a

GAO

United States Government Accountability Office

Report to the Ranking Minority Member 

Subcommittee on Transportation and 

Infrastructure, Committee on 

Environment and Public Works, U.S. 

Senate

August 2004 FEDERAL-AID 

HIGHWAYS

Trends, Effect on State 

Spending, and Options 

for Future Program 

Design

GAO-04-802
www.gao.gov/cgi-bin/getrpt?GAO-04-802.

To view the full product, including the scope 

and methodology, click on the link above. 

For more information, contact JayEtta Hecker 

at (202) 512-2834 or heckerj@gao.gov. 

Highlights of GAO-04-802, a report to the 

Ranking Minority Member, Subcommittee 

on Transportation and Infrastructure, 

Committee on Environment and Public 

Works, U.S. Senate 

August 2004

FEDERAL-AID HIGHWAYS 

Trends, Effect on State Spending, and 

Options for Future Program Design 

In 2004, both houses of Congress 

approved separate legislation to 

reauthorize the federal-aid highway 

program to help meet the Nation’s 

surface transportation needs, 

enhance mobility, and promote 

economic growth. Both bills also 

recognized that the Nation faces 

significant transportation 

challenges in the future, and each 

established a National Commission 

to assess future revenue sources for 

the Highway Trust Fund and to 

consider the roles of the various 

levels of government and the 

private sector in meeting future 

surface transportation financing 

needs. 

This report (1) updates 

information on trends in federal, 

state, and local capital investment 

in highways; (2) assesses the 

influence that federal-aid highway 

grants have had on state and local 

highway spending; (3) discusses 

the implications of these trends for 

the federal-aid highway program; 

and (4) discusses options for the 

federal-aid highway program. 

Congress may wish to consider 

expanding the mandate of the 

proposed National Commission to 

consider options to redesign the 

federal-aid highway program in 

light of these issues. 

DOT officials commented on a 

draft of this report and said that the 

report raised important issues that 

merit further study. 

The Nation’s investment in its highway system has doubled in the last 20 

years, as state and local investment outstripped federal investment—both in 

terms of the amount of and growth in spending. In 2002, states and localities 

contributed 54 percent of the Nation’s capital investment in highways, while 

federal funds accounted for 46 percent. However, as state and local 

governments faced fiscal pressures and an economic downturn, their 

investment from 1998 through 2002 decreased by 4 percent in real terms, 

while the federal investment increased by 40 percent in real terms. 

Evidence suggests that increased federal highway grants influence states and

localities to substitute federal funds for funds they otherwise would have 

spent on highways. Our model, which expanded on other recent models, 

estimated that states used roughly half of the increases in federal highway 

grants since 1982 to substitute for state and local highway funding, and that 

the rate of substitution increased during the 1990s. Therefore, while state 

and local highway spending increased over time, it did not increase as much 

as it would have had states not withdrawn some of their own highway funds. 

These results are consistent with our earlier work and with other evidence. 

For example, the federal-aid highway program creates the opportunity for 

substitution because states typically spend substantially more than the 

amount required to meet federal matching requirements—usually 20 percent. 

Thus, states can reduce their own highway spending and still obtain 

increased federal funds. 

These trends imply that substitution may be limiting the effectiveness of 

strategies Congress has put into place to meet the federal-aid highway 

program’s goals. For example, one strategy has been to significantly 

increase the federal investment and ensure that funds collected for highways 

are used for that purpose. However, federal increases have not translated 

into commensurate increases in the nation’s overall investment in highways, 

in part because while Congress can dedicate federal funds for highways, it 

cannot prevent state highway funds from being used for other purposes. 

GAO identified several options for the future design and structure of the 

federal-aid highway program that could be considered in light of these 

issues. For example, increasing the required state match, rewarding states 

that increase their spending, or requiring states to maintain levels of 

investment over time could all help reduce substitution. On the other hand, 

the ability of states to meet a variety of needs and fiscal pressures might be 

better accomplished by providing states with funds through a more flexible 

federal program—this could also reduce administrative expenses associated 

with the federal-aid highway program. While some of these options are 

mutually exclusive, others could be enacted in concert with each other. The 

commission separately approved by both houses of Congress in 2004 may be 

an appropriate vehicle to examine these options. 
Page i GAO-04-802 Federal-Aid Highways

Contents

Letter 1

Results in Brief 3

Background 7

States and Localities Invest More in Highways Than the Federal 

Government; However, Recent Federal Investment Has Outpaced 

State and Local Investment 16

Evidence Suggests Federal Highway Grants Have Increasingly Been 

Used to Substitute for Rather Than Supplement Spending from 

States’ Own Resources 21

Substitution May Be Limiting the Effectiveness of Strategies to 

Accomplish the Federal-Aid Highway Program’s Overall Goals 32

We Identified Several Options for the Design and Structure of the 

Federal-Aid Highway Program 40

Conclusions 46

Matter for Congressional Consideration 47

Agency Comments and Our Evaluation 47

Appendixes

Appendix I: Objectives, Scope, and Methodology 50

Appendix II: Description of Grant Substitution Model, Statistical 

Methods, and Results 53

Summary of Previous Studies 53

Description of GAO’s Statistical Model 62

Statistical Results 72

Appendix III: State Characteristics Associated with States’ Level of Effort 

to Fund Highways from State Resources 87

Appendix IV: Program Options Designed to Reduce Substitution 89

Appendix V: GAO Contacts and Staff Acknowledgments 94

GAO Contacts 94

Staff Acknowledgments 94

Tables Table 1: Federal-Aid Highway Program Grant Programs and 

Formulas 9

Table 2: Range of Estimates of Highway Substitution Rates by Time 

Period Based on a 95 Percent Confidence Level 24

Table 3: Options to Reduce Substitution 41

Table 4: Summary of Fiscal Substitution Studies 56
Contents

Page ii GAO-04-802 Federal-Aid Highways

Table 5: Highway Grant Substitution Rates Reported in Fiscal 

Substitution Studies 60

Table 6: Variables Considered in the Second Stage State Highway 

Expenditure Equation 63

Table 7: Variables Used to Explain the Distribution of Federal 

Highway Grants 67

Table 8: Descriptive Statistics 70

Table 9: Instrumental Variables Estimator of Federal Grants per 

Capita 73

Table 10: Instrumental Variables Estimates of State Highway 

Spending Model, Without Correcting for 

Autocorrelation 75

Table 11: Instrumental Variables Estimates of State Highway 

Spending Model, Correcting for Autocorrelation 77

Table 12: Summary Results of the Statistical Testing of the Variable 

Coefficients 79

Table 13: State Highway Spending Model with Statistically 

Insignificant Variables Removed 81

Table 14: State Highway Spending Model with Substitution Rates by 

Time Period 83

Table 15: Statistical Tests for the Endogeneity of Federal Grants and 

State Highway Spending 85

Table 16: Stepwise Regression Analysis of the Fixed Effects 86

Figures Figure 1: Illustrative Effects of $1 Increase in Federal Highway 

Grant 15

Figure 2: Federal and State and Local Highway Capital 

Expenditures, 1982 through 2002 (2001 dollars) 17

Figure 3: Amount of Yearly Capital Expenditures, 1998 through 

2002 (2001 dollars) 19

Figure 4: Federal and State and Local Highway Capital Investment, 

1991 through 2002 (2001 dollars) 20

Figure 5: Rates of Fiscal Substitution into Nonhighway Uses by 

Time Period 23

Figure 6: Summary of Federal Grant Substitution Rates Reported 

in Various Studies Using Data from Various Time 

Periods 28

Figure 7: State and Local Highway Spending for Capital Projects as 

a Percent of Total (Federal Plus State and Local) Capital 

Spending (1997 through 2000) 31

Figure 8: Federal Obligations by System in Fiscal Year 2001 37
Contents

Page iii GAO-04-802 Federal-Aid Highways

Figure 9: DOT Performance Measures for Condition and System 

Performance 39

Abbreviations

DOT Department of Transportation

BEA Bureau of Economic Analysis

FHWA Federal Highway Administration

GPRA Government Performance and Results Act

ISTEA Intermodal Surface Transportation Efficiency Act 

MOE Maintenance of Effort

NHTSA National Highway Traffic Safety Administration

TEA-21 Transportation Equity Act for the 21st Century

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Page 1 GAO-04-802 Federal-Aid Highways

United States Government Accountability Office

Washington, D.C. 20548

A

August 31, 2004 Letr

The Honorable Harry Reid

Ranking Minority Member

Subcommittee on Transportation and Infrastructure 

Committee on Environment and Public Works

United States Senate

Dear Senator Reid: 

In 2004, both houses of Congress approved separate legislation to 

reauthorize the federal-aid highway program to help meet the Nation’s 

surface transportation needs, enhance mobility, and promote economic 

growth. Each bill also recognized that the Nation faces significant 

transportation challenges in the future. Many transportation experts have 

noted that eventually, the introduction of more fuel-efficient vehicles and 

clean fuels may undermine the sustainability of financing the Nation’s 

surface transportation program through motor fuel taxes. As such, both 

bills established a National Commission to assess future revenue sources 

for the Highway Trust Fund and to consider the roles of the various levels 

of government and the private sector in meeting future surface 

transportation financing needs. In the longer term, broader fiscal 

challenges face the Nation, including federal and state budget deficits and 

the fiscal crisis looming as the baby boomer generation retires, causing 

mandatory commitments to Social Security and Medicare to consume a 

greater share of the Nation’s resources, squeezing funding available for all 

domestic discretionary programs. These challenges require the Nation to 

think critically about existing government programs and commitments.

In light of these issues, you asked us to provide information on past trends 

in the federal, state, and local capital investment in highways, and on how 

federal-aid highway program grants influence the level of state and local 

highway spending. We responded to the first part of your request in June 

2003.1

 This report (1) updates information on trends in federal, state, and 

local capital investment in highways; (2) assesses the influence that 

federal-aid highway grants have had on state and local highway spending; 

(3) discusses the implications of these trends for the federal-aid highway 

program; and (4) discusses options for the structure and design of the 

1

GAO, Trends in Federal and State Capital Investment in Highways, GAO-03-744R

(Washington, D.C.: June 18, 2003).
Page 2 GAO-04-802 Federal-Aid Highways

federal-aid highway program that could be considered in light of these 

issues. In addition, this report identifies characteristics associated with 

differences among states’ levels of effort for highway investment (see app. 

III).

To respond to your request, we reviewed data from the Department of 

Transportation’s (DOT) Federal Highway Administration (FHWA), the 

Bureau of the Census, and other sources for the period from 1982 through 

2002. We determined that the data were sufficiently reliable for the 

purposes of our analyses. We also reviewed and synthesized the research 

literature on the influence that federal highway grants have had on the level 

of state and local highway spending. Our literature review revealed a 

number of studies that used statistical models developed by the studies’ 

authors to estimate the influence of federal funding on state spending 

choices. These models examined different time periods, employed different 

statistical methods, and considered different social, demographic, 

economic, and political factors that may affect state highway spending 

decisions. None of the models used in the studies we reviewed included the 

most recent data now available on highway funding, and none examined 

whether the effect of federal grants on state spending changed over the 

time period covered in the study. Therefore, based on the models used in 

the earlier studies, we developed a statistical model of state highway 

spending outcomes to estimate the fiscal effects of federal highway funding 

on state highway spending choices. This model included the most recent 

data available and examined whether the effect of federal grants on state 

spending changed over the time period covered by our data. The purpose of 

the statistical model was to isolate the effect that federal grants have on 

state highway spending by controlling for other factors that also affect 

state spending decisions. The model therefore takes into account changing 

state economic conditions, the size and intensity of highway usage, and 

other factors that may be associated with states’ willingness to support 

highway spending. This statistical model was reviewed by experts in DOT 

and peer reviewed by three authors of the earlier studies on the fiscal 

effects of federal highway grants. These experts and authors generally 

agreed with our methods, and we made revisions based on their comments 

as appropriate. A more detailed description of the literature and the 

statistical model is contained in appendix II. We conducted our work from 

August 2003 through July 2004 in accordance with generally accepted 

government auditing standards.
Page 3 GAO-04-802 Federal-Aid Highways

Results in Brief The Nation’s capital investment in its highway system has doubled in the 

last 20 years, and during that time period as a whole, state and local 

investment in highways outstripped federal investment in highways—both 

in terms of the amount of and growth in spending. Between 1982 and 2002, 

state and local capital investment in highways increased 150 percent, from 

$14.1 billion to $35.7 billion in real terms, whereas the federal investment 

increased 98 percent, from $15.5 billion to $30.7 billion in real terms.2

 For 

every year after 1986, states and localities invested more in the Nation’s 

highways than did the federal government. Most recently, in 2002, states 

and localities contributed 54 percent of the Nation’s capital investment in 

highways, spending $35.7 billion, while the federal government contributed 

46 percent, or $30.7 billion. However, since the early 1990s, state and local 

investment in highways has increased at a slower rate than federal 

investment in highways. From 1991, when the Intermodal Surface 

Transportation Efficiency Act (ISTEA) was enacted, through 2002, state 

and local investment increased 23 percent, from $29.0 to $35.7 billion in 

real terms. During that same time period, federal investment increased 47 

percent, from $20.9 to $30.7 billion in real terms. In the period following the 

enactment of the Transportation Equity Act for the 21st Century (TEA-21), 

from 1998 through 2002, during which state and local governments faced 

fiscal pressures and an economic downturn, the trend intensified, with 

state and local investment decreasing by 4 percent—from $37.0 to $35.7 

billion in real terms—and federal investment increasing by 40 percent—

from $21.9 to $30.7 billion in real terms. 

The preponderance of evidence suggests that federal-aid highway grants 

have influenced state and local governments to substitute federal funds for 

state and local funds that otherwise would have been spent on highways. 

Therefore, according to our model—which refined and expanded on other 

recent models and controlled for the effects of other factors—and 

according to other studies, when federal highway grants increased, total 

highway spending did not increase as much as it would have had states not 

withdrawn some of their own highway-related funds. Specifically, our 

model examined how federal highway spending affected state spending, 

and it estimated that state and local governments have used roughly half of 

the increases in federal highway grants since 1982 to substitute for funding 

they would otherwise have spent from their own resources. In addition, our 

2

Dollar amounts in this report are adjusted to 2001 dollars, matching adjustments made in 

the earlier related report GAO-03-744R.
Page 4 GAO-04-802 Federal-Aid Highways

model estimated that the rate of grant substitution increased significantly 

over the past two decades, rising from about 18 cents on the dollar during 

the early 1980s to roughly 60 cents on the dollar during the 1990s, when 

ISTEA and TEA-21 were in effect.3

 Three previous studies of this issue all 

found that substitution occurred, although their estimates of levels of 

substitution varied, probably due to differences in time periods studied, 

definitions of substitution, and statistical methods employed. There are a 

number of reasons why substitution may occur. Our earlier work found 

that in general, the federal grant system as a whole does not encourage 

states to use federal dollars as a supplement rather than a substitute for 

their own spending.4

 Specifically, the structure of the federal-aid highway 

program creates an opportunity for substitution because states typically 

spend substantially more in state and local funds than is required to meet 

current federal matching requirements. As a consequence, when federal 

funding increases, states are able to reduce their own highway spending 

and yet obtain the increased federal funds. If states substitute some of the 

increase in federal funds for their own funds, then total highway spending 

may increase, but not by as much as it would have had substitution not 

occurred. 

These trends imply that substitution may be limiting the effectiveness of 

the strategies Congress has put into place to meet the federal-aid highway 

program’s overall goals. Congress and DOT have at various times 

enumerated goals for the federal-aid highway program, including, among 

other things, enhancing safety, promoting economic growth, enhancing 

mobility, supporting interstate and international commerce, and meeting 

national security needs. To meet these goals, Congress has put in place 

strategies that include significantly increasing the federal investment in the 

highway system—particularly since 1991—and ensuring that funds 

collected by the federal government for highways are used for that 

purpose. However, due to probable substitution, the sizable increases in 

3

While these estimates represent our most likely estimates of the substitution that occurred, 

they are only estimates. The uncertainty surrounding our estimates can be expressed in 

terms of a level of confidence that a given range of values encompasses the actual 

substitution rate. This is discussed later in this report. For example, the estimate of an 18 

percent substitution rate for the early 1980s is not statistically different from a finding of no 

substitution. Regarding our estimate of 60 cents on the dollar during the 1990s, the actual 

substitution rate, with a 95 percent level of confidence, may be as high as 96 percent or as 

low as 21 percent. 

4

GAO, Federal Grants: Design Improvements Could Help Federal Resources Go Further

(GAO/AIMD-97-7), December 18, 1996.
Page 5 GAO-04-802 Federal-Aid Highways

dedicated federal funding that Congress has provided for highways since 

1991 have not translated into commensurate increases in the Nation’s 

overall investment in its highway system. In part this is because, while 

Congress can dedicate federal funds for highways, it cannot prevent state 

highway funds from being used for other purposes. Furthermore, Congress 

has sought to meet the goals of the program through a strategy of 

emphasizing states’ priorities and decision-making. Specifically, Congress 

has incorporated return-to-origin features into the highway program and 

returned to each state more of the fuel and other taxes collected in that 

state, and has given states wide latitude in deciding how to use and 

administer federal grants to best meet their transportation needs. However, 

substitution may be limiting the effectiveness of this strategy. Although the 

federal-aid highway program has a considerable regulatory component that 

requires states to follow and enact certain laws as a condition of receiving 

federal funds, from a funding standpoint, the program’s return-to-origin 

features and flexibility, combined with substitution and the use of state and 

local highway funds for other purposes, means that the federal-aid highway 

program is to some extent functioning as a cash transfer, general purpose 

grant program. This raises broader questions about the effectiveness of the 

federal investment in highways in accomplishing the program’s goals and 

outcomes. While under the Government Performance and Results 

Accountability Act (GPRA), DOT has established performance measures 

and outcomes for the federal-aid highway program to enhance mobility and 

economic growth, the program’s current structure does not link funding 

with performance or the accomplishment of these goals and outcomes.

We identified several options for the design and structure of the federal-aid 

highway program that could be considered in light of these issues. These 

options include program designs that have been used for other federal 

programs and which could reduce substitution. For example, increasing 

the required state match on federal highway projects, rewarding states that 

increase their highway spending effort, or requiring states to maintain 

levels of highway investment over time to receive federal funds could all 

reduce substitution. On the other hand, the ability of states to meet a 

variety of needs and fiscal pressures might be better accomplished by 

providing states with funds through a more flexible federal program. 

Adopting such an option could be seen as recognizing substitution as an 

appropriate response on the part of states to increasing fiscal challenges 

and competing demands. It could also reduce the level of administrative 

involvement needed and thereby reduce administrative expenses 

associated with the federal-aid highway program. Finally, policy makers 

may wish to consider the design of the federal-aid highway program in the 
Page 6 GAO-04-802 Federal-Aid Highways

broader context of aligning the program with program-related goals, 

possibly taking into account performance measures and results. While 

some of these options are mutually exclusive, others could be enacted in 

concert with each other. For instance, requiring states to maintain levels of 

highway investment over time or other options to limit substitution could 

be combined with an effort to align funding with the accomplishment of 

performance measures. Similarly, aligning funding with the 

accomplishment of performance measures could also be carried out in 

conjunction with creating a more flexible federal program.

The proposed National Commission to assess future revenue sources to 

support the Highway Trust Fund may be an appropriate vehicle through 

which to examine these options. This commission is to consider how the 

program is financed and the roles of the federal and state governments and 

other stakeholders in financing it; the appropriate program structure and 

mechanisms for delivering that funding are important components of 

making these decisions. Therefore, in light of the issues raised in this report 

and the fiscal challenges the Nation faces in the 21st Century, Congress may 

wish to consider expanding the mandate of the National Commission to 

assess possible changes to the federal-aid highway program to maximize 

the effectiveness of federal funding and promote national goals and 

strategies. Consideration could be given to the program’s design, structure, 

and funding formulas; the roles of the various levels of government; and the 

inclusion of greater performance and outcome oriented features.

We provided a draft of this report to DOT for review and obtained 

comments from departmental officials, including FHWA’s Director of 

Legislation and Strategic Planning. These officials said that our analysis 

raised interesting and important issues regarding state funding flexibility 

and the federal-aid highway program that merit further study. We agree 

with DOT’s characterization of the importance of the issues raised in this 

report, and we continue to believe that Congress has the opportunity to 

maximize the effectiveness of federal funding and promote national goals 

and strategies by expanding the proposed mandate of the National 

Commission. DOT also provided some technical comments, which we 

incorporated where appropriate. 
Page 7 GAO-04-802 Federal-Aid Highways

Background Federal funding for highways is provided to the states mostly through a 

series of formula grant programs collectively known as the federal-aid 

highway program.5

 Periodically Congress enacts multiyear legislation that 

authorizes the Nation’s surface transportation programs, including 

highway, transit, highway safety, and motor carrier programs. This 

legislation authorizes the federal-aid highway program and the individual 

grant programs that comprise it, and it sets overall funding for it and other 

surface transportation programs. In 1991, for example, Congress enacted 

ISTEA, which authorized $121 billion for highways for the 6-year period 

from fiscal years 1992 through 1997, and in 1998 Congress enacted TEA-21, 

which authorized $171 billion for the federal-aid highway program from 

fiscal years 1998 through 2003. In 2004, the House and Senate each 

approved separate legislation to reauthorize the federal-aid highway 

program, the House authorizing $226.3 billion and the Senate authorizing 

$256.4 billion for fiscal years 2004 through 2009. These authorizations 

provide multiyear “contract authority” that gives the states notice several 

years in advance of the size of the federal-aid program and the approximate 

amount of federal funding they may expect to receive. 

Funding for the federal-aid highway program is provided through the 

Highway Trust Fund. Established by the Highway Revenue Act of 1956, the 

Highway Trust Fund is a dedicated source of revenues generated by 

highway user fees such as taxes on motor fuels, tires, and trucks. TEA-21 

established two additional mechanisms to support the dedication of 

highway user fees to highways. First, the act established guaranteed 

funding for certain highway, transit, and highway safety programs, 

including the federal-aid highway program, by protecting them with 

“firewalls” from competing for funding with other domestic discretionary 

programs through the congressional budget process. Second, the act 

provided that the highway program funding authorizations would be 

adjusted to reflect changes in estimates of Highway Trust Fund revenue, 

ensuring that funding available for the federal-aid highway program 

reflected the revenue taken in by the Highway Trust Fund. Both the Senate 

and the House have each approved separate legislation to extend the 

collection of fuel taxes to the Highway Trust Fund, the Senate through 2009 

and the House through 2011. Amid concerns that the introduction of more 

5

The federal-aid highway program also includes discretionary grants and research and 

development programs. While grants are provided to states, localities may also sponsor 

federal-aid projects and can receive some federal funds, primarily through their state.
Page 8 GAO-04-802 Federal-Aid Highways

fuel-efficient vehicles and clean fuels may undermine the sustainability of 

financing the Highway Trust Fund through fuel taxes in the future, both 

houses also included provisions to create a National Commission to 

examine future revenue sources to support the Highway Trust Fund and to 

consider, among other things, the roles of the various levels of government 

and the private sector in meeting future surface transportation financing 

needs. 

Once Congress authorizes funding, FHWA makes federal funding available 

to the states annually at the start of each fiscal year through 

apportionments based on formulas specified in law for each of the several 

formula grant programs that make up the federal-aid highway program. 

Ninety-two percent of the funds apportioned to the states in fiscal year 

2003 were apportioned by formula. The remaining highway program funds 

were distributed through allocations to states with qualifying projects. The 

highway programs with apportionments based on formulas are shown in 

table 1.
Page 9 GAO-04-802 Federal-Aid Highways

Table 1: Federal-Aid Highway Program Grant Programs and Formulas

Program Purpose

FY 2003 funding 

(in billions)a Grant formula Minimum apportionment

Interstate Maintenance 

Program

Resurfacing, restoring, 

rehabilitating, and 

reconstructing most 

routes on the Interstate 

Highway System. 

$4.2 Interstate System lane 

miles (33 1/3%)

Vehicle miles traveled on 

the Interstate System (33 

1/3%)

Annual contributions to 

the Highway Account of 

the Highway Trust Fund 

attributable to commercial 

vehicles (33 1/3%)

1⁄2 percent of Interstate 

Maintenance and National 

Highway System 

apportionments combined

National Highway System 

Program

Improvements to rural 

and urban routes that 

are part of the National 

Highway System 

(including the Interstate 

System) and designated 

connections to major 

intermodal terminals. 

$5.1 Lane miles on principal 

arterial routes, excluding 

the Interstate System 

(25%)

Vehicle miles traveled on 

principal arterial routes, 

excluding the Interstate 

System (35%)

Diesel fuel used on 

highways (30%)

Total lane miles on 

principal arterial highways 

divided by the State’s total 

population (10%)

1⁄2 percent of Interstate 

Maintenance and National 

Highway System 

apportionments combined

Surface Transportation 

Program

Projects on any federalaid highway, bridge 

projects on any public 

road, transit capital 

projects, intracity and 

intercity bus terminals 

and facilities, and other 

uses.

$5.9 Total lane miles of federalaid highways (25%)

Total vehicle miles 

traveled on federal-aid 

highways (40%)

Estimated tax payments 

attributable to highway 

users paid into the 

Highway Account of the 

Highway Trust Fund 

(35%)

1⁄2 percent

Highway Bridge 

Replacement and 

Rehabilitation Program

Replacing or 

rehabilitating deficient 

highway bridges and 

seismic retrofits for 

bridges on public roads.

$3.6 Relative share of total 

cost to repair or replace 

deficient highway bridges 

(100%)

1⁄4 percent (10 percent 

maximum)
Page 10 GAO-04-802 Federal-Aid Highways

Source: FHWA. 

a

Reflects amounts apportioned by formula before the distribution of Minimum Guarantee Program 

funding among the core programs.

b

Includes funds for the Appalachian Development Highway System and Recreational Trails Programs.

As we reported in 1995, the federal funding formula derives from a 

complicated set of calculations and is a complex process in which the 

underlying data and factors are ultimately not meaningful because they are 

overridden by other provisions that yield a predetermined outcome.

6

 One 

reason is the presence of “equity provisions” that ensure that states receive 

set amounts based on historic funding levels and other considerations. 

These equity provisions were strengthened after our 1995 report. For 

example, as table 1 shows, TEA-21’s Minimum Guarantee Program ensures 

that each state’s share of apportionments from nearly all federal-aid 

highway funds is not less than 90.5 percent of that state’s percentage share 

Congestion Mitigation and 

Air Quality Improvement 

Program

Projects which reduce 

transportation related 

emissions in air quality 

nonattainment and 

maintenance areas for 

ozone, carbon 

monoxide, and 

particulate matter.

$1.4 Weighted population in 

non- attainment and 

maintenance areas 

(100%)

1⁄2 percent

Minimum Guarantee 

Program

Funding to states based 

on equity considerations 

including specific shares 

of overall program funds 

and minimum return on 

contributions to the 

highway account of the 

Highway Trust Fund. A 

portion of the funds are 

distributed among core 

highway programs while 

remaining funds are 

eligible under the same 

rules as the Surface 

Transportation Program.

$6.4 90.5 percent of the 

percentage share of 

contributions to the 

Highway Account of the 

Highway Trust Fund from 

motor fuel and other taxes 

collected in that state 

based on latest available 

data

N/A

Other b $0.5

(Continued From Previous Page)

Program Purpose

FY 2003 funding 

(in billions)a Grant formula Minimum apportionment

6

GAO, Highway Funding: Alternatives for Distributing Federal Funds (GAO/RCED-96-6) 

Nov. 28, 1995.
Page 11 GAO-04-802 Federal-Aid Highways

of contributions to the Highway Account of the Highway Trust Fund.7

Funds from this program accounted for nearly a quarter of all highway 

funding in fiscal year 2003. Under separate legislation approved by both the 

House and the Senate, each state’s share of apportionments could rise to 95 

percent by 2009.8

 Furthermore, as table 1 shows, states receive minimum 

apportionments regardless of the formula for several grant programs. 

States have broad flexibility to transfer funds between the various grant 

programs. For example, states may transfer up to 50 percent of their 

Interstate Maintenance and National Highway System Program funds to 

other programs, including the Surface Transportation Program, which, as 

table 1 shows, has broad eligibility rules. In addition, ISTEA and TEA-21 

provided the states broad authority to transfer federal-aid highway funds to 

transit projects and vice versa. Between fiscal years 1992 and 2002, 47 

states and the District of Columbia transferred about $8.8 billion from 

federal-aid highway funds to transit programs to fund rail line 

improvements, motor vehicle purchases, new or improved passenger 

facilities, and other projects. During that same time, about $40 million was 

transferred from FTA to FHWA for highway projects.

Once FHWA apportions funds to the states, funds are available to be 

obligated by the states for construction, reconstruction, and improvement 

of highways and bridges on eligible federal-aid highway routes and for 

other purposes authorized in law. About 1 million of the Nation’s 4 million 

miles of roads are eligible for federal aid; however, these roads accounted 

for 85 percent of the vehicle miles traveled on the Nation’s roadways in 

2001. The roads that are generally ineligible are functionally classified as 

local roads or minor collectors. Around 161,000 miles of federally eligible 

roadways are on the National Highway System, of which around 47,000 

belong to the Interstate Highway System. With few exceptions, federal 

funds for highways must be matched by funds from other sources—usually 

state and local governments. The matching requirement on most projects is 

7

According to FHWA, although never legally described and named as such, the portion of the 

Highway Trust Fund that is not specifically credited by law to the Mass Transit Account of 

the Highway Trust Fund has come to be called the “Highway Account” and receives all Trust 

Fund receipts not specifically designated for the Mass Transit Account. 

8

The Senate approved the 95 percent amount while the House bill contained a “reopener” 

provision that would delay fiscal year 2006 funding for most federal-aid highway programs 

from October 2005 until August 2006 if Congress has not enacted legislation by September 

30, 2005, raising each states’ guaranteed rates of return to 95 percent, effective in fiscal year 

2009.
Page 12 GAO-04-802 Federal-Aid Highways

80 percent federal and 20 percent state or local funding. In addition to 

matching federal funds, states and localities spend funds to finance 

highway capital projects and to maintain existing roadways.

The federal-aid highway program is administered by FHWA, whose 

responsibilities include reviewing periodic transportation improvement 

plans prepared by state and local governments, approving projects for 

federal aid, apportioning grant funding to the states, providing technical 

support, and overseeing federally funded projects. In fiscal year 2004, 

FHWA received $334 million to provide these services, with an authorized 

staff level of 2,931 positions. FHWA personnel are located in Washington, 

D.C., and in 52 field offices located in each state, the District of Columbia, 

and Puerto Rico, as well as a regional “resource center” with four offices 

across the country that provide specialized technical assistance to the field 

offices and the states. 

The federal-aid highway program has a considerable regulatory 

component. As a condition of receiving federal aid, states agree to apply 

and enforce certain federal laws on federally aided projects, such as the 

environmental assessment provisions in the National Environmental Policy 

Act, the Americans With Disabilities Act, the nondiscrimination protections 

found in the Civil Rights Act of 1964, and others. In addition, states are 

required to establish goals and to award a set percentage of contracts (the 

national goal is 10 percent) on federally aided projects to small businesses 

owned and controlled by socially and economically disadvantaged 

individuals, including minority and women-owned businesses. 

Furthermore, in accepting federal-aid highway funds, states must enact 

certain laws to improve highway safety or face penalties in the form of 

either withholdings or transfers in their federal grants.9 In addition to these 

penalties, states may apply for and receive highway safety incentive grants 

through programs administered outside the federal-aid highway program 

by the National Highway Traffic Safety Administration (NHTSA). For 

example, states in which the use of seat belts exceeds the national average 

or improves over time are eligible for incentive grants based on NHTSA’s 

9

Under TEA-21, states are subject to withholdings or transfers in their federal grants if they 

fail to enact laws that (1) prohibit open alcoholic beverage containers in the passenger area 

of a motor vehicle, (2) establish minimum penalties for repeat drunk-driving offenders, and 

(3) establish laws making it illegal for people to drive with the specified level of alcohol in 

their blood of .08 blood alcohol concentration—the level at which a person’s blood contains 

2/25th of 1 percent alcohol.
Page 13 GAO-04-802 Federal-Aid Highways

calculation of the annual savings to the federal government in medical 

costs that resulted from the increased use. 

In general, there are three possible ways that federal grant funding can 

influence state spending for a program, as illustrated in figure 1. First, 

increased federal funding may stimulate, or leverage, additional spending 

from state resources. For example, a state may have to increase its own 

spending in order to meet federal matching requirements and obtain 

federal funds, thus increasing the overall level of spending by more than 

the amount of the federal grant.10 As the federal-aid highway program in 

most cases requires that states must contribute 20 percent of the total cost 

of a project in order to receive federal matching funds of 80 percent of the 

total cost, the suggestion is that every $1.00 increase in federal funds would 

go towards a total spending increase of $1.25 ($1.00 is 80 percent of $1.25), 

$0.25 of which would be funded with state and local government funds 

($0.25 is 20 percent of $1.25). The result of a stimulative effect of federal 

grant funding is illustrated in the first panel of figure 1, in which an 

additional $1.00 of federal aid increases spending from state resources by 

25 cents, increasing the overall level of highway spending by $1.25. 

Alternatively, increased federal funding may supplement state spending by 

adding to what states would otherwise have spent, increasing the overall 

level of spending by the amount of the federal grant, as illustrated in the 

second panel of figure 1. To the extent that states maintain their own 

spending when they receive additional federal funding, either because 

federal policy requires that they do so or because they do so voluntarily, 

then the additional federal aid supplements state spending. Finally, states 

may use increased federal funding to substitute for, or replace, what they 

would otherwise have spent from state resources, so that the overall level 

of spending increases by less than the amount of the federal grant. This 

substitution of federal funds for state funds is illustrated in the third panel 

of figure 1, in which an additional $1.00 in federal funding results in only a 

50 cent increase to total spending because in response to the influx of 

10With matching requirements, states must contribute their own funds in order to receive 

federal matching funds. Economic theory suggests that grants requiring matching, by 

lowering the effective price of aided programs relative to other state spending priorities, 

encourage states to spend more of their own funds. Matching grants typically contain either 

a single rate (e.g., 50 percent) or a range of rates (e.g., 50 percent to 80 percent) at which the 

federal government will match state spending on an aided program.
Page 14 GAO-04-802 Federal-Aid Highways

federal funds, the state withdraws 50 cents of its own spending on the 

program and uses these funds for other purposes.11

11Although the fiscal effect of grants has been described in the text only in terms of an 

increase in federal grant funding, stimulation and substitution may also occur when federal 

funding is declining. If in response to a decline in federal aid, for example, states increase 

spending from state resources to compensate for the loss in federal funding, this too 

represents grant substitution, the substitution of state funds for federal funding. 
Page 15 GAO-04-802 Federal-Aid Highways

Figure 1: Illustrative Effects of $1 Increase in Federal Highway Grant

State highway 

spending

Stimulative Effect: Total Highway Spending Increases by $1.25

Before Grant After Grant

Before Grant After Grant

After Grant

$5.25

$5.00

$5.00

$0.50

$6.25 

$0.25 $1.00 

$1.00 

$1.00 

$6.00 

$5.50 

Federal grant

Supplemental Effect: Total Highway Spending Increases by $1.00

Substitutive Effect: Total Highway Spending Increases by $0.50

Source: GAO.

State

spending

State

spending

State

spending

State

spending

Federal

spending

State

spending

State

spending

Federal

spending

Federal

spending

$5.00

$4.50

Before Grant

$5.00

Federal grant

Federal grant

Other public 

services or 

state 

taxpayer 

relief

State highway 

spending

State highway 

spending

State highway 

spending

State highway 

spending State highway 

spending
Page 16 GAO-04-802 Federal-Aid Highways

States and Localities 

Invest More in 

Highways Than the 

Federal Government; 

However, Recent 

Federal Investment 

Has Outpaced State 

and Local Investment 

The Nation’s capital investment in its highway system has doubled in the 

last 20 years, and during that time period as a whole, state and local 

investment in highways outstripped federal investment in highways—both 

in terms of the amount of and growth in spending. Between 1982 and 2002, 

state and local capital investment in highways increased 150 percent, from 

$14.1 billion to $35.7 billion in real terms, whereas the federal investment 

increased 98 percent, from $15.5 billion to $30.7 billion in real terms.12 For 

every year after 1986, states and localities invested more in the Nation’s 

highways than did the federal government. (See fig. 2.) Most recently, in 

2002, states and localities contributed 54 percent of the Nation’s capital 

investment in highways, spending $35.7 billion, while the federal 

government contributed 46 percent or $30.7 billion in real terms. 

12To determine trends in real terms, we adjusted the data to 2001-year dollars to coincide 

with the data in our related report, GAO-03-744R, which presented data from 1982 through 

2001. We converted these data using the Bureau of Economic Analysis’ (BEA) Price Indexes 

for Gross Government Fixed Investment—Highways and Streets.
Page 17 GAO-04-802 Federal-Aid Highways

Figure 2: Federal and State and Local Highway Capital Expenditures, 1982 through 2002 (2001 dollars)

In addition to the billions of dollars states and localities invest in capital 

highway projects to expand highway capacity or rehabilitate existing 

highways, states and localities spend additional funds maintaining and 

policing their roadways. For example, in 2001, states and localities spent 

about 27 percent of their total capital and maintenance funding on 

maintenance activities, including fixing potholes, sealing cracks in bridge 

decks, and fixing highway lighting. 

Although states and localities still spend more on highway capital 

investment than the federal government, recently, state and local highway 

investment has increased at a slower pace than federal highway 

investment. In addition, state and local investment has decreased in real 

terms three times since 1996: between 1996 and 1997, between 1999 and 

2000, and between 2001 and 2002. Last year, we reported that since TEA-21 

was passed, from 1998 through 2001, federal investment increased faster 

Dollars in billions (2001)

Source: GAO analysis of FHWA data.

Year

0

5

10

15

20

25

30

35

40

45

State and local

Federal

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Page 18 GAO-04-802 Federal-Aid Highways

than state and local investment.13 In real terms, federal investment 

increased 29 percent, while state and local investment increased 2 

percent.14 This trend of federal investment increasing more quickly than 

state and local investment continued in 2002. From 2001 through 2002, 

federal investment increased 8.5 percent, while state and local investment 

decreased 5 percent in real terms. Thus, from 1998 through 2002, federal 

investment increased 40 percent, while state and local investment 

decreased by 4 percent. Figure 3 shows the annual federal and state and 

local capital expenditures on highways during these years.

13The percent change from 1998 through 2001 is computed by comparing the investment in 

these 2 years. The calculation does not describe the variations in the intervening years.

14As we reported, federal investment did not follow this pattern from 1997 to 1998, despite 

the large increase in funding authorized by TEA-21. When comparing the change in funding 

from 1997 through 2001, federal investment increased 23 percent while state and local 

investment increased 16 percent. This lower level of increase in federal expenditures was 

likely due to the midyear passage of TEA-21 in June 1998 and the amount of time it takes 

states to spend capital project funds. 
Page 19 GAO-04-802 Federal-Aid Highways

Figure 3: Amount of Yearly Capital Expenditures, 1998 through 2002 (2001 dollars)

The general trend of federal investment in highways increasing at a faster 

pace than state and local investment in highways holds over a longer period 

of time as well, including the period following the passage of ISTEA in 

1991. Although there was some variation on a year-by-year basis, from 1991, 

when ISTEA was enacted, through 2002, state and local investment 

increased 23 percent, from $29.0 to $35.7 billion in real terms. During that 

same time period, federal investment increased 47 percent, from $20.9 to 

$30.7 billion in real terms, as shown in figure 4. 

0

5

10

15

20

25

30

35

40

45

State and local

Federal

1998 1999 2000 2001 2002 

Dollars in billions (2001) 

Year

Source: GAO analysis of FHWA data.

$21.9

$37.0 $38.2

$24.1

$36.5

$27.1 $28.3

$37.6

$30.7

$35.7
Page 20 GAO-04-802 Federal-Aid Highways

Figure 4: Federal and State and Local Highway Capital Investment, 1991 through 

2002 (2001 dollars)

Although the reasons for this change in spending patterns by level of 

government are unclear, tough economic times, with a majority of states 

needing to reduce spending to avoid budget deficits, along with large 

increases in federal funds for highways may have influenced these 

spending patterns. For example, a recent survey of states by the National 

Conference of State Legislatures found that even after the economy began 

growing after the March 2001 national recession, 36 states still have budget 

shortfalls with a cumulative gap of about $25.7 billion.15

15National Conference of State Legislatures, State Budget Update: February 2003.

0

5

10

15

20

25

30

35

40

45

State and local

Federal

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Dollars in billions (2001) 

Year

Source: GAO analysis of FHWA data.
Page 21 GAO-04-802 Federal-Aid Highways

Evidence Suggests 

Federal Highway 

Grants Have 

Increasingly Been Used 

to Substitute for Rather 

Than Supplement 

Spending from States’ 

Own Resources 

The preponderance of evidence suggests that increases in federal-aid 

highway grants influence state and local governments to substitute federal 

funds for funding they would have otherwise spent on highway projects 

from their own resources.16 We built on earlier studies to develop a model 

that analyzed data from 1982 through 2000 to examine whether and to what 

extent states have substituted increases in federal highway funds for state 

highway funds. Our preferred model analyzes data from 1983 through 2000 

because of the statistical techniques we used.17 Our analysis suggests that 

significant substitution has occurred and that the rate of grant substitution 

increased significantly over the past two decades, rising from 18 percent in 

the early 1980s to about 60 percent during the 1990s—the periods that 

ISTEA and TEA-21 were in effect. Three previous studies of this issue also 

found that substitution existed, although their estimates of levels of 

substitution varied.18 The structure of the federal grant system as a whole 

may encourage substitution. Specifically, the structure of the federal-aid 

highway program creates an opportunity for substitution because states 

typically spend substantially more in state and local funds than is required 

to meet current federal matching requirements. As a consequence, when 

federal funding increases, states are able to reduce their own highway 

spending and yet obtain the increased federal funds. If states substitute 

some of the increase in federal funds for their own funds, then total 

highway spending may increase, but not by as much as it would have had 

substitution not occurred. 

16Alternatively, our results suggest that during periods of declining federal aid, states may 

replace some of the decline in federal funding with additional funding from state resources.

17See appendix II for a description of the various statistical models we considered and the 

rationale for our selection of a preferred model.

18Shama Gamkhar, “The Role of Federal Budget and Trust Fund Institutions in Measuring 

the Effect of Federal Highway Grants on State and Local Government Highway 

Expenditure,” Public Budgeting and Finance, Spring 2003; Brian Knight, “Endogenous 

Federal Grants and Crowd-out of State Government Spending: Theory and Evidence from 

the Federal Highway Aid Program,” The American Economic Review, Vol. 92 No. 1, March 

2002, pp. 71-92; and Harry Meyers, “Displacement Effects of Federal Highway Grants,” 

National Tax Journal, Vol. XL, No. 2, June 1987, pp. 221-235. 
Page 22 GAO-04-802 Federal-Aid Highways

Our Statistical Model 

Suggests Federal Highway 

Funds Have Increasingly 

Been Substituted for State 

Funds That Were Shifted to 

Nonhighway Uses 

Our statistical model, which we developed from previous models, 

estimates that states have used a significant portion of increases in federal 

highway funding to substitute for state and local funding for highways, and 

that the rate of substitution increased during the 1990s. According to our 

preferred model, for the entire period from 1983 through 2000, state 

governments used roughly half of the increases in federal highway grants to 

substitute for funding they would have otherwise spent from their own 

resources on highways.19 When our model examined four separate time 

periods from 1983 through 2000 that corresponded to the four 

authorization periods for the federal-aid highway program, the results 

suggest that the rate of grant substitution increased in the 1990s, during the 

periods in which ISTEA and TEA-21 were in effect, in comparison to the 

early 1980s.20 Specifically, our model suggests that states substituted 

approximately 18 cents (not statistically significant) of every dollar 

increase in federal aid from 1983 to 1986 for funds they would have spent 

on highways from their own resources. Our model suggests that the 

substitution rate rose to approximately 36 cents of every dollar increase in 

federal aid for the period from 1987 to 1991, and that the substitution rates 

then rose again to approximately 60 cents for every dollar increase in 

federal aid for the two periods examined in the 1990s: 1992 through 1997 

and 1998 through 2000. (See fig. 5.) 

19Our model and all the studies we examined used grant expenditures recorded by states as 

the measure of federal grants. Grant expenditures are recorded when the federal 

government reimburses states for eligible project expenses. One study, described later in 

the report, also used an alternative measure.

20Because grant allotments remain available for expenditures for up to 4 years, some of the 

grant expenditures for a given time period includes grant obligations from prior periods.
Page 23 GAO-04-802 Federal-Aid Highways

Figure 5: Rates of Fiscal Substitution into Nonhighway Uses by Time Period 

The rates of grant substitution for the time periods reported in figure 5 are 

derived from our statistical model of state spending choices and are subject 

to some uncertainty. While these estimates represent our most likely 

estimates of the rate at which states substituted federal funds for state and 

local funds, the actual substitution may be larger or smaller than these 

estimates. The uncertainty surrounding our estimates can be expressed in 

terms of a level of confidence that a given range of values encompasses the 

actual substitution rate. The range of values surrounding each of our 

estimates is shown in table 2 at a 95 percent level of confidence. The size of 

each interval provides a sense of the uncertainty associated with our 

estimates. The intervals associated with the two time periods during the 

1980s contain possible values of zero, meaning that we cannot be 95 

percent confident that substitution occurred during these periods. In 

contrast, the range of estimates for both time periods in the 1990s does not 

encompass zero; therefore, they are statistically different from zero, which 

means that our results imply at least a 95 percent level of confidence that 

substitution occurred. Our most likely estimates for the two periods we 

looked at in the 1990s are in both cases just under 60 percent, and we can 

0

10

20

30

40

50

60

70

80

90

100

 

 

1983-1986

1987-1991

1992-1997

1998-2000

Percentage

59 58

18

36

Time period

Source: GAO.
Page 24 GAO-04-802 Federal-Aid Highways

be 95 percent confident that the actual substitution rate was between 21 

percent and 97 percent. 

Table 2: Range of Estimates of Highway Substitution Rates by Time Period Based on 

a 95 Percent Confidence Levela

Source: GAO

a

Positive values represent grant substitution and negative values indicate grant stimulation.

These results are roughly consistent with previous studies that, when taken 

together, also seem to suggest increasing substitution rates over time. We 

made four primary enhancements to the models used in previous studies in 

developing our model. First, we used more recent data on highway 

expenditures than were available for previous studies. Second, we used a 

conservative definition of substitution. Our model defined substitution as 

occurring only when, in response to increased federal highway funds, state 

and local funds were moved out of highway-related projects altogether. We 

did not consider it substitution if in response to increased federal highway 

funds, state and local funds were moved from highway projects that were 

eligible for federal aid to highway projects that were not eligible for federal 

aid. Third, our model is structured to examine substitution rates over time, 

rather than being limited to one estimate covering all the years included in 

our study. Finally, compared to previous studies, we employed a more 

comprehensive collection of factors related to state spending decisions. 

Combined, we believe these enhancements increase the ability of our 

model to provide a conservative and more reliable estimate of the extent to 

which states substitute federal highway aid for spending that would 

otherwise have come from state and local resources. However, all 

estimates that are based on statistical models, particularly of complex 

processes such as the determination of states’ budget choices, are subject 

to uncertainty. This uncertainty can derive from both choices about what 

factors to include in a model and the inherent impreciseness in estimating 

relationships between one factor—in this case federal highway grants—

Time period

Point estimate 

(percent)

Low estimate 

(percent)

High estimate 

(percent)

1983-1986 18 -21 57

1987-1991 36 -2 74

1992-1997 59 22 97

1998-2000 58 21 95
Page 25 GAO-04-802 Federal-Aid Highways

and another, state and local highway spending. While we have attempted to 

take many factors affecting state spending decisions into account, there 

may be other factors that are not subject to precise measurement, such as 

the influence of citizen and interest groups on states’ funding decisions, 

that could not be included in our analysis. As a result of the uncertainty in 

both the data and the statistical formulation of our model, the precision of 

our estimate, or any other estimate, is limited and our estimate should be 

considered one point in a range within which the actual extent of 

substitution falls, and one piece of a body of evidence on the existence of 

substitution. (See app. II for additional details on our statistical model.)

In commenting on a draft of this report, DOT officials said that to the 

extent substitution occurred and increased during the 1990s, it was likely 

due to a number of factors, including changes in states’ revenues and 

priorities. While our analysis specifically took changing economic 

conditions into account when assessing state spending choices, 

determining specific causes is beyond the scope of our statistical model. 

For example, states faced rising demands for health care and education 

during the 1980s and early 1990s that they may have funded, in part, by 

reducing their own levels of highway funding effort when federal highway 

funding increased. Accordingly, our model establishes an association 

between substitution and increases in federal highway grants; it does not 

identify the specific causes responsible for these rising rates. 

Earlier Studies Found That 

Federal Grants Reduced 

States’ Highway Spending, 

Although Substitution 

Estimates Varied 

Three other studies, including two published in the past 3 years, have 

reported that states substituted additional federal highway spending for 

state spending. These studies reported a wide range of estimates for the 

percentage of federal funds that has been used as a substitute for state and 

local funds, from zero to nearly 100 percent. The wide range of estimates is 

the result of different time periods examined, different definitions of 

substitution, and differences in the statistical methods employed.21

A study by Brian Knight, which, of the three studies, included the most 

recent data, found that from 1983 through 1997, roughly 90 percent of 

21Issues related to the differing statistical methods employed in previous studies are 

discussed in appendix II. 
Page 26 GAO-04-802 Federal-Aid Highways

increased federal aid was substituted for state highway spending.22 Knight 

used a different definition of substitution than we used in our study. Knight 

defined substitution as occurring when, in response to increased federal 

highway funds, state funds were moved out of highway-related projects. He 

did not take into account local spending on highways, which might possibly 

have mitigated the reduction in state funds. 

Another study, by Shama Gamkhar,23 analyzed data from 1976 through 1990 

using two different measures of federal grants. Gamkhar reported an 

average substitution rate of 63 percent when measuring federal grants 

through grant expenditures (the same measure of federal grants used by 

the other studies, including our model) and an average substitution rate of 

22 percent when measuring federal grants through grant obligations.24

Gamkhar defined substitution the same way our model did, as when, in 

response to increased federal highway funds, state and local funds were 

moved out of highway-related projects altogether. 

22Knight, op. cit.

23Gamkhar, op. cit.

24The grant distribution process first allots federal funding to states. States then obligate 

these funds for eligible highway projects, and, finally, the federal government reimburses 

states at the time obligated balances are actually spent. Thus, obligations are the second 

step in the federal grant making process, and grant expenditures are the final step of the 

process. 
Page 27 GAO-04-802 Federal-Aid Highways

A study by Harry G. Meyers examined data from 1976 through 1982, and 

modeled substitution based on two different definitions of substitution.25

Using a definition of substitution similar to the definition employed in our 

model, the study found no evidence of substitution during this period. 

Meyers also modeled the substitution rate based on a different definition of 

substitution, defining substitution as occurring when state funds were 

moved out of federal-aid highway projects, even if those funds were used 

for highway projects that were ineligible for federal aid. Using this 

definition of substitution, the study found a substitution rate of 63 percent. 

The findings of these studies and GAO’s results are summarized in figure 6. 

In this figure, we placed next to our finding the findings of the three models 

that used the same measure of federal grants and the same or a similar 

definition of substitution that we did, organizing these chronologically.26

25Meyers, op. cit.

26Gamkhar and Meyers’s findings on the second and third bars of the figure used the same 

measure of federal grants and similar definitions of substitution. Knight’s study used the 

same measure of federal grants that we did and a definition of substitution that was closer 

to our definition than Meyers’s second analysis, and so we placed his finding as the fourth 

bar on the figure. Gamkhar and Meyers’s alternative ways of modeling (shown in the fifth 

and sixth bars of the figure) used considerably different measures of federal grants 

(Gamkhar) and substitution (Meyers) than we did in our model.
Page 28 GAO-04-802 Federal-Aid Highways

Figure 6: Summary of Federal Grant Substitution Rates Reported in Various Studies 

Using Data from Various Time Periods

Alternative approaches employed to measure grant substitution:

a

Substitution defined as the reduction in state and local government spending on all highway-related 

projects; federal grants measured as grant expenditures.

b

Substitution defined as the increase in state and local government nonhighway spending; federal 

grants measured as grant expenditures.

c

Substitution defined as the reduction in state (but not local) government spending on all highwayrelated projects; federal grants measured as grant expenditures.

d

Substitution defined as the reduction in state and local government spending on all highway-related 

projects; federal grants measured as grant obligations.

e

Substitution defined as the reduction in state and local government spending on federal-aid eligible 

highway projects; federal grants measured as grant expenditures.

As can be seen from this figure, generally, those studies with the same or 

similar definitions of substitution as our model also suggest that 

substitution rates may have increased over time. Specifically, Meyers 

reported no evidence of substitution into nonhighway spending from 1976 

through 1982; Gamkhar, based on data through 1990, reported higher rates 

of substitution; and Knight, based on data through 1997, reported even 

higher rates of substitution, although using a somewhat different definition 

of substitution. Our model also found evidence of such a trend. 

0

10

20

30

40

50

60

70

80

90

100

 

Meyerse

1976-1982

Gamkhard

1976-1990

Knightc

1983-1996

Gamkhara

1976-1990

Meyersb

1976-1982

GAOa

1983-2000

Percentage

50

63

91

22

63

0

Source: GAO, Meyers, op. cit., Gamkhar, op. cit., and Knight, op. cit.
Page 29 GAO-04-802 Federal-Aid Highways

Structure of the Federal 

Grant System in General 

May Encourage Substitution 

In 1996, we reported that the federal grant system as a whole does not 

encourage states to use federal dollars to supplement their own spending 

but rather results in states using federal grants to substitute for their own 

spending.27 In summarizing research over the past 30 years for a wide 

variety of federal grant programs, we reported that each additional dollar 

of federal grant funding substitutes for between 11 and 74 cents of funding 

states otherwise would have spent. On balance, we found that for every 

dollar of additional federal aid, states have withdrawn about 60 cents of 

their own funding. 

Our 1996 study found that federal grant programs produced a variety of 

fiscal effects, in part depending on the grant program’s structure. For 

example, grants are considered “open-ended” when there is no limit on 

federal matching, and “closed-ended” when total federal matching funds 

are capped. The influence of federal matching is essentially the same for 

both types of grants until a state obtains the maximum federal contribution 

for a closed-ended grant. After this point, closed-ended grants no longer 

provide additional matching funds in response to additional state spending. 

This lack of additional federal matching funds reduces the incentive for 

states to increase their own spending on aided activities. As a result, we 

found that open-ended grant programs, for example, Foster Care, Adoption 

Assistance and Medicaid, generally stimulated additional spending from 

state resources because the more states spent of their own resources, the 

more federal resources they would obtain.28 In contrast, closed-ended 

matching grant programs, such as the federal-aid highway program, which 

place a limit on the total amount of federal funds that states can receive 

through meeting matching requirements, as well as programs that do not 

require states to contribute matching funds to receive federal funds, were 

associated with higher rates of grant substitution and stimulated less 

additional spending on the aided activity. 

27GAO/AIMD-97-7.

28The median estimate, from the studies reviewed, was that each additional dollar of federal 

matching aid leverages an additional $0.38 in state spending. 
Page 30 GAO-04-802 Federal-Aid Highways

Structure of Federal-Aid 

Highway Program Creates 

an Opportunity for 

Substitution 

The federal-aid highway program is particularly susceptible to substitution 

because in general the current matching requirement for states is not high 

enough to require states to maintain or increase their spending in order to 

receive increases in federal funds. In most cases, the federal-aid highway 

program requires that the federal contribution be no more than 80 percent 

of the total cost of the project, while the state’s matching contribution be at 

least 20 percent. If the federal highway program worked to stimulate state 

spending, this might suggest that every $1.00 increase in federal funds 

would result in a total spending increase of $1.25 ($1.00 is 80 percent of 

$1.25), $0.25 of which would be funded with state and local government 

funds ($0.25 is 20 percent of $1.25). However, because in most cases state 

funding already exceeds the required state matching contribution, often by 

large amounts, states are not required to increase or even maintain their 

level of funding for projects in order to receive increases in federal funds. 

Several studies have demonstrated that state highway spending 

substantially exceeds federal matching requirements. The earliest study we 

reviewed found that, during the 1960s, 38 percent of aggregate state capital 

spending for noninterstate federal-aid highways was in excess of federal 

matching requirements.29 This study found that for the large majority of 

states, state spending on federal-aid highway system projects exceeded 

federal matching requirements by more than 10 percent. Another study 

found that in 1982, state spending on federal-aid highway system projects 

exceeded the required federal match by more than 19 percent.30 Other 

studies that have analyzed the fiscal effects of federal highway aid have 

also reported that state spending typically exceeds federal matching 

requirements.31

In general, states continue to spend more than their required match on 

federal-aid highway projects. In 2000, the most recent year for which data 

are available for federal-aid highways, states accounted for approximately 

49 percent of all federal-aid-eligible highway capital spending, which is 

over twice the required 20 percent match on most federal-aid highway 

29Edward Miller, “The Economics of Matching Grants: The ABC Highway Program,” 

National Tax Journal, Vol. XXVII, No. 2 pp. 221-229, June 1974. 

30Meyers, op. cit., considered his estimate of the over match by states conservative due to 

data limitations.

31Gamkhar, op. cit., and Knight, op. cit.
Page 31 GAO-04-802 Federal-Aid Highways

projects.32 Figure 7 shows the variation among states in their highway 

capital spending as a percent of total (federal plus state and local) highway 

capital spending during the period from 1997 through 2000. Although these 

data include spending on nonfederal-aid-eligible highways and therefore 

can not be used to determine precisely to what extent states are exceeding 

federal matching requirements, they show that in the majority of states, 

state and local spending counts for over half of total capital highway 

spending. 

Figure 7: State and Local Highway Spending for Capital Projects as a Percent of 

Total (Federal Plus State and Local) Capital Spending (1997 through 2000)

32States and localities invest in capital projects on both their federal-aid-eligible highways 

and roads where federal aid is not eligible to be used, such as roads functionally classified 

as local. The amount of funding spent on only federal-aid-eligible roads is periodically 

estimated by FHWA. This estimate is used for the national number. However, this 

information is not available for state-by-state analysis. Thus, figure 7 includes state and local 

spending on roads that are not eligible for federal aid, overstating the amount of state 

“match” on federal-aid eligible roads.

0

2

4

6

8

10

12

14

16

18

20

 

 

81% and

 above

20% or

21-35%

36-50%

51-65%

66-80%

 less

Number of states

1

6

12

19

13

0

Percentage of state and local capital spending

Source: GAO analysis of FHWA data.
Page 32 GAO-04-802 Federal-Aid Highways

Substitution May Be 

Limiting the 

Effectiveness of 

Strategies to 

Accomplish the 

Federal-Aid Highway 

Program’s Overall 

Goals

The trends in funding and probable substitution described in this report 

imply that substitution may be limiting the effectiveness of strategies 

Congress has put into place to help the federal-aid highway program 

accomplish its overall goals. Congress and DOT have at various times 

enumerated goals for the federal-aid highway program, and, to meet these 

goals, Congress has put in place a number of strategies, including 

increasing its investment in highways and giving states wide latitude in 

deciding how to use and administer federal grants to best meet their 

transportation needs. However, because of substitution, the sizable 

increases Congress provided in federal funding for highways have not 

translated into commensurate increases in the Nation’s overall spending in 

its highway system. In part, this is because, while Congress can dedicate 

federal funds to highways, it cannot prevent state highway funds from 

being used for other purposes. Congress has also sought to meet the goals 

of the program through a strategy of emphasizing states’ priorities and 

decision-making. However, substitution may be limiting the effectiveness 

of this strategy. Although the federal-aid highway program has a 

considerable regulatory component, from a funding standpoint, the 

program is to some extent functioning as a cash transfer, general purpose 

grant program. This raises broader questions about the effectiveness of the 

federal investment in highways in accomplishing the program’s goals and 

outcomes, for although DOT has created performance measures and 

outcomes under GPRA, currently there is no link between the achievement 

of these measures and outcomes and federal funding provided to the states.

Congress and DOT Have Set 

Out Goals for the FederalAid Highway Program

Congress and DOT have at various times enumerated goals for the federalaid highway program to, among other things, enhance safe and reliable 

travel, promote economic growth, enhance mobility, support interstate and 

international commerce, and meet national security needs. According to 

DOT’s 2003-08 Strategic Plan, the department’s mission is enumerated in 49 

U.S.C. 101, which states that “the national objectives of general welfare, 

economic growth and stability, and the security of the United States require 

the development of transportation policies and programs that contribute to 

providing fast, safe, efficient, and convenient transportation...”. In 

establishing the Interstate Highway System, Congress, in the Federal-Aid 

Highway Act of 1956, stated that the Interstate system was to serve 

principal metropolitan areas and industrial centers, support the national 

defense, and connect with routes of continental importance in Canada and 

Mexico. Current law defines the primary focus of the federal-aid highway 

program as completion and expansion of the National Highway System, of 
Page 33 GAO-04-802 Federal-Aid Highways

which the Interstate is a part, to provide interconnected routes that serve, 

among other things, major population centers, international border 

crossings, commercial ports, airports, and major travel destinations. 

Congress continued to set out these goals in reauthorization legislation that 

the Senate and House each passed in 2004. For example, the legislation 

approved by the Senate states that: 

“...among the foremost needs that the surface transportation system must meet to provide 

for a strong and vigorous national economy are safe, efficient, and reliable (i) national and 

interregional personal mobility (including personal mobility in rural and urban areas) and 

reduced congestion; (ii) flow of interstate and international commerce and freight 

transportation; and (iii) travel movements essential for national security.”

To meet the program’s goals, Congress has set out a number of strategies, 

including increasing investment in highways and providing states flexibility 

to best meet their transportation needs. Furthermore, under Congress’ 

direction, DOT has established strategic goals and performance measures 

and outcomes for the federal-aid highway program to enhance mobility and 

economic growth. Among these goals are to reduce the growth of 

congestion on the Nation’s highways and improve the condition of the 

National Highway System.

One Strategy to Meet Goals 

Has Been to Increase 

Investment and Ensure 

Federal Highway Funds Go 

to Highway Program 

Since the Federal-Aid Highway Act was enacted in 1956, every time 

Congress has reauthorized the highway program it has expanded either the 

size or scope, or both, of the federal-aid highway program.33 Since 1991, 

Congress has provided significant increases in federal spending on 

highways. ISTEA’s authorization of $121 billion for highways for the 6-year 

period from fiscal years 1992 through 1997 was a 73 percent increase over 

the $70 billion authorized in the prior 6-year bill, and TEA-21’s 

authorization of $171 billion for the federal-aid highway program from 

fiscal years 1998 through 2003 represented an increase of 41 percent over 

ISTEA’s authorization level. In 2004, the House and Senate each approved 

separate legislation to reauthorize the federal-aid highway program, 

increases of 32 percent and 50 percent over TEA-21, respectively.34 Despite 

these increases, numerous congressional transportation leaders stated that 

33See CRS report 98-221: ISTEA Reauthorization: Highway and Transit Legislative 

Proposals in the 105th Congress, 2nd Session.

34Increases are shown in nominal dollars.
Page 34 GAO-04-802 Federal-Aid Highways

these increases were not enough, and that further spending was required to 

meet the country’s needs. 

Congress has also included features in the design of the federal-aid 

highway program to attempt to ensure that funds collected by the federal 

government for highways are used for that purpose. Prior to 1956, federal 

fuel and motor vehicle taxes were directed to the General Fund of the U.S. 

Treasury, and there was no relationship between the receipts from these 

taxes and federal funding for highways. Amid concerns that federal taxes 

on motor fuel were being used for nontransportation purposes, Congress 

established the Highway Trust Fund in 1956 and specifically provided that 

revenues from most highway user taxes would be used to finance the 

greatly expanded highway program enacted by the Federal-Aid Highway 

Act of 1956. Despite having a dedicated source of funding, highways 

competed for federal funding with other forms of domestic discretionary 

spending through the appropriations process over the years. As a result, 

Congress often appropriated less money than was authorized, even though 

sufficient funds were being collected in the Highway Trust Fund to support 

the authorized levels. So Congress took further action in TEA-21, 

establishing guaranteed spending levels for highway programs that 

protected highway programs from having to compete for funding through 

the congressional budget and appropriations process. It also established 

“Revenue Aligned Budget Authority,” directly linking highway revenues 

collected into the Highway Trust Fund with the apportionments provided 

annually to the states for their highway programs.

Despite congressional efforts to increase the federal investment in the 

highway system and to ensure that funds collected by the federal 

government for highways are used for that purpose, due to probable 

substitution, the sizable increases in dedicated federal funding that 

Congress has provided for highways have not translated into 

commensurate increases in the Nation’s overall investment in its highway 

system. Moreover, the effectiveness of Congress’ strategy to dedicate 

federal funds to highways is limited because Congress has no similar ability 

to prevent state and local highway funds, where most of the investment 

occurs, from being used for other purposes. Therefore, while Congress can 

ensure that certain federal moneys are dedicated to highways and given to 

the states for that purpose, it cannot ensure that state and local highway 

funds are not used for other purposes. When substitution occurs, some 

dedicated federal highway funds replace state highway funds, and those 

state highway funds are then used for other purposes. 
Page 35 GAO-04-802 Federal-Aid Highways

Another Strategy Has Been 

to Emphasize Importance of 

States’ Priorities and 

Decision-making

Congress has also sought to meet the goals of the program by emphasizing 

the importance of states’ priorities and decision-making regarding how to 

meet their most pressing transportation needs. One way it has done so is by 

incorporating return-to-origin features into the program--returning to the 

states more of the money collected in fuel taxes. TEA-21’s Minimum 

Guarantee provisions ensure that each state receives back from most 

highway programs 90.5 percent of the total estimated percentage share of 

contributions to the Highway Account of the Highway Trust Fund from 

motor fuel and other taxes collected in that state. Under separate 

legislation passed by both the House and Senate in 2004, this amount could 

rise to 95 percent by 2009.35

In addition, Congress has given the states broad flexibility in the use of its 

federal aid grant funds by providing states significant discretion to use 

these funds flexibly across highway, bridge, transit, and other 

transportation projects. States have, if they choose, broad flexibility in the 

use of slightly more than half of their federal-aid highway funds. For 

example, the Surface Transportation grant program has broad eligibility 

rules, and states can use those funds for highways, bridges, transit capital 

projects, bus terminals, and many other uses. States may use some of their 

Minimum Guarantee Program grant funds under the same rules;36 in fiscal 

year 2003, the funds apportioned under these two programs accounted for 

one third of all federal aid highway funds apportioned nationwide. For 

eight states that receive higher levels of Minimum Guarantee grant funds, 

these two programs account for more than 40 percent of their funding, and 

in one of these eight states, for just over 50 percent. While other federal-aid 

highway grant funds have more limited uses, states have the authority to 

transfer funds from these limited programs to more flexible programs and 

uses. For example, states may transfer up to 50 percent of their National 

Highway System and Interstate Maintenance program funds to the Surface 

Transportation Program or certain other grant programs, and, in the case of 

35Specifically, the Senate bill provides that each state would achieve a 95 percent return on 

payments to the highway account of the Highway Trust Fund by 2009. While the House bill 

does not contain this provision, it would delay fiscal year 2006 funding for most federal-aid 

highway programs from October 2005 until August 2006, if Congress has not enacted 

legislation by September 30, 2005, raising each state’s guaranteed rate of return to 95 

percent, effective in fiscal year 2009.

36Specifically, those funds that are not distributed to the core highway programs. See

table 1.
Page 36 GAO-04-802 Federal-Aid Highways

the National Highway System program, 100 percent under certain 

conditions. 

Furthermore, states have broad flexibility in deciding which projects to 

pick and how to implement them. The projects for which states use federal 

funding must be for construction, reconstruction, and improvement on 

eligible federal-aid highway routes. Nevertheless, federal law (23 U.S.C. 

§145) provides that the authorization or appropriation of federal funds 

“shall in no way infringe on the sovereign rights of the States to determine 

which projects shall be federally financed.” Moreover, FHWA’s role in 

overseeing the design and construction of most projects is limited. 

Specifically, only high cost construction or reconstruction projects on the 

Interstate Highway System are always subject to “full” oversight in which 

FHWA prescribes design and construction standards, approves design 

plans and estimates, approves contract awards, inspects construction 

progress, and renders final acceptance when projects are completed. For 

projects that are not located on the National Highway System, states are 

required to assume oversight responsibility for the design and construction 

of projects unless a state determines that it is not appropriate for it to do 

so.37 As figure 8 shows, in 2002, about $1 out of every $5 obligated for 

federal-aid projects occurred on the Interstate system, while projects off 

the National Highway System accounted for about 57 percent, nearly 3 

times as much.

37FHWA approves state transportation plans, environmental assessments, and property 

acquisition for all federally financed highway projects. On projects that are not located on 

the Interstate system but are part of the National Highway System, states may assume 

responsibility for overseeing the design and construction of projects unless either the state 

or FHWA determines that this responsibility is not appropriate. While FHWA and each state 

enter into an agreement documenting the types of projects for which the state will assume 

these oversight responsibilities, FHWA does not maintain information centrally on how 

many states have opted for federal versus state oversight in cases where discretion is 

permitted.
Page 37 GAO-04-802 Federal-Aid Highways

Figure 8: Federal Obligations by System in Fiscal Year 2001

Substitution may be limiting the effectiveness of Congress’ strategy of 

emphasizing the role of states’ priorities and decision-making regarding 

how to meet their most pressing transportation needs. The program does 

have a substantial regulatory component that requires states to enact and 

follow certain laws as a condition of receiving federal funds; for example, 

states are required to enact drunk-driving laws, such as .08 blood alcohol 

laws, and to contract with disadvantaged business enterprises. However, 

from a funding standpoint, the federal-aid highway program’s return-toorigin features and flexibility, combined with substitution and the use of 

state and local highway funds for other purposes, means that the program 

is, to some extent, functioning as a cash transfer, general purpose grant 

program. This raises broader questions about the effectiveness of the 

federal investment in highways in accomplishing the program’s goals and 

outcomes. 

Broader Questions Exist 

about the Program’s Goals 

and Outcomes

Our findings on substitution lead to broader questions about whether the 

federal-aid highway program is effective in meeting its goals. As required 

by the Government Performance and Results Act (GPRA), DOT has 

articulated goals for the department’s programs, including the federal-aid 

highway program, to achieve by establishing measurable performance 

goals, measures, and outcomes. One of the purposes of GPRA is to provide 

57%

24%

19%

Projects on the National Highway System

(noninterstate)

Interstate projects

Projects off the National Highway System

Source: GAO analysis of FHWA data.
Page 38 GAO-04-802 Federal-Aid Highways

decisionmakers a means of allocating resources to achieve desired results. 

Linking resources and results will become even more important than it is 

today in the years ahead, as the Nation faces a fiscal crisis in which 

mandatory commitments to Social Security and Medicare will consume a 

greater share of the Nation’s resources, squeezing the funding available for 

discretionary programs, potentially including highways. These challenges 

require the Nation to think critically about all existing government 

programs and commitments.

Among its performance goals, DOT has articulated goals for mobility and 

economic growth, including to improve the condition of the transportation 

system, reduce travel times, and increase access to and reliability of the 

transportation system. Two major performance measures related to the 

federal-aid highway program are to (1) improve the percentage of travel on 

the National Highway System meeting pavement performance standards 

for acceptable ride and (2) slow the growth of congestion--in particular, to 

limit the annual growth of urban area travel time under congested 

conditions to one-fifth of 1 percent below the growth that has been 

projected. These goals are shown in figure 9.
Page 39 GAO-04-802 Federal-Aid Highways

Figure 9: DOT Performance Measures for Condition and System Performance

Although DOT has articulated performance measures, the federal-aid 

highway program does not have the mechanisms to link funding levels with 

the accomplishment of specific performance-related goals and outcomes. 

In contrast, NHTSA has some incentive grant programs that link funding to 

particular outcomes, such as increasing the use of seat belts within states. 

As we have reported, although a variety of tools are available to measure 

the costs and benefits of transportation projects, they often do not drive 

investment decisions, and many political and other factors influence 

project selections.38 For example, the law in one state requires that most 

highway funds, including federal funds, be distributed equally across all the 

state’s congressional districts. Consequently, there is currently no way to 

measure how funding provided to the states is being used to accomplish 

particular performance-related results such as reducing congestion or 

improving conditions. 

100

95

90

85

80

1996 1998 2000 2002 2004

NHS Pavement Condition

Trend

Target

0

Percentage miles with acceptable ride quality

26.0

28.5

31.0

Travel in Urban Areas in Congested Conditions

1996 1997 1998 1999 2000 2001 2002 2003 2004

Trend

Target

Unconstrainted growth

Percentage of travel

0

Source: DOT's Fiscal Year 2004 Performance Plan.

38GAO, Surface Transportation: Many Factors Affect Investment Decisions, GAO-04-744

(Washington, D.C.: June 30, 2004).
Page 40 GAO-04-802 Federal-Aid Highways

We Identified Several 

Options for the Design 

and Structure of the 

Federal-Aid Highway 

Program

We identified several options for the design and structure of the federal-aid 

highway program that could be considered in light of the issues raised by 

our findings. On the one hand, there are options that have been used in 

other federal programs that could limit substitution. Another option to 

consider may be to simplify the program towards a more flexible approach. 

Another option would be to consider whether a different program structure 

and different financing mechanisms could be used to target funding and 

more closely align resources with desired results. 

Reduce Substitution To increase the extent to which federal-aid highway program funds are 

used to supplement state highway funds rather than substitute for them, 

several options exist to re-design the program to limit substitution. These 

include:

• Revising federal matching requirements to increase the percentage of 

projects’ costs that must be paid for with state and local funds. 

• Instituting the use of funding formulas that reward states that increase 

state and local highway funding by increasing their federal funding, 

while reducing the federal funding of those states that do not.

• Adding a requirement that states maintain their own level of highway 

spending effort over time in order to receive additional federal funds. 

All three options are designed to reduce or eliminate substitution. The first 

two options are designed to stimulate additional state spending on 

highways, while the third option is designed so that increased federal 

funding will supplement state spending rather than replace it. These 

objectives may not be perfectly achieved because models of substitution, 

like any models, produce estimates that are subject to uncertainty. As such, 

there is no way to objectively determine with certainty what states would 

have spent in the absence of increased federal funding. Table 3 summarizes 

the options, along with possible approaches that could be taken in 

implementing them. 
Page 41 GAO-04-802 Federal-Aid Highways

Table 3: Options to Reduce Substitution

Source: GAO.

Each of these options and approaches would be likely to have somewhat 

different effects and would require careful consideration of various factors. 

Some possible effects are summarized below; see appendix IV for 

additional discussion of these options. 

• The likely effect of revising the matching requirement would depend on 

the magnitude of the change. For example, if the requirement was 

changed so that states generally had to provide 60 percent of the total 

funding for eligible projects, states currently spending less than 60 

percent of total highway funds for eligible projects would have an 

incentive to increase their spending in order to obtain the maximum 

federal match, while those spending more than 60 percent would not 

have an incentive to increase their spending. A few states with a low 

state/federal spending ratio might have to more than double their 

current spending in order to receive additional federal funds. Setting the 

required match at 40 percent would give fewer states an incentive to 

increase their spending and would generally require less of an increase 

in spending from those states with low state/federal spending ratios. An 

advantage of continuing to set the state match at 20 percent but 

counting only state spending in excess of what each state spent during a 

base time period towards the match is that it would stimulate state 

spending in all states to a similar degree.

Option Approaches

Revise matching 

requirements

Revise state match to a higher percentage than current 20 

percent of total funding for project

Keep state match at 20 percent but count only state spending 

in excess of base time period for match

Link federal funding to 

states’ highway funding 

effort

Provide federal funds to states proportionally, based on their 

effort compared to average effort of all states

Provide federal funds to states proportionally, based on each 

state’s own effort relative to an initial base time period

Institute a maintenance 

of effort provision

Require states to maintain existing levels of state spending in 

order to receive federal funds
Page 42 GAO-04-802 Federal-Aid Highways

• Using funding formulas that link federal funds to states’ highway 

funding effort could also be achieved through various approaches.39 For 

example, providing federal funds to states proportionally based on their 

effort in comparison to the average effort of all states would put states 

in competition with each other, rewarding states whose funding effort is 

already high and penalizing states whose funding effort is currently low. 

On the other hand, providing federal funds to states proportionally 

based on each state’s own effort during an initial base time period would 

put each state in competition with the funding effort it made in the base 

period, rewarding states whose spending grew more quickly in 

comparison to their spending during the base period and penalizing 

states whose spending stayed the same or dropped when compared to 

their spending during the base period.40 Such provisions could be 

designed so they could be suspended in a recession or severe economic 

downturn in order to prevent states from having to make 

disproportionate reductions in other state services to maintain highway 

funding.

• Instituting a maintenance of effort provision would require each state to 

continue to spend what it spent in a defined base period, plus inflation, 

in order to obtain increased federal funds. Therefore, it would not 

stimulate state spending, but it would attempt to ensure that states used 

federal funds to supplement rather than replace state and local funds. In 

previous work, we concluded that, to be effective, maintenance of effort 

provisions need to define a minimum level of state spending effort that 

can be objectively quantified and updated to keep pace with inflation in 

program costs so that the maintenance of effort provision ensures a 

continued level of activity when measured in inflation adjusted dollars.41

This could be achieved by defining a state’s base spending level as the 

39Defining a state’s highway spending effort would need to avoid unfairly penalizing lowincome states, which may not have the resources to compete with the highway spending of 

wealthier states. Therefore, each state’s highway funding effort could be defined as the 

state’s highway spending compared to some measure of the state’s taxing capacity. The most 

comprehensive measure of states’ taxing capacity that is available annually is Total Taxable 

Resources (TTR), which is produced annually by the Department of the Treasury. 

40Defining a state’s spending during a base time period should, to the extent possible, be 

established by measuring spending levels that are typical rather than unusually high or low. 

41GAO, Proposed Changes in Federal Matching and Maintenance of Effort Requirements 

for State and Local Governments, GAO/GGD-81-7 (Washington, D.C.: Dec. 23, 1980); and 

Block Grants: Issues in Designing Accountability Provisions, GAO/AIMD-95-226

(Washington, D.C.: Sept. 1, 1995).
Page 43 GAO-04-802 Federal-Aid Highways

amount spent per year during a recent historical period and then 

adjusting that base spending level for inflation.42

Increase Flexibility in 

States’ Use of Funds and 

Reduce Administrative 

Expenses

Another potential option would be to build on trends giving states greater 

flexibilities and discretion with their federal-aid highway program funds. In 

contrast to changes in program designs that would limit substitution, 

adopting such an option could be seen as recognizing substitution as an 

appropriate response on the part of states to increasing fiscal challenges 

and competing demands. Adopting such an option could also be seen as 

recognizing that the ability of states to meet a variety of needs and fiscal 

pressures might be better accomplished by providing states with federal 

funding for highways through a more flexible federal program. 

Such an option would also recognize the changing nature of FHWA’s role 

and the federal-aid highway program. Currently, FHWA reviews and 

approves transportation plans and environmental reviews, and—on some 

projects—designs, plans, specifications, estimates, and contract awards. 

FHWA also has duties related to the program’s considerable regulatory 

component. To carry out these responsibilities, FHWA has among the 

largest field office structure in DOT, and a larger field structure than many 

other federal agencies. FHWA has personnel in over 50 field offices, 

including one office in each state, and has had a field office in each state 

since 1944. However, the federal-aid highway program has changed 

considerably in 60 years. In 2004, the program’s return-to-origin features 

and flexibility, combined with substitution and the use of state and local 

highway funds for other purposes, means that from a funding standpoint, 

the federal-aid highway program is, to some extent, functioning as a cash 

transfer, general purpose grant program. Devolving funding responsibilities 

to the states in a manner consistent with that function would build on the 

flexibilities already present and obviate much of the need for FHWA’s 

extensive field organization, allowing it to be greatly reduced in scope. This 

could produce budgetary savings of some portion of FHWA’s $334 million 

annual budget.

42One drawback of a maintenance of effort provision is that basing it on a historical 

spending period could result in a base spending period that represents an unusually high 

spending level for some states, effectively locking them into continued high spending in 

future years. This could be ameliorated however by establishing waivers for states that are 

able to demonstrate that spending in the base period chosen is unusually high, to allow a 

more “typical” spending level for purposes of the maintenance of effort provision.
Page 44 GAO-04-802 Federal-Aid Highways

Adopting such an option would involve weighing numerous factors, 

including FHWA’s role and value. But devolving funding responsibilities to 

the states would not require abandoning the program’s regulatory 

component. Some federal laws and requirements in place originated 

outside the transportation program and would doubtless remain in force, 

such as civil rights compliance. Others that are currently part of the 

transportation program could also remain in effect. Depending on 

priorities, these could continue to be overseen by FHWA directly or a 

process could be established through which states certify their compliance 

with the requirements, as is done in other programs. In this manner, it 

would be possible to enforce these laws and requirements without an 

extensive field structure, as other federal agencies and programs do. 

Devolving authority to the states could also take the form of devolving not 

only the federal programs, but the revenue sources that support it. 

Considerable federal effort goes into collecting and accounting for motor 

fuel taxes and other highway user fees. One argument for maintaining a 

federal fuel tax is that this tax may be a useful public policy to prevent tax 

competition between states to avoid the disinvestment in the highway 

system that could potentially result. Such a “turnback” provision was 

considered in the form of an amendment to TEA-21 in the House of 

Representatives in 1998, but it did not pass.

Devolving federal responsibilities to the states is not dissimilar to the 

Surface Transportation System Performance Pilot Program that was 

proposed in the administration’s reauthorization proposal, but which was 

not included in either the House or Senate version of the bill. Up to five 

states could have participated in the program, which would have allowed a 

state to assume some or all of FHWA’s authorities and responsibilities 

under most federal law or regulations.43 Once approved to participate, a 

state would have had to identify annually what goals it wanted to achieve 

with its federal funds and what performance measures it would use to 

gauge success. A state would also have had to agree to a maintenance of 

effort requirement that it maintain its total combined state and federal 

43Under the proposed pilot program, the federal government would not have devolved its 

responsibilities (1) to review states and local governments’ transportation plans, (2) to 

oversee “major” projects costing over $1 billion, (3) under Title VI of the Civil Rights Act of 

1964, or (4) under any laws relating to federally recognized tribes. In addition, the proposal 

specified that nothing in it would be interpreted to relieve any project from the requirements 

of the National Environmental Policy Act, nor would it preclude DOT from issuing 

rulemaking actions as needed. 
Page 45 GAO-04-802 Federal-Aid Highways

highway program expenditures at the level of at least the average level of 

the three previous years. A state’s participation in the pilot program would 

have been terminated if that state did not achieve the agreed performance 

for two consecutive years. 

Link Federal-Aid Highway 

Funding with Program 

Goals

Another option could be to consider whether a different program structure 

and different financing mechanisms could be used to target funding and 

more closely align resources with desired results. Restructuring the 

program in this way could take several forms. For example, the program 

could be reoriented to function more like a competitive discretionary grant 

program, in which program sponsors justify projects seeking federal aid 

based on an assessment of their potential benefits. This is not dissimilar to 

the program used by DOT to fund large transit capital projects.44 The 

program could also be revised to include the use of incentive grant 

programs similar to those that NHTSA has to link funding to particular 

outcomes, such as increasing the use of seat belts within states. 

Adopting such an option would require asking the following questions: 

• What policy goals have been established by Congress for the 

performance of the federal-aid highway program, what outcomes and 

results have been articulated in DOT’s strategic plans to fulfill those 

goals, and are they the right goals and outcomes?

• What is the appropriate role of each level of government? Would the 

roles need to be redefined in order to align federal spending more 

closely with a greater performance and outcome orientation? In 

particular, what refocusing of federal involvement (e.g., interstate 

commerce, homeland security, national defense) would need to occur?

• How could the design of the federal-aid highway program’s grants and 

funding mechanisms best support accomplishment of agreed-upon 

44Under the Federal Transit Administration’s New Starts Program, local transit agencies 

compete for project funds based on specific financial and project justification criteria. FTA 

assesses the technical merits of a major transit project proposal and its finance plan and 

then notifies Congress that it intends to commit, subject to appropriations, New Starts 

funding to certain projects through full funding grant agreements. The agreement 

establishes the terms and conditions for federal participation in the project, including the 

maximum amount of federal funds—which by law must be no more than 80 percent of the 

estimated net cost of the project, but in practice is often less than that percentage.
Page 46 GAO-04-802 Federal-Aid Highways

performance goals and outcomes? What funding incentives are needed 

to introduce a greater performance and outcome orientation?

• What type of departmental administrative structure for the federal-aid 

highway program would best ensure that the performance goals 

established by Congress and articulated in DOT’s strategic plans and 

outcomes are measured and accomplished?

• Can a greater performance and outcome orientation to the federal-aid 

highway program be reconciled with congressional and state legislative 

policies and preferences toward providing at least some transportation 

funding in the form of specific project earmarks? 

Conclusions Addressing the issues raised in this report would require weighing 

competing and sometimes conflicting options and strategies. If, for 

example, reducing the level of grant substitution is an important concern, 

then design changes in the current program, including adopting features 

that have been used in other federal programs, may be warranted. If, on the 

other hand, preserving states’ flexibility, including their ability to meet a 

variety of needs and fiscal pressures is a higher priority, then design 

changes in the direction of a different, more flexible program may be 

warranted. While some options are mutually exclusive, others could be 

enacted in concert. For instance, an option to limit substitution could be 

combined with efforts to align resources with desired results, and returning 

program authorities and resources to the states could be accompanied by 

adding performance measures. 

Beyond these options, our work raises broader and more fundamental 

issues given the challenges the Nation faces in the 21st Century. The fact 

that both the federal and state governments face budget deficits totaling 

hundreds of billions of dollars and a growing fiscal crisis requires 

policymakers to think critically about existing government programs and 

commitments and make tough choices in setting priorities and linking 

resources to results to ensure that every federal dollar is wisely and 

effectively spent. The opportunity to better align the federal-aid highway 

program with performance goals and outcomes comes at a time when both 

houses of Congress have already approved separate legislation to create a 

National Commission to examine future revenue sources to support the 

Highway Trust Fund and to consider the roles of the various levels of 

government and the private sector in meeting future surface transportation 

financing needs. The proposed commission is to consider how the program 
Page 47 GAO-04-802 Federal-Aid Highways

is financed and the roles of the federal and state governments and other 

stakeholders in financing it; the appropriate program structure and 

mechanisms for delivering that funding are important components of 

making these decisions. Thus, this commission may be an appropriate 

vehicle through which to examine these options for the future structure 

and design of the federal-aid highway program. 

Matter for 

Congressional 

Consideration

In light of the issues raised in this report and the fiscal challenges the 

Nation faces in the 21st Century, Congress may wish to consider expanding 

the proposed mandate of the National Commission to assess possible 

changes to the federal-aid highway program to maximize the effectiveness 

of federal funding and promote national goals and strategies. Consideration 

could be given to the program’s design, structure, and funding formulas; the 

roles of the various levels of government; and the inclusion of greater 

performance and outcome-oriented features.

Agency Comments and 

Our Evaluation

We provided DOT a draft of this report for review and obtained comments 

from departmental officials, including FHWA’s Director of Legislation and 

Strategic Planning. These officials said that our analysis raised interesting 

and important issues regarding state funding flexibility and the federal-aid 

highway program that merit further study. DOT officials also stated that 

while they recognize that federal-aid highway grants can influence state 

and local governments to substitute federal funds for state and local funds 

that otherwise might have been spent on highways, they believe that this 

substitution is likely due to numerous factors. Specifically, the officials said 

that to the extent substitution occurred and increased during the 1990s, it 

was also likely due to changes in states’ revenues and priorities. DOT 

officials also emphasized that regardless of changes in the availability of 

state funds for highway programs, the overall federal share of capital 

spending on highways declined during the period we studied, from over 55 

percent in the early 1980s to around 45 percent today. DOT officials also 

emphasized that there is no evidence that the substitution discussed in our 

report resulted in the diversion of federal-aid highway funds apportioned to 

the states. They further stated that substitution may reflect appropriate 

resource allocations by states and that preserving states’ flexibility has 

been a priority of the federal-aid highway program and is a goal of DOT’s 

reauthorization proposal. Finally, regarding options for changes in the 

design of the federal-aid highway program, officials emphasized that FHWA 

adds considerable value to the federal-aid highway program by providing 
Page 48 GAO-04-802 Federal-Aid Highways

program oversight and sharing its expertise with states to ensure states 

uniformly address key areas of national concern including safety and 

environmental protection. 

We agree with DOT’s characterization of the importance of the issues 

raised in this report, including the effect that federal-aid highway grants 

have on state spending decisions and states’ funding flexibility. We also 

agree with DOT officials that many factors influence state budgetary 

decisions, including changing state budget priorities and the availability of 

state revenues. It was for this reason that we used a statistical model that 

specifically took changing economic conditions and revenues into account 

in order to better isolate the effect of federal grants on state spending 

choices. We believe that our model has reasonably distinguished between 

the effects of changing economic conditions and revenues and the effect of 

federal grants, and, consistent with earlier models and studies, we found 

the relationship between federal grants and state spending, indicating 

substitution, to be statistically significant, particularly during the 1990s. 

However, determining specific causes of substitution is beyond the scope 

of our statistical model. For example, while states faced rising demands for 

health care and education during the 1980s and 1990s that could have 

resulted in states reducing their highway spending when federal highway 

funding increased, our model does not identify the specific causes 

responsible for rising substitution rates. Although DOT officials said that 

the overall federal share of capital spending on highways declined during 

the period we studied, these relative shares do not affect our findings on 

substitution since substitution can occur when the federal share of funding 

is either rising or falling; if substitution occurs when state funding is rising 

it simply means that state spending increased less than the increase that 

might have occurred had there been no substitution. While DOT officials 

stated that there is no evidence that substitution resulted in the diversion of 

federal-aid highway funds, there are important differences between 

diversion and substitution. In the context in which DOT officials raised it, 

diversion is the transfer of federal funds for purposes other than those 

authorized by law, while substitution, as we have reported it, is the transfer 

of state funds that would have otherwise been spent on highways. States 

can both use federal funds for the purposes authorized by law and at the 

same time substitute federal funds for state funds. Thus, while we agree 

that there is no evidence that substitution resulted in the diversion of 

federal-aid highway funds, we do not believe our report suggests the 

existence of such evidence. 
Page 49 GAO-04-802 Federal-Aid Highways

Finally, we agree with DOT officials that states’ flexibility and FHWA’s role 

are important factors in the federal-aid highway program; however, we 

believe that options for changing the design, structure, and funding 

mechanisms of the federal-aid highway program should be considered in 

light of substitution and the issues raised in this report, and that a variety of 

factors, including but not limited to these two, should be weighed when 

considering such changes. While the department took no position on the 

matter for congressional consideration to expand the mandate of the 

proposed National Commission, officials did state that they believe these 

issues merit further study. We continue to believe that Congress has the 

opportunity to maximize the effectiveness of federal funding and promote 

national goals and strategies by expanding the proposed mandate of the 

National Commission to consider these issues. 

We are sending copies of this report to the Honorable Norman Mineta, 

Secretary of Transportation. We will also make copies available to others 

upon request. In addition, the report will be available at no charge on the 

GAO Web site at http://www.gao.gov.

If you have any questions about this report, please contact me at 

heckerj@gao.gov, or (202) 512-2834, or contact Jerry Fastrup at 

fastrupj@gao.gov or (202) 512-7211, or Steve Cohen at cohens@gao.gov or 

(202) 512-4864. GAO contacts and acknowledgments are listed in 

appendix V.

Sincerely yours,

JayEtta Z. Hecker

Director, Physical Infrastructure
Page 50 GAO-04-802 Federal-Aid Highways

Appendix I

Objectives, Scope, and Methodology ApApenednxidexiIs

In light of the increasing federal-aid highway program funding and 

concerns over future federal revenues for highways, you asked us to 

provide information on past trends in the federal, state, and local capital 

investment in highways, and how federal-aid highway program grants 

influence the level of state and local highway spending. We responded to 

the first part of your request in June 2003. This report (1) updates 

information on trends in federal, state, and local capital investment in 

highways; (2) assesses the influence that federal-aid highway grants have 

had on state and local highway spending; (3) discusses the implications of 

these issues on the federal-aid highway program; and (4) discusses options 

for the federal-aid highway program that could be considered in light of 

these issues. In addition, this report identifies characteristics associated 

with differences among states’ levels of effort for highways (see app. III).

To update information on federal, state, and local capital investment in 

highways, we obtained 2002 (the most recent year available) expenditure 

data from the Federal Highway Administration. We converted these 

expenditure data to 2001-year dollars to coincide with the data in our 

previous report,1

 which presented data from 1982 through 2001. 

To assess the influence that federal-aid highway grants have had on all state 

and local highway spending, we reviewed and synthesized the research 

literature on this issue. Our literature review revealed a number of studies 

that used statistical models to estimate the influence of federal funding on 

state spending. These models examined different time periods, employed 

different statistical methods, and considered different potential social, 

demographic, economic, and political factors that may affect state highway 

spending decisions. None of the models used in the studies we reviewed 

included the most recent data now available on highway funding, and none 

examined whether the effect of federal grants on state spending changed 

during the time period covered in the study. Therefore, based on the 

models used in the earlier studies, we developed our own statistical model 

of state highway capital and maintenance outcomes to estimate the fiscal 

effects of federal highway funding on state highway spending. The purpose 

of our statistical model was to isolate the effect of federal grants on 

highway spending in states by controlling for other factors that affect state 

spending decisions. Our model therefore considered a wide range of 

potential factors such as economic conditions and the size of a state’s 

highway system, that may affect state spending choices. In addition, our 

1

GAO, Trends in Federal and State Highway Investment (GAO-03-744R).
Appendix I

Objectives, Scope, and Methodology

Page 51 GAO-04-802 Federal-Aid Highways

model included the most recent data available and examined whether the 

effect of federal grants on state spending changed during the time period.2

A more detailed description of the literature and our statistical model is 

contained in appendix II. Finally, our model was reviewed by experts in the 

Department of Transportation (DOT) and peer reviewed by three authors 

of the earlier studies on the fiscal effects of federal highway grants. These 

experts and authors generally agreed with our methods, and we made 

revisions based on their comments as appropriate. 

To address the implications of the effect of federal highway grants on state 

and local highway spending and options raised by these implications, we 

reviewed pertinent legislation and congressional actions affecting the 

federal-aid highway program, including goals, funding trends, program 

features, and financing mechanisms. We reviewed the Government 

Performance and Results Act and DOT’s strategic and performance plans 

and reports for 2003 and 2004. We then evaluated how our model results 

and other analysis on the existence of substitution affect the design and 

performance of the federal-aid highway program.

Finally, to identify state characteristics associated with their effort to fund 

highways from state resources, we defined a state’s level of effort broadly 

to include both a state’s and its local governments’ spending for highway 

maintenance and capital construction relative to the personal income of 

state residents.3

 We determined a multivariate analysis is required so that 

other factors, in addition to the state characteristic under consideration, 

can be taken into account and held constant. (See app. III for results.)

To perform this multivariate analysis, we utilized the same statistical model 

of state highway spending used to analyze the fiscal effect of federal 

highway grants (see app. II). The variables expected to affect state highway 

spending fall into four broad categories: (1) fiscal capacity, (2) the cost of 

transportation services to the representative voter/consumer (tax price), 

2

We adjusted for the changing cost of highway services over time by deflating expenditures 

using the chain-price deflator for state and local government streets and highways published 

by the Bureau of Economic Analysis.

3

Our previous report defined level of effort more narrowly as highway capital spending as a 

percentage of gross state product. We have adopted a broader definition for the current 

analysis that is consistent with the scope of this report’s focus on highway spending broadly 

defined to include capital as well as maintenance spending. Also consistent with this report, 

we have used the personal income of state residents rather than gross state product to 

reflect states’ fiscal capacities. 
Appendix I

Objectives, Scope, and Methodology

Page 52 GAO-04-802 Federal-Aid Highways

(3) federal grants, and (4) indicators of state preferences for highway 

spending. The specific variables we considered are listed in 

table 6.

We conducted our work from August 2003 through July 2004 in accordance 

with generally accepted government auditing standards.
Page 53 GAO-04-802 Federal-Aid Highways

Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results ApendxiI

This appendix presents a thorough description of the statistical analysis 

that we conducted to estimate the extent to which states substitute federal 

highway grants for funds that would have been spent on highways from 

their own resources. The first section summarizes the literature on this 

topic because we built upon models from previous studies in developing 

our model. The next section describes the model that we developed. The 

final section describes the statistical tests that we used and presents the 

results of those tests. 

Summary of Previous 

Studies

We reviewed a number of studies on substitution and relied most heavily on 

the models used in three of them in developing our statistical model.1

 The 

three studies are similar in that each draws upon economic models that 

explain states’ highway spending in terms of the demand for mobility that 

flows from the construction and maintenance of a highway network. Within 

the context of these models, the potential for grant substitution arises in 

the response of state highway spending to changes in federal grant funding. 

However, these models differ in key details, such as the statistical methods 

used to estimate the extent of substitution, the definition of state highway 

expenditures, and the control variables used in the model. They also differ 

in their estimation of substitution rates. 

Conceptual Framework The models in each of the key studies are built upon the premise that the 

political process responds to the preferences of voters/consumers for 

highway transportation services. As a result, the models characterize the 

demand for and supply of highway spending as depending on four types of 

factors:

1

The three studies that we relied on most heavily were: Harry G. Meyers, op. cit; Brian 

Knight, op. cit; and Shama Gamkhar, op. cit. Other studies that we reviewed include: Shama 

Gamkhar, “Is the Response of State and Local Highway Spending Symmetric to Increases 

and Decreases in Federal Highway Grants?” Public Finance Review, Vol. 28 No. 1, January 

2000 pp. 3-25: Janet G. Stotsky, “State Fiscal Responses to Federal Government Grants,” 

Growth and Change, Summer 1991, pp 17-31; Roger D. Congleton and Randall W. Bennett, 

“On the Political Economy of State Highway Expenditures: Some Evidence of the Relative 

Performance of Alternative Choice Models,” Public Choice, 84 (1995), pp. 1-24; Rajeev K. 

Goel and Michael A. Nelson, “Use or Abuse of Highway Tax Revenues?: An Economic 

Analysis of Highway Spending,” unpublished draft, April 2001; Edward Miller, “The 

Economics of Matching Grants: The ABC Highway Program,” National Tax Journal, XXVII, 

no. 2, pp. 221-229; Herman B. Leonard, By Choice or By Chance: Tracking the Values in 

Massachusetts' Public Spending (Pioneer Institute for Public Policy Research, 1992).
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 54 GAO-04-802 Federal-Aid Highways

1. Fiscal capacity (FC), which is the ability of states to fund services using 

within-state resources;

2. The tax price (TP) faced by the typical voter/consumer of highway 

services, which can be thought of as the cost of an additional unit of 

mobility; 

3. Intergovernmental grant funding (G), including both grants intended 

for highways and grants for other public services; and 

4. Differences in voter/consumer preferences (P) for highway 

transportation services. 

This relationship can be summarized in the following relationship:

State Highway Expenditure = f(FC,TP, G, P)

In these models, greater tax paying capacity is expected to result in a 

higher demand for mobility that in turn increases the demand for a larger 

highway network. Similarly, more grant funding (both for highways as well 

as for other public services) increases the resources available to states and 

is expected to increase total highway spending. Differences in political 

culture are also expected to result in different preferences for 

transportation services relative to other public services, such as health and 

education. Finally, if the typical voter/consumer faces a higher unit cost of 

transportation services, also called the tax price of highway services, the 

demand for transportation services is likely to be lower. 

The tax price of highway services is, in turn, dependent upon several 

factors: 

1. A higher cost of inputs (labor, building materials, supplies, etc.) used to 

build and maintain highways results in more expensive transportation 

services. A higher unit cost of mobility is expected to reduce the 

demand for transportation services, but will increase highway spending 

as long as the demand for transportation services is price inelastic.

2. Economies and/or diseconomies of scale may also affect the unit cost 

of mobility. A required minimum facility size may result in more lane 

miles per resident in smaller states, which may result in a higher unit 

cost for the typical voter/consumer. Similarly, very low lane miles per 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 55 GAO-04-802 Federal-Aid Highways

resident may be associated with more intensive usage, which may also 

result in a higher unit cost as well. Thus, unit cost may be U-shaped. 

3. A greater number of voter/consumers with whom the cost of highway 

services may be shared is expected to reduce unit cost to the typical 

state voter, increasing the demand for transportation services. This will 

result in higher total highway spending and lower spending per voter so 

long as demand is price inelastic. 

4. More highway users may lead to greater deterioration in the quality of 

highways and greater congestion, raising the unit cost of transportation 

services to the typical voter/consumer, reducing the demand for 

highway services. The effect on spending is expected to be positive if 

demand is price inelastic. In addition to cost considerations, more 

users could also be thought of as reflecting a stronger preference for 

highway services relative to other goods and services.

5. Matching grants on the marginal dollar of highway spending reduce the 

unit cost of services to the typical voter/consumer. To the extent that 

matching requirements apply to additional state spending the typical 

voter/consumer pays a smaller share of additional spending, lowering 

the cost of additional spending to the typical voter/consumer and 

raising the demand for highway services.2

In table 4, we summarize three studies that are representative of the variety 

of models that have been considered in the literature and upon which we 

base our analysis. 

2

Closed-ended matching programs that limit the availability of federal matching funds at the 

margin of spending do not lower the cost of additional highway spending and hence the tax 

price faced by the typical voter/consumer.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 56 GAO-04-802 Federal-Aid Highways

Table 4: Summary of Fiscal Substitution Studies

Source: GAO analysis.

a

Treated as an endogenous variable.

Statistical Methods The three studies employ a variety of statistical methods in estimating the 

substitution effect of federal highway grants. All use simultaneous 

equations estimators, but they treat different variables as endogenous. 

Knight and Gamkhar treat federal grant expenditures and state own-source 

Study

Time 

period

State highway 

expenditures

Fiscal 

capacity Tax price variables Grant variables Preferences Other variables

Knight 1983-

1997

State (but not 

local) 

government 

spending for 

highway-related 

projects (capital 

and 

maintenance, 

real per capita)

Personal 

Income per 

capita

1. Population

2. Drivers per capita

3. Registered 

vehicles per 

capita

Highway grant 

expenditures per 

capitaa

1. Governor 

Democrat

2. Percent 

Democrats in 

State House 

3. Percent 

Democrats in 

State Senate 

State fixed effects

Gamkhar 1976-

1990

State & local 

government 

spending for 

highway-related 

projects (capital 

and 

maintenance, 

real per capita)

Personal 

income per 

capita

1. Effective 

nonhighway 

match rate

2. Registered 

Vehicles per 

capita

3. Vehicle miles 

traveled per 

capita

4. Percent light 

vehicles

5. Percent metro 

population

6. Population 

density

1. Highway 

grant 

expenditures 

per capitaa

2. Highway 

grant 

obligations 

per capita

3. Other fed 

grants per 

capita

1. State fixed 

effects

2. Time fixed 

effects

3. Percent 

unemployed

4. Debt as a 

percent of 

income

Meyers 1976-

1982

State capital 

spending on 

federal-aid 

highways (net of 

interstate 

highways, real 

per capita)

Personal 

income per 

capita

1. Effective highway 

match ratea

2. Effective 

nonhighway 

match rate

3. Registered 

Vehicles per 

capita

4. Vehicle miles 

traveled per 

capita

5. Lane miles per 

capita

1. Highway 

grant 

expenditures 

per capita

2. Other federal 

grants per 

capita
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 57 GAO-04-802 Federal-Aid Highways

highway expenditures as jointly determined and therefore use an 

instrumental variable estimator for their per capita federal grant variable to 

remove the endogenous component associated with this variable.3

 In 

contrast, Meyers does not treat per capita federal highway grants as an 

endogenous variable and may have a biased estimate of the substitution 

rate. He does, however, treat the effective matching rate associated with 

highway grants (i.e., the ratio of highway grants to total highway spending) 

as endogenous and uses an instrumental variable procedure to correct for 

potential bias in that variable.4

Both Gamkhar and Meyers find autocorrelation in their error terms and, 

therefore, make an adjustment for autocorrelation. The Knight study does 

not correct for autocorrelation. Finally, both Knight and Gamkhar use a 

fixed effect estimating procedure to control for unique circumstances 

across states that are not captured by the other control variables included 

in their models. Neither study reports the significance of fixed effects in 

their model. In addition, Gamkhar also includes time dummy variables to 

capture systematic effects over time that the other control variables do not 

capture. Knight does not include a time adjustment in his model. Meyers 

includes neither a fixed effects nor time adjustment. 

Differing Definitions of 

State Highway Expenditures

Each of the three studies define state highway spending differently, which 

has important implications regarding how grant substitution is measured 

and influences the interpretation of the studies’ results.5

 The earliest study, 

by Meyers, includes state capital spending only for projects eligible under 

the federal-aid highway program, excluding spending for interstate 

highways. Measuring the dependent variable in this way means the 

3

If state expenditures and federal grants were jointly determined, ordinary least squares 

(OLS) methods would provide biased estimates of the substitution rate. Gamkhar does, 

however, use OLS methods in a model in which federal grants are measured using grant 

obligations, arguing that obligations are known prior to states’ expenditure decisions and 

therefore treated obligations data as exogenous. 

4

Neither Knight nor Gamkhar includes a price effect associated with federal highway grant 

funding arguing that such an effect is not present because states spend substantially more 

than is required to satisfy the matching requirements associated with federal funding.

5

Gamkhar uses the implicit price deflator for government purchases, and Meyers uses the 

implicit price deflator for state and local government purchases to adjust for changes in the 

purchasing power of a dollar over time. Knight does not identify the deflator he uses. None 

of the studies adjusts for cross-state differences in input costs. All three studies express 

state highway spending and federal grants on a per capita basis.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 58 GAO-04-802 Federal-Aid Highways

highway grant coefficient measures only the response of state capital 

spending on federal-aid highway projects to changes in federal funding. As 

a consequence, Meyers counts increased state or local spending for 

maintenance on federal-aid highway projects, or increased state or local 

capital and maintenance on nonfederal-aid highway spending, as grant 

substitution in the same way as increased spending for other state services 

such as education and health or increased state taxpayer relief would be 

counted as substitution. 

In contrast, Knight defines state highway spending more broadly to include 

all highway spending by state governments, whether for federal-aid 

highways or for other state highway projects. However, Knight does not 

include local spending on highways in his definition of state highway 

spending. As a consequence, increased state maintenance spending on 

federal-aid highway projects or spending on state government highway 

projects that are not part of the federal-aid system is not considered grant 

substitution in his study, even though such spending is not eligible for 

federal assistance. However, increased highway spending by local 

governments is considered to be grant substitution in the same way that 

increased state or local spending for other state services and increased tax 

relief are considered substitution. Finally, the Gamkhar study defines 

highway spending to include both capital and maintenance spending by 

both state and local governments. This study, therefore, counts only 

increased state or local spending for nonhighway purposes, including 

increased tax relief, as representing grant substitution. 

The Estimated Effect of 

Federal Highway Grants on 

State Highway Spending

All three studies use federal grants expenditures to measure federal grants 

received by states. This variable is statistically significant in all studies. In 

addition to grant expenditures, Gamkhar also considers grant obligations 

as an alternative measure. Since obligated funds are available for 

expenditure for several years, she included this variable with lagged 

values.6

The reported estimates of substitution rates associated with federal 

highway grants vary across the three studies. These differences are, in part, 

due to differences in the time periods studied, the definitions of state 

6

Gamkhar treats grant obligation data as a predetermined variable and therefore uses OLS 

methods to estimate the grant coefficient. However, if state spending and federal grants are 

jointly determined this may yield biased estimates of the substitution rate.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 59 GAO-04-802 Federal-Aid Highways

highway spending, and the statistical methods employed. Among the 

highlights of the studies were the following: 

• Knight’s study reports a grant substitution rate of over 90 percent for the 

period from 1983 to 1997. Knight defines substitution as the reduction in 

state (but not local) government spending on all highway-related 

projects. 

• Gamkhar reports a substitution rate of 63 percent for the period 1976 

through 1990. Gamkhar defines substitution as the reduction in state 

and local government spending on all highway-related projects; 

Gamkhar measured federal grants using grant expenditures. When 

grants were measured using obligations rather than actual grant 

expenditures, a lower substitution rate of 22 percent is reported.7

• Meyers also reports a 63 percent substitution rate for the period 1976 

through 1982. Meyers defines the substitution rate as the reduction in 

state and local government spending on federal-aid eligible highway 

projects net of spending on the Interstate Highway Systems; federal 

grants are measured using grant expenditures. However, when he 

defined substitution as the increase in state and local government 

nonhighway spending, he reports no substitution. 

7

The estimate based on grant obligations data may be downwardly biased if, as argued by 

Knight, federal grants and state expenditures are jointly determined (see Knight op. cit, p. 

77).
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 60 GAO-04-802 Federal-Aid Highways

Table 5 summarizes the definitions used and findings of these three studies. 

Table 5: Highway Grant Substitution Rates Reported in Fiscal Substitution Studies

Source: GAO analysis.

a

Meyers’s formal test for substitution into nonhighway spending is to test whether federal highway 

grants are systematically related to state nonhighway spending. He finds no statistical evidence of 

such a relationship. 

Controls for Other Factors 

Associated with State 

Spending Choices

To isolate the effect of federal highway grants on state highway spending, 

these studies include additional variables in their models to control for 

other factors also related to state spending. Some of the control variables 

are similar across the studies, but others differ.

Fiscal Capacity All three studies use per capita personal income to represent states’ 

funding capacity, and in each study the variable is found to be statistically 

significant. 

Tax Price All three studies include a wide variety of variables that are intended to 

capture various components of the tax price faced by the typical 

voter/consumer. 

Study

Definitions of state highway 

expenditures Substitution rate

Knight State (but not local) government 

spending for highway-related 

projects (capital and 

maintenance, real per capita 

dollars)

91 percent

Gamkhar State and local government 

spending for highway-related 

projects (capital and 

maintenance real per capita 

dollars) 

63 percent (grant expenditures)

22 percent (grant obligations)

Meyers State capital spending on federalaid highways (net of interstate 

highways, real per capita)

State and local government 

nonhighway spending, (real per 

capita)a

63 percent 

 0 percent
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 61 GAO-04-802 Federal-Aid Highways

Input prices All three studies measure financial variables in real dollars by adjusting for 

price level differences over time but otherwise do not explicitly include an 

input cost adjustment as a tax price proxy, except to the extent that the 

fixed effects procedure employed by Knight and Gamkhar capture these 

differences.8

 

Highway System Size Only Meyers uses an indicator of highway system size: lane miles on 

federal-aid highways. While this variable has the expected positive sign it is 

statistically insignificant. However, a quadratic term to capture a possible 

U-shaped functional form was not used.

Highway usage All studies use the number of registered vehicles as a measure of highway 

usage. In addition, Knight uses the number of drivers, whereas Meyers 

includes vehicle miles traveled. Gamkhar includes several additional 

proxies for highway use that are not included in the other studies: the 

percentage of light motor vehicles, population density, and percentage of 

population living in metropolitan areas. However, none of these factors was 

statistically significant. In general, only one of the use variables is 

statistically significant in each study and no one measure is statistically 

significant across studies. In several instances the coefficient has a 

negative sign, although a positive relationship between highway usage and 

state spending would be expected.

Highway matching rates Although highway grants require state matching, Knight and Gamkhar do 

not include highway matching rates as part of their models because they 

found that states’ highway spending exceeds the amounts required for their 

federal grant allotments and, therefore, have only an income effect but no 

price effect. Meyers, in contrast, does include the effective matching rate 

(highway grants as a percentage of highway expenditures) and reports a 

price elasticity of one.

Nonhighway matching rates Other grants may also have a price effect because programs such as 

Medicaid, Foster Care, and Adoption Assistance are all open-ended 

matching grants. Including the effective matching rate associated with 

other grant spending (i.e., other grants as a percent of 

8

However, to the extent that cross-state differences in input costs is relatively stable over 

time, Knight and Gamkhar may have accounted for these differences through the fixed 

effects estimating procedure.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 62 GAO-04-802 Federal-Aid Highways

nonhighway spending) captures the potential price effect of other grants.9

The sign on the effective matching rate is expected to be negative because 

higher demand for other state services would reduce the demand for 

highway spending. These variables are statistically significant in both 

studies. The Knight study does not consider the tax price effect of 

nonhighway grant funding. 

Cost sharing Only Knight, by including population in his model, includes a factor that 

could be interpreted as reflecting the cost-reducing effect of having more 

taxpayers sharing the cost of highway services. Neither Gamkhar nor 

Meyers includes such a factor. 

Other Grant Funding In addition to the tax price effect of nonhighway grant funding, the studies 

may also have income effects. Both Meyers and Gamkhar include other 

nonhighway grants per capita in their models to capture the income effect 

of these grants.10 The income effect is expected to have a negative effect on 

own-source spending as some of these grants may be substituted into 

highway spending and supplant funding from state resources. The Knight 

study does not consider either price or income effects associated with 

nonhighway grant funding.

Political Culture/Preferences Only Knight includes variables that are intended to reflect differences in 

state preferences for highway spending that may be associated with the 

political party of the state governor and the partisan representation in the 

state legislature. He finds the party of the state governor to be statistically 

significant at the 10 percent level, while the other political variables are not 

statistically significant.

Description of GAO’s 

Statistical Model

Consistent with previous studies, we model state spending choices as being 

conditioned on states’ fiscal capacities, the tax price faced by state voters, 

federal grant funding for highways and for other state services, and 

preferences of state voters for highway spending. Because both theory and 

the results of previous studies suggest that federal grants and state 

9

The effective matching rate is measured by expressing other grant funding as a percentage 

of total nonhighway spending. 

10As noted above, both studies also include these grants as a share of total nonhighway 

spending to capture any price effect these grants may have. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 63 GAO-04-802 Federal-Aid Highways

spending decisions are jointly determined, we use an instrumental 

variables (IV) approach to estimate the fiscal effect of federal grants. 

To capture other factors that may be systematically associated with 

differences in state spending choices, we estimate the model using a fixed 

effects estimating procedure. The fixed effects procedure is intended to 

capture factors such as topographical differences and weather conditions 

across states that do not change over time and to capture other 

unmeasured factors with large cross-state variation that exhibit relatively 

little change over time.11 In addition, we include a time trend to capture 

trend changes in state spending that may not be captured by the other 

variables included in our model. 

The specific variables considered for our model are listed in table 6.12 

Table 6: Variables Considered in the Second Stage State Highway Expenditure 

Equation

11Both Knight and Gamkhar adopt this strategy.

12Consistent with previous studies, we expressed state highway spending on a per capita 

basis and adjusted for the changing cost of highway services over time by deflating 

expenditures using the chain-price deflator for state and local government streets and 

highways published by the Bureau of Economic Analysis as part of the National Income 

Accounts. 

Variable name 

Dependent variable (per capita)

Real state and local government spending for highway capital and maintenance 

Fiscal capacity (per capita)

Real personal income 

Real income squared

Tax price

Vehicle miles traveled per capita 

Drivers per capita

Registered motor vehicles per capita 

Effective match rate of nonhighway grants

Population

Lane miles per capita
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 64 GAO-04-802 Federal-Aid Highways

Source: GAO analysis.

a

Predicted values of federal highway grants.

b

With the exception of some independents, office holders are either Democratic or Republican. 

Therefore, the choice of using the percentage Democrats or Republicans is arbitrary and has no effect 

on the statistical results except to change the sign of the regression coefficient. 

Testing the Stability of the 

Substitution Rate

With each time period, various rules and regulations change that may affect 

the ability of states to substitute federal grants for state spending. Given 

the range of estimates over different time periods reported in past 

research, we also want to test whether the rate of grant substitution, if 

found, systematically differ across the time periods included in our data. To 

see if the substitution rate differs over time, we introduce dummy variables 

for each of the time periods covered in our study into our model.13 We then 

multiply these dummy variables by the grants variables and included these 

interaction variables in the model. If statistically significant, these variables 

would provide evidence that substitution has varied from one time period 

to another. 

Squared lane miles per capita 

Federal grants (per capita)

Real highway grantsa

Real other federal grants 

State preferencesb

Governor democratic

Percentage of state House represented by Democratic party

Percentage of state Senate represented by Democratic party

Other variables

Utah Olympics (=1 for 1997-2000)

Time trend

Time trend squared

Inverse time trend

State fixed effects

(Continued From Previous Page)

Variable name 

13Our grant expenditures variable reflects, in part, obligations made in prior years. As a 

consequence, the substitution rate for a particular time period will, in part, be conditioned 

on grant obligations made in prior time periods.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 65 GAO-04-802 Federal-Aid Highways

Definition of State Highway 

Spending 

The estimated effect of federal highway grants on state highway spending 

is measured by the regression coefficient associated with federal highway 

grants. As a consequence, the interpretation of that coefficient is directly 

affected by how the dependent variable, state expenditures, is defined. If 

we defined state highway spending narrowly as only capital expenditures 

on federal-aid highway projects, the federal grants coefficient in our model 

would be interpreted as the response of state capital spending to changes 

in federal highway aid. This approach, taken by Meyers,14 represents a 

definition of state spending that is consistent with the requirements of the 

federal-aid highway program, which restricts federal grants to authorized 

uses, such as capital investment on eligible federal-aid highway routes. 

Under this approach, grant funds that are used for purposes that are not 

eligible for federal aid, would represent grant substitution in the same way 

that increased spending for health and education and for state tax relief 

would represent grant substitution. Some policymakers may not view this 

as substitution, perhaps arguing that state transportation officials are 

better positioned to determine the best use of available funding for 

highway-related projects. Our analysis uses this broader definition of state 

highway spending. Thus, our measure of grant substitution considers only 

state grant funds that are effectively used for nonhighway purposes as 

substitution.15 

We adopt this approach for two reasons. First, we want to be conservative 

in our definition of grant substitution. A broader definition of state highway 

spending that includes state and local spending on highway projects not 

eligible for federal funding would yield a lower estimate for the substitution 

rate because some types of adjustments would not be treated as grant 

substitution. Second, an estimate of grant substitution that is based only on 

state (but not local) government spending would be affected by cross-state 

differences in the extent to which highway spending is centralized at the 

state level. Since there are large differences across states in the extent to 

which highway spending is centralized, we include local as well as state 

government spending so that our measure of highway spending would be 

comparable across states. 

14Meyers, op. cit.

15Knight, op. cit, takes an intermediate approach by using only state government capital and 

maintenance spending, excluding highway spending by local governments. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 66 GAO-04-802 Federal-Aid Highways

Definition of Federal 

Highway Grants and 

Specification of the Federal 

Grants Equation 

Because federal highway grants are provided on a reimbursement basis, we 

obtained from FHWA federal highway grant expenditures that are 

contemporaneous with states’ reported own-source highway spending. As 

with state spending, we express federal grants in real per capita dollars, 

using the BEA chain-price index for state and local government streets and 

roads. Because federal grant expenditures, by definition, represent formula 

grant allotments from current and prior years, any lagged response in state 

spending to federal highway grant funds is already included in our grants 

variable. We therefore do not include lagged values of federal highway 

grants in our model.

Knight provides an economic argument explaining that state highway 

spending and federal grant funding are jointly determined because elected 

officials reflect the preferences of state voter/consumers both in state 

legislatures and in Congress. His study tests for and finds confirming 

evidence for his theoretical argument.16 Based on these findings, we also 

employ an IV estimator that provides a consistent estimate of the federal 

grant coefficient to measure the fiscal effect of federal grants. Using this 

approach, we estimate a first stage instrumental variable equation that 

models federal highway funding in terms of exogenous variables that are 

expected to influence the distribution of federal grants. The instrumental 

variables include the exogenous variables from the state expenditure 

equation (e.g., fiscal capacity, the individual components of tax price, and 

preferences) and variables that are highly correlated with federal grants 

but uncorrelated with state highway spending (e.g., variables included in 

federal grant formulas and those that may affect the distribution of 

discretionary grants). Predicted values of federal grants, derived from the 

instrumental variables (highway grants) equation, are then used in lieu of 

actual grant values to correct for the bias in ordinary least squares (OLS) 

estimates of the federal grants coefficient in the state expenditure 

equation. 

The excluded exogenous variables we consider include state contributions 

to the highway trust fund and variables that are intended to reflect the 

influence of state representatives on the distribution of federal highway 

grants: tenure in Congress, state representation on transportation 

committees, and state representation in the majority party. The exogenous 

variables we consider are summarized in table 7.

16Knight, op. cit.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 67 GAO-04-802 Federal-Aid Highways

Table 7: Variables Used to Explain the Distribution of Federal Highway Grants

Source: GAO analysis.

Consistent with the state highway spending equation, we include real per 

capita income, real nonhighway grant funding, registered vehicles, licensed 

drivers, and vehicle miles traveled—including 1- and 2-year lagged values 

for each of these variables—and use a fixed effects estimating procedure. 

Fixed effects are intended to capture factors that have substantial variation 

across states with little variation over time. Examples would be factors 

such as state land area—a factor that has been part of highway funding 

Instrumental Variables Equation:Federal Highway Grants 

Exogenous variables from spending equation

 Real personal income per capita

 Real personal income per capita squared

 Real nonhighway federal grants per capita

 Effective nonhighway matching rate 

 Lane miles per capita – 1-yr. lag

 Lane miles per capita squared – 1 yr. lag

 Vehicle miles traveled per capita 

 Drivers per capita 

 Registered vehicles per capita 

 Population

 Governor democratic (1=Dem. 0 = other)

 Percent Democrats in state house 

 Percent Democrats in state senate 

 Utah Olympics (=1 for 1997 - 2000)

 Time trend

 Time trend squared

 Inverse time trend

 State fixed effects dummy variables

Excluded exogenous variables

Percentage of state representatives in majority party (in year grants were authorized)

Percentage of state representatives on House transportation authorization committee

Average tenure of state representatives in House (in year grants were authorized)

Percentage of state senators in majority party (in the year grants authorized)

Percentage of state representatives on Senate transportation authorization committee

Average tenure of state Senators (in year grants were authorized)

Real federal highway trust fund receipts per capita 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 68 GAO-04-802 Federal-Aid Highways

formulas and that does not change over time—and constraints that are 

applied to funding formulas, such as the 1⁄2-of 1 percent minimum state 

grant that is included in highway funding formulas (see table 1).

State Funding Capacity Consistent with previous studies, we use real per capita personal income to 

measure states’ taxing capacities. Unlike previous studies, we also include 

the squared value of per capita income to capture the possibility that 

demand for highways does not increase in proportion to increases in 

income, perhaps signifying that as basic transportation needs are met, 

increases in income are increasingly allocated to other uses such as health 

and education. Personal income is published by the BEA in the Department 

of Commerce. We include 1- and 2-year lagged values of real per capita 

income in the model to allow for lagged responses to changes in income 

and also to reflect cyclical changes affecting the level of state revenues. 

Tax Price The tax price faced by state voters/consumers is reflected in a number of 

variables included in the model. Highway usage is reflected by vehicle 

miles traveled on state highways, and by registered vehicles and licensed 

drivers in the state, as reported by FHWA. We include 1- and 2-year lagged 

values in each of these variables to allow for lagged responses in spending 

to changes in highway usage.

Consistent with prior studies, we do not include the matching rate on 

highway grants because states spend more than the required federal match, 

and therefore, states pay 100 percent of the cost of funding additional 

highway projects, and because highway matching rates vary little both over 

time and across states. However, we do include the effective match rate on 

other grant funding to capture the price effect of other grant funding. 

Medicaid, Foster Care, and Adoption Assistance, for example, are openended matching programs with price effects that may encourage states to 

spend less on highways in order to provide matching funds for these and 

possibly other matching programs. We include 1- and 2-year lagged values 

to capture these effects. Using data from the Census Bureau, we measure 

the effective matching rate for nonhighway spending by deducting states’ 

federal highway grants from their total federal grants and expressing the 

net amount (nonhighway grants) as a proportion of each state’s 

nonhighway spending, also calculated by deducting highway spending from 

total spending. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 69 GAO-04-802 Federal-Aid Highways

Although previous studies do not include the size of the highway network 

to be maintained, we expect the per capita cost of maintaining an existing 

highway network to be higher in states with more miles of road per capita. 

Therefore, we include this variable in our model along with its squared 

value to test for evidence of per capita costs varying with the scale of the 

road network—that is, economies or diseconomies of scale. We obtained 

data on total lane miles of state highways from FHWA.

Other Federal Grants In addition to federal highway grants, states receive federal grants for a 

variety of other purposes, including health, education, and welfare. While it 

is possible that state highway funds may be substituted into spending for 

other state services, it is also possible that some state funds that would 

have otherwise been used for other purposes may be redirected into 

highways. For this reason, we also include other federal grant funding in 

our model to capture the income effect of these grants and their potential 

substitution into highway spending. While some of this aid is provided on a 

reimbursement basis (Medicaid, for example) other grants can remain 

eligible for expenditure in subsequent years. For this reason, we include 1- 

and 2-year lagged values of other federal grants to capture these potential 

effects. Other federal grants are also expressed in real per capita dollars. 

State Preferences The political culture of states may affect both the overall level of spending 

on public services, as well as spending priorities for different types of 

services, such as highways, versus education and health care. Differences 

in political culture and spending priorities may be relatively stable over 

time, in which case the fixed effects adjustment may adequately control for 

cross-state differences in these spending preferences. Nonetheless, in 

addition to including fixed effects, we have also included variables that 

may be associated with differences in political culture. For this purpose, 

we have included dummy variables that are equal to one if the state 

governor is Democratic and zero otherwise, and the percentage of the state 

Senate and state House that is represented by the Democratic Party. With 

the exception of some independents, office holders are either Democratic 

or Republican. Therefore, the choice of using the percentage Democrats or 

Republicans is arbitrary and has no effect on the statistical results except 

to change the sign of the regression coefficient. We obtained these data 

from the Elections section of the Census Bureau’s Statistical Abstract.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 70 GAO-04-802 Federal-Aid Highways

Other Variables To capture trend changes in state spending that cannot be captured by the 

other variables included in our model, while allowing for a possible 

curvilinear trend, we have also included time, time squared, and the inverse 

of time. Finally, we include a dummy variable for the state of Utah that was 

equal to 1 during the years 1997 through 2000 and zero otherwise to 

account for the unusually large increase in highway spending in that state 

just prior to the 2002 Winter Olympics. 

The means and standard deviations for the variables included in our 

statistical model are shown in table 8. 

Table 8: Descriptive Statistics 

Source: GAO analysis.

Variables Units Mean

Standard 

deviation

Real State Highway Spending 

Per Capita 

Dollars per person

$203 $80

Real Federal Highway Grants 

Per Capita 

Dollars per person

$94 $59

Real Non-Hwy Federal Grants 

Per Capita 

Dollars per person

$671 $235

Federal Nonhighway Grants 

percent of Nonhighway 

Expenditures

Ratio

16% 4%

Road Miles Per Person Lane Miles per 1,000 

population 53 53

Registered Vehicles per 

Person

Registered vehicles per 1,000 

population 786 117

Vehicle Miles Traveled per 

Person

1,000 miles per person

9 2

Licensed Drivers per Person Licensed drivers per 1,000 

population 679 50

Real Per Capita Income Dollars per person 21,272 4,223

Percent Democratic in State 

House

Percent

57% 17%

Percent Democratic in State 

Senate

Percent

58% 18%

Governor Democrat, 

(1=Democrat; 0=otherwise)

Not applicable

52% 50%
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 71 GAO-04-802 Federal-Aid Highways

Statistical Methods Because we use time series and cross-section data to estimate the model, 

we expect autocorrelation to bias the estimates of the standard errors 

associated with variables in our model. To reduce the problem of 

heteroscedasticity, we normalize variables by expressing them on a per 

capita basis (except for those already expressed in ratio or percentage 

terms). We conducted statistical tests to determine if our data are affected 

by autocorrelation and found statistical evidence of its presence. 

Therefore, we estimate all our models using a correction for 

autocorrelation. As noted above, we use a fixed effects procedure that 

allows for a separate constant term associated with each state to represent 

differences in state funding that are unique to each state and independent 

of the other variables included in the model. 

Additional Analysis of Fixed 

Effects

The fixed effects coefficients of our model represent state differences in 

highway spending, after controlling for the other explanatory variables in 

our model. They are intended to capture the effect of variables that have 

comparatively little variation over time but are systematically associated 

with differences in spending across states. To identify those state 

characteristics that are systematically related to the fixed effects 

associated with state highway expenditures, we perform an additional 

stepwise regression analysis that regresses the following explanatory 

variables on our estimated fixed effects, using the following: 

• Heating degree days,

• State land area,

• Lane miles per capita,

• Population,

• Vehicles per capita,

• Drivers per capita,

• Federal land area,

• Percentage of Democrats in state House,

• Percentage of Democrats in state Senate,
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 72 GAO-04-802 Federal-Aid Highways

• Governor Democratic,

• Federal nonhighway grants per person, and

• Ratio of federal nonhighway grants per person to state nonhighway 

spending 

We use the mean value of 21 observations from 1980 to 2000 per state to 

represent each variable in explaining our estimated fixed effects. 

Statistical Results We report the statistical results explaining federal highway grants in terms 

of exogenous instrumental variables in table 9. Based on the R2 statistics, 

the fixed effects adjustment accounts for 85 percent of the variation in 

federal grants funding and the additional exogenous variables added to the 

model increases the R2

 by 5 percent to 90 percent. Variables that are 

statistically significant at the 5 percent level appear in bold in the table. In 

addition to the fixed effects coefficients, per capita income, highway lane 

miles of roads, and state contributions to the Highway Trust Fund are 

strongly associated with the distribution of federal highway funding. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 73 GAO-04-802 Federal-Aid Highways

Table 9: Instrumental Variables Estimator of Federal Grants per Capita

Model R2

Constant term only 0.000

State fixed effects only 0.854

X - variables only 0.739

X and group effects 0.895

Variables Coefficients Standard error Probability value

Personal income, real per capita 0.015 0.007 0.035

Personal income, real per capita, (t-1) 0.008 0.009 0.375

Personal income, real per capita, (t-2) -0.021 0.006 0.000

Personal income squared, real per capita -0.3121E-06 0.1500E-06 0.037

Personal income squared, real per capita, (t-1) -0.1150E-06 0.2005E-06 0.566

Personal income squared, real per capita, (t-2) 0.4831E-06 0.1288E-06 0.000

Nonhighway federal grant, real per capita 0.035 0.027 0.187

Nonhighway federal grant, real per capita, (t-1) 0.133 0.032 0.000

Nonhighway federal grant, real per capita, (t-2) -0.051 0.026 0.048

Effective nonhighway match ratea -201.622 129.481 0.119

Effective nonhighway match ratea (t-1) -388.050 148.409 0.009

Effective nonhighway match ratea (t-2) 139.497 118.758 0.240

Vehicle miles traveled per capita -7.331 3.204 0.022

Vehicle miles traveled per capita, (t-1) -0.852 3.721 0.819

Vehicle miles traveled per capita, (t-2) 2.688 2.637 0.308

Registered vehicles per capita 0.048 0.024 0.041

Registered vehicles per capita, (t-1) -0.013 0.028 0.643

Registered vehicles per capita,(t-2) -0.007 0.024 0.785

Drivers per capita -0.022 0.034 0.514

Drivers per capita,(t-1) -0.018 0.038 0.634

Drivers per capita, (t-2) 0.041 0.033 0.221

Population, in 1,000 0.002 0.002 0.138

Road miles per capita, (t-1) 1.231 0.313 0.000

Road miles squared per capita, (t-1) -0.004 0.001 0.002

Governor Democrat, (1=Democrat; 0=otherwise) -3.836 1.737 0.027

Percent Democratic in State House 2.758 14.498 0.849

Percent Democratic in State Senate 32.801 11.695 0.005

Utah Olympics = 1 for Utah in 1997-2000, 0 otherwise -12.757 12.055 0.290

Time trend -3.123 2.627 0.234
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 74 GAO-04-802 Federal-Aid Highways

Source: GAO analysis.

a

Ratio of federal nonhighway grants to state and local nonhighway expenditures.

Displacement Effect of 

Federal Highway Grants 

We report the results for the second stage expenditure equation without a 

correction for autocorrelation in table 10. Again, regression results for 

variables that are statistically significant at the 5-percent level appear in 

bold in the table. The model explains 78 percent of the variation in state 

own-source highway spending and fixed effects alone account for 69 

percent of the variation. The estimated substitution rate associated with 

federal grants is 84 percent17 and is statistically significant. That is, other 

things being equal, a dollar increase in federal highway grants is associated 

with an 84-cent reduction in highway spending from state own-source 

revenues. Alternatively, the coefficient also implies that states replace 84 

cents of each dollar decline in federal funding.18 These results are similar to 

the findings reported by Knight, who reported a substitution rate of 91 

percent, higher than the substitution rates reported by Gamkhar. 

Inverse time trend 66.101 33.632 0.049

Time trend squared -0.009 0.089 0.923

Highway trust fund per capita 0.294 0.088 0.001

Highway trust fund per capita, (t-1) 0.330 0.089 0.000

Highway trust fund per capita, (t-2) 0.225 0.088 0.010

Percent of the State's House delegation on the authorizing 

committee 8.233 5.761 0.153

Percent of the State's Senate delegation on the authorizing 

committee -14.760 4.515 0.001

Percent of the State's Senate delegation in the majority 

party 1.649 2.223 0.458

Percent of the State's House delegation in the majority party 5.940 3.863 0.124

Tenure for each State's U.S. House Delegation 0.148 0.283 0.601

Tenure for each State's U.S. Senate Delegation 0.063 0.202 0.756

(Continued From Previous Page)

Variables Coefficients Standard error Probability value

17The substitution rate is the coefficient of the federal grants variable after removing the 

negative sign. 

18In a related paper Gamkhar tests whether the substitution rate is symmetrical during 

periods of rising and falling federal aid and found no statistically significant difference; see 

Shama Gamkhar, op. cit.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 75 GAO-04-802 Federal-Aid Highways

Table 10: Instrumental Variables Estimates of State Highway Spending Model, Without Correcting for Autocorrelation

Model statistics R2

Constant term only 0.000

State fixed effects only 0.685

X - variables only 0.445

X and group effects 0.783

Variables Coefficients Standard error Probability

Predicted FHWA payments / per capita -0.8412 0.233 0.000

Personal income, real per capita, (t) 0.0160 0.013 0.221

Personal income, real per capita, (t-1) 0.0196 0.017 0.249

Personal income, real per capita, (t-2) 0.0110 0.011 0.322

Personal income squared, real per capita, (t) -0.6259E-07 2.860E-07 0.827

Personal income squared, real per capita, (t-1) -0.0416E-07 3.857E-07 0.280

Personal income squared, real per capita, (t-2) -0.9145E-07 2.572E-07 0.722

Nonhighway federal grants, real per capita, (t) 0.0719 0.051 0.159

Nonhighway federal grants, real per capita, (t-1) 0.0789 0.070 0.261

Nonhighway federal grants, real per capita, (t-2) -0.0483 0.051 0.341

Effective nonhighway grant match ratea, (t) -509.8810 250.807 0.042

Effective nonhighway grant match ratea, (t-1) -394.9280 300.760 0.189

Effective nonhighway grant match ratea, (t-2) -102.9480 230.545 0.655

Vehicle miles traveled per capita, (t) -6.4858 6.106 0.288

Vehicle miles traveled per capita, (t-1) 7.8859 7.135 0.269

Vehicle miles traveled per capita,(t-2) 2.0446 5.113 0.689

Registered vehicles per capita, (t) 0.0444 0.046 0.338

Registered vehicles per capita, (t-1) 0.0210 0.054 0.695

Registered vehicles per capita, (t-2) -0.0683 0.046 0.135

Drivers per capita, (t) -0.1290 0.065 0.046

Drivers per capita, (t-1) -0.0498 0.072 0.491

Drivers per capita, (t-2) 0.0777 0.064 0.227

Governor Democrat, (1=Democrat; 0=otherwise) 1.2802 3.400 0.707

% Democratic in State House -4.5781 27.136 0.866

% Democratic in State Senate 46.8598 23.539 0.047

Utah Olympics = 1 for 1997-2000 in Utah, 0 otherwise 154.8240 22.803 0.000

Time trend -32.6570 4.883 0.000

Inverse time trend -95.4868 54.237 0.078

Time trend squared 1.0301 0.153 0.000
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 76 GAO-04-802 Federal-Aid Highways

Source: GAO analysis.

a

Ratio of federal nonhighway grants to state and local nonhighway expenditures.

However, the model also indicates the presence of autocorrelation (ρ=0.53, 

shown in the last row of table 10). As a consequence the standard error for 

the grants coefficient is biased downward, which raises the prospect that 

the grants coefficient may not be statistically significant. We therefore reestimated the model adjusting for autocorrelation using two methods: 

Cochrane-Orcutt and Newey-West.19 The results are reported in table 11.20 

The Cochrane-Orcutt procedure produces a feasible generalized-least 

squares estimate of the grants coefficient and its standard error. With this 

procedure, the point estimate of the substitution rate drops from 84 to 39 

percent and is statistically insignificant (shown in the second column of 

tables 10 and 11). The Newey-West correction for autocorrelation does not 

involve re-estimating the grants coefficient, so the estimated substitution 

rate remains at 84 percent. The coefficient continues to be statistically 

significant after correcting for the bias in its standard error.

Population, in 1,000 0.0033 0.003 0.287

Road miles per capita, (t-1) 1.1212 0.677 0.098

Road Miles squared per capita, (t-1) -0.0013 0.003 0.630

Autocorrelation coefficient 0.5298

(Continued From Previous Page)

Variables Coefficients Standard error Probability

19We used two software packages to estimate the model: Limdep version 7 and Stata version 

8. Limdep uses the Cochrane-Orcutt method to correct for autocorrelation, which results in 

a revised generalized-least-squares estimate of the model coefficients and their standard 

errors, while Stata uses the Newey-West method, which only corrects the estimates of the 

standard errors. Each method yields a different but equally valid estimate of the substitution 

rate. Because the Cochrane-Orcutt method does not include the first observation for each 

state, these estimates are based on observations from 1983 through 2000. In contrast, the 

Newey-West method includes the first observation.

20We also adjusted for heteroscedasticity using White’s methods. The effect of this 

adjustment was minor and therefore we did not report it. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 77 GAO-04-802 Federal-Aid Highways

Table 11: Instrumental Variables Estimates of State Highway Spending Model, Correcting for Autocorrelation 

Model statistics R2 R2

Constant term only 0.000

State fixed effects only 0.481

X - variables only 0.233

X and group effectsa 0.558 0.783

Variables

Autocorrelation corrected model estimates

Cochrane-Orcutt estimates Newey-West estimates

Coefficients Probability Coefficients Probability

FHWA payments / per capita -0.3859 0.222 -0.841 0.002

Personal income, real per capita, (t) 0.0028 0.824 0.016 0.226

Personal income, real per capita,, (t-1) 0.0177 0.157 0.020 0.211

Personal income, real per capita, (t-2) 0.0058 0.567 0.011 0.309

Personal income squared, real per capita, (t) 1.083E-07 0.683 -0.0626E-07 0.827

Personal income squared, real per capita, (t-1) -3.273E-07 0.231 -4.160E-07 0.237

Personal income squared, real per capita, (t-2) -0.6321E-07 0.785 -0.9140E-07 0.716

Nonhighway federal grants, real per capita, (t) 0.1065 0.012 0.072 0.140

Nonhighway federal grants, real per capita, (t-1) 0.0312 0.595 0.079 0.214

Nonhighway federal grants, real per capita, (t-2) -0.0715 0.118 -0.048 0.330

Effective nonhighway grant match rateb, (t) -624.9567 0.004 -509.881 0.034

Effective nonhighway grant match rateb, (t-1) -311.9012 0.176 -394.928 0.124

Effective nonhighway grant match rateb, (t-2) 119.4099 0.553 -102.948 0.646

Vehicle miles traveled per capita, (t) 2.1109 0.689 -6.486 0.268

Vehicle miles traveled per capita, (t-1) 3.6408 0.461 7.886 0.159

Vehicle miles traveled per capita,(t-2) -0.2714 0.953 2.045 0.657

Registered vehicles per capita, (t) 0.0180 0.640 0.044 0.319

Registered vehicles per capita, (t-1) 0.0336 0.348 0.021 0.633

Registered vehicles per capita, (t-2) -0.0342 0.353 -0.068 0.118

Drivers per capita, (t) -0.0826 0.107 -0.129 0.036

Drivers per capita, (t-1) -0.0555 0.277 -0.050 0.407

Drivers per capita, (t-2) 0.0381 0.470 0.078 0.206

Governor Democrat, (1=Democrat; 0=otherwise) 3.4241 0.387 1.280 0.735

% Democratic in State House -9.4411 0.753 -4.578 0.878

% Democratic in State Senate -13.8934 0.613 46.860 0.073

Utah Olympics, = 1 for 1997-2000 in Utah, 0 otherwise 142.8233 0.000 154.824 0.000

Time trend -17.7499 0.199 -32.657 0.000
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 78 GAO-04-802 Federal-Aid Highways

Source: GAO analysis.

a

The R2 with the correction for autocorrelation is not comparable to the R2 without the correction 

because the dependent variable is different between the two models due to the autocorrelation 

adjustment.

b

Ratio of federal non-highway grants to state and local nonhighway expenditures.

The Effect of Removing 

Statistically Insignificant 

Variables 

The full model includes over 30 variables when all the lags are included and 

many of these variables are statistically insignificant. To simplify the 

model, we performed F- tests for the statistical significance of variables 

and removed variables with a statistical significance level below 10 

percent. We tested variables that were included with 1- and 2-year lags as a 

group and removed them as a group if found insignificant. We summarize 

the results of these tests in table 12. The primary result is that neither the 

highway usage variables nor the variables intended to capture state 

differences in preferences are statistically significant. The only variables 

that are systematically associated with differences in state highway 

spending are the variables reflecting financial resources that could be used 

to fund highways.

Inverse time trend 110.4277 0.895 -95.487 0.234

Time trend squared 0.5692 0.089 1.030 0.000

Population, in 1,000 0.0018 0.741 0.003 0.361

Road miles per capita, (t-1) -0.3525 0.711 1.121 0.147

Road Miles squared, per capita, (t-1) 0.0034 0.364 -0.001 0.674

Autocorrelation coefficient 0.5297

(Continued From Previous Page)

Variables

Autocorrelation corrected model estimates

Cochrane-Orcutt estimates Newey-West estimates

Coefficients Probability Coefficients Probability
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 79 GAO-04-802 Federal-Aid Highways

Table 12: Summary Results of the Statistical Testing of the Variable Coefficients

Source: GAO analysis.

a

Vehicle miles traveled per capita, registered vehicles per capita, and licensed drivers per capita.

The result of removing statistically insignificant variables is shown in table 

13. With the Cochrane-Orcutt method for autocorrelation correction, the 

grant substitution coefficient is 0.50 and with the Newey-West correction 

the coefficient is 0.58; both estimates are statistically significant at the 1 

percent significance level. Thus, the difference in estimated substitution 

rates under the two methods narrowed with the simplified model. To be 

conservative in our findings regarding grant substitution, we are using the 

lower estimate of 0.50, based on the Cochrane-Orcutt method, as our 

preferred estimate. The 95 percent confidence interval ranges from 12 to 88 

percent, which includes Gamkhar’s estimate of 63 percent but not Knight’s 

higher estimate of 91 percent. Because the Cochrane-Orcutt method does 

not include the first observation for each state, these estimates are based 

on observations from 1983 through 2000. 

Analysis of Remaining 

Explanatory Variables

The full model includes per capita income squared to test for nonlinear 

effects of income on state spending. However, the squared term is 

statistically insignificant. We conclude that state spending is proportional 

to income, which implies that both high- and low-income states respond to 

changes in income in roughly the same proportion, once other factors 

affecting state spending choices are taken into account. The lag structure 

on per capita income indicates that the largest increase occurs in the first 

Variables tested

Statistical results

F Statistic Probability

Personal income, all 3.6169 0.0000

 Linear 2.5524 0.0545

 Squared 1.1269 0.3373

Nonhighway grants, all 3.5888 0.0016

 Amounts 2.3880 0.0677

 Ratio 3.5081 0.0150

Use variablesa 0.8952 0.5447

Political preference 0.3476 0.7909

Time trend 4.3000 0.0050

Lane miles 1.3333 0.2642
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 80 GAO-04-802 Federal-Aid Highways

year, but prior year changes in income also affect state expenditures (see 

table 13).

The effect of nonhighway grants enters into the model in two ways: the 

absolute size of other grant funding, measured in per capita terms, 

representing the income effect of other-grant funding; and the ratio of the 

nonhighway grants to state nonhighway spending, representing the tax 

price effect of other-grant funding. The net income effect of other grants is 

small but positive. The coefficients on the nonhighway grant variables sum 

to a small positive effect with a statistically significant positive effect in the 

current year and a statistically significant negative effect in year 2. This 

result is contrary to expectations in that the net effect would be expected 

to result in some of the funding from other federal grants to be used as a 

substitute for states’ own highway spending. 

In contrast, the tax price effect of other grants is strongly negative 

indicating that matching requirements associated with other federal 

programs, such as Medicaid, result in states spending less of their own 

resources on highways. For every dollar spent by a state, the federal 

government reimburses the state for a percentage of the cost, reducing the 

tax price of these services to the state. The lower price for other public 

services raises the demand for those services and reduces the demand for 

highways, suggesting that highways and other public services are 

substitute goods. 

We enter the time trend variable into the model in linear, quadratic, and 

inverse form to provide a flexible functional form. The inverse term was 

statistically insignificant and we dropped it from the model. The 

coefficients on the linear and quadratic term indicate a negative trend for 

most of the years in state highway spending when other factors affecting 

state spending are taken into account. 

Varying Substitution Rates 

Over Time

As we noted in our summary of previous studies, Meyers reports no 

evidence of substitution into nonhighway spending during the 1976 to 1982 

time period. Gamkhar, based on data from 1976 through 1990, reports 

higher rates of substitution, and Knight’s study, based on data from 1983 

through 1997, reports even higher rates of substitution. We therefore tested 

for evidence of increasing substitution rates using the Cochran-Orcutt 

method, which, as discussed earlier, uses the estimation period 1983 to 

2000. The results are shown in table 14. 
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 81 GAO-04-802 Federal-Aid Highways

Table 13: State Highway Spending Model with Statistically Insignificant Variables Removed

Source: GAO analysis.

Model statistics R2

Constant term only 0.000

State fixed effects only 0.426

X – variables only 0.078

X and group effects 0.479

Autocorrelation Adjustment Method

Cochrane-Orcut Newey-West

Variables Coefficients

Standard 

errors

Probability 

values

95 Percent 

confidence 

interval Coefficients

Standard 

errors

Probability

values

FHWA highway 

grants, real per capita -0.501 0.194 0.010 -0.881 -0.121 -0.580 0.174 0.001

Personal income, real 

per capita, (t) 0.006 0.002 0.005 0.002 0.010 0.009 0.003 0.000

Personal income, real 

per capita, (t-1) 0.005 0.002 0.033 0.001 0.009 0.006 0.003 0.041

Personal income, real 

per capita, (t-2) 0.002 0.002 0.280 -0.002 0.006 0.001 0.002 0.652

Nonhighway federal 

grants, real per 

capita, (t) 0.115 0.040 0.004 0.037 0.193 0.064 0.046 0.168

Nonhighway federal 

grants, real per 

capita, (t-1) 0.044 0.049 0.370 -0.052 0.140 0.037 0.058 0.522

Nonhighway federal 

grants, real per 

capita, (t-2) -0.081 0.041 0.045 -0.161 -0.001 -0.036 0.047 0.445

Effective nonhighway 

grant match ratea

, (t) -630.218 204.465 0.002 -1030.969 -229.467 -475.541 231.228 0.040

Effective nonhighway 

grant match rate, (t-1) -310.799 208.831 0.137 -720.108 98.510 -238.395 242.269 0.325

Effective nonhighway 

grant match rate, (t-2) 214.391 186.720 0.251 -151.580 580.362 -172.916 212.623 0.416

Utah Olympics, = 1 for 

1997-2000, 0 

otherwise 140.309 27.778 0.000 85.864 194.754 165.540 25.423 0.000

Time trend -17.804 5.107 0.000 -27.814 -7.794 -15.166 3.150 0.000

Time trend squared 0.570 0.162 0.000 0.252 0.888 0.461 0.098 0.000

Autocorrelation 

coefficient 0.584
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 82 GAO-04-802 Federal-Aid Highways

a

Ratio of federal nonhighway grants to state and local nonhighway expenditures 

To test whether the substitution rate has increased over the period of our 

sample data, we divided our sample into four time estimation periods, 

corresponding with the authorization periods for the federal-aid highway 

program.21

• 1983 to 1986, 

• 1987 to 1990, 

• 1991 to 1997, and 

• 1998 to 2000. 

Allowing the substitution rate to vary over time improves the explanatory 

power of the model, increasing the R2

 of our preferred model from 48 

percent to 57 percent. The first period from 1983 to 1986 shows a 

substitution rate of 18 percent that is not significantly different from zero. 

The estimated substitution rate increases to 36 percent in the 1987 to 1990 

period and is significant at the 10 percent level. The substitution rate rises 

to just under 60 percent during the two periods of the 1990s and is 

statistically significant at the 1 percent level. As shown in Table 14, these 

results are roughly consistent with previous studies that, when taken 

together, seem to suggest increasing matching rates over time. 

21As stated earlier, grant expenditures represent, in part, obligation authority provided in 

prior years.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 83 GAO-04-802 Federal-Aid Highways

Table 14: State Highway Spending Model with Substitution Rates by Time Period

Source: GAO analysis.

a

Ratio of federal nonhighway grants to state and local nonhighway expenditures.

When the substitution rate is allowed to vary over time, the time trend 

coefficients become statistically insignificant. This lack of significance 

suggests that there is no negative time trend in state spending once the 

increasing substitution rate associated with different time periods is taken 

into account. 

We use an IV estimator because we assume federal grants and state 

spending are jointly determined. To test the reliability and validity of the IV 

estimator we ran three additional statistical tests: (1) a weak instruments 

Model R2

Constant term only 0.000

State fixed effects only 0.494

X – variables only 0.145

X and group effects 0.565

Variables Coefficients

Standard 

errors

Probability 

values

95 Percent confidence 

interval

FHWA Grant, real per capita for 1983-1986. -0.178 0.198 0.370 -0.566 0.211

FHWA Grant, real per capita for 1987-1990. -0.360 0.195 0.065 -0.742 0.022

FHWA Grant, real per capita for 1991-1997. -0.592 0.190 0.002 -0.965 -0.22

FHWA Grant, real per capita for 1998-2000. -0.581 0.188 0.002 -0.95 -0.213

Personal income, real per capita, (t) 0.007 0.002 0.004 0.002 0.011

Personal income, real per capita, (t-1) 0.000 0.002 0.857 -0.004 0.005

Personal income, real per capita, (t-2) 0.004 0.002 0.067 0 0.007

Non-Hwy federal grants, real per capita, (t) 0.147 0.041 0.000 0.068 0.227

Non-Hwy federal grants real per capita, (t-1) 0.046 0.049 0.346 -0.05 0.142

Non-Hwy federal grants real per capita, (t-2) -0.084 0.041 0.039 -0.163 -0.004

Effective federal nonhighway-grant match ratea, (t) -756.328 204.332 0.000 -1156.819 -355.837

Effective federal nonhighway-grant match ratea, (t-1) -243.191 208.038 0.242 -650.945 164.563

Effective federal nonhighway-grant match ratea, (t-2) 241.691 188.098 0.199 -126.981 610.363

Utah Olympics, = 1 for 1997-2000, 0 otherwise 144.022 26.282 0.000 92.51 195.534

Time Trend -5.423 5.193 0.296 -15.602 4.756

Time Trend Squared 0.187 0.168 0.265 -0.142 0.516

Autocorrelation coefficient 0.51599
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 84 GAO-04-802 Federal-Aid Highways

test, (2) a test for exogeneity of excluded exogenous instruments, and (3) a 

test for endogeneity of federal grants. 

The weak instruments test is intended to verify that the excluded 

exogenous instrumental variables included in the grants equation are 

correlated with federal grants. If they are not, the IV estimator provides no 

advantage to a simple (and more efficient) OLS estimator. To test the 

significance of the excluded exogenous variables, we calculated the partial 

R2

 associated with the excluded exogenous instruments and found the 

instruments to be statistically significant at the 1 percent level. 

To test for the exogeneity of excluded exogenous instruments, we 

conducted a Hausman over-identifying restrictions test.22 This test 

compares the estimated federal grant coefficients for each time period 

using the full set of excluded exogenous variables with coefficients derived 

from using a subset of instruments composed of predetermined variables 

that can safely be assumed to be exogenous. A finding that the set of grant 

coefficients from the two models are not statistically different from one 

another lends support for the hypothesis that the full set of excluded 

exogenous instruments are independent of the error term in the second 

stage expenditure equation. For this test, we used a subset of excluded 

exogenous variables. Differences between the grant coefficients for each 

time period using all instruments, and the coefficients using the subset of 

exogenous instruments, were not statistically significant and are 

quantitatively very similar to one another. Thus, we found no evidence that 

our excluded exogenous instruments were correlated with the error term 

of the expenditure equation.

Finally, we conducted a Hausman test for the endogeneity of the federal 

grant variable.23 This test consists of comparing the IV estimate of the grant 

coefficient for each time period with the corresponding grant coefficient 

based on the OLS estimate. If the differences were not statistically 

significant there would be little justification for using the IV estimator. This 

test yielded statistically significant differences between the two sets of 

estimates, lending support for the assumption that federal grants and state 

22Jeffrey M. Woolridge, Econometric analysis of Cross-section and Panel Data, The MIT 

Press, Cambridge, Massachusetts, 2002.

23William H. Greene, Econometric Analysis, 5th Edition, Prentice Hall, New Jersey, 2003, pp. 

80-81.
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 85 GAO-04-802 Federal-Aid Highways

spending are jointly determined. The results of each of the three tests are 

summarized in table 15.

Table 15: Statistical Tests for the Endogeneity of Federal Grants and State Highway 

Spending

Source: GAO analysis.

Additional Tests for Varying 

Substitution Rates 

We also estimated alternative models that allow the substitution rate to 

vary according to state size (measured by population), per capita income, 

and state per capita spending on mass transit to test for a varying 

substitution rate related to these factors. The results of these models were 

negative. Overall we found no evidence that substitution rates 

systematically differ by either population size or the level of mass transit 

spending. We did obtain higher estimates of substitution rates in states with 

higher per capita income (56-66 percent in high income states compared to 

just over 30 percent in lower income states), but these differences were not 

statistically different from the average substitution rate of 50 percent found 

for the period from 1983 to 2000. 

Weak instrument test Partial R2 Probability value

0.10 0.000

Grant coefficient

Hausman overidentifying 

restrictions test All instruments

Subset of 

instruments Probability value

’83-‘86 -0.178 -0.187 0.531

’87-‘90 -0.360 -0.366

’91-‘97 -0.592 -0.590

’98-‘00 -0.581 .581

Grant coefficient

Hausman 

endogeneity test 2SLS OLS Probability value

’83-‘86 -0.178 -0.047 .0001

’87-‘90 -0.360 -0.160

’91-‘97 -0.592 -0.340

’98-‘00 -0.582 -0.343
Appendix II

Description of Grant Substitution Model, 

Statistical Methods, and Results

Page 86 GAO-04-802 Federal-Aid Highways

State Characteristics 

Associated with Fixed 

Effects

In the models reported above, state fixed effects account for most of the 

variation in state highway spending. Based on our preferred model (the 

model in table 12 using the Cochrane-Orcutt autocorrelation correction 

method), differences in state spending associated with these fixed effects 

can be as much as $400 per capita. However, these fixed effects are difficult 

to interpret since they represent all factors that are systematically related 

to cross-sectional differences in state spending not included in the model 

(e.g., geography, weather, and other variables that have substantial crosssectional variation). 

To determine if the differences in state spending measured by the fixed 

effects of our model are systematically associated with particular state 

characteristics, we performed a step-wise regression using the fixed effects 

from our preferred model as the dependent variable. Of the 12 variables we 

considered, 3 are statistically significant: per capita highway lane miles, per 

capita income, and heating degree days (see table 16). In the first step, lane 

miles account for 51 percent of the cross-state variation in our fixed 

effects, the second step equation added per capita income, and increases 

the explained variation to 68 percent. The third step equation adds heating 

degree-days, raising the variation explained to 77 percent. The remaining 

variables are statistically insignificant and provide little additional 

explanatory power. 

Table 16: Stepwise Regression Analysis of the Fixed Effects

Source: GAO analysis.

The positive coefficient on lane miles per capita may reflect a higher per 

capita cost of maintaining a larger highway network. The negative 

coefficient on per capita income suggests that, other things being equal, 

states with high average real incomes per capita spend less for highways 

than states with low average real incomes per capita. Finally, the positive 

coefficient on heating-degree days indicates that states in colder climates 

spend more on highways than states in warmer climates, all other things 

remaining equal. 

Step Variables Coefficient

Probability 

value R2

1 Average lane miles per capita 0.58322 0.002 51%

2 Average real income per capita -0.01778 0.000 68%

3 Average heating degree days 0.01324 0.004 77%
Page 87 GAO-04-802 Federal-Aid Highways

Appendix III

State Characteristics Associated with States’ 

Level of Effort to Fund Highways from State 

Resources ApendxiI

Based on our model of state highway spending, we found a number of 

factors that are systematically related to state highway spending and, in 

turn, a state’s level of effort to fund highway from state resources.1

 Perhaps 

most importantly, more federal highway aid is associated with less state 

effort to fund highways from state resources once other factors related to 

state spending are taken into account. Our conservative estimate of grant 

substitution suggests that about half the increase in federal highway grants 

is used to reduce states’ level of highway spending effort.

Increases in federal grant funding for nonhighway purposes, such as health, 

education, and welfare, are also associated with reduced effort on the part 

of states to fund highways. Based on our model of state highway spending, 

we found that states with a higher percentage of their nonhighway 

spending funded by federal grants reduced their effort to fund highways, 

presumably, to provide matching funds for programs like Medicaid, which 

is an open-ended matching program.

In addition to federal grants, we found two cost factors that are 

systematically related to states’ levels of highway spending effort, other 

things being equal. States with large highway networks, as measured by the 

number of highway lane miles, systematically spend more per capita. 

Presumably, a larger road network is more expensive to maintain and 

states must therefore devote a larger share of their funding capacity to 

maintaining their highway network. In addition, we found that colder than 

average temperatures, as measured by heating degree days, are associated 

with higher state spending, suggesting that colder weather creates more 

wear and tear on the highways and hence the need for states to make a 

greater spending effort to maintain their highway network, other things 

being equal.

Finally, we found that high per capita income states make less effort than 

states with lower incomes. This result is, perhaps, not surprising since the 

same effective tax rate, (level of effort), generates more revenues in high1

Since level of effort is defined as state spending relative to funding capacity, factors that are 

shown to be directly related to state spending are also directly related to a state’s level of 

effort. In an earlier report, GAO, Trends in Federal and State Capital Investment in 

Highways, (GAO-03-744R, June 18, 2003), we reported considerable variation among states 

in the level of highway funding effort that persisted over the entire period of our study from 

1982 through 2000. In addition, we reported wide movement in the states’ relative levels of 

effort over time. That is, some states making a low level of effort in the 1980s ranked above 

average in the 1990s and vice versa.
Appendix III

State Characteristics Associated with States’ 

Level of Effort to Fund Highways from State 

Resources

Page 88 GAO-04-802 Federal-Aid Highways

income states than in states with lower incomes. Thus, the same level of 

highway spending can be funded with less effort in high-income states and 

low-income states compensate by undertaking a greater effort to fund 

highways from state resources.2

 

2

The relationship between income and level of effort is complex. We found that low-income 

states make a greater level of effort to fund highway from state resources compared to 

higher income states. At the same time, there was no evidence of a difference in the 

spending response of high- and low-income states to a change in income, that is, the squared 

term from the substitution model was not statistically significant. In our model of state 

highway spending, we found that the fixed effect coefficients were negatively related to 

state per capita income, indicating that high-income states make less effort than states with 

lower income. In addition to the fixed effects, we also included per capita income and per 

capita income squared in our model to test whether the spending response to changes in 

income differed between high- and low-income states. As reported in appendix II we found 

no evidence of a differential response. 
Page 89 GAO-04-802 Federal-Aid Highways

Appendix IV

Program Options Designed to Reduce 

Substitution ApendxiIV

One program option that could be designed to reduce substitution would 

be to modify the matching requirement to leverage additional state highway 

spending. While the use of matching requirements as an economic tool is 

designed to leverage additional spending, the federal-aid highway 

program’s current matching requirements, which typically call for 20 

percent state funding and 80 percent federal funding of eligible projects, 

permit substitution because most states’ highway funding is already higher 

than 20 percent of their total highway funds. The matching requirement, 

therefore, does not provide states with an incentive to increase or even 

maintain their level of funding in order to receive additional federal funds. 

Instead, states are free to substitute federal funds for funds they would 

have spent from their own resources and to use their own funds in other 

ways. 

For the matching requirement to leverage additional state spending, the 

states’ matching portion would have to be set high enough so that states 

would not receive additional federal funds without spending beyond what 

they would have otherwise spent without additional federal assistance. 

This objective cannot be perfectly achieved because models of 

substitution, like any models, produce estimates that are subject to 

uncertainty, and there is no way to objectively determine with certainty 

what states would have spent in the absence of increased federal funding. 

However, the likelihood that increased federal funding will leverage 

additional state highway spending can be achieved in several ways.

Increase State Matching 

Requirements

The most direct approach would be to change the current 80 percent 

federal/20 percent state match ratio to a matching ratio closer to the 45 

percent federal/55 percent state division of funding in fiscal year 2002. This 

would likely mean that some states (those whose spending is less than 60 

percent of combined federal and state spending) would be required to 

increase their highway spending in order to qualify for any increased 

federal funding, while other states whose spending is already over 60 

percent of combined federal and state spending would not have to increase 

or maintain their spending in order to receive increased federal funds.

Increasing the required state match from 20 percent to 60 percent might 

require a few states, whose state highway funding levels are currently a 

comparatively small proportion of their total highway spending, to more 

than double their current level of highway spending to avoid losing federal 

funds. If increases of this magnitude were deemed too extreme, a more 

moderate increase in the state match could be established. For example, 
Appendix IV

Program Options Designed to Reduce 

Substitution

Page 90 GAO-04-802 Federal-Aid Highways

raising the state matching share to 40 percent instead of 60 percent would 

require smaller funding increases in states whose state and local spending 

is currently a smaller proportion of the total highway spending, but it 

would also reduce the number of states that would be required to increase 

their level of funding in response to increased federal funding.

Another drawback of simply increasing state matching requirements is that 

even substantial increases in the requirements (raising the required state 

match from 20 percent to 60 percent) would not be likely to leverage 

additional state spending in all states. An alternative that would increase 

the likelihood of leveraging additional state spending in all states would be 

to continue with the 80 percent federal/20 percent state matching ratio but 

stipulate that only state spending in excess of what the state had spent for 

highways in an appropriate base time period be counted against its federal 

matching requirement. This approach has the advantage of maintaining the 

current 20 percent state matching rate, yet provides a leveraging incentive 

in all states rather than in only those states with below average spending. 

However, it might have the effect of making it easier for those states that 

were not spending much in the base time period to increase their spending 

and receive increased federal funds than it would be for those states whose 

spending was already high.

Modify Funding Formulas to 

Reward State Highway 

Funding Effort

Another approach that would reduce substitution by creating an incentive 

for states to increase their own highway spending would be to directly link 

the level of federal highway aid to each state’s level of highway funding 

effort. This link could be achieved by setting aside a fixed percentage of 

formula grant funding to be distributed in accordance with states’ highway 

funding efforts. As stated in the text, to avoid penalizing low income states, 

each state’s highway funding effort could be defined as the state’s highway 

spending compared to some measure of the state’s taxing capacity. There 

are a variety of indicators that could serve as a measure of states’ funding 

capacity. The most comprehensive that is available annually is Total 

Taxable Resources (TTR), which is produced annually by the Department 

of the Treasury and used to distribute substance and mental health block 

grants. Less comprehensive measures would include Gross State Product 

(GSP) and Personal Income (PI), both published annually by the 

Department of Commerce. 

This approach could be implemented in a variety of ways. One approach 

would be to compare each state’s funding effort to the average effort of all 

states. If, for example, $100 per capita were set aside and distributed in this 
Appendix IV

Program Options Designed to Reduce 

Substitution

Page 91 GAO-04-802 Federal-Aid Highways

way, states whose highway spending efforts were above the average 

spending effort would receive funding proportionally above the $100 per 

capita average and states whose effort was below the average spending 

effort would receive funding proportionally below the $100 per capita 

average. 

Initially, those states with an above-average highway funding effort would 

be rewarded with higher per capita funding, and those states with a belowaverage highway funding effort would be penalized with lower per capita 

funding. In following years, each state’s highway spending effort would 

continue to be compared to the average state highway spending effort, so 

that states whose funding effort rose relative to the national average would 

automatically be rewarded with higher per capita funding, while states 

whose effort fell relative to the national average would automatically be 

penalized. Distributing the set aside in this fashion would, in effect, put all 

states in competition with one another, automatically rewarding states 

whose effort rose compared to the national average and penalizing states 

whose effort fell compared to the national average. 

The approach just described would reward those states whose funding 

effort is currently high and penalize those whose effort is currently low. 

However, this approach could be modified to avoid rewarding or penalizing 

states based on their current level of effort. Instead, the linking of federal 

funds to state effort could be based only on future changes in each state’s 

level of highway funding effort. In this approach, each state’s highway 

funding effort would be compared to its own effort during an initial time 

period, such as the year (or an appropriate average of years) prior to 

initiation of the set aside. For example, all states could be awarded the 

same per capita grant amount in the first year of the set-aside program. 

Then, in future years, each state’s funding effort would be compared to its 

own funding effort in the first year of the set aside program and adjusted 

accordingly. Each state whose funding effort increased compared to the 

initial base year would receive an increase in federal funding proportionate 

to the increase in its own spending. Such an approach would, in effect, put 
Appendix IV

Program Options Designed to Reduce 

Substitution

Page 92 GAO-04-802 Federal-Aid Highways

each state in competition with the effort it made in the base period.1 If both 

approaches to rewarding state highway funding effort were deemed 

desirable, a combination of the two approaches could be employed. The 

strength of the incentive would depend on the amount of total formula 

funding distributed through the set aside program; the greater the amount 

of funding distributed in this manner, the larger the financial consequences 

to states of changing their level of highway funding effort. 

Introduce a State 

Maintenance of Effort 

Requirement

If, instead of seeking to stimulate additional state spending on highways, 

the goal of federal policy makers is for federal grants to supplement state 

spending on highways, then instituting a maintenance-of-effort (MOE) 

provision may be a more appropriate approach. MOE provisions require 

states to maintain existing levels of state spending on an aided program as 

a condition of receiving federal funds. As a tool, MOE requirements are 

designed not to stimulate additional state spending but to guard against 

grant substitution so that increased federal spending will supplement 

rather than replace states’ own spending. 

As with matching requirements, this objective cannot be perfectly achieved 

because models of substitution, like any models, produce estimates that 

are subject to uncertainty and there is no way to objectively determine with 

certainty what states would have spent in the absence of increased federal 

funding. However, the likelihood that increased federal funding will not be 

used as a substitute for state spending can be strengthened if MOE 

requirements are designed appropriately. In previous work, we concluded 

that, to be effective, MOE provisions should define a minimum level of 

state spending effort that can be objectively quantified based on reasonably 

current expenditures on the aided activity. 2

 Adjusting the MOE 

requirement for inflation in program costs would ensure the minimum 

spending level is maintained when measured in inflation adjusted dollars. 

1

To work in the way described here, funding for the set-aside program, as described in the 

text, would have to be adjusted annually to reflect the overall change in states’ funding 

effort. If states’ overall level of state effort remained unchanged from year-to-year, funding 

for the set-aside program would not have to change in order to ensure that states whose 

effort increased were rewarded and states whose effort declined were penalized. If, 

however, the overall average state effort increased, funding for the set-aside program would 

have to increase proportionally to ensure that all states with increased effort were rewarded 

and those with declining effort were penalized. 

2

GAO, Proposed Changes in Federal Matching and Maintenance of Effort Requirements 

for State and Local Governments, GAO/GGD-81-7, December 23, 1980.
Appendix IV

Program Options Designed to Reduce 

Substitution

Page 93 GAO-04-802 Federal-Aid Highways

This could be achieved by defining a state’s base spending level as the 

amount spent per year during a recent historical period and then adjusting 

that base spending level for inflation. 

One drawback of an MOE provision is that basing it on historical spending 

period could result in a base spending period for the MOE provision that 

represents an unusually high spending level for some states, effectively 

locking them into continued high spending in future years. This could be 

ameliorated however by establishing waivers for states that are able to 

demonstrate that spending in the base period chosen is unusually high, to 

allow a more “typical” spending level for purposes of the MOE provision.

Developing an indicator of state highway spending effort to link federal 

funding to state spending or establishing a state’s base spending level to 

design an MOE requirement would require careful consideration. Among 

other issues, in defining these indicators, consideration would have to be 

given to whether to measure:

• Capital expenditures for highways or capital plus maintenance 

spending;

• Expenditures on all state roads or for federal-aid roads only;

• State government expenditures only, or spending by state and local 

governments;

• Total expenditures, or expenditures normalized on a per capita, per lane 

mile, or other basis.

In addition, an indicator of state funding effort or a state’s base funding 

level for an MOE provision should, to the extent possible, be established by 

measuring spending levels that are typical rather than unusually high or 

low. Highway capital expenditures in a state can increase or decrease 

dramatically from year to year and may be unusually high or low for variety 

of reasons (e.g., Utah’s unusually high spending during preparations for the 

2002 Winter Olympics, or a state particularly hard hit by recession that 

drops spending below its usual effort). To some extent, such factors can be 

taken into account by defining a state’s funding effort or base level of 

spending for an MOE provision using multi-year averages so that such 

unique circumstances are averaged out. 
Page 94 GAO-04-802 Federal-Aid Highways

Appendix V

GAO Contacts and Staff Acknowledgments ApendxiV

GAO Contacts JayEtta Z. Hecker (202) 512-2834

Steve Cohen (202) 512-4864

Jerry Fastrup (202) 512-7211

Staff 

Acknowledgments

In addition to those named above, Jay Cherlow, Catherine Colwell, Gregory 

Dybalski, Edda Emmanuelli-Perez, Scott Farrow, Donald Kittler, Alex 

Lawrence, Sara Ann Moessbauer, Robert Parker, Paul Posner, Teresa 

Renner, Stacey Thompson, and Alwynne Wilbur made key contributions to 

this report.

(544074)
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