. associated
    with serving these

    population groupings. Other public welfare Adjust the threshold of the
    poverty estimate

    See elementary and secondary education. for cost of living. Health and
    hospitals Adjust the threshold of the poverty estimate

    See elementary and secondary education for cost of living. Highways No
    change NA

    Mass transit Use urbanized population, with the *daytime

    Adding mass transit subsidies is intended to capture the fact subsidies
    population* adjustment. that general purpose local governments often
    subsidize mass

    transit systems as an alternative to more highway building and
    maintenance. Therefore, including highway spending but ignoring these
    subsidies understates transportation needs in more urban settings. The use
    of urbanized population as a workload indicator reflects the role of
    population density in the typical choice to provide mass transit in an
    area.

    Police Apply the *daytime population* adjustment Population is used as a
    workload factor because some police to the one- third resident population

    responsibilities have little to do with crime. For such workload.

    responsibilities, including temporary additions and subtractions to the
    resident population due to commuting to work seems appropriate.
    Corrections No change NA

    Fire protection Assign to fire services the workload factors Alternative
    workload factors reflect conditions associated with of 40 percent *daytime
    adjusted* resident

    higher costs of providing fire prevention and suppression in population,
    50 percent housing units in

    dense urban areas. Such higher costs result from differences buildings
    with five or more units, and 10 in equipment, apparatus, and staffing (e.
    g., greater reliance on percent housing units built prior to 1940.

    professionals rather than volunteers.) Sewerage Assign the workload factor
    of 1990 Census

    In urban areas such as the District, 100 percent of housing data on
    housing units connected to a public units are connected to a public sewer
    system. In rural areas, it sewer system, rather than total resident

    is a lower percentage because septic tanks are common. population.

    Social insurance The modified workload factor is the number

    This category is the administration of the unemployment administration of
    unemployed. compensation system, including associated employment services
    such as job placement and counseling.

    (Continued From Previous Page)

    Expenditure category Workload modification Rationale

    Libraries Resident population with the *daytime Adjusting resident
    population allows for the workload indicator  Parking facilities

    population* adjustment. to reflect the impact of the net inflow of
    workers.  Solid waste management

     Housing and community No change. Resident population (without

    NA development

    adjustment) is the workload measure.  Parks and recreation  Protective
    inspection and regulation  Governmental administration

    Interest on debt Assigned a workload factor to equal to the The amount of
    interest owed is directly related to the amount of average workload of all
    other categories

    debt incurred. Everything else the same, the circumstances (except the
    *not elsewhere classified*

    determining the amount of debt incurred are the workloads for category).

    various expenditure functions and the input costs for them. Thus, the
    overall workloads and input costs indexes for every other function are
    used.

    General expenditures, not Assigned a workload factor to equal to the

    These expenditures are unallocable to other spending elsewhere classified
    average workload of every category (except

    categories because they are multifunction goods and services the average
    excludes this category and the

    supplied within state and local governments such as centralized previous
    one). data processing services, a motor pool, and so on. Since these
    expenditures provide goods and services to other expenditure

    categories, assigning the average of those workload factors (and the
    associated input cost indexes too) seems appropriate. Source: GAO. Note:
    GAO analysis of District expenditure data discussed in this appendix.

    Modifications to Unit Cost As described above, in the ACIR methodology,
    the unit cost of public

    Adjustments services is measured by a weighted average of an index of
    labor

    compensation rates across all industries, and the costs of other inputs
    used in the production of public services (assumed not to systematically
    vary across states). In addition, we control for cross- state differences
    in the age, gender, and educational attainment of the labor force.
    Adjusting for these differences presumably avoids attributing higher labor
    costs to governments whose labor forces contain a disproportionately large
    fraction of older and more expensive workers, such as males with
    disproportionately high educational attainment. The rationale would be
    that the cost of a standard worker used in the production of public
    services would be independent of differences in the composition of the
    labor force across geographic locations. For each state and expenditure
    category, the index of labor and nonlabor costs (assumed to be 1.0 for all
    states) is

    calculated as the national average labor and nonlabor shares of government
    expenditures within each spending category.

    We modified the above procedure by (1) using an alternative wage index
    based on place of employment rather than residence, (2) including a proxy
    for differences in the cost of buildings and related capital assets used
    to deliver services, (3) for medical vendor payments, using an index of
    the average private sector wage in the health industry as a proxy for the
    cost of labor used to deliver services, and (4) for the public welfare
    function, including a cost- of- living adjustment to reflect the nominal
    cost of

    providing a real dollar value of public assistance benefits. Use of an
    Alternative Wage Index

    The ACIR method used Census earnings data of residents to generate an by
    Place of Employment

    index of unit labor costs. That data yield implausibly low estimates for
    the cost of labor. With an influx of 481,000 workers, according to the
    2000 Decennial Census journey to work data, the Census earnings data for
    the

    District may not adequately reflect the labor market in which the District
    government seeks to hire and retain workers. Using 1990 earnings data (the
    latest available), the District*s resident earnings per employee was only
    104 percent of the national average. Since this figure appears less than
    the cost- of- living difference between the District and the nation, these
    data

    seem unlikely to reflect the competitive wage the District would have to
    offer to attract and retain workers. As an alternative, we chose to use
    Bureau of Labor Statistics (BLS) average wage rates for all private
    industry (but excluding manufacturing). However, using BLS data, it is not
    possible to control for the effects of age, gender, and educational
    attainment.

    Include an Index of Capital Cost In addition to labor, another major input
    used to provide public services is

    Differences the office space and related building assets used to deliver
    services.

    However, an index of office space costs across states was not readily
    available. We, therefore, used an index of rents for two- bedroom rental
    housing units as a proxy for these costs on the assumption that, where the
    cost of housing is high, office space costs will also be high. The cost of
    rental housing is currently used as a cost factor in the Substance Abuse
    and Mental Health Services Block Grant allocation process. The index is

    calculated from HUD*s fair market rents for metropolitan and
    nonmetropolitan areas for its Section 8 Housing Assistance Program. The
    data were aggregated to the state level using population to weight data
    for each area within the state.

    The choice of a percentage weighting to be applied to an index of office
    space costs would, in principle, be determined by this factor*s share of
    total spending in each function. However, the data for this calculation
    are not

    readily available. As a rough alternative, we assumed that these costs
    represent 15 percent of total spending in each category of spending.

    Use of Health Industry Wage In principle, the opportunity wage used for
    each spending category should

    Costs for Medical Vendor reflects the mix of skills required for that
    function; the labor market for

    Payments educators is different from that for health care professionals.
    While

    development of a unique labor cost for each function is beyond the scope
    of this project, our past work in the health area has resulted in the
    development of a wage cost factor for health services. Because of its
    broad

    coverage of health industry personnel, we used BLS health industry wage
    data.

    Cost- of- Living Adjustment for The basic premise of the RES is that it
    represents the nominal dollar cost of Cash Assistance in the Public

    providing a real level of public service benefits. In the case of cash
    Welfare Category

    assistance, 29 the cost of providing a uniform level of real benefits per
    program beneficiary would reflect differences in the cost of living. For
    this adjustment, we use the same cost- of- living index described above in
    connection with measuring the number of people in poverty on a cost-
    ofliving

    adjusted basis. Alternative Expenditure

    To compute per capita RES amounts by function for the District (and all
    Weights

    states), and to compute an overall RES amount as well, a set of national
    expenditure amounts for each function is needed. These expenditure shares
    for each category of spending are what provide the RES with the *average
    basket of services,* that is, a set of proportions reflecting average
    expenditures for each governmental function. Expenditures enter into the
    RES calculation in order to compute RES amounts in terms of dollars or
    dollars per capita. While the RES indexes can be computed without
    expenditures for each of the detailed functions listed in table 15 by
    multiplying the per capita workload indexes by the respective input cost
    indexes, the overall RES index for all functions is, in effect, a weighted

    average of the individual indexes where the weights applied are the shares
    of total expenditures. 29 The function in question here excludes medical
    vendor payments, welfare institutions, inkind

    benefits, and welfare administration that are cost adjusted separately,
    and thus it consists solely of cash amounts paid to program recipients (e.
    g., under Temporary Assistance for Needy Families and other cash
    assistance programs.) More specifically, it consists of amounts Census
    classifies under codes E67 and E68, which exclude any intergovernmental
    payments (that could include some Medicaid), and exclude in- kind
    benefits. Also excluded from this category are amounts classified under
    codes 75 (payments to social service and income maintenance vendor
    payments), 77 (welfare institutions), and 79 (public employment for all
    public welfare activities and welfare activities not classified
    elsewhere).

    The original ACIR method used national average spending by function. We
    basically continue with these weights, although we use a more
    disaggregated list of expenditure categories. However, we modified the RES
    expenditure weights in two ways. First, the category of mass transit
    subsidies was included in the RES while certain expenditure categories
    that did not pertain to expenditures in the District were removed. Second,
    as a form of sensitivity analysis, we employed a set of urban expenditure

    weights to test the degree to which the District*s overall RES is
    sensitive to the expenditure weights chosen. Modifying Expenditure

    The category of mass transit subsidies is basically excluded from the
    Categories Included and

    original ACIR method. 30 Since the District subsidizes transit provided by
    Excluded from RES

    the Washington Metropolitan Area Transit Authority (WMATA) and does not
    provide transit itself, we chose to include the transit subsidy but not
    the full level of such spending. This is a departure from the usual
    practice under RES and the representative tax system of including
    consideration of all the governments in the geographic area (including
    special districts such

    as WMATA), but we believe that it is important to focus on the District*s
    structural balance without including consideration of WMATA, which is an
    independent entity. Had we continued to exclude mass transit from the RES,
    the effect would have been to make RES less appropriate for application to
    the District. A number of characteristics of the District make mass
    transit an important alternative to highway funding:

     Twenty- two percent of the District*s total land area is devoted to
    highways,

     the District*s streets and highways are already intensively used
    (vehicle miles traveled per lane mile of road are 175 percent greater than
    the national average),  households with no vehicle available are three
    times as prevalent in the

    District as the nation, and 30 The Rafuse method included only those mass
    transit subsidies provided to privatelyowned transit companies and these
    were subsumed under the *all other* category with resident population
    assigned as a workload factor. Such subsidies are 5 percent of total

    transit subsidies.

     the District has to contend with air pollution problems connected with
    vehicle emissions.

    Thus, we believe it is important that our estimate of the District*s RES
    include transit subsidies. Further, by including only the transit subsidy,
    we are making a conservative change in terms of its impact on the
    District*s RES amount.

    The following detailed Census expenditure functions were eliminated from
    the RES in order to better reflect a basket of services that the District
    would actually purchase: state veterans* bonuses and services;
    miscellaneous commercial activities, not elsewhere classified; air
    transportation; water transportation; agriculture; fish and game;
    forestry; and other natural resources. 31 While state governments perform
    virtually all these functions, local governments and the District do not
    perform most of them.

    Urban Alternative Expenditure As an alternative to the national
    expenditure weights, we calculated the Weights

    aggregate expenditure of all local governments in 20 county areas that had
    over 250,000 population and population density in excess of 3,000 persons
    per square mile. 32 Though other methodologies could have been used to
    choose county areas, we thought this method would provide a simple way

    to choose areas more similar to the cost and workload characteristics of
    the District than all the state and local governments in the nation. 31
    While the other categories are relatively straightforward, the category of
    *other natural

    resources* is not. Census* classification manual (www. census. gov/ govs/
    www/ classfunc59. html) defines it to be *Conservation, promotion, and
    development of natural resources (soil, water, energy, minerals, etc.) and
    the regulation of industries which develop, utilize, or affect natural
    resources.* Further, *Examples: Irrigation; drainage; flood control; soil
    conservation and reclamation including prevention

    of soil erosion; surveying, development, and regulation of water
    resources; regulation of mineral resources and related industries
    including land reclamation; wetlands and watershed management and
    protection; geological surveying and mapping; regulation of gas and oil
    drilling and production; dam and reservoir safety; public education
    programs related

    to the above; technical and fiscal assistance to private or other
    governmental efforts in these areas.* The District*s relatively
    insignificant workload per capita for such expenditure is undoubtedly a
    result of its geography: its area is 6 percent of the smallest state and
    its population density is 8 times the densest state.

    32 New York City was counted as if it were one county. That is, we
    collected data for the New York City area and 19 other county areas. The
    expenditure data used are for fiscal year 1997 because these are presently
    the most current data available by county area.

    We adjusted the local government expenditures of these 20 county areas in
    two ways. First, the share of expenditure for medical vendor payments
    (Medicaid) is set equal to the state average, because Medicaid is a
    significant source of state expenditure benefiting these counties and
    because no data are available on the amounts that state governments
    directly spend in all these county areas. This increases the percentage
    share of total expenditures for medical vendor payments from the 0.9
    percent actually spent by urban governments to the 10.5 percent that is
    the national average. Second, to make the per capita RES amounts under the
    urban alternative comparable to those under the state expenditure weights,
    we proportionally increased the urban weights so that the per capita RES
    amount for the nation was equal under either the national weights or the
    urban alternative weights.

    Revenue Capacity Analysis: Methodology and

    Appendi x II

    Detailed Estimates This appendix provides further details on our
    methodology for estimating the total revenue capacity of the District and
    the 50 state fiscal systems. In separate sections we explain how we
    estimated the two components of total revenue capacity: (1) the grants
    that a fiscal system would receive if it provided an average basket of
    services and (2) the fiscal system*s ownsource revenue capacity. At the
    end of the appendix we provide detailed results from our analyses.

    Estimating Grants Our analysis covers those categories of federal grants
    that are used to fund Associated with

    the types of functions that we covered in our expenditure analysis. Thus,
    we included grants in the education, employment security administration,
    Average Services

    general local government support, health and hospitals, highways, housing
    and community development, public welfare, sewerage, and the "all other"
    categories. For most of these grants we simply use the actual amounts that
    state fiscal systems received from the federal government because those
    amounts are not likely to change significantly in response to changes in
    state and local spending choices. In the case of the Medicaid program,
    however, the federal government provides open- ended matching grants to
    the District and the state fiscal systems and the federal assistance that
    those fiscal systems receive depends on the decisions that states make

    regarding the coverage of their Medicaid programs. To estimate the amount
    of Medicaid grants that each fiscal system would receive if it provided
    average Medicaid services, we multiplied its actual fiscal year 2000
    Medicaid grant by the following ratio: the amount that the system would
    have to spend in order to provide average Medicaid services, divided by
    the amount that the system actually spent on Medicaid services.

    Using the approach just described, we estimate that the District would
    have received about $2,700 per capita in federal grants if it had provided
    average services in fiscal year 2000. This amount was 2.7 times the
    national average.

    Estimating OwnSource This section provides background information on
    different measures of

    Revenue own- source revenue capacity and describes in detail how we
    implemented the representative tax system (RTS) approach for this study.

    Capacity

    Measures of Own- Source Two general types of measures have been used to
    estimate the own- source

    Revenue Capacity revenue capacity of states* those that use income to
    measure the ability of

    governments to fund public services with a standardized tax burden on
    state residents and those that attempt to measure the amount of revenue
    that could be raised in each state if a standardized set of tax rates were
    applied to a specified set of statutory tax bases *typically* used to fund
    public services. Total taxable resources (TTR), developed by the U. S.
    Department of the Treasury (Treasury), is a leading example of the first

    type of measure and the RTS, developed by the Advisory Commission on
    Intergovernmental Relations (ACIR), is a leading example of the second.
    Experts disagree as to which approach is superior. Proponents of TTR
    believe that a measure of revenue capacity should be independent of policy
    decisions and should avoid judgments about the administrative or political
    feasibility of taxing particular bases. Proponents of the RTS believe that
    administrative and political constraints should be taken into account,
    even though it may be difficult to say what is a constraint and what is a
    choice. In order to provide as much balance as possible, we will present
    separate

    results using both methodologies. The TTR was designed to overcome
    limitations of two other indices of aggregate income in a state* state
    personal income (SPI) and gross state product (GSP). The former accounts
    for all of the income flows received by residents in a given state, while
    the latter accounts for all of the income produced in the state. There is
    considerable overlap between these two measures, but each contains items
    that are not counted in the other. Since states generally have the ability
    to tax the income counted in either SPI or GSP, the TTR was developed to
    count all of the income flows included in either of the two measures, but
    to count each flow only once.

    A typical RTS analysis estimates the per capita tax yield that a uniform,
    hypothetical, representative set of tax rates would yield if applied to a
    specified set of statutory tax bases that states typically tax. For each
    tax a uniform base is defined, which excludes all tax incentives or *tax-
    breaks,* it also excludes items that are rarely taxed in any jurisdiction.
    The analyst then applies a standard tax rate to each tax base across all
    of the states. Each rate is set equal to the national average effective
    tax rate that states

    actually impose for the particular tax. This average effective tax rate is
    computed by dividing nationwide state and local tax collections for a
    particular type of tax (from U. S. Census Bureau data on state and local
    government finances) by the aggregate tax base (across all state and local
    governments) for the tax. The result of this computation is that each
    state's revenue capacity for a particular tax is equal to the total
    national

    collections for that tax, multiplied by the state's share of the national
    aggregate value for the tax base.

    Identified Limitations of the Each approach to estimating revenue capacity
    has limitations, which are

    Revenue Capacity Measures described below. This is one reason that we
    report results using both

    approaches. For the most part, both approaches appropriately reflect the
    atypical constraints on the District's revenue capacity. In order to
    address several specific concerns raised by District officials or others,
    we make special adjustments to the District's tax bases in at least one of
    our scenarios. These adjustments are identified below, in the descriptions
    of the methodologies we used for the various taxes.

    In theory, the TTR should be computed by taking GSP; subtracting out
    depreciation, federal income and indirect business taxes, and
    contributions to social insurance; and then adding in various items of
    income earned outside of the state, along with federal transfers and
    accrued capital gains. In practice, data are not available to make all of
    these adjustments. 1 Specifically, depreciation and federal income taxes
    are not subtracted from GSP because they are not estimated on a GSP-
    consistent basis. Additionally, it is assumed that all interest and
    dividend income in SPI is

    earned out of state and all rent and royalty income is earned in state,
    and already included in GSP. Social insurance transfers are used in place
    of total federal transfers, because other components of federal transfers
    are not estimated on a SPI- consistent basis. Data on net realized capital
    gains are substituted for accrued capital gains, again due to data
    availability. One additional limitation of the TTR that has been noted in
    the literature is that

    it does not adequately reflect the capacity of states to tax nonresident
    tourists.

    A principal limitation of the RTS is that its estimates of tax potential
    are distorted by the actual tax policies of states. This occurs because
    the sizes of the tax bases that are measured by the RTS are influenced by
    the tax rates that are currently being applied to them. For example,
    states with

    relatively high sales tax rates are likely to have smaller sales tax bases
    than they would with lower sales tax rates because the high rates will
    encourage consumers to make more purchases out of state. Our analysis of
    the

    1 For details, see Michael Compson and John Navratil, An Improved Method
    for Estimating the Total Taxable Resources of the States, Research Paper
    no. 9702 (Washington, D. C.: Office of Economic Policy, U. S. Department
    of the Treasury, 1997).

    District*s *tax effort* (the ratio of its actual revenues to its revenue
    capacity) indicates that, overall, the District*s tax rates are higher
    than average. Therefore, this particular limitation of the methodology is
    more

    likely to cause us to underestimate the District*s revenue capacity than
    to overestimate it.

    Additional RTS limitations that have been noted in the literature are
    that:  Because the size of a state*s sales and property tax bases have a
    strong influence on that state*s RTS score, the measure reflects patterns
    of

    consumption or resource use in the state, rather than resource
    availability or purchasing power.

     It does not include all sources of income, such as federal transfer
    payments.

     It does not reflect the ability of states with higher per capita incomes
    to pass on larger shares of their tax burden to the federal government
    (through the deductibility of state income taxes under the federal income
    tax) than states with lower per capita income. 2

    Our Implementation of the The scope of our analysis actually falls in
    between that of a representative

    RTS Approach tax system study, which covers only taxes, and that of a
    representative

    revenue system, which covers all taxes, user charges, and fees. Our
    analysis covers all state and local government taxes and some of the fees
    charged by those governments. We exclude certain fees and user charges
    because they have either already been netted out from our expenditure
    estimates, or they are linked to private- sector- type services that are
    not covered by our expenditure analysis.

    In the case of some tax bases where there is more than one valid
    estimation approach or more than one valid choice for a critical
    assumption, we estimated more than one distribution of the tax base across
    the states and the District. We computed estimates of total own- source
    revenue capacity

    2 For further discussions of these issues see Steven M. Barro, *State
    Fiscal Capacity Measures: a Theoretical Critique,* in H. Clive Reeves,
    ed., Measuring Fiscal Capacity (Cambridge, Mass.: Lincoln Institute for
    Land Policy, 1986), 51- 86. And Robert Tannenwald,

    *Fiscal Disparities Among the States Revisited* in New England Economic
    Review (Boston, Mass.: July/ August 1999), 3- 25; and Compson and
    Navratil, *An Improved Method.*

    for "high" and "low" scenarios. Under the high RTS scenario, for each tax
    we used the approaches and assumptions that yielded higher estimates of
    the District's tax bases, relative to those of the states. We did the
    converse for the low RTS scenario.

    In considering the following methodologies one should keep in mind that
    what we call a "tax base" is not always the same as the statutory
    definition of the base upon which tax rates are applied. In some cases the
    "base" is simply a proxy whose distribution across states is expected to
    be highly correlated with the distribution of the actual tax base across
    states. An example of this is where we use the distribution of federal
    estate tax

    collections across states as a proxy for the distribution of the value of
    estates across states. What is important for obtaining accurate estimates
    of each state's revenue capacity for a particular tax is not how close the
    absolute value of our estimated base for a given state is to that state's
    actual base, but how close the percentage distribution of our estimated
    base across states is to the percentage distribution of the actual tax
    base

    across states. Details on Individual Taxes

    Property Tax We used two quite different approaches to estimate the
    property tax base in the District and each state. Each approach has its
    own limitations so, as a sensitivity analysis, we present results using
    both approaches.

    Under the first approach, total property value nationwide is estimated
    from national level data sources as the sum of farm property, corporate
    property, partnership property, utility property, and residential
    property. The value of farm property is obtained from U. S. Department of
    Agriculture statelevel data on farm acreage and farm value per acre.
    Corporate and partnership property value 3 is estimated, by industry at
    the national level, from the Internal Revenue Service (IRS) for 1999,
    inflated to its 2000 value

    and then allocated to the District and the states based upon their shares
    of state personal income, by industry. National aggregates for utility
    property (the sum of the gas, electric and telephone industry property)
    are also obtained from IRS and are allocated to the District and the
    states based upon the percentage of national capacity (pipelines,
    telephone lines, etc.) that is located in each jurisdiction. 4 Tax- exempt
    property owned by governments, embassies, and other tax- exempt entities
    is not included in our estimated tax base because those entities do not
    file federal corporate or partnership tax returns.

    Residential property is the sum of owner- occupied and rental property
    values. Owner- occupied residential property value and actual rent paid
    for rental property is reported, by state and the District, in the 2000
    Decennial Census. An estimate of imputed rent for owner- occupied housing
    is

    reported in *Housing*s Impact on the Economy,* Report of the National
    Association of Home Builders submitted to the Millennial Housing
    Commission, November 2001. We assume that the ratio of property value to
    rent, imputed or actual, is the same across residential property types.
    This assumption allows us to arrive at a value for rental property. 5
    Given that our empirical estimate for the ratio of property value to rent
    comes

    from a single study and that the relative size of the District*s property
    tax base is likely to be overstated if this ratio is overestimated, we
    computed alternative results with the ratio reduced by half for our lower-
    bound

    estimate of the District*s property tax capacity. 3 Corporate and
    partnership property are comprised of the sum of depreciable assets,
    depletable assets, and land less accumulated depreciation and depletion. 4
    The 1999 values for corporate, partnership, and utility property are grown
    to 2000 values using indexes based on national- level data on fixed assets
    from the Bureau of Economic Analysis.

    5 We solve for x in the following formula: x owner - occupied housing
    value , actual rent = imputed rent where x equals the value of rental
    property.

    A principal limitation of this first approach is the reliance on
    allocating corporate and partnership to the states using industry-
    specific state personal income. While we believe that the choice of state
    personal income to allocate property is sensible and this approach has
    been used in a prior study, we have been unable to find empirical
    estimates to support

    the correlation between distribution of state personal income and the
    distribution of industry property value. Additional limitations to this
    approach include the unknown accuracy of self- reported data from the 2000
    Decennial Census on rent paid and residential property value and the fact
    that our estimate for commercial property does not include property owned
    directly by individuals (rather than through corporations or
    partnerships).

    The second approach for estimating property tax bases involved searching
    the Web sites of each state and contacting state property tax officials to
    obtain data on the total value of property in each state. We made a

    considerable effort to get the data for each state to be as close as
    possible to our uniform definition, which was: the total market value of
    all real property in the state, excluding the value of property owned by
    governments and other entities that are typically exempted from property

    taxes, but including the value of property owned by individuals who
    receive homestead exemptions or other forms of property tax relief. We
    tried to get the data on the market value of all such property, valued as

    close to January 1, 2000, as possible. We attempted to exclude the value
    of personal property from our data because the scope of the personal
    property tax base varied considerably across states and many states do not
    tax such property. In cases where the property value data were more than
    one- half year before or after January 1, 2000, we adjusted the values for

    both price and quantity changes (if both were needed) using indexes based
    on national- level data on fixed assets from the Bureau of Economic
    Analysis (BEA).

    The principal limitation of this second approach is the fact that we were
    not able to apply our definition of the property tax base with perfect
    consistency across all states. For example, the states differed in how
    they valued agricultural land. Although most states valued this land on
    the basis of its productive value in agricultural use, some states
    estimated market values for the land. We were unable to adjust for these
    differences and simply used the values provided by the states. More
    important, we could not obtain adequate property value data from 5 states.
    We estimated the "state- reported" data for those states by multiplying
    the estimates that we obtained for those states with our first approach by
    the following ratio: the

    aggregate state- reported market value for the 45 other states and the
    District, divided by the aggregate property value for those 45 states and
    the District as estimated with our first approach. Personal Income Tax We
    calculate two different estimates of the tax base for the personal

    income tax. Both of the estimates are based on federal tax return data for
    2000, as reported by IRS* statistics of income. We start with the
    aggregate adjusted gross income that IRS reports by state and we add back
    in the

    aggregate adjustments to obtain an aggregate measure of gross income for
    each state. Then we subtract the aggregate value of personal exemptions
    that were claimed in each state. We use the resulting figures as one
    measure of the potential personal income tax base for states. For an

    alternative measure we take our first set of figures and subtract an
    estimate of the aggregate amount of deductions claimed in each state. We
    adjust each set of estimates using BEA's residence adjustment (in the same
    manner followed by ACIR (1993) and Tannenwald (1999)) to reflect the fact
    that states typically tax the income that nonresidents earn within their

    boundaries and provide credits to their own residents for income taxes
    that they pay to other states. No residency adjustment is made for the
    District because it is prohibited from taxing the income of nonresidents.

    In response to concerns raised by District officials, we also examined how
    the District's personal income tax capacity would change if we used state
    personal income, reported by BEA, as a proxy for the tax base, instead of
    the income data from federal tax returns. The District officials were
    concerned that the use of federal tax data, which are allocated to states
    and the District on the basis of the addresses provided on the tax
    returns,

    would overstate the District's tax base because they believed that a
    substantial number of nonresidents used tax preparers in the District and
    used the latter's addresses on their returns. The District officials could

    provide no data to substantiate this concern. In any case, the
    substitution of state personal income resulted in a higher estimated
    personal income tax capacity for the District.

    General Sales and Gross Our starting point for estimating the general
    sales and gross receipts tax

    Receipts Taxes base were 2000 U. S. Census Bureau (Census) data on sales
    of the retail

    trade and service industries, which comprise most of the base of state and
    local general sales taxes. These Census data were disaggregated by the
    industries defined in the North American Industry Classification System

    (NAICS). We included those NAICS sectors that are taxed under the general
    sales taxes of most states.

    Census provides a state- by- state disaggregation of sales only every 5
    years. The latest available disaggregation is for 1997. 6 Consequently, we
    needed to allocate the sales across states, either by applying the 1997
    state percentage shares to the 2000 sales data, or by distributing the
    sales in

    proportion to employment, by state, in the retail and services industries.
    7 We had no way to determine which approach is more accurate, so we
    present results using each approach. Approximately 5 percent of sales in
    the retail sector are *nonstore* sales. Two- thirds of the nonstore sales
    are remote (mail order or Internet) sales; the remainder are sales by
    direct sellers. Given that states have difficulty collecting tax on remote
    sales in cases where the purchasers are individuals (rather than
    businesses) and the sellers do not have legal nexus in the state of the
    purchasers, we count only a fraction of such sales in our tax base. 8
    Because we do not know what percent of the total remote sales are
    purchased by individuals and sold by retailers that do not have nexus, we
    cannot say precisely what share of these sales are effectively not

    taxable by state and local governments. We present results using the
    alternative assumptions that 25 and 50 percent of the remote sales are
    taxable.

    6 The two most recent state- by- state disaggregations of sales are
    available in the 1992 Economic Census and 1997 Economic Census, both of
    which are reported by the U. S. Census Bureau. The next edition of the
    Economic Census will capture conditions in 2002 and is expected to be
    released in early 2004.

    7 Brian D. Francis, The Feasibility of State Corporate Data Internal
    Revenue Service, Statistics of Income Division (Washington, D. C.: March
    2000), provides empirical evidence that the distributions of sales and
    employment across states in the retail and services industries are highly
    correlated. For this employment- based approach, we made separate
    distributions for the retail sales, accommodations, and food services
    categories, which account for over 90 percent of the sales included in our
    tax base. These are categories in which one would expect a high
    correlation between location of employees and destination of sales or
    services. For the remaining category of sales, we used the 1997 percentage
    distribution of sales. The state- level data on employment by industry
    come from the Census county business patterns.

    8 We treat sales by direct sellers the same as we treat in- store sellers
    because we presume that the direct sellers have nexus in the state of
    their customers. For more information on states* difficulties with remote
    sales, see U. S. General Accounting Office, Sales Taxes: Electronic
    Commerce Growth Presents Challenges; Revenue Losses Are Uncertain,

    GAO/ GGD/ OCE- 00- 165 (Washington, D. C.: June 2000). We use only the
    extrapolation, not the employment distribution approach, for estimating
    state- level nonstore sales in 2000.

    One limitation of the Census data for our purposes is that they do not
    cover sales to business purchasers by industries other than the retail and
    services industries. Some of these missing sales are taxable, while others
    are exempt. Unlike the case of retail and service sales, the exemptions of
    other business- to- business sales are typically dependent on the nature
    of the purchaser and/ or the use that is made of the product or service
    purchased. Adequate data are not available on the purchasers or uses made
    of the sales by other industries, so we could not reliably estimate the
    proportion of those sales that would be taxable. For this reason, we
    excluded all such sales from our estimated tax base. This data limitation
    means that our

    distribution of general sales tax capacity across the states will be
    inaccurate to the extent that the missing business- to- business sales are
    distributed in different proportions than are the sales of the retail and
    services industries.

    One concern that District officials have raised about our method for
    estimating the sales tax base is that our data include nontaxable sales to
    the federal government. If sales to the federal government are included,
    then the District*s sales tax base may be overstated relative to those of
    the states because of the disproportionate federal presence in the
    District. We do not know the extent to which sales to the federal
    government are

    represented in the Census sales data because these data are not classified
    by type of purchaser and District officials had no information that would
    help us estimate the extent of such sales in the District.

    We used data from the Federal Procurement Data System (FPDS) to get at
    least a rough idea of the magnitude of purchases by the federal government
    in the District and in each state, so that we could subtract those
    purchases from our estimated tax base. The FPDS purchase data available to
    us were distributed across states and across industrial sectors, but they
    were not

    distributed across both states and sectors at the same time. Therefore, we
    had to make the simplifying assumption that the percentage distribution of
    the purchases across sectors was the same in all jurisdictions (even
    though the absolute amount of purchases varied considerably). As we did
    with Census data, we determined which of the purchases are typically
    subject to

    general sales taxes (if sold to the private sector) on a sector- by-
    sector basis. We then subtracted these *taxable* sales to the federal
    government from our estimated sales tax base for each fiscal system. Given
    uncertainty regarding the categories of sales that would be subject to
    tax, we used two different selections of categories* a narrower selection
    that led us to subtract an amount equal to about 0.4 percent of District-
    based federal procurement from the base and a broader selection that led
    us to subtract an amount equal to about 3.0 percent of that procurement. 9

    9 Our narrower selection included retail trade, personal services, hotels,
    motion pictures, amusement, and telecom services. In addition to the
    preceding categories, our broader selection included wholesale trade,
    furniture, and equipment and computers. The procurement is categorized on
    the basis of the seller*s line of business. Even though sales by
    wholesalers to retailers generally are not taxed, some sales by
    wholesalers to final

    business purchasers are taxed. Although we do not include nonretail
    business- to- business sales in our tax base proxy (because we have no
    reliable means of estimating the taxable amounts of those sales and
    because we have no reason to believe that their exclusion would cause a
    significant over- or underestimate of the relative size of the District*s
    sales tax base), we felt that ignoring the business- to- government sales
    in the District would result in greater inaccuracy than if we made this
    rough adjustment for those sales. However, in order to correct for the
    inconsistency of subtracting some nonretail sales to government from a tax
    base that does not include nonretail sales, we multiplied the nonretail
    sales to government by the following ratio: our aggregate retail sales tax
    base / (our aggregate retail sales tax base + sales in the nonretail
    categories included in our procurement adjustment).

    A second concern that District officials have raised about our method for
    estimating the sales tax base is that our data include nontaxable sales to
    embassies and military personnel. To the extent that these sales are
    included, our estimate of the District*s sales tax base may be overstated,
    relative to those of the states, because of the disproportionate presence
    of embassies and military personnel in the District. A 1995 study by the

    District included an estimate of the District*s revenue loss due to the
    sales and excise tax exemption for sales to embassies and military
    personnel. 10 We are unable to assess the accuracy of the District*s
    estimate but, lacking

    any other relevant information, we use their estimate to adjust our lower
    estimate of the District*s sales tax capacity. We do this by assuming that
    the exempted sales are in the same proportion to total taxable sales as
    they were in 1995.

    Corporate Income Tax The tax base proxy for the corporate income tax is
    corporate profits in 2000, as reported by BEA. These data are not
    available on a state- by- state basis, so we needed to estimate the
    allocation across states. The profits

    data are disaggregated by industry and we allocated each industry*s
    profits across the states on the basis of each state's share of national
    industry payroll. We make one District- specific adjustment to this
    methodology to subtract out the estimated payroll of two government-
    sponsored enterprises (GSEs) that have disproportionate presences in the
    District. 11 Given that state and local governments are not permitted to
    tax the profits

    of GSEs, it would not be appropriate to allocate taxable profits to the
    District on the basis of GSEs* payrolls. We estimate the District*s
    portion of GSEs* payrolls using information from their financial
    statements and from the District*s 1995 study of tax exemptions. We then
    subtract these amounts from the District*s share of the financial services
    industry*s total payroll.

    10 District of Columbia, Department of Finance and Revenue, Study of
    Property, Income and Sales Tax Exemptions in the District of Columbia
    (Washington, D. C.: 1995). 11 The two GSEs that we adjust for are the
    Federal National Mortgage Association (Fannie Mae) and SLM Corporation
    (Sallie Mae).

    Selected Sales Taxes Motor Fuel The base for selected sales taxes on motor
    fuels is the net volume of all

    motor fuels taxed by each state in 2000 as reported by the U. S.
    Department of Transportation, Federal Highway Administration.

    Public Utility The base for selected sales taxes on public utilities is
    the sum of gas, electric, and telephone revenue by state in 2000 as
    reported by the American Gas Association, the U. S. Department of Energy*s
    Energy Information Administration, and the Federal Communications
    Commission, respectively.

    Insurance The base for selected sales taxes on insurance is the sum of
    premiums, by state, for life insurance and property/ casualty insurance
    for 2000 reported by the American Council of Life Insurers and the
    Insurance Information Institute, respectively.

    Tobacco The base for selected sales taxes on tobacco is number of packs of
    cigarettes sold by state in 2000. Per capita information is provided by
    the National Center for Chronic Disease Prevention and Health Promotion,
    Tobacco Information and Prevention Source and inflated to totals using
    Census population data.

    Alcoholic Beverages The base for selected sales taxes on alcohol is the
    sum of wine, malt beverage and spirits sales by volume, by state, in 2000
    as reported by the Beer Institute.

    Amusements The base for selected sales taxes on amusements is the sum of
    spending on arts, entertainment, recreation, motion pictures, and
    exhibitions minus the sum of spending on promoters of performing arts;
    sports and similar events; agents/ managers for artists, athletes, and
    other public figures; independent artists, writers and performers and coin
    operated amusement

    devices (except slots) for 2000 from Census.

    Parimutuels The tax base for selected sales taxes on parimutuels is gross
    parimutuel wagering by state in 1997. 12

    Licenses Motor Vehicle Registration The tax base for motor vehicle
    registrations is the sum of motor vehicle and

    motorcycles registered, by state, in 2000, as reported by the U. S.
    Department of Transportation, Federal Highway Administration. Motor
    Vehicle Operators The tax base for motor vehicle licenses is the number of
    drivers licenses,

    by state, in 2000, as reported by the U. S. Department of Transportation,
    Federal Highway Administration.

    Corporations The tax base for corporate licenses is the number of
    corporate returns filed, by state, in 2000 as reported in *Internal
    Revenue Service Data Book 2000.*

    Hunting and Fishing The tax base for hunting and fishing licenses is the
    number of hunting and fishing licenses sold, by state, for 2000 as
    reported by Automated Wildlife Data Systems using U. S. Fish and Wildlife
    Service information.

    Estate and Gift Tax The tax base for state- level estate and gift taxes is
    2000 federal estate and gift tax collections, by state, reported in
    *Internal Revenue Service Data Book 2000.*

    Severance Tax The tax base for severance taxes is the sum of the value of
    oil, coal, natural gas, and nonfuel mineral production, by state, for
    2000. Nonfuel mineral production value is from the U. S. Geological
    Survey. All of the remaining

    information was reported by the U. S. Department of Energy, Energy
    Information Administration.

    12 The tax base used in Robert Tannenwald, Interstate Fiscal Disparity in
    1997, New England Economic Review, (Boston, MA: Third Quarter, 2002) for
    parimutuels is sourced to Christian Capital Advisors LLC., *Table 3: 1997
    Gross Wagering by State,* International Gaming and Wagering Business
    (1997). We did not attempt to verify these figures.

    User Charges and Special The tax base for user charges and special
    assessments is state personal Assessments

    income, by state, of residence, from BEA for 2000. Rents and Royalties The
    tax base for rents and royalties is the actual receipts of rent and
    royalty

    taxes, by state, in 2000 from Census. This tax base was chosen because of
    the inherent difficulty in determining the state in which the rent or
    royalty actually takes place. The accuracy of this proxy for the actual
    tax base rests, in large part, on the assumption that, for each state,
    inflows and outflows are equal.

    All Other Revenues This category captures a variety of revenue sources
    that are either small or sporadically levied by the states, including
    lottery revenue. The tax base

    for this category is state personal income by state of residence from BEA
    for 2000.

    Resulting Estimates of Table 16 presents our lowest and highest RTS
    estimates (using the range of the District*s OwnSource

    assumptions and approaches described above) of the District*s revenue
    capacity for specific sources of revenue. We present the estimates in per
    Revenue

    capita dollar amounts and as indexes (where the national average capacity
    Capacity equals 100). We also show how the District*s capacity would rank
    against the 50 state fiscal systems. Our *low* estimate of the District
    total ownsource revenue capacity combines our lowest estimates for all of
    the revenue sources; our *high* estimate combines our highest estimates
    for all of the revenue sources. The dollar amounts represent how much the
    District could raise by applying national average tax rates to its
    estimated tax bases, multiplied by a small adjustment factor. 13 We also
    computed a

    13 The national average tax rate for each revenue source is computed as:
    (the aggregate amount of actual revenue collected by all state and local
    governments from that source) / (the aggregate value of the estimated tax
    bases for all of the state and District fiscal systems for that source).
    Each of these average tax rates was then multiplied by 0.9657. This latter
    adjustment is needed to make state and local budgets balance (in the
    aggregate) for fiscal year 2000. The aggregate value of actual state and
    local expenditures that we used when computing our RES estimates was less
    than the sum of the aggregate values of state and local own- source
    revenue, plus federal grants.

    third estimate of own- source revenue capacity for the District based on
    the Treasury*s estimates of the TTR. 14 The per capita value for this
    estimate was $5, 684, the index value was 134, and the District*s value
    was higher than that of any state fiscal system, except for Connecticut.

    Tabl e 16: RTS Estimates of the District*s Own- Source Revenue Capacity
    *Low* estimates *High* estimates Per capita Per capita Revenue source
    amount Index Rank amount Index Rank

    Property tax $1, 108 130 3 $1, 426 167 2 Personal income tax 940 129 3 946
    130 3

    Sales and gross receipts taxes 882 89 50 971 98 32

    Corporate income tax 199 161 3 199 161 3

    Other taxes 227 119 7 227 119 7 Nontax revenue 1,684 126 2 1,684 126 2

    Total own- source revenue capacity $5, 039 119 4 $5, 445 129 3

    Source: GAO. Note: GAO analysis of data from the methodologies described
    in this appendix.

    14 The TTR is a measure of taxable resources and is not expressed in terms
    of how much revenue can be raised from those resources. In order to
    facilitate comparisons with our RTS estimates, we took the same aggregate
    amount of state and local own- source revenue that we used in our RTS
    approach and distributed that amount across the fiscal systems in

    proportion to each system*s share of aggregate TTR.

    Computation of the District*s Structural

    Appendi x III

    Deficit This appendix explains how we used the estimates of the District*s
    per capita cost of providing an average level of expenditures (presented
    in table 5) and per capita total revenue capacity (presented in app. II)
    to compute estimates of its aggregate structural deficit. It also provides
    a comparison of the District*s structural deficit to those of the state
    systems with the largest structural deficits, as percentages of own-
    source revenues.

    The Structural Deficit As discussed above, a fiscal system has a
    structural deficit when its cost of

    Computation providing an average level of services exceeds its total
    revenue capacity. Most of our quantitative analysis was conducted in per
    capita terms.

    However, to compute the structural deficit or surplus for each fiscal
    system, we needed to inflate the per capita estimates of costs and total
    revenue- raising capacities to aggregate levels by multiplying our
    estimates for each fiscal system by that system*s population. 1 We then
    subtracted each system*s aggregate total revenue capacity from its
    aggregate cost to determine the size of its deficit or surplus.

    We obtained our lowest estimate of the District*s structural deficit ($
    470 million) by taking the difference between our lower estimate of DC's
    cost of services ($ 5,272 million), based on the state basket of services
    and our higher estimate of total revenue capacity ($ 4,802 million). That
    estimate of total revenue capacity was the sum of our highest estimate for
    the District's own- source revenue capacity ($ 3,251 million), based on
    the TTR approach, and our estimate of the amount of grants that the
    District would have received ($ 1,551 million) if it provided an average
    level of services. Table 17 summarizes this computation as well as the
    computation of our highest estimate of the Districts* structural deficit.

    1 Estimates of the District*s per capita costs of providing an average
    level of services are reported in table 5. Total revenue capacity is the
    sum of representative grants and ownsource revenue capacity; estimates for
    both of these components are reported in per capita terms in app. II.
    Apps. I and II describe the methodologies we used to make these per capita
    estimates.

    Table 17: Computation of the District*s Structural Deficit under
    Alternative Estimation Approaches, Using Fiscal Year 2000 Data

    Dollars in millions

    Computation Cost of an Own- source average level

    revenue Federal

    Structural Estimation approach

    of services capacity grants deficit

    State services basket; TTR for revenue capacity $5, 272 $3, 251 $1, 551
    $470

    Urban services basket; *Low* RTS for revenue capacity $5, 597 $2, 883 $1,
    551 $1, 163

    Source: GAO. Note: GAO analysis of methodologies described in apps. I and
    II.

    Deficit as a Percentage Figure 10 shows how the District*s structural
    deficit compares to the state of Own- Source

    systems with the largest structural deficits as a percentage of own-
    source revenues. The figure shows that, if the District*s actual
    structural deficit is Revenue Capacity

    close to our lower estimate, then it is not much different than the
    deficits of most of the state fiscal systems in the top 10 as a percentage
    of own- source revenue capacity. However, if the District*s actual
    structural deficit is close to our higher estimate, then it is much larger
    as a percentage of own- source revenue than the deficits of any state
    fiscal system.

    Figure 10: Fiscal Systems with the Largest Structural Deficits as a
    Percentage of Own- Source Revenue Capacity 45

    Percentage of own- source revenue capacity (national average = 0)

    40 35 30 25 20 15 10

    5 0

    District of Alabama Arizona Arkansas California Georgia Louisiana
    Mississippi New Mexico New York Oklahoma Texas Columbia Fiscal system

    State services, TTR capacity Urban services, RTS *Low* capacity Source:
    GAO.

    Note: GAO analysis based on methodologies described in apps. I and II.

    The District*s Deferred Maintenance and

    Appendi x IV

    Acquisitions Projects Table 18: The District*s Capital Improvement
    Program: Deferred Maintenance Projects and Costs for Fiscal Year 2003 and
    Fiscal Years 2003 through 2008

    Agency 6- year Agency 1- year request for request for fiscal years Project
    name

    fiscal year 2003 2003- 2008

    Office of Property Management

    D. C. Warehouse - Mechanical Upgrade $470,000 $720, 000 Recorder of Deeds
    - Complete Modernization 0 4,640, 000

    Government Centers - New DMV Facility 2, 500,000 7,500, 000 Government
    Centers - Improve Property Management ITS 0 4,500, 000

    Government Centers - Government Centers 15, 000,000 15,000, 000

    Subtotal $17, 970,000 $32,360, 000 Office of the Chief Financial Officer

    410 E Street Renovation $1, 235,000 $9,000, 000

    Subtotal $1, 235,000 $9,000, 000 Office of the Secretary

    Archives Project - Modernization/ Renovation 0 $3,386, 000

    Subtotal 0 $3,386, 000 Metropolitan Police Department

    3rd District Station New Building - Mod/ Renovation $7, 739,874 $12,571,
    902

    6th District Station New Building - Mod/ Renovation 7, 739,874 12,571, 902

    Municipal Center Renovation 16, 243,034 86,873, 258 Evidentiary Property
    Warehouse 5, 053,726 5,053, 726 SOD Consolidation New Building 12, 475,070
    20,472, 353 Multi- Function Facility 5, 259,842 5,259, 842

    Subtotal $54, 511,420 $142,802, 983 Fire and Emergency Medical Services
    Department

    Engine 5 - Complete Renovation/ Modern's $569,320 $2,724, 919 Engine 12 -
    Haz Mat Unit Facility 263,386 491, 771 Disaster Vehicle Facility 1,
    083,397 2,088, 094

    Subtotal $1, 916,103 $5,304, 784 Department of Corrections

    Exterior Structural Finishing $136,500 $1,184, 000 Storage Space Const.
    Outside R& D 4, 005,000 4,005, 000

    (Continued From Previous Page)

    Agency 6- year Agency 1- year request for request for fiscal years Project
    name

    fiscal year 2003 2003- 2008

    Lot Adjacent to CDF Parking Lot Construction 708,000 7,104, 000

    Subtotal $4, 849,500 $12,293, 000 District of Columbia Public Schools

    Distribution Piping Upgrade $27, 257,986 $245,321, 872 Terminal Unit
    Systems 13, 642,583 122,783, 250 Heating Plant Replacement 24, 768,994
    222,920, 944 Boiler Plant Overhauls 2, 172,598 19,553, 380 Central Air
    Handling Systems 4, 172,078 37,548, 699 Cooling Plant Replacement 7,
    574,589 68,171, 302 Generator System Replacement 1, 547,771 13,929, 935
    Electrical System Replacement 1, 019,168 9,172, 509 Fire Alarm, Intercom,
    Master Clock Upgrades 35, 977,562 323,798, 054

    Corrective Maintenance (Carpentry, Welding, Plumbing etc) 7, 193,651
    64,742, 858 Corrective Maintenance (Grounds) 684,461 6,160, 153

    Subtotal $126, 011,440 $1, 134,102, 956 University of the District of
    Columbia

    Building 46E Auditorium $550,000 $6,650, 000 Building 32 - Cooling Plants
    - HVAC 223,000 1,846, 000 Building 38 - Cooling Plants - HVAC 165,000
    2,142, 000 Building 39 - Cooling Plants - HVAC 165,000 2,142, 000 Building
    41 - Cooling Plants - HVAC 165,000 2,142, 000 Building 42 - Cooling Plants
    - HVAC 223,000 1,846, 000 Building 44 - Cooling Plants - HVAC 200,000 800,
    000 Building 46W - Cooling Plants - HVAC 125,000 900, 000 Building 47 -
    Cooling Plants - HVAC 130,000 970, 000

    Subtotal $1, 946,000 $19,438, 000 Department of Parks and Recreation

    Lammond Recreation Center $1, 807,000 $4,432, 000 Mitchell Park
    Renovations 1, 940,000 1,940, 000 Aquatic Center New Construction 1,
    317,000 4,600, 000 Douglas Recreation/ Aquatic 1, 680,000 10,272, 000
    Georgetown Pool Renovations 2, 445,000 2,445, 000 General Improvements
    Mitchell Park 200,000 1,000, 000

    (Continued From Previous Page)

    Agency 6- year Agency 1- year request for request for fiscal years Project
    name

    fiscal year 2003 2003- 2008

    Subtotal $9, 389,000 $24,689, 000 Department of Health

    JB Johnson Facility - Renovation 0 $705, 000 Asbestos Abatement - Asbestos
    Abatement $1, 000,000 3,000, 000 Lighting System Retrofit 1, 200,000
    1,200, 000 Fire Alarm Systems - Fire Alarm Systems 650,000 850, 000
    Security Monitoring System 450,000 450, 000 Chiller Room Ceiling 460,000
    460, 000 Upgrade Mechanical Air Duct System 850,000 1,000, 000 Plumbing
    System Upgrade 485,000 1,000, 000 Building Renovation 550,000 550, 000
    Elevator Modernization 28 & 29 50,000 50, 000

    Subtotal $5, 695,000 $9,265, 000 Department of Human Services

    Bundy School Upgrade $3, 000,000 $3,000, 000 Blair Shelter - Complete
    Modernization 175,000 1,288, 000 Crummel School 0 4,417, 000

    Subtotal $3, 175,000 $8,705, 000 Department of Public Works

    Snow Equipment Dry Storage Building $425,000 $4,935, 000 Recycling
    Collection Expansion 3, 370,400 4,270, 400 Sweeper Repair and Storage
    Garage 2, 340,000 3,600, 000 Packer Storage Facility @ W Va Ave., NE 2,
    100,000 20,000, 000

    Subtotal $8, 235,400 $32,805, 400 Department of Mental Health

    Elevator Modernization $2, 000,000 $2,000, 000 Renovation - HVAC 4,
    500,000 4,500, 000 Tunnel Repair - Structural Work 500,000 500, 000 North
    Center Repair/ Replacement 14, 400,000 14,400, 000 Replace Generator -
    Emergency System 100,000 100, 000 Allison Relocation - Site Preparation 1,
    742,000 1,752, 150

    Subtotal $23, 242,000 $23,252, 150 Department of Transportation

    Bridge Rehabilitation $78, 000,000 $470,000, 000 Series Street Light
    Conversion 4, 000,000 21,000, 000

    (Continued From Previous Page)

    Agency 6- year Agency 1- year request for request for fiscal years Project
    name

    fiscal year 2003 2003- 2008

    Street Light Pole Replacement 750,000 4,500, 000 Alley Paving and Sidewalk
    25, 000,000 125,000, 000 Street Resurfacing 5, 000,000 25,000, 000

    Subtotal $112, 750,000 $645,500, 000 Office of the Chief Technology
    Officer

    Tech City - Infrastructure Support System 0 $9,100, 000 Share Facility
    Upgrade 0 800, 000

    Subtotal 0 $9,900, 000 Total $370, 925,863 $2, 112,804, 273

    Source: District of Columbia, Office of the Chief Financial Officer,
    Office of Budget and Planning.

    Table 19: The District*s Capital Improvement Program: Deferred
    Acquisitions Projects for Fiscal Year 2003 and Fiscal Years 2003 through
    2008 Agency acquisition Agency acquisition costs * 1- year costs - 6- year
    request * fiscal

    request- fiscal Project name

    year 2003 years 2003- 2008 Emergency Management Agency

    Mobile Command Vehicle and Technology $302,000 $302, 000 Backup Emergency
    Operation Center 2,000,000 2,000, 000

    Subtotal $2,302,000 $2,302, 000 D. C. Public Library

    Digital Dimension of the 21st Century Library $275,000 $2,275, 000

    Subtotal $275,000 $2,275, 000 Metropolitan Police Department

    IT- Automatic Personnel Locator $2,000,000 $3,250, 000 IT- MDC Index
    Fingerprinting 1,800,000 7,780, 000

    Subtotal $3,800,000 $11,030, 000 Fire and Emergency Medical Services
    Department

    800Mhz Metro Radio System $4,500,000 $4,500, 000

    Subtotal $4,500,000 $4,500, 000 Department of Human Services

    (Continued From Previous Page)

    Agency acquisition Agency acquisition costs * 1- year costs - 6- year

    request * fiscal request- fiscal

    Project name year 2003 years 2003- 2008

    Low Income Family Units - Site Acquisition $1,500,000 $6,000, 000 Acquire
    New Site for LaCasa Shelter 2,560,000 2,560, 000

    Subtotal $4,060,000 $8,560, 000 Department of Public Works

    Snow Event Management System $1,315,000 $1,315, 000

    Subtotal $1,315,000 $1,315, 000 Department of Mental Health

    Procurement Systems and Implementation $1,540,000 $3,000, 000

    Subtotal $1,540,000 $3,000, 000 Total $17,792,000 $32,982, 000

    Source: District of Columbia, Office of the Chief Financial Officer,
    Office of Budget and Planning.

    Appendi x V

    Information Related to the District*s Debt Tabl e 20: The District*s Total
    Outstanding General Obligation Debt Dollars in thousands

    Fiscal years 1995 1996 1997 1998 1999 2000 2001 2002

    General obligation debt $3,157,003 $2,965, 756 $3, 084,763 $3,091, 403
    $3,098,582 $3, 109,728 $2, 582,017 $2,670, 573 Water & Sewer Authority
    323,172 303, 719 282,100 114, 122 107,662 100,147 95,296 79, 070

    Total GO debt $3,480,175 $3,269, 475 $3, 366,863 $3,205, 525 $3,206,244
    $3, 209,875 $2, 677,313 $2,749, 643

    Source: District of Columbia Fiscal Year 2002 Comprehensive Annual
    Financial Report (January 27, 2003).

    Tabl e 21: The District*s Debt Per Capita for Fiscal Years 1995 through
    2002 (Actual) Year Total general obligation debt ($ 000s) Population Debt
    per capita ($)

    1995 $3, 480,175 552, 466 $6, 299 1996 3,269,475 539, 646 6,059 1997
    3,366,863 529, 895 6,354 1998 3,205,525 523, 124 6,128 1999 3,206,244 519,
    100 6,177 2000 3,209,875 572, 059 5,611 2001 2,677,313 571, 822 4,682 2002
    2,749,643 570, 898 4,816 Source: District of Columbia Fiscal Year 2002
    Comprehensive Annual Financial Report (January 27, 2003).

    Tabl e 22: The District*s Percentage of Debt Service to General Fund
    Expenditures for Fiscal Years 1995 through 2002 (Actual) and 2003 through
    2006 (Projected)

    Debt service costs Percentage of debt

    service to Fiscal

    General fund general fund Year Principal Interest charges Tot al
    expenditures expenditures

    1995 $157,308 $184,510 $3, 077 $344,895 $4, 395,388 7.85 1996 191,247
    173,807 2,650 $367,704 4, 486,273 8.20 1997 207,903 174,085 13, 567
    $395,555 4, 290,397 9.22 1998 219,435 171,430 8,997 $399,862 3, 964,246
    10. 09 1999 261,534 191,903 6,597 $460,034 4, 597,628 10. 01

    (Continued From Previous Page)

    Debt service costs Percentage of debt

    service to Fiscal

    General fund general fund Year Principal Interest charges Total
    expenditures expenditures

    2000 220,054 172,326 2,732 $395,112 5, 064,215 7.80 2001 108,725 146,043
    3,134 $257,902 5, 387,695 4.79 2002 131,750 135,688 4,744 $272,182 5,
    317,459 5.12 2003 a 137,880 166,871 N/ A $304,751

    2004 a 166,320 173,042 N/ A $339,362

    2005 a 181,165 189,352 N/ A $370,517

    2006 a 195,005 206,427 N/ A $401,432

    Source: District of Columbia Fiscal Year 2002 Comprehensive Annual
    Financial Report (January 27, 2003). a These numbers are estimates.

    Tabl e 23: The District*s Percentage of Debt Service Costs to General Fund
    Revenues for Fiscal Years 1995 through 2002 (Actual) and 2003 through 2006
    (Projected) Debt service

    General Percentage fund

    of debt revenues

    service to (local funds)

    general fund Year Principal Interest Tot al ($ 000s)

    revenues

    1995 $157,308 $184, 510 $341, 818 $2,729, 112 12. 52 1996 191,247 173, 807
    $365, 054 2,831, 637 12. 89 1997 207,903 174, 085 $381, 988 2,904, 530 13.
    15 1998 219,435 171, 430 $390, 865 3,177, 932 12. 30 1999 261,534 191, 903
    $453, 437 3,436, 873 13. 19 2000 220,054 172, 326 $392, 380 3,616, 116 10.
    85 2001 108,725 146, 043 $254, 768 3,853, 610 6.61 2002 131,750 135, 688
    $267, 438 3,666, 604 7.29 2003 a 137,880 166, 871 $304, 751 3,654, 072
    8.34 2004 a 166,320 173, 042 $339, 362 3,703, 308 9.16 2005 a 181,165 189,
    352 $370, 517 3,906, 512 9.48 2006 a 195,005 206, 427 $401, 432 4,063, 889
    9.88 Source: District of Columbia Fiscal Year 2002 Comprehensive Annual
    Financial Report (January 27, 2003). Note: Percentage of debt service
    costs to revenues is a common measure used by local governments to measure
    a municipality's capacity to issue debt. a These numbers are estimates.

    Appendi x VI Comments from the District of Columbia

    Appendi x VII

    GAO Contacts and Staff Acknowledgments GAO Contacts Expenditure analysis
    was led by Jerry Fastrup (202) 512- 7211. Revenue analysis was led by Jim
    Wozny (202) 512- 9084. Program reviews and case studies were led by Ann
    Calvaresi Barr (202) 512- 6986. Deferred infrastructure and debt capacity
    work was led by Norma Samuel (202) 512- 6905

    Acknowledgments Strategic Issues Ann Calvaresi- Barr, Assistant Director
    James Wozny, Assistant Director/ Economist Tom Yatsco, Senior Analyst- in-
    Charge Bertha Dong, Senior Analyst Phyllis Knox, Senior Analyst Donald
    Marples, Senior Economist James Whitcomb, Senior Communications Analyst
    Jennifer Gravelle, Analyst Eric Mader, Analyst

    Health Care Jerry Fastrup, Assistant Director/ Economist Robert
    Dinkelmeyer, Senior Economist Teresa Renner, Analyst Financial Management
    and

    Jeanette Franzel, Director Assurance Norma Samuel, Assistant Director
    Linda Elmore, Senior Analyst Maxine Hattery, Senior Communications Analyst
    Margaret Mills, Senior Communications Analyst Theresa Patrizio, Analyst
    John Saylor, Analyst

    Applied Research and Methods Susan Wallace, Senior Social Scientist
    Beverly A. Ross, Senior Information Technology Specialist Christopher L.
    Moriarity, PhD, Senior Mathematical Statistician Terence Lamb, Economist

    (450135)

    a

    GAO United States General Accounting Office

    GAO used a multifaceted approach to measure structural imbalance that GAO
    defines as a fiscal system*s inability to fund an average level of public
    services with revenues that it could raise with an average level of
    taxation, plus the federal aid it receives. This approach compared the
    District*s circumstances to a benchmark based on the average spending and
    tax policies of the 50 state fiscal systems (each state and its local
    governments). However, the benchmark is

    adjusted by taking into account circumstances that are beyond the control
    of state and local government officials (e. g., number of school- age
    children and value of tax bases). GAO supplemented this analysis with
    reviews of the District*s key programs to provide insights on factors
    influencing spending, and reviewed deferred infrastructure and outstanding
    debt. GAO found:

    The cost of delivering an average level of services per capita in the
    District far exceeds that of the average state fiscal system due to
    factors such as high poverty, crime, and a high cost of living. The
    District*s per capita total revenue capacity is higher than all state
    fiscal systems but not to the same extent that its costs are higher. In
    addition, its revenue capacity would be larger without constraints on its
    taxing authority, such as its inability to tax federal property or the
    income of nonresidents.

    The District faces a substantial structural deficit in that the cost of
    providing an average level of public services exceeds the amount of
    revenue it could raise by applying average tax rates. Data limitations and
    uncertainties surrounding key assumptions in our analysis made it
    difficult to determine the exact size of the District*s structural
    deficit, though it likely exceeds

    $470 million annually. Consequently, even though the District*s tax burden
    is among the highest in the nation, the resulting revenues plus federal
    grants are only sufficient to fund an average level of public services, if
    those services were delivered with average efficiency. The District*s
    significant management problems in key programs waste resources and make
    it difficult to provide even an average level of services. Examples
    include inadequate financial management, billing systems, and internal
    controls, resulting in tens of millions of dollars being wasted, and

    hindering its ability to receive federal funding. Addressing management
    problems would not offset the District*s underlying structural imbalance
    because this imbalance is determined by factors beyond the District*s
    direct control. However, addressing these management problems would help

    offset its current budget gap or increase service levels. The District
    continues to defer major infrastructure projects and capital investment
    because of its structural imbalance and its high debt level. These two
    factors make it difficult for the District to raise taxes, cut services,
    or assume additional debt. Although difficult, District officials could
    address a budget gap by taking actions such as cutting spending, raising
    taxes, and improving management efficiencies. In contrast, a structural
    imbalance is largely beyond District officials* direct control. If this
    imbalance is to be addressed, in the near term, it may be necessary to
    change federal policies to expand the District*s tax base or to

    provide additional financial support. However, given the existence of
    structural imbalances in other jurisdictions and the District*s
    significant management problems, federal policymakers face difficult
    choices regarding what changes, if any, they should make in their
    financial relationship with the District. District officials have recently
    reported both a budget gap and a more permanent structural imbalance
    between costs and

    revenue raising capacity. They maintain that the structural imbalance
    largely stems from the federal government*s presence and restrictions on
    the District*s tax base. Accordingly, at various times District officials
    have asked the Congress for additional funds and

    other measures to enhance revenues. In a preliminary September 2002
    report, GAO concluded that the District had not provided sufficient data
    and

    analysis to discern whether, or to what extent, it is facing a structural
    imbalance. At that time, GAO also agreed to perform a more comprehensive
    analysis and was asked to (1) determine whether, or to what extent, the
    District faces a structural imbalance between its revenue capacity and its
    public service responsibilities, (2) identify any significant constraints
    on the

    District*s revenue capacity, (3) discuss factors beyond the control of
    District officials that influence the District*s spending in key program
    areas as well as factors within its control, such as management problems,
    and (4) report on the District*s deferred

    infrastructure projects and outstanding debt service and related expenses
    that might be affected by a structural imbalance.

    The District concurred with our key findings.

    www. gao. gov/ cgi- bin/ getrpt? GAO- 03- 666. To view the full report,
    including the scope and methodology, click on the link above. For more
    information, contact Patricia A. Dalton at (202) 512- 6806 or daltonp@
    gao. gov. Highlights of GAO- 03- 666, a report to the

    Ranking Minority Member, Subcommittee on the District of Columbia,
    Committee on Appropriations, United States Senate; and the Honorable
    Eleanor Holmes Norton, House of Representatives May 2003

    DISTRICT OF COLUMBIA

    Structural Imbalance and Management Issues

    Page i GAO- 03- 666 District of Columbia

    Contents

    Contents

    Page ii GAO- 03- 666 District of Columbia

    Contents

    Page iii GAO- 03- 666 District of Columbia

    Contents

    Page iv GAO- 03- 666 District of Columbia

    Contents

    Page v GAO- 03- 666 District of Columbia

    United States General Accounting Office Washington, D. C. 20548 Page 1
    GAO- 03- 666 District of Columbia

    A

    May 22, 2003 Transmi t tal Lett er

    The Honorable Mary Landrieu Ranking Minority Member Subcommittee on the
    District of Columbia Committee on Appropriations United States Senate The
    Honorable Eleanor Holmes Norton House of Representatives In response to
    your request, this report discusses the results of our review of the
    District of Columbia*s (the District) reported structural imbalance
    between its revenue capacity and the cost of meeting its public service
    responsibilities. Specifically, it provides information on the nature of
    the District*s structural imbalance as well as information on significant
    constraints on its revenue capacity; costs conditions that are beyond the
    control of District officials and management challenges in key program
    areas; and the District*s ability to fund infrastructure projects and pay
    related debt.

    We are sending copies of this report to other appropriate congressional
    committees, the Mayor and Chief Financial Officer of the District of
    Columbia, and other interested parties. We will also make copies available
    to others upon request. This report will also be available at no charge on
    the GAO

    Web site at http:// www. gao. gov. If you or your staffs have any
    questions on this report, please call me on (202) 512- 6737 or Ann
    Calvaresi Barr, Assistant Director, on (202) 512- 6986. Key contributors
    are listed in appendix VII.

    Patricia A. Dalton Director, Strategic Issues

    Page 2 GAO- 03- 666 District of Columbia

    Executive Summary Page 3 GAO- 03- 666 District of Columbia

    Executive Summary Page 4 GAO- 03- 666 District of Columbia

    Executive Summary Page 5 GAO- 03- 666 District of Columbia

    Executive Summary Page 6 GAO- 03- 666 District of Columbia

    Executive Summary Page 7 GAO- 03- 666 District of Columbia

    Executive Summary Page 8 GAO- 03- 666 District of Columbia

    Executive Summary Page 9 GAO- 03- 666 District of Columbia

    Executive Summary Page 10 GAO- 03- 666 District of Columbia

    Executive Summary Page 11 GAO- 03- 666 District of Columbia

    Executive Summary Page 12 GAO- 03- 666 District of Columbia

    Executive Summary Page 13 GAO- 03- 666 District of Columbia

    Executive Summary Page 14 GAO- 03- 666 District of Columbia

    Executive Summary Page 15 GAO- 03- 666 District of Columbia

    Executive Summary Page 16 GAO- 03- 666 District of Columbia

    Executive Summary Page 17 GAO- 03- 666 District of Columbia

    Page 18 GAO- 03- 666 District of Columbia

    Chapter 1

    Chapter 1 Introduction

    Page 19 GAO- 03- 666 District of Columbia

    Chapter 1 Introduction

    Page 20 GAO- 03- 666 District of Columbia

    Chapter 1 Introduction

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    Chapter 1 Introduction

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    Chapter 1 Introduction

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    Chapter 1 Introduction

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    Chapter 1 Introduction

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    Chapter 1 Introduction

    Page 26 GAO- 03- 666 District of Columbia

    Chapter 1 Introduction

    Page 27 GAO- 03- 666 District of Columbia

    Chapter 1 Introduction

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    Chapter 1 Introduction

    Page 29 GAO- 03- 666 District of Columbia

    Chapter 1 Introduction

    Page 30 GAO- 03- 666 District of Columbia

    Page 31 GAO- 03- 666 District of Columbia

    Chapter 2

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 32 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 33 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 34 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 35 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 36 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 37 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 38 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 39 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 40 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 41 GAO- 03- 666 District of Columbia

    Chapter 2 The District*s Cost of Meeting Its Public Service
    Responsibilities Exceeds Its Revenue Capacity, Resulting in a Structural
    Deficit

    Page 42 GAO- 03- 666 District of Columbia

    Page 43 GAO- 03- 666 District of Columbia

    Chapter 3

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 44 GAO- 03- 666 District of Columbia

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 45 GAO- 03- 666 District of Columbia

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 46 GAO- 03- 666 District of Columbia

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 47 GAO- 03- 666 District of Columbia

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 48 GAO- 03- 666 District of Columbia

    Chapter 3 The District*s Revenue Capacity Would Be Even Higher in the
    Absence of Several Constraints on Its Taxing Authority

    Page 49 GAO- 03- 666 District of Columbia

    Page 50 GAO- 03- 666 District of Columbia

    Chapter 4

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 51 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 52 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 53 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 54 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 55 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 56 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 57 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 58 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 59 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 60 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 61 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 62 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 63 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 64 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 65 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 66 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 67 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 68 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 69 GAO- 03- 666 District of Columbia

    Chapter 4 The District Faces High Cost Conditions and Significant
    Management Problems

    Page 70 GAO- 03- 666 District of Columbia

    Page 71 GAO- 03- 666 District of Columbia

    Chapter 5

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 72 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 73 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 74 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 75 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 76 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 77 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 78 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 79 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 80 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 81 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 82 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 83 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 84 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 85 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 86 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 87 GAO- 03- 666 District of Columbia

    Chapter 5 The District Continues to Defer Infrastructure Projects While
    Debt Pressures Remain

    Page 88 GAO- 03- 666 District of Columbia

    Page 89 GAO- 03- 666 District of Columbia

    Appendix I

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 90 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 91 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 92 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 93 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 94 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 95 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 96 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 97 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 98 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 99 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 100 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 101 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 102 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 103 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 104 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 105 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 106 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 107 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 108 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 109 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 110 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 111 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 112 GAO- 03- 666 District of Columbia

    Appendix I Methodology for Calculating the Cost of Providing a
    Representative Basket of Public

    Services Page 113 GAO- 03- 666 District of Columbia

    Page 114 GAO- 03- 666 District of Columbia

    Appendix II

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 115 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 116 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 117 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 118 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 119 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 120 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 121 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 122 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 123 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 124 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 125 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 126 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 127 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 128 GAO- 03- 666 District of Columbia

    Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

    Page 129 GAO- 03- 666 District of Columbia

    Page 130 GAO- 03- 666 District of Columbia

    Appendix III

    Appendix III Computation of the District*s Structural Deficit

    Page 131 GAO- 03- 666 District of Columbia

    Appendix III Computation of the District*s Structural Deficit

    Page 132 GAO- 03- 666 District of Columbia

    Page 133 GAO- 03- 666 District of Columbia

    Appendix IV

    Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

    Page 134 GAO- 03- 666 District of Columbia

    Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

    Page 135 GAO- 03- 666 District of Columbia

    Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

    Page 136 GAO- 03- 666 District of Columbia

    Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

    Page 137 GAO- 03- 666 District of Columbia

    Page 138 GAO- 03- 666 District of Columbia

    Appendix V

    Appendix V Information Related to the District*s Debt

    Page 139 GAO- 03- 666 District of Columbia

    Page 140 GAO- 03- 666 District of Columbia

    Appendix VI

    Appendix VI Comments from the District of Columbia Page 141 GAO- 03- 666
    District of Columbia

    Appendix VI Comments from the District of Columbia Page 142 GAO- 03- 666
    District of Columbia

    Appendix VI Comments from the District of Columbia Page 143 GAO- 03- 666
    District of Columbia

    Appendix VI Comments from the District of Columbia Page 144 GAO- 03- 666
    District of Columbia

    Page 145 GAO- 03- 666 District of Columbia

    Appendix VII

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