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

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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

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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

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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

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Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

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Appendix II Revenue Capacity Analysis: Methodology and Detailed Estimates

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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

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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

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Page 130 GAO- 03- 666 District of Columbia

Appendix III

Appendix III Computation of the District*s Structural Deficit

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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

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Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

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Appendix IV The District*s Deferred Maintenance and Acquisitions Projects

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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

GAO*s Mission The General Accounting Office, the audit, evaluation and
investigative arm of Congress, exists to support Congress in meeting its
constitutional responsibilities

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