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Report to Congressional Requesters:

May 2003:

DISTRICT OF COLUMBIA:

Structural Imbalance and Management Issues:

GAO-03-666:

GAO Highlights:

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 

Why GAO Did This Study:

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 governments presence and restrictions on the 
Districts 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 Districts revenue capacity, 
(3) discuss factors beyond the control of District officials that 
influence the Districts spending in key program areas as well as 
factors within its control, such as management problems, and 
(4) report on the Districts 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. 

What GAO Found:

GAO used a multifaceted approach to measure structural imbalance that 
GAO defines as a fiscal systems 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 Districts 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 Districts 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 Districts 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 Districts structural 
deficit, though it likely exceeds $470 million annually. Consequently, 
even though the Districts 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 Districts 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 
Districts underlying structural imbalance because this imbalance is 
determined by factors beyond the Districts 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 Districts tax base or to provide 
additional financial support. However, given the existence of 
structural imbalances in other jurisdictions and the Districts 
significant management problems, federal policymakers face difficult 
choices regarding what changes, if any, they should make in their 
financial relationship with the District. 

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.

[End of section]

Transmittal Letter:

Executive Summary:

Purpose:

Background:

Results in Brief:

Principal Findings:

Concluding Observations:

District of Columbia Comments:

Chapter 1: Introduction:

Characteristics of the District:

The District's Fiscal Relationship with the Federal Government:

Reports on the District's Unique Circumstances, Fiscal Health, and 
Management Problems:

The Economic Slowdown and the District's Finances:

Scope and Methodology:

Chapter 2: The District's Cost of Meeting Its Public Service 
Responsibilities Exceeds Its Revenue Capacity, Resulting in a 
Structural Deficit:

The Spending Necessary to Fund an Average Basket of Public Services 
Exceeds That of All State Fiscal Systems:

The District's Per Capita Total and Own-Source Revenue Capacities Are 
High Relative to Those of State Fiscal Systems:

The District's Structural Deficit Results from a High Cost of Funding 
an Average Level of Services:

The District's High Tax Burden Yields Revenues That Could Only Support 
an Average Level of Services:

Chapter 3: The District's Revenue Capacity Would Be Even Higher in the 
Absence of Several Constraints on Its Taxing Authority:

The Federal Prohibition against a District Tax on the Income of 
Nonresidents Is Unique:

The District's Property Tax Base Is Relatively Large despite the 
Disproportionate Presence of Properties Owned by the Federal and 
Foreign Governments:

District Officials Believe That the Federally Imposed Height 
Restriction on Buildings Also Limits the District's Property Tax Base:

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

Chapter 4: The District Faces High Cost Conditions and Significant
Management Problems:

Special Circumstances and Management Problems Influence High Medicaid 
Costs in the District:

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

The District Faces Significant Public Safety Demands due to the Federal 
Presence, but Related Costs Are Not Adequately Tracked:

Chapter 5: The District Continues to Defer Infrastructure Projects 
While Debt Pressures Remain:

District Infrastructure Continues to Be Deferred:

District Debt Pressures Remain:

Selected District Debt Statistics Compared to Other 
Jurisdictions:

Appendixes:

Appendix I: Methodology for Calculating the Cost of Providing a 
Representative Basket of Public Services:

Defining a Representative Basket of Public Services: The Rafuse/ACIR 
Method:

Limitations to the Interpretation of the Representative Expenditure 
Model:

Modifications to the Rafuse Methodology:

Appendix II: Revenue Capacity Analysis: Methodology and Detailed
Estimates:

Estimating Grants Associated with Average Services:

Estimating Own-Source Revenue Capacity:

Details on Individual Taxes:

Resulting Estimates of the District's Own-Source Revenue Capacity 

Appendix III: Computation of the District's Structural Deficit:

The Structural Deficit Computation:

Deficit as a Percentage of Own-Source Revenue Capacity:

Appendix IV: The District's Deferred Maintenence and Acquisitions
Projects:

Appendix V: Information Related to the District's Debt:

Appendix VI: Comments from the District of Columbia:

Appendix VII: GAO Contacts and Staff Acknowledgments:

Tables:

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

Table 2: Significant Statutes or Actions That Affected the District's 
Fiscal Relationship with the Federal Government since Home Rule:

Table 3: Recent Reports on the District's Fiscal and Management 
Problems:

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

Table 5: The District's Estimated Per Capita Cost of Funding an Average 
Basket of Public Services, Fiscal Year 2000:

Table 6: Estimated Size of the District's Structural Deficit in Fiscal 
Year 2000, Using Alternative Measures and Estimation Approaches:

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

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

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

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

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

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

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

Table 14: RES Workload Indicators and Weights by Expenditure Category:

Table 15: Modifications of Workload Indicators:

Table 16: RTS Estimates of the District's Own-Source Revenue Capacity:

Table 17: Computation of the District's Structural Deficit under 
Alternative Estimation Approaches, Using Fiscal Year 2000 Data:

Table 18: The District's Capital Improvement Program: Deferred 
Maintenance Projects and Costs for Fiscal Year 2003 and Fiscal Years 
2003 through 2008:

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:

Table 21: The District's Debt Per Capita for Fiscal Years 1995 through 
2002 (Actual):

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):

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):

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):

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

Figure 3: Fiscal Systems with the Largest Structural Deficits Per 
Capita:

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

Figure 5: The District's Total Outstanding General Obligation Debt for 
Fiscal Years 1995 through 2002:

Figure 6: The District's Debt Per Capita for 1995 through 2002:

Figure 7: The District's Percentage of Debt Service Costs to Total 
General Fund Expenditures for 1995 through 2002 (Actual):

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):

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

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

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:

Transmittal Letter May 22, 2003:

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:

Signed by Patricia A. Dalton:

[End of section]

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 Imbalance:

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

The District has reported both a current services and a more permanent 
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.[Footnote 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.[Footnote 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 Methodology--Representative Services:

GAO used a representative services analysis to determine whether and to 
what extent the District has a structural imbalance. This approach 
allowed 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 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 Services:

Determining the appropriate benchmarks for the District's spending is 
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 Representative Services:

To calculate the cost of providing a representative level of public 
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 
own-source 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 Imbalance:

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 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 Costs Are the Highest in the Nation:

Using other state fiscal systems as a benchmark, GAO's analysis 
indicates that the cost of delivering an average level of services per 
capita in the 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 Capacity Is among the Highest in the Nation, 
despite Some Constraints on Its Taxing Authority:

GAO's analysis indicated that the District's per capita total revenue 
and own-source revenue capacities are higher than those of all but a 
few state fiscal systems. Its capacity is high even though the District 
faces some significant constraints on its taxing authority, such as the 
inability to tax federal property or the income of nonresidents who 
work in the District. 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 Structural Deficit:

Using a representative services analysis (which compares the District's 
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, the District's Revenues Are Only Sufficient 
to Fund an Average Level of Services:

In addition to having a high revenue capacity, the District also 
imposes above-average tax rates; however, high taxes are only 
sufficient to fund an average level of services. Because of its high 
tax rates, actual revenues 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 Result in Unnecessary Spending That Compromises the 
District's Ability to Provide an Average Level of Public Services:

The District's long-standing management problems waste resources that 
it cannot afford to lose and draw resources away from providing even an 
average level of services. In three key program areas (Medicaid, 
elementary and secondary education, and police and fire services), GAO 
identified significant management problems, such as inadequate 
financial management, billing systems, and internal controls. While the 
District has taken some actions to correct management inefficiencies, 
more 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 Defer Improvements to Its Infrastructure 
While Debt Pressures Remain:

Although the District is making some attempts to address its backlog of 
infrastructure projects, it has nonetheless continued to defer 
significant amounts of infrastructure projects because of constraints 
in its operating 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 Observations:

Due to a combination of its significant management problems and its 
substantial structural deficit, the District is likely providing a 
below-average 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 Comments:

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

[End of section]

Chapter 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.[Footnote 3] 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 District:

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

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

Characteristics: Percentage of population under 19 years; District of 
Columbia: 24; United States: 29.

Characteristics: Percentage of population 65 years and older; District 
of Columbia: 12; United States: 12.

Characteristics: Percentage of population by race:

Characteristics: * White; District of Columbia: 31; United States: 75.

Characteristics: * Black or African-American; District of Columbia: 60; 
United States: 12.

Characteristics: Estimated median household income; District of 
Columbia: $40,926; United States: $41,486.

Characteristics: Percentage of individuals below poverty; District of 
Columbia: 18; United States: 12.

Source: U.S. Census Bureau.

[End of table]

The District's Fiscal Relationship with the Federal Government:

The fiscal relationship between the federal government and the District 
has been a subject of perennial debate. Although the U.S. Constitution 
gives the Congress exclusive legislative authority and control over the 
District as the seat of the federal government,[Footnote 4] 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.

Table 2: Significant Statutes or Actions That Affected the District's 
Fiscal Relationship with the Federal Government since Home Rule:

Federal statutes or actions[A]: The District of Columbia Self-
Government Reorganization Act of 1973[B] (subsequently renamed the 
District of Columbia Home Rule Act); Purpose of statute or action: 
Provided for an elected mayor and city council. However, the District 
cannot obligate or spend funds unless appropriated by an act of the 
Congress. The act also continued the annual payment to the District, 
but the actual amount appropriated was within the discretion of the 
Congress; Implementation of statute or action: In recognition of the 
constraints on the District's revenue capacity, such as its inability 
to tax the income of nonresidents, the act required the District to 
estimate the budgetary impact of these limitations each year and to 
include in its budget submission a request for a federal payment.

Federal statutes or actions[A]: The District of Columbia Financial 
Responsibility and Management Assistance Act of 1995; Purpose of 
statute or action: Intended to restore the city to financial solvency 
and improve its management in response to a serious financial and 
management crisis. The act created a federal control board whose 
authority supplanted that of the elected mayor and city council; it 
also created a chief financial officer (CFO). The act also extended the 
powers of the District Inspector General (IG); Implementation of 
statute or action: The control board was responsible for helping the 
District recover its financial solvency and improve management 
effectiveness. The CFO was charged with developing long-term financial 
plans and 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.

Federal statutes or actions[A]: The National Capital Revitalization and 
Self-Government Improvement Act of 1997; Purpose of statute or action: 
Enacted to provide key structural changes to the District's finances 
and to repeal the annual federal payment. The act also repealed the 
provision in the Home Rule Act requiring the District to submit an 
annual federal payment request as part of its budget; Implementation 
of statute or action: The federal government assumed the District's 
unfunded pension liabilities and a larger share of its Medicaid 
expenditures. The act authorized a federal financial 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.

Federal statutes or actions[A]: In September 2001, the control board 
suspended its oversight responsibilities; Purpose of statute or 
action: The control board certified that the provisions of the 
Financial Responsibility and Management Assistance Act had been met. 
However, under the law the control board will return if any one of 
seven events occur, such as if the District fails to meet its payroll 
or if it has a cash deficit at the end of any quarter; Implementation 
of statute or action: The last of the preconditions for suspension of 
the control board was achieved in February 2001 when the fourth 
consecutive balanced budget for the 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).

[End of table]

Reports on the District's Unique Circumstances, Fiscal Health, and 
Management Problems:

Several recent reports address some of the unique challenges the 
District faces as the nation's capital, the status of its fiscal 
health, and the management inefficiencies that continue to affect its 
programs, costs, and service delivery. While these studies reach 
similar conclusions about the District's unique costs associated with 
the federal presence, as well as its 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.

Table 3: Recent Reports on the District's Fiscal and Management 
Problems:

Report: GAO's interim September 2002 report on the District's fiscal 
structural imbalance[A]; Conclusions: This report provided our 
preliminary assessment of several elements of the District's reported 
fiscal structural imbalance. The report concluded that the District had 
not provided sufficient data or analysis 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.

Report: Brookings Institution's October 2002 report[ B]; Conclusions: 
Federal restrictions on the District and the burdens associated with 
the federal presence prevent it from 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.

Report: Federal City Council report, Assessing the District of 
Columbia's Financial Position (conducted by McKinsey and Company 
2002)[C]; Conclusions: The report concludes that the District is on 
a path that will lead to a budget deficit of $500 million annually by 
2005. Factors contributing to the projected deficit include the 
economic downturn and unbudgeted spending increasing in several areas, 
including public schools, Medicaid, the Washington Metropolitan Area 
Transit Authority, and the constraints the District is faced with due 
to the presence of 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.

[End of table]

The Economic Slowdown and the District's Finances:

After the economic boom of the 1990s, all levels of government are now 
experiencing serious fiscal challenges and are likely to face even more 
fundamental ones in the future. The federal budget has moved from 
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.[Footnote 5] 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.

Similarly, states are experiencing significant, recurring revenue 
declines--estimates show state budget shortfalls of about $80 billion 
by 2004.[Footnote 6] 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.[Footnote 7]

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

Revenue source: Property taxes: Fiscal year 2000 actual: $732.0; 
Fiscal year 
2003 projected: (as of February 2003): $897.1; Change in real dollars: 
$165.1; Percentage change: 22.6.

Revenue source: Sales and use taxes: Fiscal year 2000 actual: 738.5; 
Fiscal year 
2003 projected: (as of February 2003): 708.6; Change in real dollars: -
29.9; Percentage change: -4.0.

Revenue source: Individual income taxes: Fiscal year 2000 actual: 
1,138.3; Fiscal year 
2003 projected: (as of February 2003): 924.2; Change in real dollars: -
214.1; Percentage change: -18.8.

Revenue source: Franchise taxes: Fiscal year 2000 actual: 276.0; 
Fiscal year 
2003 projected: (as of February 2003): 200.9; Change in real dollars: -
75.1; Percentage change: -27.2.

Revenue source: Gross receipts taxes: Fiscal year 2000 actual: 224.0; 
Fiscal year 
2003 projected: (as of February 2003): 250.7; Change in real dollars: 
26.7; Percentage change: 11.9.

Revenue source: Other taxes: Fiscal year 2000 actual: 149.6; Fiscal 
year 
2003 projected: (as of February 2003): 204.9; Change in real dollars: 
55.3; Percentage change: 37.0.

Revenue source: Nontax revenue[A]: Fiscal year 2000 actual: 266.7; 
Fiscal year 
2003 projected: (as of February 2003): 285.3; Change in real dollars: 
18.5; Percentage change: 6.9.

Revenue source: Total local source revenue: Fiscal year 2000 actual: 
$3,525.2; Fiscal year 
2003 projected: (as of February 2003): $3,471.7; Change in real 
dollars: -53.5; Percentage change: -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.

[End of table]

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 Methodology:

The Ranking Minority Member of the Subcommittee on the District of 
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.[Footnote 8]

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 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 
own-source 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 open-ended 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.[Footnote 9]

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 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.

[End of section]

Chapter 2: The District's Cost of Meeting Its Public Service 
Responsibilities Exceeds Its Revenue 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 (own-source 
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 Necessary to Fund an Average Basket of Public Services 
Exceeds That of All State Fiscal Systems:

Using an average of the 50 state fiscal systems as a benchmark, our 
analysis 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 approximately 75 percent (and is over a third more than the 
second highest cost fiscal system, New York). In dollar terms, the 
District would have to 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 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.[Footnote 10] 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.

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):

[See PDF for image]

Note: GAO analysis based on the methodology described in app. I.

[End of figure]

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.[Footnote 11]

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 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.

Table 5: The District's Estimated Per Capita Cost of Funding an Average 
Basket of Public Services, Fiscal Year 2000:

Expenditure function: All functions; Average basket of services: State 
basket of services: Per capita: $9,216; Average basket of services: 
State basket of services: Percentage of 
national average: 176; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: $9,783; 
Average basket of services: Urban basket of services: Percentage of 
national average: 187.

Expenditure function: Education:.

Expenditure function: Elementary & secondary; Average basket of 
services: State basket of services: Per capita: 1,576; Average basket 
of services: State basket of services: Percentage of 
national average: 118; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 1,645; 
Average basket of services: Urban basket of services: Percentage of 
national average: 118.

Expenditure function: Higher; Average basket of services: State basket 
of services: Per capita: 836; Average basket of services: State basket 
of services: Percentage of 
national average: 162; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 126; Average 
basket of services: Urban basket of services: Percentage of 
national average: 162.

Expenditure function: Public welfare:

Expenditure function: Medical vendor payments (Medicaid); Average 
basket of services: State basket of services: Per capita: 1,315; 
Average basket of services: State basket of services: Percentage of 
national average: 239; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 1,315; 
Average basket of services: Urban basket of services: Percentage of 
national average: 239.

Expenditure function: Health and hospitals; Average basket of services: 
State basket of services: Per capita: 732; Average basket of services: 
State basket of services: Percentage of 
national average: 162; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 608; Average 
basket of services: Urban basket of services: Percentage of 
national average: 162.

Expenditure function: Other public welfare; Average basket of services: 
State basket of services: Per capita: 595; Average basket of services: 
State basket of services: Percentage of 
national average: 214; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 745; Average 
basket of services: Urban basket of services: Percentage of 
national average: 213.

Expenditure function: Highways:

Average basket of services: State 
basket of services: Per capita: 234; Average basket of services: State 
basket of services: Percentage of 
national average: 65; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 119; Average 
basket of services: Urban basket of services: Percentage of 
national average: 65.

Expenditure function: Public safety:

Expenditure function: Police; Average basket of services: State basket 
of services: Per capita: 964; Average basket of services: State basket 
of services: Percentage of 
national average: 478; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 1,718; 
Average basket of services: Urban basket of services: Percentage of 
national average: 478.

Expenditure function: Corrections; Average basket of services: State 
basket of services: Per capita: 765; Average basket of services: State 
basket of services: Percentage of 
national average: 441; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 532; Average 
basket of services: Urban basket of services: Percentage of 
national average: 441.

Expenditure function: Fire protection; Average basket of services: 
State basket of services: Per capita: 157; Average basket of services: 
State basket of services: Percentage of 
national average: 192; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 275; Average 
basket of services: Urban basket of services: Percentage of 
national average: 192.

Expenditure function: Interest on Debt: Average basket of services: 
State basket of services: Per capita: 437; Average basket of services: 
State basket of services: Percentage of 
national average: 176; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 520; Average 
basket of services: Urban basket of services: Percentage of 
national average: 187.

Expenditure function: Administration: Average basket of services: State 
basket of services: Per capita: 436; Average basket of services: State 
basket of services: Percentage of 
national average: 143; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 339; Average 
basket of services: Urban basket of services: Percentage of 
national average: 136.

Expenditure function: All Other; Average basket of services: State 
basket of services: Per capita: 1,168; Average basket of services: 
State basket of services: Percentage of 
national average: 160; Average basket of services: Average 
basket of services: Urban basket of services: Per capita: 1,842; 
Average basket of services: Urban basket of services: Percentage of 
national average: 160.

Source: GAO analysis of data from the U.S. Census Bureau.

[End of table]

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 Capita Total and Own-Source Revenue Capacities Are 
High Relative to Those of State Fiscal Systems:

Our analysis indicated that the District's per capita total revenue and 
own-source 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 sum of its own-source revenue capacity (the revenue 
that it could raise from its own economic base), plus the amount of 
federal grants that the District would receive if it provided a 
representative level of services.

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.[Footnote 12] 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.

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.[Footnote 13] 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 own-source 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.[Footnote 
14]

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 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):

[See PDF for image]

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.

[End of figure]

The District's Structural Deficit Results from a High Cost of Funding 
an Average Level of Services:

The District has a structural deficit because its costs of providing an 
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 of estimating approaches and assumptions we used. We 
obtained our lowest deficit estimate of about $470 million by combining 
our lowest 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 (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 own-source revenue is sixth largest 
according to our lower estimate, and the largest according to our 
higher estimate.

Table 6: Estimated Size of the District's Structural Deficit in Fiscal 
Year 2000, Using Alternative Measures and Estimation Approaches:

State services basket;
TTR for revenue capacity; Absolute deficit (in millions): Value: $470; 
Absolute deficit (in millions): Rank: 18; Deficit per capita: 
Value: $821; Deficit per capita: Rank: 1; Deficit as a 
percentage of own-source revenue: Value: 14.4; Deficit as a percentage 
of own-source revenue: Rank: 6.

Urban services basket;
Low RTS for revenue capacity; Absolute deficit (in millions): Value: 
$1,163; Absolute deficit (in millions): Rank: 8; Deficit per 
capita: Value: $2,032; Deficit per capita: Rank: 1; Deficit as 
a percentage of own-source revenue: Value: 40.3; Deficit as a 
percentage of own-source revenue: Rank: 1.

Source: GAO.

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

[End of table]

Figures 3 shows how the District's structural deficit per capita 
compares to the state systems with the largest structural 
deficits.[Footnote 15] 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.

Figure 3: Fiscal Systems with the Largest Structural Deficits Per 
Capita:

[See PDF for image]

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

[End of figure]

The District's High Tax Burden Yields Revenues That Could Only Support 
an Average Level of Services:

The District's tax burden (actual revenues collected from local 
resources 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 fund an average level of services. The District's 
actual tax burden exceeded that of the average state fiscal system by 
33 percent, based on 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. 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:

[See PDF for image]

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

[End of figure]

[End of section]

Chapter 3: The District's Revenue Capacity Would Be Even Higher in the 
Absence of Several 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 Prohibition against a District Tax on the Income of 
Nonresidents Is Unique:

Unlike that of any state, the District's government is prohibited by 
federal law from taxing the District-source income of 
nonresidents.[Footnote 16] The 41 states that have income taxes tax the 
income of residents of at least some other states. Fifteen states 
participate in reciprocal nontaxation agreements, but no state has an 
agreement with more than 6 other states.[Footnote 17] States that 
impose income taxes also typically provide tax credits to their 
residents for income taxes paid to other states.

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 
city-source earnings. Other cities are not authorized to levy commuter 
taxes by their state governments.[Footnote 18] 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.[Footnote 19]

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.[Footnote 20] 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.

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.[Footnote 21] Another study indicates that spending by 
commuters supports jobs for District residents who are subject to the 
District's income tax.[Footnote 22]

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.[Footnote 23] 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.[Footnote 24]

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.[Footnote 25] 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 Tax Base Is Relatively Large despite the 
Disproportionate Presence of Properties Owned by the Federal and 
Foreign Governments:

Like all state and local governments, the District is unable to tax 
property owned by the federal government and foreign governments. As 
the nation's capital, the District clearly has a higher percentage of 
its total property value owned by the federal government and by foreign 
governments than most jurisdictions and, therefore, would benefit more 
than most jurisdictions if the federal government and foreign 
governments paid property taxes or made payments-in-lieu-of-taxes. 
Nevertheless, our quantitative analysis indicates that the District's 
per capita property tax base is already larger than those of all but a 
few state fiscal systems. (See app. II.):

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.[Footnote 26]

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.[Footnote 27] 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 
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 Believe That the Federally Imposed Height 
Restriction on Buildings Also Limits the District's Property Tax Base:

District officials cite the congressionally imposed height restrictions 
on buildings[Footnote 28] as another factor that constrains the 
District's property tax base. Although these restrictions may affect 
the distribution of commercial and residential buildings within the 
District, it is difficult to determine whether, or to what extent, 
these restrictions affect the aggregate amount and value of those 
buildings.

Two factors are likely to mitigate the potential negative impact on the 
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 Restrictions on Taxing Authority Are Likely to Affect 
the District Disproportionately:

In addition to the restrictions discussed above, the District is unable 
to tax the incomes or most purchases of foreign embassies and 
diplomats, purchases or sales by the federal government, the personal 
property of the United States or foreign exempt entities,[Footnote 29] 
the income of military personnel who are stationed in the District but 
claim residence in another 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.

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.

[End of section]

Chapter 4: The District Faces High Cost Conditions and 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.[Footnote 30] 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 and Management Problems Influence High Medicaid 
Costs in the District:

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 average.[Footnote 31] Certain population and delivery 
characteristics largely outside the District's control influence these 
high Medicaid costs. These characteristics include a high poverty rate 
that contributes to the large 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 long-term 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.

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 Medicaid Is Slightly More Than That Needed 
to Fund Average Levels of Coverage and Services:

The District's per capita costs of providing Medicaid services were 
more than twice the national average. However, when we adjusted for the 
District's high-cost environment, it spent only 11 percent more than 
what it 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 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 Service Delivery Characteristics Influence High 
Medicaid Costs:

Special population and service delivery characteristics create a high-
cost environment in the District, requiring it to spend substantially 
more than other jurisdictions to fund an average level of Medicaid 
coverage and 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.[Footnote 32]

Management Problems Result in the District Foregoing Significant 
Federal Matching Funds, but the District Is Taking Steps to Address 
Them:

Billing and claims management problems are forcing the District to 
forego millions in federal matching funds and, as a result, requiring 
it to use more local funds than necessary to pay for expenditures 
already incurred. Key issues that lead to rejected federal 
reimbursement claims include incomplete documentation, inadequate 
computerized billing systems, submission of reimbursement requests past 
federal deadlines, providing 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.[Footnote 33] 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 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).[Footnote 34] 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,[Footnote 35] 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.

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 Problems:

District officials have acknowledged the severity of the District's 
Medicaid 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.[Footnote 36] District officials told us they expect to use at 
least a portion of these funds during the current fiscal year.

* 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 Enhanced Medicaid Matching Support and Other 
Assistance from the Federal Government:

Recognizing the District's Medicaid situation, the federal government 
has provided additional funding, as well as technical assistance and 
other programmatic flexibilities. Most significantly, in 1997 Congress 
provided the District with a fixed, enhanced Medicaid federal medical 
assistance percentage (FMAP) of 70 percent,[Footnote 37] which has 
resulted in an influx of 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.

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

When we adjusted for the District's service costs and workload factors, 
our cost analysis suggests that the District spent 18 percent more than 
what would be necessary to fund an average level of services. However, 
our analysis was not able to take into account all of the special 
circumstances facing the District. Specifically, it is likely that 
significant management problems and disproportionately high special 
education costs are drawing resources away from elementary and 
secondary education, suggesting that 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 Spending Is Somewhat Higher Than What It Would 
Take to Fund an Average Level of Services:

We estimate that the District's elementary and secondary education 
costs were 18 percent above what it would take to fund an average level 
of services. Our analysis incorporated several workload factors that 
represent cost conditions that are largely beyond the control of 
District officials, which include the number of school age children 
(excluding those 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 Problems Are Further Drawing Resources Away from 
Educational Services:

We, along with the District IG, the District Auditor, and federal 
inspectors general have identified--and District officials have 
acknowledged--serious management problems throughout DCPS's programs 
and divisions in areas 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.[Footnote 38] 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 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 Costs May Result in Less Funding Available for 
All Other Elementary and Secondary Education Services:

Our program review revealed that the District has a high demand for 
special education and related costs, which are not adequately captured 
in our quantitative analysis. The District has a disproportionately 
large share 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 costly non-public schools; and operates under 
an array of court orders 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 1998-1999 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.[Footnote 39] 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 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-of-District 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.[Footnote 40] 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.[Footnote 41] 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 non-public 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.

The Federal Government Provides Technical Assistance to the District, 
Recognizing Its Challenges:

In recognition of the District's special circumstances and management 
problems, the federal government, to some extent, has provided 
technical assistance to the District. Specifically, Education has 
provided substantial 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.[Footnote 42] Education staff has also hosted 
conferences to help the DCPS leadership better understand their 
oversight responsibilities for federal funding programs.

The District Faces Significant Public Safety Demands due to the Federal 
Presence, but Related Costs Are Not Adequately Tracked:

The District's costs for the key public safety functions of police and 
fire protection were far above average, according to our analysis. In 
fact, the District's costs were higher for police than any other 
category. However, our analysis showed that when we adjusted for the 
District's high-cost environment, the District spent far less on both 
police and fire than it 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 capture the demands the District 
faces. Most significantly, our factors do 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 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 District's Police and Fire Spending Is Below 
Average When Its High-Cost Environment Is Considered:

According to our analysis, the District's costs of providing police 
services were very high--at four and one-half times the national 
average--as were the costs of providing fire protection services, which 
were nearly double the national average. However, our analysis 
indicated that when we 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.[Footnote 43]

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 
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 Significant Public Safety Services to the Federal 
Government, Likely Resulting in Less Spending on Services for 
Residents:

As the nation's capital, the District is continually faced with paying 
for expenses to support the federal government's presence, such as 
extra services for federal officials, including the President and Vice 
President, 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 and political demonstrations that often draw 
thousands of people, 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 Federal Officials and Dignitaries:

Although the 1973 Home Rule Act requires the District, including the 
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 Demonstrations:

District officials told us that special events and demonstrations also 
result 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.[Footnote 44]

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 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.[Footnote 45]

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 government 
has provided some funding to MPD for other capital improvements to MPD 
facilities.

Effects of Increased Terrorist Threats:

District public safety officials told us that in recent years the 
number of 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 Could Strengthen the District's Case for 
Federal Reimbursement:

The District's current cost tracking processes do not provide officials 
in MPD or FEMS, or the District CFO, with reliable financial 
information to allow them to better estimate and budget for federally 
related 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 Has Provided Some Amount of Financial 
Assistance:

Although it is unlikely that the federal government fully compensates 
the District for all related expenses, the federal government has 
provided the 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 non-District 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.

[End of section]

Chapter 5: The District Continues to Defer Infrastructure 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-of-date 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[Footnote 
46] 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 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 Continues to Be Deferred:

The District is deferring significant amounts of capital projects by 
not funding or taking action on specific repairs and improvements to 
the District's infrastructure. For the 6-year period fiscal years 2003 
through 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[Footnote 47] 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.

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

Agency: District of Columbia Public Schools; Deferred maintenance 
fiscal year 2003, capital improvement plan: $126,011,441; Deferred 
maintenance: fiscal years 2003-08: $1,134,102,956.

Agency: Department of Transportation; Deferred maintenance fiscal year 
2003, capital improvement plan: 112,750,000; Deferred maintenance: 
fiscal years 2003-08: 645,500,000.

Agency: Metropolitan Police Department; Deferred maintenance fiscal 
year 2003, capital improvement plan: 54,511,420; Deferred maintenance: 
fiscal years 2003-08: 142,802,983.

Agency: Department of Mental Health; Deferred maintenance fiscal year 
2003, capital improvement plan: 23,242,000; Deferred maintenance: 
fiscal years 2003-08: 23,252,150.

Agency: Office of Property Management; Deferred maintenance fiscal year 
2003, capital improvement plan: 17,970,000; Deferred maintenance: 
fiscal years 2003-08: 32,360,000.

Agency: Department of Parks & Recreation; Deferred maintenance fiscal 
year 2003, capital improvement plan: 9,389,000; Deferred maintenance: 
fiscal years 2003-08: 24,689,000.

Agency: Department of Public Works; Deferred maintenance fiscal year 
2003, capital improvement plan: 8,235,400; Deferred maintenance: fiscal 
years 2003-08: 32,805,400.

Agency: Department of Health; Deferred maintenance fiscal year 2003, 
capital improvement plan: 5,695,000; Deferred maintenance: fiscal years 
2003-08: 9,265,000.

Agency: Department of Corrections; Deferred maintenance fiscal year 
2003, capital improvement plan: 4,849,500; Deferred maintenance: fiscal 
years 2003-08: 12,293,000.

Agency: Department of Human Services; Deferred maintenance fiscal year 
2003, capital improvement plan: 3,175,000; Deferred maintenance: fiscal 
years 2003-08: 8,705,000.

Agency: University of the District of Columbia; Deferred maintenance 
fiscal year 2003, capital improvement plan: 1,946,000; Deferred 
maintenance: fiscal years 2003-08: 19,438,000.

Agency: Fire and Emergency Medical Services Department; Deferred 
maintenance fiscal year 2003, capital improvement plan: 1,916,103; 
Deferred maintenance: fiscal years 2003-08: 5,304,784.

Agency: Office of the Chief Financial Officer; Deferred maintenance 
fiscal year 2003, capital improvement plan: 1,235,000; Deferred 
maintenance: fiscal years 2003-08: 9,000,000.

Agency: Office of the Chief Technology Officer; Deferred maintenance 
fiscal year 2003, capital improvement plan: 0; Deferred maintenance: 
fiscal years 2003-08: 9,900,000.

Agency: Office of the Secretary; Deferred maintenance fiscal year 2003, 
capital improvement plan: 0; Deferred maintenance: fiscal years 2003-
08: 3,386,000.

Agency: Total; Deferred maintenance fiscal year 2003, capital 
improvement plan: $370,925,864; Deferred maintenance: fiscal years 
2003-08: $2,112,804,273.

Source: District of Columbia, Office of the Chief Financial Officer, 
Office of Budget and Planning.

Note: Differences due to rounding.

[End of table]

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.

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

Overview: Total number of projects approved for the 6-year period; 
Amount: 229.

Overview: Number of ongoing projects; Amount: 192.

Overview: Number of new projects; Amount: 37.

Overview: Total fiscal year 2003 planned funding; Amount: $881,428,000.

Overview: Total fiscal year 2003 planned expenditures; Amount: 
$881,428,000.

Overview: Total fiscal year 2003 to fiscal year 2008 planned funding; 
Amount: $3,332,700,000.

Overview: Total fiscal year 2003 to fiscal year 2008 planned 
expenditures; Amount: $3,332,700,000.

Overview: Fiscal year 2003 appropriated budget authority request[A]; 
Amount: $639,069,780.

Overview: Fiscal year 2003 appropriated budget authority (actual); 
Amount: $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.

[End of table]

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[Footnote 48] 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.

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

Capital projects: Unapproved projects: 

Capital projects: Deferred maintenance projects; Number of projects: 
Unapproved projects: 80; Fiscal year: 2003 costs: Unapproved 
projects: $ 371 million; Fiscal year: 2003-08 costs: $ 2.1 billion.

Capital projects: Other deferred infrastructure; projects; Number of 
projects: Unapproved projects: 35; Fiscal year: 2003 costs: Unapproved 
projects: 51 million; Fiscal year: 2003-08 costs: 345 million.

Capital projects: Subtotal unapproved projects; Number of projects: 
Unapproved projects: 115; Fiscal year: 2003 costs: Unapproved 
projects: 422 million; Fiscal year: 2003-08 costs: 2.5 billion.

Capital projects: Approved projects:

Number of projects: 229; Fiscal year: 2003 costs: 881 
million; Fiscal year: 2003-08 costs: 3.3 billion.

Capital projects: Total all projects; Number of projects: 344; Fiscal 
year: 2003 costs: $1.3 
billion; Fiscal year: 2003-08 costs: $ 5.8 billion.

Capital projects: Unapproved projects as a percentage of total 
identified needs; Fiscal year: 2003 costs: 32.5%; 
Fiscal year: 2003-08 costs: 43.1%.

Source: District of Columbia, Office of the Chief Financial Officer, 
Office of Budget and Planning.

Note: Differences due to rounding.

[End of table]

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: Deferred Acquisition Projects:

Agency: Metropolitan Police Department; Agency costs - 
1-year request 
fiscal year 2003: $3,800,000; Agency costs -: 6-year request fiscal 
year 2003-08: $11,030,000.

Agency: Fire and Emergency Medical Services Department; Agency costs - 
1-year request 
fiscal year 2003: 4,500,000; Agency costs -: 6-year request fiscal year 
2003-08: 4,500,000.

Agency: Department of Human Services; Agency costs - 
1-year request 
fiscal year 2003: 4,060,000; Agency costs -: 6-year request fiscal year 
2003-08: 8,560,000.

Agency: Emergency Management Agency; Agency costs - 
1-year request 
fiscal year 2003: 2,302,000; Agency costs -: 6-year request fiscal year 
2003-08: 2,302,000.

Agency: Department of Public Works; Agency costs - 
1-year request 
fiscal year 2003: 1,315,000; Agency costs -: 6-year request fiscal year 
2003-08: 1,315,000.

Agency: Department of Mental Health; Agency costs - 
1-year request 
fiscal year 2003: 1,540,000; Agency costs -: 6-year request fiscal year 
2003-08: 3,000,000.

Agency: D.C. Public Library; Agency costs - 
1-year request 
fiscal year 2003: 275,000; Agency costs -: 6-year request fiscal year 
2003-08: 2,275,000.

Subtotal deferred acquisition projects; Agency costs - 
1-year request 
fiscal year 2003: 17,792,000; Agency costs -: 6-year request fiscal 
year 2003-08: 32,982,000.

Agency: Other deferred infrastructure and acquisition projects:

Agency: Office of the Chief Financial Officer; Agency costs - 
1-year request 
fiscal year 2003: 14,250,000; Agency costs -: 6-year request fiscal 
year 2003-08: 32,350,000.

Agency: Commission on the Arts and Humanities; Agency costs - 
1-year request 
fiscal year 2003: 1,520,000; Agency costs -: 6-year request fiscal year 
2003-08: 3,955,000.

Agency: Office of the Chief Technology Officer; Agency costs - 
1-year request 
fiscal year 2003: 3,700,000; Agency costs -: 6-year request fiscal year 
2003-08: 170,580,000.

Agency: Fire and Emergency Medical Services Department; Agency costs - 
1-year request 
fiscal year 2003: 3,193,684; Agency costs -: 6-year request fiscal year 
2003-08: 6,645,256.

Agency: Department of Human Services; Agency costs - 
1-year request 
fiscal year 2003: 5,200,000; Agency costs -: 6-year request fiscal year 
2003-08: 8,700,000.

Agency: Washington Metropolitan Area Transit Authority; Agency costs - 
1-year request 
fiscal year 2003: 0; Agency costs -: 6-year request fiscal year 2003-
08: 80,800,000.

Agency: Office of Contracts & Procurement; Agency costs - 
1-year request 
fiscal year 2003: 1,500,000; Agency costs -: 6-year request fiscal year 
2003-08: 1,500,000.

Agency: Department of Mental Health; Agency costs - 
1-year request 
fiscal year 2003: 3,500,000; Agency costs -: 6-year request fiscal year 
2003-08: 7,500,000.

Subtotal other deferred projects; Agency costs - 
1-year request 
fiscal year 2003: $32,863,684; Agency costs -: 6-year request fiscal 
year 2003-08: $312,030,256.

Total; Agency costs - 
1-year request 
fiscal year 2003: $50,655,684; Agency costs -: 6-year request fiscal 
year 2003-08: $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.


[End of table]

District Debt Pressures Remain:

There has been little change in the District's outstanding general 
obligation 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.):

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

Dollars in thousands.

General obligation bonds; Fiscal year: 2003: 
$587,833; Fiscal year: 2004: $432,541; Fiscal 
years: 2005: $320,372; Fiscal year: 2006: $258,719; Fiscal year: 
2007: $118,860; Fiscal year: 2008: $349; Total fiscal year 2003-08: 
$1,718,674; Percentage
of total fiscal year 2003-08 funding: 52.

Federal grants; Fiscal year: 2003: 208,440; 
Fiscal year: 2004: 240,950; Fiscal year: 2005: 
218,859; Fiscal year: 2006: 194,737; Fiscal year: 2007: 146,984; 
Fiscal year: 2008: 136,615; Total fiscal year 2003-08: $1,146,585; 
Percentage
of total fiscal year 2003-08 funding: 34.

Rights of way fees; Fiscal year: 2003: 36,940; 
Fiscal year: 2004: 37,950; Fiscal year: 2005: 
37,350; Fiscal year: 2006: 37,500; Fiscal year: 2007: 36,133; Fiscal 
years: 2008: 36,127; Total fiscal year 2003-08: $222,000; Percentage
of total fiscal year 2003-08 funding: 7.

Highway trust fund; Fiscal year: 2003: 38,330; 
Fiscal year: 2004: 43,544; Fiscal year: 2005: 
41,576; Fiscal year: 2006: 36,639; Fiscal year: 2007: 25,606; Fiscal 
years: 2008: 24,447; Total fiscal year 2003-08: $210,142; Percentage
of total fiscal year 2003-08 funding: 6.

Equipment lease; Fiscal year: 2003: 9,885; 
Fiscal year: 2004: 3,200; Fiscal year: 2005: 0; 
Fiscal year: 2006: 0; Fiscal year: 2007: 0; Fiscal year: 2008: 0; 
Total fiscal year 2003-08: $13,085; Percentage
of total fiscal year 2003-08 funding: .4.

Other; Fiscal year: 2003: 0; Dollars in 
thousands: Fiscal year: 2004: 11,102; Fiscal year: 2005: 11,112; 
Fiscal year: 2006: 0; Fiscal year: 2007: 0; Fiscal year: 2008: 0; 
Total fiscal year 2003-08: $22,214; Percentage
of total fiscal year 2003-08 funding: .6.

Total funding; Fiscal year: 2003: $881,428; 
Fiscal year: 2004: $769,287; Fiscal year: 2005: 
$629,269; Fiscal year: 2006: $527,595; Fiscal year: 2007: $327,583; 
Fiscal year: 2008: $197,538; Total fiscal year 2003-08: $3,332,700; 
Percentage
of total fiscal year 2003-08 funding: 100.

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

[End of table]

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 Obligation Debt:

There was little change in the District's total outstanding general 
obligation 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[Footnote 49] 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 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:

[See PDF for image]

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.

[End of figure]

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 long-term 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:

[See PDF for image]

[End of figure]

Expenditures Required to Service Outstanding Debt:

From 1995 through 1998, the District's debt service costs as a 
percentage of 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):

[See PDF for image]

Note: This ratio is commonly used by local governments to measure the 
portion of expenditures that are required to service outstanding debt.

[End of figure]

Revenue Available to Service Outstanding Debt:

The most recent calculations show that, for 2002, the District's debt 
service 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):

[See PDF for image]

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.

[End of figure]

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.[Footnote 50] 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.):

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

[See PDF for image]

[End of figure]

Selected District Debt Statistics Compared to Other Jurisdictions:

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 funds many infrastructure projects that in other 
U.S. cities would 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[Footnote 51] that is backed by 
the full faith and credit of the government entity issuing the 
debt.[Footnote 52] This portion of long-term debt is supported solely 
by the taxing authority of the entity issuing the debt.

Based on the Census data[Footnote 53] 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.[Footnote 54] 
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.):

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.[Footnote 55] Both of these percentages were higher 
than those of any state fiscal system and well above the state median 
of 38 percent.

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

District of Columbia; Full faith and credit debt outstanding ($000): 
$3,718,838; Population (000): 572; Debt per capita: $6,501; Debt as a 
percentage of own-source revenue capacity: Low RTS: 129; Debt as a 
percentage of own-source revenue capacity: TTR: 114.

DC (adjusted)[A]; Full faith and credit debt outstanding ($000): 
3,209,876; Population (000): 572; Debt per capita: 5,611; Debt as a 
percentage of own-source revenue capacity: Low RTS: 111; Debt as a 
percentage of own-source revenue capacity: TTR: 99.

Hawaii; Full faith and credit debt outstanding ($000): 5,270,348; 
Population (000): 1,212; Debt per capita: 4,348; Debt as a percentage 
of own-source revenue capacity: Low RTS: 104; Debt as a percentage of 
own-source revenue capacity: TTR: 107.

Connecticut; Full faith and credit debt outstanding ($000): 14,808,632; 
Population (000): 3,406; Debt per capita: 4,348; Debt as a percentage 
of own-source revenue capacity: Low RTS: 76; Debt as a percentage of 
own-source revenue capacity: TTR: 73.

Nevada; Full faith and credit debt outstanding ($000): 7,922,678; 
Population (000): 1,998; Debt per capita: 3,965; Debt as a percentage 
of own-source revenue capacity: Low RTS: 83; Debt as a percentage of 
own-source revenue capacity: TTR: 86.

Massachusetts; Full faith and credit debt outstanding ($000): 
22,766,965; Population (000): 6,349; Debt per capita: 3,586; Debt as a 
percentage of own-source revenue capacity: Low RTS: 66; Debt as a 
percentage of own-source revenue capacity: TTR: 65.

Alaska; Full faith and credit debt outstanding ($000): 2,145,416; 
Population (000): 627; Debt per capita: 3,422; Debt as a percentage of 
own-source revenue capacity: Low RTS: 59; Debt as a percentage of own-
source revenue capacity: TTR: 69.

New York; Full faith and credit debt outstanding ($000): 63,242,280; 
Population (000): 18,976; Debt per capita: 3,333; Debt as a percentage 
of own-source revenue capacity: Low RTS: 71; Debt as a percentage of 
own-source revenue capacity: TTR: 66.

Washington; Full faith and credit debt outstanding ($000): 17,921,583; 
Population (000): 5,894; Debt per capita: 3,041; Debt as a percentage 
of own-source revenue capacity: Low RTS: 66; Debt as a percentage of 
own-source revenue capacity: TTR: 68.

Minnesota; Full faith and credit debt outstanding ($000): 14,075,859; 
Population (000): 4,919; Debt per capita: 2,862; Debt as a percentage 
of own-source revenue capacity: Low RTS: 62; Debt as a percentage of 
own-source revenue capacity: TTR: 64.

Illinois; Full faith and credit debt outstanding ($000): 33,822,469; 
Population (000): 12,419; Debt per capita: 2,723; Debt as a percentage 
of own-source revenue capacity: Low RTS: 60; Debt as a percentage of 
own-source revenue capacity: TTR: 60.

Wisconsin; Full faith and credit debt outstanding ($000): 13,968,405; 
Population (000): 5,364; Debt per capita: 2,604; Debt as a percentage 
of own-source revenue capacity: Low RTS: 63; Debt as a percentage of 
own-source revenue capacity: TTR: 67.

Pennsylvania; Full faith and credit debt outstanding ($000): 
28,329,230; Population (000): 12,281; Debt per capita: 2,307; Debt as 
a percentage of own-source revenue capacity: Low RTS: 57; Debt as a 
percentage of own-source revenue capacity: TTR: 58.

Oregon; Full faith and credit debt outstanding ($000): 7,542,569; 
Population (000): 3,421; Debt per capita: 2,205; Debt as a percentage 
of own-source revenue capacity: Low RTS: 53; Debt as a percentage of 
own-source revenue capacity: TTR: 53.

Maryland; Full faith and credit debt outstanding ($000): 11,492,877; 
Population (000): 5,296; Debt per capita: 2,170; Debt as a percentage 
of own-source revenue capacity: Low RTS: 50; Debt as a percentage of 
own-source revenue capacity: TTR: 46.

Texas; Full faith and credit debt outstanding ($000): 42,816,539; 
Population (000): 20,852; Debt per capita: 2,053; Debt as a percentage 
of own-source revenue capacity: Low RTS: 53; Debt as a percentage of 
own-source revenue capacity: TTR: 51.

New Jersey; Full faith and credit debt outstanding ($000): 16,803,492; 
Population (000): 8,414; Debt per capita: 1,997; Debt as a percentage 
of own-source revenue capacity: Low RTS: 40; Debt as a percentage of 
own-source revenue capacity: TTR: 36.

Colorado; Full faith and credit debt outstanding ($000): 8,080,104; 
Population (000): 4,301; Debt per capita: 1,879; Debt as a percentage 
of own-source revenue capacity: Low RTS: 38; Debt as a percentage of 
own-source revenue capacity: TTR: 41.

Rhode Island; Full faith and credit debt outstanding ($000): 1,867,221; 
Population (000): 1,048; Debt per capita: 1,782; Debt as a percentage 
of own-source revenue capacity: Low RTS: 45; Debt as a percentage of 
own-source revenue capacity: TTR: 40.

Delaware; Full faith and credit debt outstanding ($000): 1,363,973; 
Population (000): 784; Debt per capita: 1,740; Debt as a percentage of 
own-source revenue capacity: Low RTS: 36; Debt as a percentage of own-
source revenue capacity: TTR: 32.

South Carolina; Full faith and credit debt outstanding ($000): 
6,916,351; Population (000): 4,012; Debt per capita: 1,724; Debt as a 
percentage of own-source revenue capacity: Low RTS: 48; Debt as a 
percentage of own-source revenue capacity: TTR: 51.

Arizona; Full faith and credit debt outstanding ($000): 8,753,094; 
Population (000): 5,131; Debt per capita: 1,706; Debt as a percentage 
of own-source revenue capacity: Low RTS: 45; Debt as a percentage of 
own-source revenue capacity: TTR: 47.

Michigan; Full faith and credit debt outstanding ($000): 16,583,026; 
Population (000): 9,938; Debt per capita: 1,669; Debt as a percentage 
of own-source revenue capacity: Low RTS: 40; Debt as a percentage of 
own-source revenue capacity: TTR: 43.

New Hampshire; Full faith and credit debt outstanding ($000): 
1,995,189; Population (000): 1,236; Debt per capita: 1,614; Debt as a 
percentage of own-source revenue capacity: Low RTS: 34; Debt as a 
percentage of own-source revenue capacity: TTR: 31.

Mississippi; Full faith and credit debt outstanding ($000): 4,520,007; 
Population (000): 2,845; Debt per capita: 1,589; Debt as a percentage 
of own-source revenue capacity: Low RTS: 52; Debt as a percentage of 
own-source revenue capacity: TTR: 56.

Vermont; Full faith and credit debt outstanding ($000): 964,792; 
Population (000): 609; Debt per capita: 1,584; Debt as a percentage of 
own-source revenue capacity: Low RTS: 38; Debt as a percentage of own-
source revenue capacity: TTR: 42.

Kansas; Full faith and credit debt outstanding ($000): 3,928,589; 
Population (000): 2,688; Debt per capita: 1,462; Debt as a percentage 
of own-source revenue capacity: Low RTS: 37; Debt as a percentage of 
own-source revenue capacity: TTR: 37.

Tennessee; Full faith and credit debt outstanding ($000): 8,225,817; 
Population (000): 5,689; Debt per capita: 1,446; Debt as a percentage 
of own-source revenue capacity: Low RTS: 38; Debt as a percentage of 
own-source revenue capacity: TTR: 40.

Virginia; Full faith and credit debt outstanding ($000): 10,183,759; 
Population (000): 7,079; Debt per capita: 1,439; Debt as a percentage 
of own-source revenue capacity: Low RTS: 33; Debt as a percentage of 
own-source revenue capacity: TTR: 32.

Maine; Full faith and credit debt outstanding ($000): 1,743,816; 
Population (000): 1,275; Debt per capita: 1,368; Debt as a percentage 
of own-source revenue capacity: Low RTS: 36; Debt as a percentage of 
own-source revenue capacity: TTR: 39.

Alabama; Full faith and credit debt outstanding ($000): 6,072,224; 
Population (000): 4,447; Debt per capita: 1,365; Debt as a percentage 
of own-source revenue capacity: Low RTS: 39; Debt as a percentage of 
own-source revenue capacity: TTR: 43.

Utah; Full faith and credit debt outstanding ($000): 3,002,986; 
Population (000): 2,233; Debt per capita: 1,345; Debt as a percentage 
of own-source revenue capacity: Low RTS: 37; Debt as a percentage of 
own-source revenue capacity: TTR: 38.

Ohio; Full faith and credit debt outstanding ($000): 15,229,929; 
Population (000): 11,353; Debt per capita: 1,341; Debt as a percentage 
of own-source revenue capacity: Low RTS: 33; Debt as a percentage of 
own-source revenue capacity: TTR: 35.

Louisiana; Full faith and credit debt outstanding ($000): 5,936,496; 
Population (000): 4,469; Debt per capita: 1,328; Debt as a percentage 
of own-source revenue capacity: Low RTS: 38; Debt as a percentage of 
own-source revenue capacity: TTR: 37.

California; Full faith and credit debt outstanding ($000): 44,666,627; 
Population (000): 33,872; Debt per capita: 1,319; Debt as a percentage 
of own-source revenue capacity: Low RTS: 29; Debt as a percentage of 
own-source revenue capacity: TTR: 28.

Georgia; Full faith and credit debt outstanding ($000): 10,273,721; 
Population (000): 8,186; Debt per capita: 1,255; Debt as a percentage 
of own-source revenue capacity: Low RTS: 31; Debt as a percentage of 
own-source revenue capacity: TTR: 30.

North Carolina; Full faith and credit debt outstanding ($000): 
9,701,264; Population (000): 8,049; Debt per capita: 1,205; Debt as a 
percentage of own-source revenue capacity: Low RTS: 31; Debt as a 
percentage of own-source revenue capacity: TTR: 30.

New Mexico; Full faith and credit debt outstanding ($000): 2,120,068; 
Population (000): 1,819; Debt per capita: 1,166; Debt as a percentage 
of own-source revenue capacity: Low RTS: 33; Debt as a percentage of 
own-source revenue capacity: TTR: 34.

Nebraska; Full faith and credit debt outstanding ($000): 1,711,133; 
Population (000): 1,711; Debt per capita: 1,000; Debt as a percentage 
of own-source revenue capacity: Low RTS: 24; Debt as a percentage of 
own-source revenue capacity: TTR: 25.

Iowa; Full faith and credit debt outstanding ($000): 2,919,449; 
Population (000): 2,926; Debt per capita: 998; Debt as a percentage of 
own-source revenue capacity: Low RTS: 25; Debt as a percentage of own-
source revenue capacity: TTR: 27.

Missouri; Full faith and credit debt outstanding ($000): 5,369,711; 
Population (000): 5,595; Debt per capita: 960; Debt as a percentage of 
own-source revenue capacity: Low RTS: 24; Debt as a percentage of own-
source revenue capacity: TTR: 25.

Florida; Full faith and credit debt outstanding ($000): 13,382,448; 
Population (000): 15,982; Debt per capita: 837; Debt as a percentage 
of own-source revenue capacity: Low RTS: 20; Debt as a percentage of 
own-source revenue capacity: TTR: 22.

North Dakota; Full faith and credit debt outstanding ($000): 511,520; 
Population (000): 642; Debt per capita: 797; Debt as a percentage of 
own-source revenue capacity: Low RTS: 20; Debt as a percentage of own-
source revenue capacity: TTR: 23.

South Dakota; Full faith and credit debt outstanding ($000): 587,876; 
Population (000): 755; Debt per capita: 779; Debt as a percentage of 
own-source revenue capacity: Low RTS: 18; Debt as a percentage of own-
source revenue capacity: TTR: 21.

Arkansas; Full faith and credit debt outstanding ($000): 1,991,973; 
Population (000): 2,673; Debt per capita: 745; Debt as a percentage of 
own-source revenue capacity: Low RTS: 23; Debt as a percentage of own-
source revenue capacity: TTR: 25.

Montana; Full faith and credit debt outstanding ($000): 585,007; 
Population (000): 902; Debt per capita: 649; Debt as a percentage of 
own-source revenue capacity: Low RTS: 17; Debt as a percentage of own-
source revenue capacity: TTR: 21.

Idaho; Full faith and credit debt outstanding ($000): 788,739; 
Population (000): 1,294; Debt per capita: 610; Debt as a percentage of 
own-source revenue capacity: Low RTS: 17; Debt as a percentage of own-
source revenue capacity: TTR: 17.

Wyoming; Full faith and credit debt outstanding ($000): 297,923; 
Population (000): 494; Debt per capita: 603; Debt as a percentage of 
own-source revenue capacity: Low RTS: 12; Debt as a percentage of own-
source revenue capacity: TTR: 12.

Kentucky; Full faith and credit debt outstanding ($000): 2,286,543; 
Population (000): 4,042; Debt per capita: 566; Debt as a percentage of 
own-source revenue capacity: Low RTS: 16; Debt as a percentage of own-
source revenue capacity: TTR: 16.

Indiana; Full faith and credit debt outstanding ($000): 3,271,379; 
Population (000): 6,080; Debt per capita: 538; Debt as a percentage of 
own-source revenue capacity: Low RTS: 13; Debt as a percentage of own-
source revenue capacity: TTR: 14.

West Virginia; Full faith and credit debt outstanding ($000): 710,606; 
Population (000): 1,808; Debt per capita: 393; Debt as a percentage of 
own-source revenue capacity: Low RTS: 12; Debt as a percentage of own-
source revenue capacity: TTR: 13.

Oklahoma; Full faith and credit debt outstanding ($000): 1,963,110; 
Population (000): 11,353; Debt per capita: 173; Debt as a percentage 
of own-source revenue capacity: Low RTS: 17; Debt as a percentage of 
own-source revenue capacity: TTR: 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.

[End of table]

[End of section]

Appendixes :

[End of section]

Appendix I: Methodology for Calculating the Cost of Providing a 
Representative Basket of Public 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).[Footnote 56] 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.[Footnote 57] 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 Representative Basket of Public Services: The Rafuse/ACIR 
Method:

The RES is designed to compare the cost of providing an average level 
of public services by state fiscal systems (a state government and all 
of its local governments). In the following sections of this appendix 
we describe the approach developed by ACIR and the modifications we 
made to make it 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 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.[Footnote 58] Based on this geographic unit, we 
defined a representative level of public service provided by the 
average state fiscal system.[Footnote 59]

The Representative Expenditures System Defined:

The representative basket of public services developed by ACIR is the 
sum of a representative expenditure level for seven categories of 
public spending:

1. Elementary and secondary education:

2. Higher education:

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: Elementary and secondary education; Weight 
(percentage): 24.0.

Expenditure category: Higher education; Weight (percentage): 9.2.

Expenditure category: Public welfare; Weight (percentage): 12.3.

Expenditure category: Health and hospitals; Weight (percentage): 8.7.

Expenditure category: Highways; Weight (percentage): 8.0.

Expenditure category: Police and corrections; Weight (percentage): 6.3.

Expenditure category: All other; Weight (percentage): 31.4.

Source: GAO.

Note: GAO analysis based on information in Representative Expenditures: 
Addressing the Neglected Dimension of Fiscal Capacity.

[End of table]

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 Weights:

Workload indicators generally represent the number of potential 
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:

Expenditure category: Elementary and secondary education; Workload 
indicators: 1. Children of elementary school age (5-13), net of private 
school enrollment; 2. Children of secondary school age (14-17), net of 
private school enrollment; 3. Children under age 18 living in poverty; 
Workload factor weights: 1. 0.60; 2. 1.00; 3. 0.25.

Expenditure category: Higher education; Workload indicators: 1. 
Population 14-17; 2. Population 18-24; 3. Population 25-34; 4. 
Population 35 and over; Workload factor weights: 1. 1.32%; 2. 22.44%; 
3. 4.16%; 4. 0.83%.

Expenditure category: Public welfare; Workload indicators: 1. Poverty 
population; Workload factor weights: 1. 100%.

Expenditure category: Health and hospitals; Workload indicators: 
Percentage shares of; 1. Total population; 2. Population below 150% of 
the poverty line; 3. Population 16-64; Workload factor weights: ; 1. 1/
3; 2. 1/3; 3. 1/3.

Expenditure category: Highways; Workload indicators: Percentage shares 
of; 1. Vehicle miles traveled; 2. Lane miles of streets and roads; 
Workload factor weights: ; 1. 82.5%; 2. 17.5%.

Expenditure category: Police and corrections; Workload indicators: 
Percentage shares of; 1. Total population; 2. Number of murders; 3. 
Population 18-24; Workload factor weights: ; 1. 1/3; 2. 1/3; 3. 1/3.

Expenditure category: All other; Workload indicators: 1. Total 
population; Workload factor weights: 1. 100%.

Source: GAO.

Note: GAO analysis based on information in Representative Expenditures: 
Addressing the Neglected Dimension of Fiscal Capacity, p. 9.

[End of table]

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 Interpretation of the Representative Expenditure 
Model:

Dr. Rafuse discussed a number of limitations to the interpretation and 
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 use in measuring the District's costs of providing an 
average level of 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."[Footnote 60] 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 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."[Footnote 61] 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 Rafuse Methodology:

The primary intent of the original RES analysis was to compare the 
fiscal 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:

* 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.[Footnote 62]

* 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 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 Workload Indicators:

In contrast to the 7 expenditure categories used in the ACIR report, we 
used a more detailed set of expenditure functions for our benchmark 
baskets of services using data from the U.S. Census Bureau 
(Census).[Footnote 63] 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.

* 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.[Footnote 64]

* 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-of-
living 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[Footnote 65] 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.[Footnote 66] 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.[Footnote 67] 
Therefore, NRC suggests calculating cost of living differences using 
the formula: 

cost of living index = 0.56 + 0.44 x (rent index).

Elementary and Secondary Education:

The ACIR RES applies a weight of 0.25 to the workload factor of 
children in poverty to reflect the weighting many states apply in their 
school-aid formulas, based on fiscal year 1987 information.[Footnote 
68] Based on our 1998 study,[Footnote 69] the median weight states 
accorded low-income children was 0.6. While some research suggests that 
still higher weights would be appropriate,[Footnote 70] 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.[Footnote 71] Since this function 
largely benefits low-income 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.

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 well-suited as an indicator of public 
health workloads, and including it would have increased the District's 
RES.[Footnote 72]

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, 
car-pooling, 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.

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."[Footnote 73] 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."[Footnote 74] 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.[Footnote 75]

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.[Footnote 76] 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 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.[Footnote 77] 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.[Footnote 78]

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.[Footnote 79] 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.[Footnote 80] Thus, we use the number unemployed as reported 
in the 2000 Decennial Census.[Footnote 81]

Libraries, Parking Facilities, and Solid Waste Management:

These three categories are subsumed under the "all other" expenditure 
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 Development, Parks and Recreation, Protective 
Inspection and Regulation, and Governmental Administration:

These four categories are discussed together because they share common 
treatment for their workloads. In the ACIR methodology, each is 
subsumed under the "all other" category and, in effect, assigned 
population as a workload factor. We have chosen to continue using 
population as the 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.[Footnote 82] 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.

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.[Footnote 83]

General Expenditures, Not Elsewhere Classified:

This category is assigned a workload measure equal to the average 
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.

Table 15: Modifications of Workload Indicators:

Expenditure category: Elementary and secondary education; Workload 
modification: 1. To estimate children in poverty, apply a cost-of-
living adjustment to the threshold used for determining poverty 
status; 2. Increase the weight applied to the children in poverty 
from 0.25 to 0.60; Rationale: 1. The number of low-income people 
potentially eligible for public services, in principle, should be 
measured by a uniform standard independently of differences in costs. 
This adjustment allows the low-income population to be measured in real 
dollar terms; 2. Update this parameter to reflect current median state 
weighting of children in poverty.

Expenditure category: Higher education; Workload modification: No 
change; Rationale: NA.

Expenditure category: Medical vendor payments; Workload modification: 
1. Adjust the threshold of the poverty estimate for cost of living; 2. 
Weight children, adults, and elderly based on historical cost 
differences associated with serving these population groupings; 
Rationale: 1. See elementary and secondary education; 2. These are 
superior measures of potential workload and the cost of serving these 
populations.

Expenditure category: Other public welfare; Workload modification: 
Adjust the threshold of the poverty estimate for cost of living; 
Rationale: See elementary and secondary education.

Expenditure category: Health and hospitals; Workload modification: 
Adjust the threshold of the poverty estimate for cost of living; 
Rationale: See elementary and secondary education.

Expenditure category: Highways; Workload modification: No change; 
Rationale: NA.

Expenditure category: Mass transit; subsidies; Workload modification: 
Use urbanized population, with the "daytime population" adjustment; 
Rationale: Adding mass transit subsidies is intended to capture the 
fact 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.

Expenditure category: Police; Workload modification: Apply the "daytime 
population" adjustment to the one-third resident population workload; 
Rationale: Population is used as a workload factor because some police 
responsibilities have little to do with crime. For such 
responsibilities, including temporary additions and subtractions to the 
resident population due to commuting to work seems appropriate.

Expenditure category: Corrections; Workload modification: No change; 
Rationale: NA.

Expenditure category: Fire protection; Workload modification: Assign to 
fire services 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; 
Rationale: Alternative workload factors reflect conditions associated 
with higher costs of providing fire prevention and suppression in dense 
urban areas. Such higher costs result from differences in equipment, 
apparatus, and staffing (e.g., greater reliance on professionals rather 
than volunteers.).

Expenditure category: Sewerage; Workload modification: Assign the 
workload factor of 1990 Census data on housing units connected to a 
public sewer system, rather than total resident population; Rationale: 
In urban areas such as the District, 100 percent of housing units are 
connected to a public sewer system. In rural areas, it is a lower 
percentage because septic tanks are common.

Expenditure category: Social insurance administration; Workload 
modification: The modified workload factor is the number of 
unemployed; Rationale: This category is the administration of the 
unemployment compensation system, including associated employment 
services such as job placement and counseling.

Expenditure category: * Libraries; * Parking facilities; * Solid waste 
management; Workload modification: Resident population with the 
"daytime population" adjustment; Rationale: Adjusting resident 
population allows for the workload indicator to reflect the impact of 
the net inflow of workers.

Expenditure category: * Housing and community development; * Parks and 
recreation; * Protective inspection and regulation; * Governmental 
administration; Workload modification: No change. Resident population 
(without adjustment) is the workload measure; Rationale: NA.

Expenditure category: Interest on debt; Workload modification: Assigned 
a workload factor to equal to the average workload of all other 
categories (except the "not elsewhere classified" category); 
Rationale: The amount of interest owed is directly related to the 
amount of debt incurred. Everything else the same, the circumstances 
determining the amount of debt incurred are the workloads for various 
expenditure functions and the input costs for them. Thus, the overall 
workloads and input costs indexes for every other function are used.

Expenditure category: General expenditures, not elsewhere classified; 
Workload modification: Assigned a workload factor to equal to the 
average workload of every category (except the average excludes this 
category and the previous one); Rationale: These expenditures are 
unallocable to other spending categories because they are multifunction 
goods and services supplied within state and local governments such as 
centralized 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.

[End of table]

Modifications to Unit Cost Adjustments:

As described above, in the ACIR methodology, the unit cost of public 
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 by Place of Employment:

The ACIR method used Census earnings data of residents to generate an 
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 Differences:

In addition to labor, another major input used to provide public 
services is 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 Costs for Medical Vendor Payments:

In principle, the opportunity wage used for each spending category 
should reflects the mix of skills required for that function; the labor 
market for 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 Cash Assistance in the Public Welfare 
Category:

The basic premise of the RES is that it represents the nominal dollar 
cost of providing a real level of public service benefits. In the case 
of cash assistance,[Footnote 84] 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-of-living adjusted basis.

Alternative Expenditure Weights:

To compute per capita RES amounts by function for the District (and all 
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.

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 Categories Included and Excluded from RES:

The category of mass transit subsidies is basically excluded from the 
original ACIR method.[Footnote 85] Since the District subsidizes 
transit provided by 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:

* 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.[Footnote 86] While state 
governments perform virtually all these functions, local governments 
and the District do not perform most of them.

Urban Alternative Expenditure Weights:

As an alternative to the national expenditure weights, we calculated 
the 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.[Footnote 87] 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.

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.

:

[End of section]

Appendix II: Revenue Capacity Analysis: Methodology and 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 own-source revenue capacity. At the end of the 
appendix we provide detailed results from our analyses.

Estimating Grants Associated with Average Services:

Our analysis covers those categories of federal grants that are used to 
fund the types of functions that we covered in our expenditure 
analysis. Thus, we included grants in the education, employment 
security administration, 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 Own-Source Revenue Capacity:

This section provides background information on different measures of 
own-source revenue capacity and describes in detail how we implemented 
the representative tax system (RTS) approach for this study.

Measures of Own-Source Revenue Capacity:

Two general types of measures have been used to estimate the own-source 
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 Revenue Capacity Measures:

Each approach to estimating revenue capacity has limitations, which are 
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.[Footnote 88] 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 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.[Footnote 
89]

Our Implementation of the RTS Approach:

The scope of our analysis actually falls in between that of a 
representative 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 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 state-level data on farm acreage and farm value per 
acre. Corporate and partnership property value[Footnote 90] 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.[Footnote 91] 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.[Footnote 92] 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.

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 Receipts Taxes:

Our starting point for estimating the general sales and gross receipts 
tax 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.[Footnote 93] 
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.[Footnote 94] 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.[Footnote 95] 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.

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.[Footnote 96]

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.[Footnote 97] 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.[Footnote 98] 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.

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.[Footnote 99]

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.

User Charges and Special Assessments:

The tax base for user charges and special assessments is state personal 
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 the District's Own-Source Revenue Capacity:

Table 16 presents our lowest and highest RTS estimates (using the range 
of assumptions and approaches described above) of the District's 
revenue capacity for specific sources of revenue. We present the 
estimates in per capita dollar amounts and as indexes (where the 
national average 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 own-source 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.[Footnote 100] We also computed a:

third estimate of own-source revenue capacity for the District based on 
the Treasury's estimates of the TTR.[Footnote 101] 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.

Table 16: RTS Estimates of the District's Own-Source Revenue Capacity:

Revenue source: Property tax; "Low" estimates: Per capita amount: 
$1,108; "Low" estimates: Index: 130; "Low" estimates: Rank: 3; [Empty]; 
"High" estimates: Per capita amount: $1,426; "High" estimates: Index: 
167; "High" estimates: Rank: 2.

Revenue source: Personal income tax; "Low" estimates: Per capita 
amount: 940; "Low" estimates: Index: 129; "Low" estimates: Rank: 3; 
[Empty]; "High" estimates: Per capita amount: 946; "High" estimates: 
Index: 130; "High" estimates: Rank: 3.

Revenue source: Sales and gross receipts taxes; "Low" estimates: Per 
capita amount: 882; "Low" estimates: Index: 89; "Low" estimates: Rank: 
50; [Empty]; "High" estimates: Per capita amount: 971; "High" 
estimates: Index: 98; "High" estimates: Rank: 32.

Revenue source: Corporate income tax; "Low" estimates: Per capita 
amount: 199; "Low" estimates: Index: 161; "Low" estimates: Rank: 3; 
[Empty]; "High" estimates: Per capita amount: 199; "High" estimates: 
Index: 161; "High" estimates: Rank: 3.

Revenue source: Other taxes; "Low" estimates: Per capita amount: 227; 
"Low" estimates: Index: 119; "Low" estimates: Rank: 7; [Empty]; "High" 
estimates: Per capita amount: 227; "High" estimates: Index: 119; "High" 
estimates: Rank: 7.

Revenue source: Nontax revenue; "Low" estimates: Per capita amount: 
1,684; "Low" estimates: Index: 126; "Low" estimates: Rank: 2; [Empty]; 
"High" estimates: Per capita amount: 1,684; "High" estimates: Index: 
126; "High" estimates: Rank: 2.

Revenue source: Total own-source; revenue capacity; "Low" estimates: 
Per capita amount: $5,039; "Low" estimates: Index: 119; "Low" 
estimates: Rank: 4; [Empty]; "High" estimates: Per capita amount: 
$5,445; "High" estimates: Index: 129; "High" estimates: Rank: 3.

Source: GAO.

Note: GAO analysis of data from the methodologies described in this 
appendix.

[End of table]

[End of section]

Appendix III: Computation of the District's Structural 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 Computation:

As discussed above, a fiscal system has a structural deficit when its 
cost of 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.[Footnote 102] 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.

Table 17: Computation of the District's Structural Deficit under 
Alternative Estimation Approaches, Using Fiscal Year 2000 Data:

Dollars in millions.

State services basket; TTR for revenue capacity; Computation: Cost of 
an average level of services: $5,272; Computation: Own-source revenue 
capacity: $3,251; Computation: Federal grants: $1,551; Computation: 
Structural deficit: $470.

Urban services basket;
"Low" RTS for revenue capacity; Computation: Cost of an average level 
of services: $5,597; Computation: Own-source revenue capacity: $2,883; 
Computation: Federal grants: $1,551; Computation: Structural deficit: 
$1,163.

Source: GAO.

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

[End of table]

Deficit as a Percentage of Own-Source Revenue Capacity:

Figure 10 shows how the District's structural deficit compares to the 
state 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 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:

[See PDF for image]

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

[End of figure]

[End of section]

Appendix IV: The District's Deferred Maintenance and 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:

Project name: Office of Property Management:

Project name: D.C. Warehouse - Mechanical Upgrade; Agency 1-year 
request for 
fiscal year 2003: $470,000; Agency 6-year request for 
fiscal years 
2003-2008: $720,000.

Project name: Recorder of Deeds - Complete Modernization; Agency 1-year 
request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: 4,640,000.

Project name: Government Centers - New DMV Facility; Agency 1-year 
request for 
fiscal year 2003: 2,500,000; Agency 6-year request for 
fiscal years 
2003-2008: 7,500,000.

Project name: Government Centers - Improve Property Management ITS; 
Agency 1-year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: 4,500,000.

Project name: Government Centers - Government Centers; Agency 1-year 
request for 
fiscal year 2003: 15,000,000; Agency 6-year request for 
fiscal years 
2003-2008: 15,000,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $17,970,000; Agency 6-year request for 
fiscal years 
2003-2008: $32,360,000.

Office of the Chief Financial Officer:

Project name: 410 E Street Renovation; Agency 1-year request for 
fiscal year 2003: $1,235,000; Agency 6-year request for 
fiscal years 
2003-2008: $9,000,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $1,235,000; Agency 6-year request for 
fiscal years 
2003-2008: $9,000,000.

Office of the Secretary:

Project name: Archives Project - Modernization/Renovation; Agency 1-
year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: $3,386,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: $3,386,000.

Metropolitan Police Department:

Project name: 3rd District Station New Building - Mod/Renovation; 
Agency 1-year request for 
fiscal year 2003: $7,739,874; Agency 6-year request for 
fiscal years 
2003-2008: $12,571,902.

Project name: 6th District Station New Building - Mod/Renovation; 
Agency 1-year request for 
fiscal year 2003: 7,739,874; Agency 6-year request for 
fiscal years 
2003-2008: 12,571,902.

Project name: Municipal Center Renovation; Agency 1-year request for 
fiscal year 2003: 16,243,034; Agency 6-year request for 
fiscal years 
2003-2008: 86,873,258.

Project name: Evidentiary Property Warehouse; Agency 1-year request for 
fiscal year 2003: 5,053,726; Agency 6-year request for 
fiscal years 
2003-2008: 5,053,726.

Project name: SOD Consolidation New Building; Agency 1-year request for 
fiscal year 2003: 12,475,070; Agency 6-year request for 
fiscal years 
2003-2008: 20,472,353.

Project name: Multi-Function Facility; Agency 1-year request for 
fiscal year 2003: 5,259,842; Agency 6-year request for 
fiscal years 
2003-2008: 5,259,842.

Subtotal; Agency 1-year request for 
fiscal year 2003: $54,511,420; Agency 6-year request for 
fiscal years 
2003-2008: $142,802,983.

Fire and Emergency Medical Services Department:

Project name: Engine 5 - Complete Renovation/Modern's; Agency 1-year 
request for 
fiscal year 2003: $569,320; Agency 6-year request for 
fiscal years 
2003-2008: $2,724,919.

Project name: Engine 12 - Haz Mat Unit Facility; Agency 1-year request 
for 
fiscal year 2003: 263,386; Agency 6-year request for 
fiscal years 
2003-2008: 491,771.

Project name: Disaster Vehicle Facility; Agency 1-year request for 
fiscal year 2003: 1,083,397; Agency 6-year request for 
fiscal years 
2003-2008: 2,088,094.

Subtotal; Agency 1-year request for 
fiscal year 2003: $1,916,103; Agency 6-year request for 
fiscal years 
2003-2008: $5,304,784.

Department of Corrections:

Project name: Exterior Structural Finishing; Agency 1-year request for 
fiscal year 2003: $136,500; Agency 6-year request for 
fiscal years 
2003-2008: $1,184,000.

Project name: Storage Space Const. Outside R&D; Agency 1-year request 
for 
fiscal year 2003: 4,005,000; Agency 6-year request for 
fiscal years 
2003-2008: 4,005,000.

Project name: Lot Adjacent to CDF Parking Lot Construction; Agency 1-
year request for 
fiscal year 2003: 708,000; Agency 6-year request for 
fiscal years 
2003-2008: 7,104,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $4,849,500; Agency 6-year request for 
fiscal years 
2003-2008: $12,293,000.

District of Columbia Public Schools:

Project name: Distribution Piping Upgrade; Agency 1-year request for 
fiscal year 2003: $27,257,986; Agency 6-year request for 
fiscal years 
2003-2008: $245,321,872.

Project name: Terminal Unit Systems; Agency 1-year request for 
fiscal year 2003: 13,642,583; Agency 6-year request for 
fiscal years 
2003-2008: 122,783,250.

Project name: Heating Plant Replacement; Agency 1-year request for 
fiscal year 2003: 24,768,994; Agency 6-year request for 
fiscal years 
2003-2008: 222,920,944.

Project name: Boiler Plant Overhauls; Agency 1-year request for 
fiscal year 2003: 2,172,598; Agency 6-year request for 
fiscal years 
2003-2008: 19,553,380.

Project name: Central Air Handling Systems; Agency 1-year request for 
fiscal year 2003: 4,172,078; Agency 6-year request for 
fiscal years 
2003-2008: 37,548,699.

Project name: Cooling Plant Replacement; Agency 1-year request for 
fiscal year 2003: 7,574,589; Agency 6-year request for 
fiscal years 
2003-2008: 68,171,302.

Project name: Generator System Replacement; Agency 1-year request for 
fiscal year 2003: 1,547,771; Agency 6-year request for 
fiscal years 
2003-2008: 13,929,935.

Project name: Electrical System Replacement; Agency 1-year request for 
fiscal year 2003: 1,019,168; Agency 6-year request for 
fiscal years 
2003-2008: 9,172,509.

Project name: Fire Alarm, Intercom, Master Clock Upgrades; Agency 1-
year request for 
fiscal year 2003: 35,977,562; Agency 6-year request for 
fiscal years 
2003-2008: 323,798,054.

Project name: Corrective Maintenance (Carpentry, Welding, Plumbing 
etc); Agency 1-year request for 
fiscal year 2003: 7,193,651; Agency 6-year request for 
fiscal years 
2003-2008: 64,742,858.

Project name: Corrective Maintenance (Grounds); Agency 1-year request 
for 
fiscal year 2003: 684,461; Agency 6-year request for 
fiscal years 
2003-2008: 6,160,153.

Subtotal; Agency 1-year request for 
fiscal year 2003: $126,011,440; Agency 6-year request for 
fiscal years 
2003-2008: $1,134,102,956.

University of the District of Columbia:

Project name: Building 46E Auditorium; Agency 1-year request for 
fiscal year 2003: $550,000; Agency 6-year request for 
fiscal years 
2003-2008: $6,650,000.

Project name: Building 32 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 223,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,846,000.

Project name: Building 38 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 165,000; Agency 6-year request for 
fiscal years 
2003-2008: 2,142,000.

Project name: Building 39 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 165,000; Agency 6-year request for 
fiscal years 
2003-2008: 2,142,000.

Project name: Building 41 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 165,000; Agency 6-year request for 
fiscal years 
2003-2008: 2,142,000.

Project name: Building 42 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 223,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,846,000.

Project name: Building 44 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 200,000; Agency 6-year request for 
fiscal years 
2003-2008: 800,000.

Project name: Building 46W - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 125,000; Agency 6-year request for 
fiscal years 
2003-2008: 900,000.

Project name: Building 47 - Cooling Plants - HVAC; Agency 1-year 
request for 
fiscal year 2003: 130,000; Agency 6-year request for 
fiscal years 
2003-2008: 970,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $1,946,000; Agency 6-year request for 
fiscal years 
2003-2008: $19,438,000.

Department of Parks and Recreation:

Project name: Lammond Recreation Center; Agency 1-year request for 
fiscal year 2003: $1,807,000; Agency 6-year request for 
fiscal years 
2003-2008: $4,432,000.

Project name: Mitchell Park Renovations; Agency 1-year request for 
fiscal year 2003: 1,940,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,940,000.

Project name: Aquatic Center New Construction; Agency 1-year request 
for 
fiscal year 2003: 1,317,000; Agency 6-year request for 
fiscal years 
2003-2008: 4,600,000.

Project name: Douglas Recreation/Aquatic; Agency 1-year request for 
fiscal year 2003: 1,680,000; Agency 6-year request for 
fiscal years 
2003-2008: 10,272,000.

Project name: Georgetown Pool Renovations; Agency 1-year request for 
fiscal year 2003: 2,445,000; Agency 6-year request for 
fiscal years 
2003-2008: 2,445,000.

Project name: General Improvements Mitchell Park; Agency 1-year request 
for 
fiscal year 2003: 200,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,000,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $9,389,000; Agency 6-year request for 
fiscal years 
2003-2008: $24,689,000.

Department of Health:

Project name: JB Johnson Facility - Renovation; Agency 1-year request 
for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: $705,000.

Project name: Asbestos Abatement - Asbestos Abatement; Agency 1-year 
request for 
fiscal year 2003: $1,000,000; Agency 6-year request for 
fiscal years 
2003-2008: 3,000,000.

Project name: Lighting System Retrofit; Agency 1-year request for 
fiscal year 2003: 1,200,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,200,000.

Project name: Fire Alarm Systems - Fire Alarm Systems; Agency 1-year 
request for 
fiscal year 2003: 650,000; Agency 6-year request for 
fiscal years 
2003-2008: 850,000.

Project name: Security Monitoring System; Agency 1-year request for 
fiscal year 2003: 450,000; Agency 6-year request for 
fiscal years 
2003-2008: 450,000.

Project name: Chiller Room Ceiling; Agency 1-year request for 
fiscal year 2003: 460,000; Agency 6-year request for 
fiscal years 
2003-2008: 460,000.

Project name: Upgrade Mechanical Air Duct System; Agency 1-year request 
for 
fiscal year 2003: 850,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,000,000.

Project name: Plumbing System Upgrade; Agency 1-year request for 
fiscal year 2003: 485,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,000,000.

Project name: Building Renovation; Agency 1-year request for 
fiscal year 2003: 550,000; Agency 6-year request for 
fiscal years 
2003-2008: 550,000.

Project name: Elevator Modernization 28 & 29; Agency 1-year request for 
fiscal year 2003: 50,000; Agency 6-year request for 
fiscal years 
2003-2008: 50,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $5,695,000; Agency 6-year request for 
fiscal years 
2003-2008: $9,265,000.

Department of Human Services:

Project name: Bundy School Upgrade; Agency 1-year request for 
fiscal year 2003: $3,000,000; Agency 6-year request for 
fiscal years 
2003-2008: $3,000,000.

Project name: Blair Shelter - Complete Modernization; Agency 1-year 
request for 
fiscal year 2003: 175,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,288,000.

Project name: Crummel School; Agency 1-year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: 4,417,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $3,175,000; Agency 6-year request for 
fiscal years 
2003-2008: $8,705,000.

Project name: Department of Public Works; Agency 1-year request for 
fiscal year 2003: ; Agency 6-year request for 
fiscal years 
2003-2008: .

Project name: Snow Equipment Dry Storage Building; Agency 1-year 
request for 
fiscal year 2003: $425,000; Agency 6-year request for 
fiscal years 
2003-2008: $4,935,000.

Project name: Recycling Collection Expansion; Agency 1-year request for 
fiscal year 2003: 3,370,400; Agency 6-year request for 
fiscal years 
2003-2008: 4,270,400.

Project name: Sweeper Repair and Storage Garage; Agency 1-year request 
for 
fiscal year 2003: 2,340,000; Agency 6-year request for 
fiscal years 
2003-2008: 3,600,000.

Project name: Packer Storage Facility @ W Va Ave., NE; Agency 1-year 
request for 
fiscal year 2003: 2,100,000; Agency 6-year request for 
fiscal years 
2003-2008: 20,000,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $8,235,400; Agency 6-year request for 
fiscal years 
2003-2008: $32,805,400.

Department of Mental Health:

Project name: Elevator Modernization; Agency 1-year request for 
fiscal year 2003: $2,000,000; Agency 6-year request for 
fiscal years 
2003-2008: $2,000,000.

Project name: Renovation - HVAC; Agency 1-year request for 
fiscal year 2003: 4,500,000; Agency 6-year request for 
fiscal years 
2003-2008: 4,500,000.

Project name: Tunnel Repair - Structural Work; Agency 1-year request 
for 
fiscal year 2003: 500,000; Agency 6-year request for 
fiscal years 
2003-2008: 500,000.

Project name: North Center Repair/Replacement; Agency 1-year request 
for 
fiscal year 2003: 14,400,000; Agency 6-year request for 
fiscal years 
2003-2008: 14,400,000.

Project name: Replace Generator - Emergency System; Agency 1-year 
request for 
fiscal year 2003: 100,000; Agency 6-year request for 
fiscal years 
2003-2008: 100,000.

Project name: Allison Relocation - Site Preparation; Agency 1-year 
request for 
fiscal year 2003: 1,742,000; Agency 6-year request for 
fiscal years 
2003-2008: 1,752,150.

Subtotal; Agency 1-year request for 
fiscal year 2003: $23,242,000; Agency 6-year request for 
fiscal years 
2003-2008: $23,252,150.

Department of Transportation:

Project name: Bridge Rehabilitation; Agency 1-year request for 
fiscal year 2003: $78,000,000; Agency 6-year request for 
fiscal years 
2003-2008: $470,000,000.

Project name: Series Street Light Conversion; Agency 1-year request for 
fiscal year 2003: 4,000,000; Agency 6-year request for 
fiscal years 
2003-2008: 21,000,000.

Project name: Street Light Pole Replacement; Agency 1-year request for 
fiscal year 2003: 750,000; Agency 6-year request for 
fiscal years 
2003-2008: 4,500,000.

Project name: Alley Paving and Sidewalk; Agency 1-year request for 
fiscal year 2003: 25,000,000; Agency 6-year request for 
fiscal years 
2003-2008: 125,000,000.

Project name: Street Resurfacing; Agency 1-year request for 
fiscal year 2003: 5,000,000; Agency 6-year request for 
fiscal years 
2003-2008: 25,000,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: $112,750,000; Agency 6-year request for 
fiscal years 
2003-2008: $645,500,000.

Office of the Chief Technology Officer:

Project name: Tech City - Infrastructure Support System; Agency 1-year 
request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: $9,100,000.

Project name: Share Facility Upgrade; Agency 1-year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: 800,000.

Subtotal; Agency 1-year request for 
fiscal year 2003: 0; Agency 6-year request for 
fiscal years 
2003-2008: $9,900,000.

Total; Agency 1-year request for 
fiscal year 2003: $370,925,863; Agency 6-year request for 
fiscal years 
2003-2008: $2,112,804,273.

Source: District of Columbia, Office of the Chief Financial Officer, 
Office of Budget and Planning.

[End of table]

Table 19: The District's Capital Improvement Program: Deferred 
Acquisitions Projects for Fiscal Year 2003 and Fiscal Years 2003 
through 2008:

Emergency Management Agency:

Project name: Mobile Command Vehicle and Technology; Agency acquisition 
costs - 1-year request - fiscal year 2003: $302,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $302,000.

Project name: Backup Emergency Operation Center; Agency acquisition 
costs - 1-year request - fiscal year 2003: 2,000,000; Agency 
acquisition 
costs - 6-year request-fiscal years 2003-2008: 2,000,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $2,302,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $2,302,000.

D.C. Public Library:

Project name: Digital Dimension of the 21st Century Library; Agency 
acquisition costs - 1-year request - fiscal year 2003: $275,000; Agency 
acquisition 
costs - 6-year request-fiscal years 2003-2008: $2,275,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $275,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $2,275,000.

Metropolitan Police Department:

Project name: IT-Automatic Personnel Locator; Agency acquisition costs 
- 1-year request - fiscal year 2003: $2,000,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $3,250,000.

Project name: IT-MDC Index Fingerprinting; Agency acquisition costs - 
1-year request - fiscal year 2003: 1,800,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: 7,780,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $3,800,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $11,030,000.

Fire and Emergency Medical Services Department:

Project name: 800Mhz Metro Radio System; Agency acquisition costs - 1-
year request - fiscal year 2003: $4,500,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $4,500,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $4,500,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $4,500,000.

Department of Human Services:

Project name: Low Income Family Units - Site Acquisition; Agency 
acquisition costs - 1-year request - fiscal year 2003: $1,500,000; 
Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $6,000,000.

Project name: Acquire New Site for LaCasa Shelter; Agency acquisition 
costs - 1-year request - fiscal year 2003: 2,560,000; Agency 
acquisition 
costs - 6-year request-fiscal years 2003-2008: 2,560,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $4,060,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $8,560,000.

Department of Public Works:

Project name: Snow Event Management System; Agency acquisition costs - 
1-year request - fiscal year 2003: $1,315,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $1,315,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $1,315,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $1,315,000.

Department of Mental Health:

Project name: Procurement Systems and Implementation; Agency 
acquisition costs - 1-year request - fiscal year 2003: $1,540,000; 
Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $3,000,000.

Subtotal; Agency acquisition costs - 1-year request - 
fiscal year 2003: $1,540,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $3,000,000.

Total; Agency acquisition costs - 1-year request - fiscal 
year 2003: $17,792,000; Agency acquisition 
costs - 6-year request-fiscal years 2003-2008: $32,982,000.

Source: District of Columbia, Office of the Chief Financial Officer, 
Office of Budget and Planning.

[End of table]

[End of section]

Appendix V: Information Related to the District's Debt:

Table 20: The District's Total Outstanding General Obligation Debt:

Dollars in thousands.

General obligation debt; Fiscal year: 1995: $3,157,003; Fiscal year: 
1996: $2,965,756; Fiscal year: 1997: $3,084,763; Fiscal year: 1998: 
$3,091,403; Fiscal year: 1999: $3,098,582; Fiscal year: 2000: 
$3,109,728; Fiscal year: 2001: $2,582,017; Fiscal year: 2002: 
$2,670,573.

Water & Sewer Authority; Fiscal year: 1995: 323,172; Fiscal year: 
1996: 303,719; Fiscal year: 1997: 282,100; Fiscal year: 1998: 
114,122; Fiscal year: 1999: 107,662; Fiscal year: 2000: 100,147; 
Fiscal year: 2001: 95,296; Fiscal year: 2002: 79,070.

Total GO debt; Fiscal year: 1995: $3,480,175; Fiscal year: 1996: 
$3,269,475; Fiscal year: 1997: $3,366,863; Fiscal year: 1998: 
$3,205,525; Fiscal year: 1999: $3,206,244; Fiscal year: 2000: 
$3,209,875; Fiscal year: 2001: $2,677,313; Fiscal year: 2002: 
$2,749,643.

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

[End of table]

Table 21: The District's Debt Per Capita for Fiscal Years 1995 through 
2002 (Actual):

Year: 1995; Total general obligation debt ($000s): $3,480,175; 
Population: 552,466; Debt per capita ($): $6,299.

Year: 1996; Total general obligation debt ($000s): 3,269,475; 
Population: 539,646; Debt per capita ($): 6,059.

Year: 1997; Total general obligation debt ($000s): 3,366,863; 
Population: 529,895; Debt per capita ($): 6,354.

Year: 1998; Total general obligation debt ($000s): 3,205,525; 
Population: 523,124; Debt per capita ($): 6,128.

Year: 1999; Total general obligation debt ($000s): 3,206,244; 
Population: 519,100; Debt per capita ($): 6,177.

Year: 2000; Total general obligation debt ($000s): 3,209,875; 
Population: 572,059; Debt per capita ($): 5,611.

Year: 2001; Total general obligation debt ($000s): 2,677,313; 
Population: 571,822; Debt per capita ($): 4,682.

Year: 2002; Total general obligation debt ($000s): 2,749,643; 
Population: 570,898; Debt per capita ($): 4,816.

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

[End of table]

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):

Year: 1995; Debt service costs: Principal: $157,308; Debt service 
costs: Interest: $184,510; Debt service costs: Fiscal charges: $3,077; 
Debt service costs: Total: $344,895; General fund expenditures: 
$4,395,388; Percentage of debt service to general fund expenditures: 
7.85.

Year: 1996; Debt service costs: Principal: 191,247; Debt service costs: 
Interest: 173,807; Debt service costs: Fiscal charges: 2,650; Debt 
service costs: Total: $367,704; General fund expenditures: 4,486,273; 
Percentage of debt service to general fund expenditures: 8.20.

Year: 1997; Debt service costs: Principal: 207,903; Debt service costs: 
Interest: 174,085; Debt service costs: Fiscal charges: 13,567; Debt 
service costs: Total: $395,555; General fund expenditures: 4,290,397; 
Percentage of debt service to general fund expenditures: 9.22.

Year: 1998; Debt service costs: Principal: 219,435; Debt service costs: 
Interest: 171,430; Debt service costs: Fiscal charges: 8,997; Debt 
service costs: Total: $399,862; General fund expenditures: 3,964,246; 
Percentage of debt service to general fund expenditures: 10.09.

Year: 1999; Debt service costs: Principal: 261,534; Debt service costs: 
Interest: 191,903; Debt service costs: Fiscal charges: 6,597; Debt 
service costs: Total: $460,034; General fund expenditures: 4,597,628; 
Percentage of debt service to general fund expenditures: 10.01.

Year: 2000; Debt service costs: Principal: 220,054; Debt service costs: 
Interest: 172,326; Debt service costs: Fiscal charges: 2,732; Debt 
service costs: Total: $395,112; General fund expenditures: 5,064,215; 
Percentage of debt service to general fund expenditures: 7.80.

Year: 2001; Debt service costs: Principal: 108,725; Debt service costs: 
Interest: 146,043; Debt service costs: Fiscal charges: 3,134; Debt 
service costs: Total: $257,902; General fund expenditures: 5,387,695; 
Percentage of debt service to general fund expenditures: 4.79.

Year: 2002; Debt service costs: Principal: 131,750; Debt service costs: 
Interest: 135,688; Debt service costs: Fiscal charges: 4,744; Debt 
service costs: Total: $272,182; General fund expenditures: 5,317,459; 
Percentage of debt service to general fund expenditures: 5.12.

Year: 2003[A]; Debt service costs: Principal: 137,880; Debt service 
costs: Interest: 166,871; Debt service costs: Fiscal charges: N/A; Debt 
service costs: Total: $304,751; General fund expenditures: [Empty]; 
Percentage of debt service to general fund expenditures: [Empty].

Year: 2004[A]; Debt service costs: Principal: 166,320; Debt service 
costs: Interest: 173,042; Debt service costs: Fiscal charges: N/A; Debt 
service costs: Total: $339,362; General fund expenditures: [Empty]; 
Percentage of debt service to general fund expenditures: [Empty].

Year: 2005[A]; Debt service costs: Principal: 181,165; Debt service 
costs: Interest: 189,352; Debt service costs: Fiscal charges: N/A; Debt 
service costs: Total: $370,517; General fund expenditures: [Empty]; 
Percentage of debt service to general fund expenditures: [Empty].

Year: 2006[A]; Debt service costs: Principal: 195,005; Debt service 
costs: Interest: 206,427; Debt service costs: Fiscal charges: N/A; Debt 
service costs: Total: $401,432; General fund expenditures: [Empty]; 
Percentage of debt service to general fund expenditures: [Empty].

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

[A] These numbers are estimates.

[End of table]

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):

Year: 1995; Debt service: Principal: $157,308; Debt service: Interest: 
$184,510; Debt service: Total: $341,818; General fund revenues (local 
funds) ($000s): $2,729,112; Percentage of debt service to general fund 
revenues: 12.52.

Year: 1996; Debt service: Principal: 191,247; Debt service: Interest: 
173,807; Debt service: Total: $365,054; General fund revenues (local 
funds) ($000s): 2,831,637; Percentage of debt service to general fund 
revenues: 12.89.

Year: 1997; Debt service: Principal: 207,903; Debt service: Interest: 
174,085; Debt service: Total: $381,988; General fund revenues (local 
funds) ($000s): 2,904,530; Percentage of debt service to general fund 
revenues: 13.15.

Year: 1998; Debt service: Principal: 219,435; Debt service: Interest: 
171,430; Debt service: Total: $390,865; General fund revenues (local 
funds) ($000s): 3,177,932; Percentage of debt service to general fund 
revenues: 12.30.

Year: 1999; Debt service: Principal: 261,534; Debt service: Interest: 
191,903; Debt service: Total: $453,437; General fund revenues (local 
funds) ($000s): 3,436,873; Percentage of debt service to general fund 
revenues: 13.19.

Year: 2000; Debt service: Principal: 220,054; Debt service: Interest: 
172,326; Debt service: Total: $392,380; General fund revenues (local 
funds) ($000s): 3,616,116; Percentage of debt service to general fund 
revenues: 10.85.

Year: 2001; Debt service: Principal: 108,725; Debt service: Interest: 
146,043; Debt service: Total: $254,768; General fund revenues (local 
funds) ($000s): 3,853,610; Percentage of debt service to general fund 
revenues: 6.61.

Year: 2002; Debt service: Principal: 131,750; Debt service: Interest: 
135,688; Debt service: Total: $267,438; General fund revenues (local 
funds) ($000s): 3,666,604; Percentage of debt service to general fund 
revenues: 7.29.

Year: 2003[A]; Debt service: Principal: 137,880; Debt service: 
Interest: 166,871; Debt service: Total: $304,751; General fund revenues 
(local funds) ($000s): 3,654,072; Percentage of debt service to general 
fund revenues: 8.34.

Year: 2004[A]; Debt service: Principal: 166,320; Debt service: 
Interest: 173,042; Debt service: Total: $339,362; General fund revenues 
(local funds) ($000s): 3,703,308; Percentage of debt service to general 
fund revenues: 9.16.

Year: 2005[A]; Debt service: Principal: 181,165; Debt service: 
Interest: 189,352; Debt service: Total: $370,517; General fund revenues 
(local funds) ($000s): 3,906,512; Percentage of debt service to general 
fund revenues: 9.48.

Year: 2006[A]; Debt service: Principal: 195,005; Debt service: 
Interest: 206,427; Debt service: Total: $401,432; General fund revenues 
(local funds) ($000s): 4,063,889; Percentage of debt service to general 
fund revenues: 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.

[End of table]

[End of section]

Appendix VI: Comments from the District of Columbia:

GOVERNMENT OF THE DISTRICT OF COLUMBIA OFFICE OF THE CHIEF FINANCIAL 
OFFICER:

Natwar M. Gandhi 
Chief Financial Officer:

May 9, 2003:

Ms. Patricia A. Dalton Director, Strategic Issues General Accounting 
Office 441 G St, NW Washington, DC 20548:

Dear Ms. Dalton:

In your draft report on Structural Imbalance and Management Issues in 
the District of Columbia (GAO-03-666), the General Accounting Office 
(GAO) adapts public sector quantitative analysis methodologies to reach 
important findings about the District of Columbia's fiscal 
circumstances. The innovative effort to adapt these methodologies to 
the District's unique government and fiscal status is a significant 
achievement. The Office of the Chief Financial Officer of the District 
of Columbia agrees with all key findings in the draft report. Further, 
we have discussed the report and findings with the Mayor who also 
concurs in the report's findings. Our comments herein reflect the 
observations of the Mayor and his staff as well as our own views.

This draft report should prove enormously helpful to the Congress and 
others in understanding and solving long-standing structural problems 
with District finances. These matters must be addressed with some 
urgency to assure the long-term financial viability of the nation's 
capital city.

The draft report steps back from the details of individual programs or 
tax policies to compare the District's revenue and spending environment 
with that of other jurisdictions in the United States, using standard 
measures of revenue capacity and spending needs applied to each 
jurisdiction's specific demographic, economic, and labor market 
features. In this way, it excludes the impact of policy choices that 
might increase or decrease either revenue or spending. The result is 
comparisons that are as fair and objective as can be accomplished given 
the unique nature of the District of Columbia within the U.S. 
government structure of the United States.

The draft report reaches three major conclusions.

I. The report confirms the existence of a structural deficit in the 
District. We concur.

The GAO's analysis supports the District's and other independent 
analyses that the District faces an endemic structural imbalance, and 
calculates this deficit to be between $470 million
and $1.1 billion annually based on FY 2000 information. It would appear 
to us that this imbalance is likely more toward the upper end of this 
range because of the District's urban character, a fact noted in the 
report. While noting that there is no empirical way to determine a 
specific estimate, the report is clear that there is a structural 
imbalance, it is substantial, and it adversely affects the ability of 
the District of Columbia to provide high quality services in the 
District of Columbia.

At the current time, state and local governments throughout the nation 
are struggling with cutting expenditures or raising taxes in order to 
keep their budgets in balance. The District, too, is caught up in this 
situation in making sure that its FY 2003 and FY 2004 budgets are in 
balance. These budget difficulties faced by the District and other 
governments are cyclical. While the current economic downturn 
exacerbates our structural imbalance, the report is clear that the 
imbalance is present irrespective of prevailing economic conditions.

II. The draft report clarifies four fundamental features of the 
District's fiscal problems which we agree are present.

1. The District's expenditure requirements for providing a standard 
group of services are far higher than any state fiscal system. Total 
expenditure requirements are much higher than the average state, and 
more than one third higher than those of the next highest state. The 
District faces these high expenditure requirements because it provides 
public services in a market with high labor costs, it provides services 
to a large commuter population, and it has many residents with high 
service needs. Although the draft report identifies areas where the 
District has the potential to improve the efficiency of operations, the 
District's higher costs are determined by factors beyond its control 
that are based on the provision of an average level of services.

2. The District taxes itself very heavily. The District's tax effort is 
as much as 33 percent higher than the average state. Although the 
District's tax capacity is large--more than 47% above the national 
average--because of its large expenditure requirements, the District 
must compensate with a tax effort that is among the highest, if not the 
highest, in the nation. In fact, the District raises between $600 and 
$950 million more annually on the D.C. tax base than it would raise 
with an average tax effort.

3. Even with high taxes, the District cannot pay for average levels of 
service to residents, commuters, and visitors. Although the District's 
capacity to raise revenue is much higher than average, this additional 
capacity is not enough to compensate for the District's higher 
expenditure burden. The draft report suggests that the District's high 
tax effort is insufficient to pay for an urban-oriented basket of 
services given the District's population characteristics. The current 
tax effort is just barely enough to pay for an average level of a 
state-type basket of services, but the draft report points out that 
neither the urban nor state bundle estimates incorporates the millions 
of dollars that the District must pay for because it is the nation's 
capital. Nor do the estimates factor in the costs of providing services 
to tourists or the legal obligations that raise costs in the District's 
special education program.

4. The District has a serious infrastructure problem. The District faces 
an accumulated infrastructure backlog of $2.5 billion. The District has 
deferred capital investment to avert the operating costs associated 
with debt service. For example, in FY 2003 alone, the District trimmed 
$250 million in planned capital expenditures. The problem is acute 
because additional borrowing could raise outstanding debt above the 
levels that are acceptable to the agencies that rate the District's 
credit-worthiness. Whether expressed in per capita terms or in relation 
to revenue, the District's outstanding debt is greater than any other 
state fiscal system.

III. The draft report provides a framework for constructive analysis of 
several issues that often Cloud discussions about the District's 
finances. We agree.

1. Costs and benefits of the federal presence:

In essence, this report treats the federal government as if it were 
like any other employer. The considerable benefits of the federal 
presence are therefore fully reflected in the District's high tax base. 
District personal income is high in part because of federal government 
salaries paid to DC residents. Sales tax revenues in part reflect the 
spending of tourists and conventions drawn to the nation's capital. 
Residential property values reflect the incomes of DC residents, many 
of whom work for the federal government. Commercial property values 
reflect the activities of business and associations who contract with, 
lobby, or otherwise interact with the federal government. All Federal 
grants that the District receives--either the local share of national 
programs or amounts given to the District for special purposes-are 
included in the report's revenue calculations.

However, the report also recognizes that the federal presence imposes 
costs and limitations as well. To the extent that the federal 
government's property and purchases are off the tax rolls, or that non-
resident income earned in the District cannot be taxed, these 
limitations are reflected in the tax base. Given these limitations, in 
order to try to pay for even an average level of service, District tax 
rates on the tax base available to it must be high. While the report 
does not quantify the actual costs of services provided to the federal 
government or incurred as a result of being the nation's capital, it 
puts these costs in perspective. When millions of dollars of 
expenditures related to being the nation's capital are absorbed by the 
city, this diverts resources from ordinary services to residents, 
commuters, and visitors.

2. Inefficiencies in District programs:

We concur with GAO's observations that improved program performance 
would permit the District to enhance the quality of the services it 
does deliver. The GAO points out that better documentation of costs in 
both the delivery of Medicaid services and public safety services to 
the federal government would position the District to obtain a higher 
level of reimbursement than it currently experiences. As the report 
notes, the District has recognized this area as needing management 
improvement and is taking corrective action. Specific examples include 
efforts to improve management oversight of Medicaid efforts, improve 
documentation, and improve the quality of Medicaid revenue estimates. 
On a broader scale, the District has made operating budget reductions 
of over $190 million in FY 2003, in part to balance expenditures and 
revenues but also as part of a large effort to deliver services more 
efficiently. While significant opportunities for efficiency 
improvements exist within District programs, even with such 
improvements, the draft report points out that the District would still 
face a structural deficit.

3. Framework for evaluating options:

The draft report points out that the District has few options for 
addressing its fiscal deficit. The District already has a higher tax 
effort than any state. And, as stated in the draft report, increasing 
the tax burden on District businesses and residents could have an 
adverse impact on total receipts because it could influence residents 
or businesses to move to adjacent lower-tax states. The District has 
tried to cut taxes, but has recently been forced to postpone some of 
these reductions. Also, over the FY 2003/FY 2004 period, the District 
has also cut back existing or planned spending by some $300 million 
dollars.

By law the District must balance its budget each year, but making the 
spending or revenue adjustments needed to do this is not the same as 
solving a structural deficit. By definition, the structural deficit 
would occur each year if the city were to provide an average level of 
public services, funded with an average tax effort and delivered with 
an average level of efficiency. Given the structural deficit, the 
District is forced to choose between tax levels that are even higher 
than the national average, service levels that are lower than the 
national average, or combinations of both in order to balance its 
budgets.

4. Unique nature of the Federal government's responsibility to the 
District of Columbia:

Although the draft report makes no recommendations, it provides a 
strong case for federal action to assist the District of Columbia, the 
nation's capital. As noted, the structural imbalances in both the 
operating and capital areas result primarily from cost and workload 
factors that are beyond the District's control, and, in addition, the 
District must provide services to the federal government.

With tax and debt burdens higher than other jurisdictions, it is not 
feasible for the District to solve the problem by more taxes or 
borrowing. One option noted in the draft report is for the federal 
government to relax taxing restrictions on the District to compensate 
it for its special status as the capital city.

The draft report indicates that providing federal assistance to the 
District may encourage state fiscal systems with structural deficits to 
request the same or similar treatment. However, a strong case can be 
made that the District of Columbia is unique among all local and state 
jurisdictions and that unique conditions dictate unique solutions. All 
states have federally tax-exempt property, but the District has more in 
terms of value relative to the size of the economy. All states may 
forego some tax activity due to the federal commercial activity, but 
the District certainly loses much more. The District is also subject to 
revenue 
and other constraints not imposed by the Federal government on any 
other jurisdiction. These factors have been many times documented and 
indicate that the District merits a unique fiscal relationship with the 
federal government that corresponds to its unique operational 
arrangement.

With respect to the text of the draft report itself, there are four 
suggestions we would like to make.

1. Although the text of the draft report points out that the District 
recognizes that there are management inefficiencies and is taking 
measures to address them, this is not reflected in the executive 
summary.

2. The executive summary could usefully point out that in acting on its 
FY 2003 and FY 2004 budgets the District has once again demonstrated 
its resolve to maintain balanced budgets, but these year-to-year 
adjustments do not address the underlying imbalance problem.

3. To help the reader understand the nature of the draft report, it 
would be useful for GAO to describe as clearly as possible the 
conclusion that solving inefficiencies alone will not close the fiscal 
imbalance.

4. In light of the current cyclical financial problems occurring in many 
jurisdictions throughout the United States, we urge GAO to review its 
draft report to make as clear as possible the unique situation involved 
in the District of Columbia's fiscal deficit.

There is a wide range of options available to the Federal government 
for assisting the District in overcoming its structural deficit and in 
providing a level of service quality that befits the nation's capital. 
The GAO has done a particular service by framing the magnitude of the 
issue at a time when economic conditions are highlighting the impact of 
this deficit.

We look forward to working with officials in the Administration and the 
Congress to find solutions to the District's underlying fiscal 
limitations.

Sincerely,

Natwar M. Gandhi
Chief Financial Officer

cc: The Honorable Anthony A. Williams, Mayor of the District of 
Columbia:

The Honorable Linda W. Cropp, Chairman, Council of the District of 
Columbia 

Gregory McCarthy, Deputy Chief of Staff for Policy and 
Legislative Affairs 

Noel Bravo, Special Assistant, Executive Office of 
the Mayor

[End of section]

Appendix 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 Assurance:

Jeanette Franzel, Director
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):

FOOTNOTES

[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.

[3] GAO-02-1001.

[4] U.S. Constitution., art. I,  8, cl. 17. 

[5] 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).

[6] National Associate of State Budget Officers.

[7] 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.

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

[9] 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.

[10] 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.

[11] 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.

[12] 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.

[13] 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. 

[14] 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.

[15] 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. 

[16] 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." 

[17] 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.

[18] 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.

[19] 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.

[20] 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.)

[21] 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.

[22] 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.

[23] 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.

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

[25] 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. 

[26] 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.

[27] 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.

[28] D.C. Code, 2001 Ed. Secs. 1-206.02 (6) and 6-601.05.

[29] Personal property refers to tangible property, such as machinery, 
equipment, and furniture, excluding real property, which refers to land 
and buildings.

[30] 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. 

[31] See medical vendor payments in table 5 of chapter 2.

[32] AARP, Reforming the Health Care System: State Profiles 2000 
(Washington, D.C.: 2000).

[33] McKinsey and Company, 2002. McKinsey did not audit these numbers.

[34] 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. 

[35] MAA is the District's single state Medicaid agency.

[36] 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.

[37] 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. 

[38] 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. 

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

[40] 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).

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

[42] Pub. L. 107-110.

[43] 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.

[44] However, for all three cities this information is neither 
comprehensive nor is it audited, rather the information is self 
reported.

[45] 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.

[46] 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).

[47] 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.

[48] 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. 

[49] 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.

[50] Fitch Press Release, "Fitch Rates District of Columbia's $375mm 
GO's 'BBB+'," Oct. 4, 2002.

[51] Long-term debt is typically used to finance capital projects.

[52] 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.

[53] Census data are as of April 2000, the most recent Census data 
available.

[54] 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.

[55] 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).

[56] Robert W. Rafuse, Jr., Representative Expenditures: Addressing the 
Neglected Dimension of Fiscal Capacity (Washington, D.C.: ACIR, 
December 1990).

[57] 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.

[58] 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. 

[59] 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.

[60] Rafuse, v. 

[61] Rafuse, v.

[62] 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.

[63] 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. 

[64] 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.

[65] 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 non-metropolitan 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.

[66] Panel on Poverty and Family Assistance [et al], Measuring Poverty: 
A New Approach (Washington, D.C.: National Academy of Sciences, 1995), 
197-200.

[67] 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." 

[68] Rafuse, p. 10, footnote 9.

[69] 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. 

[70] 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. 

[71] 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. 

[72] 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.

[73] Rafuse, 15.

[74] Rafuse, 15.

[75] 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.

[76] 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.

[77] 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).

[78] 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.

[79] These data are only available from the 1990 Decennial Census.

[80] See www.census.gov/govs/www/classfunc22.html.

[81] The District's unemployment rate was 10.7 percent compared to the 
national average of 5.7 percent.

[82] Of course, as noted earlier, this assumes a given average level of 
administrative efficiency.

[83] While input costs indexes are discussed later, we mention it here 
because the rationale is the same.

[84] The function in question here excludes medical vendor payments, 
welfare institutions, in-kind 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).

[85] The Rafuse method included only those mass transit subsidies 
provided to privately-owned 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.

[86] 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.

[87] 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.

[88] 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).

[89] 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."

[90] Corporate and partnership property are comprised of the sum of 
depreciable assets, depletable assets, and land less accumulated 
depreciation and depletion.

[91] 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.

[92] We solve for x in the following formula:


where x equals the value of rental property.

[93] 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.

[94] 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.

[95] 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.

[96] 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).

[97] 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).

[98] The two GSEs that we adjust for are the Federal National Mortgage 
Association (Fannie Mae) and SLM Corporation (Sallie Mae).

[99] 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.

[100] 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.

[101] 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.

[102] 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 own-source 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.

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