State Infrastructure Banks and Intergovernmental Subsidies for Local Transportation Investment

r 2008 Public Financial Publications, Inc.

State Infrastructure Banks and IntergovernmentalSubsidies for Local Transportation Investment

JUITA-ELENA YUSUF and GAO LIU

This study reviews State Infrastructure Banks (SIBs) as an innovative financingmechanism for federal and state governments to support transportationfinancing for local governments, and determines the cost savings realized bylocal governments from receiving SIB loans rather than financing through themunicipal bond market. The study finds that SIBs provide a mechanism throughwhich local governments receive subsidized loans for their transportationinvestments. With the Ohio SIB, localities realized average borrowing costsavings between 34 and 184 basis points. Under the worst- and best-casescenarios, 83 and 98 percent of projects, respectively, benefited from lowerborrowing costs.

INTRODUCTION

State Infrastructure Banks (SIBs), state-run revolving loan funds that offer financial

assistance for transportation projects mainly through low interest loans, have developed

rapidly since the initial pilot program was set up in 1996. As of September 2006, 32 states

(and Puerto Rico) had active loan programs through their SIBs, having issued 520 loans,

for a total loan amount of over $6 billion. An additional six states have established SIBs

but have not yet put them into operation.

Given such popularity and the reauthorization for SIBs in the 2005 federal trans-

portation legislation, research on the operation and effectiveness of SIBs is both nec-

essary and timely. To date, no study, to the best of the authors’ knowledge, has

compared the borrowing costs through SIBs and through alternative financing methods.

In response, the present research has a dual purpose. First, it introduces and reviews

SIBs as an innovative financing mechanism for allowing federal and state governments to

assist local governments in securing funding for transportation projects. As such, SIBs

Wie Yusuf is an assistant professor in the Department of Urban Studies and Public Administration at Old

Dominion University, 2096 Constant Hall, Norfolk, VA 23529. She can be reached at [email protected].

Gao Liu is a Ph.D. candidate at the Martin School of Public Policy and Administration, University of

Kentucky, 419 Patterson Office Tower, Lexington, KY 40506. He can be reached at [email protected].

Yusuf and Liu / State Infrastructure Banks and Intergovernmental Subsidies 71

i:/BWUS/PBAF/917/[email protected]

provide an alternative source of financing for local governments other than conventional

municipal debt financing. Second, it estimates the cost savings realized by local gov-

ernments from receiving SIB loans. The cost savingsFthe interest rate spread between

SIB loans and municipal bondsFrepresent an intergovernmental subsidy provided by

state and federal governments.

Using data consisting of loans made by the Ohio SIB and municipal bonds issued by

entities in Ohio, the study’s analysis suggests that SIBs do in fact provide a mechanism

through which states can subsidize local transportation investments. Specifically the

estimates show that, by obtaining SIB financing, localities realized average borrowing

cost savings of between 34 and 184 basis points. Between 83 and 98 percent of the

projects receiving SIB loans benefited from lower borrowing costs than if they had

obtained debt financing through the municipal bond market.

This paper begins with a background discussion of SIBs, including their conceptual

roots and development. The next section reviews the role of SIBs in local transportation

finance and how SIBs could potentially lead to borrowing cost savings for localities.1

After a discussion of the loan policies of the Ohio SIB, the comparison of the borrowing

costs of Ohio SIB loans and those of the alternative municipal bond market is presented.

The comparison of these interest rates uses a two-step research approach, which involves

(1) developing a predictive model to estimate the interest rate for the non-SIB financing

alternative of debt financing using municipal bonds and (2) calculating the differential

interest rate or spread between SIB loans and municipal bonds. This second step de-

termines the borrowing cost savings from using SIB loans and the size of subsidies for

local transportation projects. The paper concludes with a discussion of policy implica-

tions, limitations of the study and suggestions for future research.

BACKGROUND OF SIB

Conceptual Roots

In the late 1970s and 1980s local government capacity to meet infrastructure spending

needs became increasingly constrained. In this environment, state bond banks became

popular as a way to provide local governments with cost effective access to financial

markets by combining multiple small issues into large issues. ‘‘State financial interme-

diation through a bond bank mechanism or loan program as a response to . . . con-

straints should facilitate funding of local capital needs.’’2

1. SIBs are required to offer loans at prevailing or below market rates, but the SIB is free to decide

which market rate to adopt. Depending on this definition of the market rate (and how SIB loan rates are

determined), there may or may not be borrowing cost savings for local governments.

2. Nancy P. Humphrey and Diane R. Maurice, ‘‘Infrastructure Bond Bank Initiatives: Policy Impli-

cations and Credit Concerns,’’ Public Budgeting and Finance 6, no. 3 (1986): 38–56.

Public Budgeting & Finance / Winter 200872

A few individuals and organizations took the bond bank concept a step farther,

leading to the development of infrastructure banks. Henton and Waldhorn,3 for exam-

ple, discussed a proposal for a national public works bank into which the federal gov-

ernment and the states would each contribute $1 billion. Peterson4 discussed a solution

to the infrastructure investment and financing dilemma based on a federal infrastructure

bank that would be linked to a series of state infrastructure banks. These banks would

make below-market rate loans for infrastructure repairs and other infrastructure pro-

jects, and upon loan repayment, funds would be recycled for other projects through

additional loans.

The SIB concept is also closely related to two other key institutional arrangements: (1)

state revolving funds (SRFs) for wastewater treatment facilities and (2) state-level trans-

portation revolving funds. SIBs were developed as a combination of different elements of

each of these precursor institutional arrangements, with the goal being to create a pool of

fundsFthat could additionally be leveraged by borrowing from the credit marketFfor

providing more flexible and revolving local government financing options at costs lower

than would be available individually to local governmental units.

Development

SIBs were first proposed under the U.S. Department of Transportation (DOT) FY 1996

budget request and became a reality with the SIB pilot program authorized through

Section 350 of the National Highway System Designation Act of 1995 (NHS Act). The

NHS Act authorized the U.S. DOT to select up to 10 states to participate in the initial

pilot program and to enter into cooperative agreements with the Federal Highway

Administration (FHWA) and/or Federal Transit Administration for the capitalization of

their SIBs with federal-aid funds.

In 1996, supplemental SIB legislation, as part of the DOT FY 1997 Appropriations

Act, provided $150 million General Fund appropriations for SIB capitalization and

enabled additional qualified states to participate in the SIB pilot program. Following this

eligibility expansion, 38 states plus the Commonwealth of Puerto Rico were selected to

participate in the SIB pilot program. As of June 2005, only six of these 38 states did not

have active SIBs. Among those without active SIBS, four have not participated due to

the inability to pass state-enabling legislation and two states have deobligated funds.

Figure 1 shows the total number of SIB loan agreements and the total loan agreement

dollar amounts from 1997 to 2006, both growing more than 100-fold over the 11- year

period.

3. Douglas C. Henton and Steven A. Waldhorn, ‘‘The Future of Urban Public Works: New Ways of

Doing Business,’’ in Perspectives on Urban Infrastructure, ed. Royce Hanson (Washington, DC: National

Academy Press, 1984).

4. George E. Peterson, ‘‘Financing the Nation’s Infrastructure Requirements,’’ in Perspectives on Urban

Infrastructure, ed. Royce Hanson (Washington, DC: National Academy Press, 1984).


The Transportation Equity Act for the 21st Century (TEA-21) extended the SIB pilot

program by allowing four states (California, Florida, Missouri, and Rhode Island) to

enter into cooperative agreements with the U.S. DOT to further capitalize their SIBs

with federal-aid funds provided in FY 1998 through FY 2003.

The 2005 Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy

for Users (SAFETEA-LU) legislation established a new SIB program under which all

states and U.S. territories were authorized to enter into cooperative agreements with the

U.S. DOT to establish SIBs. SIBs would be eligible to be capitalized with federal trans-

portation funds authorized for FY 2005 through FY 2009.

SIBS AND LOCAL TRANSPORTATION FINANCE

The primary role of SIBs in local transportation financing is to lower the overall cost of

capital for specific transportation projects and thus reduce the overall cost of the pro-

ject.5 This can be achieved in three ways. First, SIBs can offer low interest or interest-free

loans, which could be used to partially or fully replace taxable or even tax-exempt debt.

FIGURE 1

Growth in SIB Loans, 1997–2006a

aData not available for 1999

Source: Federal Highway Administration Innovative Finance website

(http://www.fhwa.dot.gov/innovativefinance/sib.htm)

5. U.S. Department of Transportation, An Evaluation of the U.S. Department of Transportation State

Infrastructure Bank Pilot Program. SIB Report to Congress. 1997 [report online]; available from: http://

www.fhwa.dot.gov/innovativeFinance/contoc.htm: accessed July 16, 2007.


Second, SIBs can offer credit enhancements that allow transportation projects to attain

higher ratings for their debt issues. Finally, SIBs can assist smaller jurisdictions and

infrequent borrowers in obtaining debt financing by pooling bond issues, thus spreading

the risk and reducing the overall cost of capital.

In most cases, the savings that can be attributed to SIBs are derived from reductions in

borrowing interest costs. This is particularly true given the current state of SIB practice,

which has tended to focus on providing low interest loans rather than other types of

credit assistance. Accordingly, this study only examines the impact on borrowing costs

of SIB loans.

The expectation of savings from reductions in interest costs are borne out of previous

studies which analyzed the impact of environmental SRFs and state bond banks. So-

lano,6 for example, determined that state bond banks netted an average interest savings

of 79 basis points. Similarly, a study by the Council of Infrastructure Financing

Authorities7 found that interest rates for SRF loans averaged 300 basis points below the

20-year General Obligation (GO) Bond Index.

This study focuses on SIB loan interest rates, because they determine the extent to

which the federal government and states are subsidizing local government investments in

transportation. This emphasis on the below-market nature of SIB loan interest rates is

also relevant, because, as argued by Holcombe,8 the General Accounting Office9 and the

DOT in its SIB Review,10 the interest rate is the most critical element for revolving loan

funds. ‘‘SIB financing terms should provide a distinct advantage when compared with

private lender rates and terms, otherwise applicants will prefer to use less expensive

sources of capital.’’11 However, SIBs must be cautious in setting interest rates, as the

corpus of funds could be damaged and become insufficient for continued lending.

SIB Interest Rates and Potential Cost Savings

Under their cooperative agreements with the federal government, states have fairly wide

discretion in operating their SIB programs. The authorizing federal legislation establishes

basic requirements and an overall operating framework for SIBs, but states have the

flexibility to tailor their SIBs to meet their specific transportation needs. The states

establish the application criteria, loan terms including interest rates, and management

6. Paul L. Solano, ‘‘An Appraisal of the Interest Cost Savings of State Bond Banks,’’ Municipal Finance

Journal 25, no. 4 (2005): 13–48.

7. Paul Ladd, Leveraged SRF Programs: A Comparative Review (Washington, DC: Council of Infra-

structure Financing Authorities, 1995).

8. Randall G. Holcombe, ‘‘Revolving Fund Finance: Case of Wastewater Treatment,’’ Public Budgeting

and Finance 12, no. 3 (1992): 50–65.

9. U.S. General Accounting Office, State Infrastructure Banks: A Mechanism to Expand Federal Trans-

portation Financing (Washington, DC, October 1996).

10. U.S. Department of Transportation, State Infrastructure Bank Review (Washington, DC, February

2002).

11. Ibid., 7.


https://www.researchgate.net/publication/229977939_Revolving_Fund_Finance_The_Case_of_Wastewater_Treatment?el=1_x_8&enrichId=rgreq-8a6f33c30675acb6b2bf1fdc4521f368-XXX&enrichSource=Y292ZXJQYWdlOzIyODI2NjUxNTtBUzoxOTYyMTYwODUzMjM3NzhAMTQyMzc5Mjk2ODM0Mg==

https://www.researchgate.net/publication/229977939_Revolving_Fund_Finance_The_Case_of_Wastewater_Treatment?el=1_x_8&enrichId=rgreq-8a6f33c30675acb6b2bf1fdc4521f368-XXX&enrichSource=Y292ZXJQYWdlOzIyODI2NjUxNTtBUzoxOTYyMTYwODUzMjM3NzhAMTQyMzc5Mjk2ODM0Mg==

structure of their SIB loan programs. However, federal requirements dictate that interest

rates be set at or below prevailing rates offered by the U.S. capital markets. Beyond this

requirement, the states are free to adopt any methodology to establish a benchmark U.S.

capital market interest rate and subsequently the SIB interest rate.

According to the U.S. DOT 2002 review of SIBs,12 most SIBs use indexed interest

rates tied to benchmarks that serve as proxies for the prevailing market rates. Examples

of such benchmarks include the prime rate, municipal bond rate indices, or expected

rates of inflation. The Colorado SIB uses the Merrill Lynch Bond Index rate for a seven

to 12 year GO bond, and the Arizona SIB ties the interest rate to Aa municipal bond

rates.13

Three categories of SIB interest rates have been adopted. Some states use fixed interest

rates that apply to the entire life of the loan, while others use floating interest rates. There

are two types of fixed interest rates. While some states vary the interest rate by date of

issue, loan size, and loan terms, others set a standard rate for all loans of a certain size

and term. For example, some states have specific pre-set rates for all loans regardless of

market conditions or loan size. Other states have fixed interest rates that are set at the

time of loan initiation, but are dependent on factors such as market conditions and loan

amount.

Floating interest rates, on the other hand, are used to ensure a stronger link to

prevailing market conditions, as the interest rate is tied to the continuously changing

market rate. The Virginia SIB ties its loan rate to the earnings on an internal trans-

portation trust fund, and the Alaska SIB uses an inflation-adjusted floating interest rate,

ensuring that the real interest rate remains constant.14

While most states offer discounted interest rates (i.e., sub-market interest rates),

the size of the discount or subsidy has not been determined. Interviews with FHWA

officials indicated that the FHWA was not aware of any studies that have estimated the

size of the interest rate advantage offered by SIBs. This gap was further evidenced in the

survey of the literature, which identified very few empirical analyses dealing with SIBs.15

12. Ibid.

13. Ibid.

14. Ibid.

15. As part of this study the authors undertook a survey of the literature to determine the extent to

which SIBs have been investigated. Most of the studies found during this search were government reports

including those by the U.S. Department of Transportation, the General Accounting Office, and the Con-

gressional Budget Office. The authors also conducted a literature search of transportation and infrastruc-

ture-related journals and the relevant public finance journals through EBSCO host and ABI databases. This

survey of the academic literature identified two journal articles on SIBs. These articles are Jay Eungha Ryu,

‘‘Fiscal Impacts of an Innovative Highway Financing Alternative on State Highway Expenditures: The

Case of Federal Assistance Funds in the State Infrastructure Bank (SIB) Programs,’’ Public Works Man-

agement and Policy 11, no. 1 (2006): 33–48; Jay Eungha Ryu, ‘‘Federal Highway Assistance Funds in the

State Infrastructure Bank Programs: Mechanisms, Merits, and Modifications,’’ Public Budgeting and Fi-

nance 27, no. 4 (2007): 43–65.


Ryu16 evaluated the impacts of federal SIB funds on state transportation expenditure.

However, this evaluation did not involve a discussion of cost savings.

Local governments have two primary options to pay for transportation projects. The

first is the pay-as-you-go approach and the second is the debt financing approach. Be-

cause of the lumpiness of investments in transportation capital projects, many local

governments use debt financing for capital projects and pay-as-you-go for maintenance

and repairs. One important goal of this study, beyond providing an overview of SIBs as

an innovative transportation finance mechanism, is to determine the cost savings realized

by local governments from receiving SIB loans rather than obtaining debt financing from

the conventional capital market. In essence, this cost savings, if realized, represents a

subsidy provided by federal and state governments to localities through SIB loans.

THE OHIO SIB

This study uses data from the loan practices of the Ohio SIB, which was established in

1996 as a direct loan program that makes loans to political subdivisions in Ohio for

transportation-related projects. As of September 2006, it had issued 82 loans, repre-

senting 16 percent of the total loans issued by all SIBs. The Ohio SIB has financed the

greatest number of loans made by SIBs, making it an appropriate candidate for this

study.

The Ohio SIB program was originally capitalized with $40 million in state General

Revenue funds, $87 million in federal funds, and $10 million in state motor fuel tax

funds. This program was authorized under the Ohio Revised Code Chapter 5501, for the

purpose of developing transportation facilities throughout Ohio through direct loans and

bond financing. Highway or transit projects eligible under federal code Title XXIII, as

well as aviation, rail, and other intermodal transportation facilities, are eligible for direct

loan funding under the SIB.

This research on SIBs and the possible intergovernmental subsidies provided through

SIBs utilizes data on 53 loans issued by the Ohio SIB between 1998 and 2005. The loan

data were collected from the Ohio SIB annual reports.17 Among these loans, 47 percent

were made to city governments, 36 percent to county governments, and the rest (17%) to

local authorities. Table 1 summarizes characteristics of these loans.

The Ohio SIB loan committee decides the loan interest rate based on the prime rate.

While the loan rate policy is set to be at a maximum of three-quarters of the prime rate,

the actual loan rate has been well below this upper limit. Furthermore, the loan rate has

16. Ryu, ‘‘Fiscal Impacts of an Innovative Highway Financing Alternative’’; Ryu, ‘‘Federal Highway

Assistance Funds.’’

17. The FY 2004, 2005, and 2006 State Infrastructure Bank Annual Financial Reports published by the

Ohio Department of Transportation are available from http://www.dot.state.oh.us/Divisions/Finance/Pages/

StateInfrastructureBank.aspx: accessed October 30, 2007.


not closely followed changes in market interest rates, and has been relatively stable

across time. Table 2 summarizes the Ohio SIB loan rates between 1998 and 2005. While

the range of loan interest rates is from zero to 6 percent, there was only one loan at zero

percent (a one-year loan for a small dollar value) and two loans at 6 percent. The table

also shows that there is some variation in loan interest rates in the early years of the Ohio

SIB, but the loan rate policy beginning 2003 has been to provide all loans at a 3 percent

interest rate. These 3 percent interest rate loans represent 64 percent of all loans in the

sample.

TABLE 2

Summary of Loan Interest Rates

Year Interest rates (%) No. of loans

1998 4.00 3

5.00 1

1999 3.00 1

4.00 1

6.00 1

2000 3.00 1

4.00 1

6.00 1

2001 4.00 2

5.00 1

2002 3.00 2

4.00 2

2003 0 1

2.50 1

3.00 6

2004 3.00 15

2005 3.00 13

TABLE 1

Descriptive Statistics for SIB Loans in the Study Sample (N5 53)

Mean Standard deviation Min Max

Loan interest rate (%) 3.29 0.87 0 6.00

Loan amount ($ million) 2.58 2.71 0.13 11.10

Size of project ($ million) 9.77 11.71 0.25 62.40

Repayment period (years) 9.50 4.53 1.00 25.00

Note: All dollar amounts reported are nominal.


EMPIRICAL ANALYSIS

This section addresses the second goal of the study of determining the cost savings

realized by local governments from receiving SIB loans rather than obtaining financing

from the municipal bond market. Denoting the actual interest rate of the SIB loan as

RSIB and the interest rate from the alternative source (the municipal bond market), had

the municipality gone to the bond market, as Rm, this analysis seeks to determine the

yield spread, DR5Rm�RSIB, where RSIB can be observed from actual SIB borrowing,

but Rm must be predicted.

The empirical analysis involves a two-step approach. The first step develops a pre-

dictive model by regressing the bond interest rate on predictor variables using a sample

of municipal bonds issued by entities in Ohio. Second, the predictive model is then

employed to estimate the municipal bond interest rate, Rm. Given this estimated mu-

nicipal bond interest rate, the spread, DR, is calculated to determine if interest rate cost

savings are realized.

Step 1: Predictive Model for Municipal Bond Interest Rates

To develop the predictive model for the interest rate of municipal bonds (as the alter-

native non-SIB financing source), a sample of bond issues was extracted from SDC

Platinum18 and Bloomberg terminal.19 Bond issues included in the sample satisfied the

following criteria: (1) issued by public entities in Ohio, (2) issued between 1998 and 2005,

(3) not subject to alternative minimum tax (AMT), (4) not for the purpose of refunding

previous outstanding debt, and (5) used fixed coupon rate. These criteria generated a

sample of 286 observations.

This sample is used to estimate the relationship between municipal bond interest rate,

measured as true interest cost (TIC), and explanatory variables. Based on previous

literature,20 TIC can be modeled as a function of market interest rate and characteristics

of the bond issue and issuer type, as indicated in the following equation:

TIC ¼ b0 þ b1ðmarket interest rateÞ þ b2ðbond characteristicsÞ þ b3ðissuer typeÞþ b4ðyear dummyÞ ð1Þ

In the model, market interest rate is measured using the Bond Buyer 20 Index; bond

characteristics comprises a vector of variables that may affect municipal bond interest

18. Source: [TIC and other characteristics of municipal bond issues], SDC Platinum, a Thomson

Financial product, accessed October 2006.

19. Source: [Cash flow information and ratings of municipal bond issues], Bloomberg terminal, a

Bloomberg, L.P. product, accessed March 2008. For issues with missing TICs values from SDC Platinum,

their redemption schedules are extracted from Bloomberg terminal, and their TICs are calculated based on

their cash flows.

20. Jun Peng, ‘‘Do Investors Look beyond Insured Triple-A Rating? An Analysis of Standard & Poor’s

Underlying Ratings,’’ Public Budgeting and Finance 22, no. 3 (2002): 115–131; Solano.


rate; and the issuer type is a set of dummy variables for the type of government issuing

the bond. A description of variables is provided below.

(1) TIC: true interest cost, is the internal rate of return of all series of a bond issue.

(2) BBI20: Bond Buyer 20 Index, provided by the Bond Buyer based on the weekly

average of market yields on 20 municipal bonds maturing in 20 years. The Bond

Buyer 20 Index is a widely accepted benchmark for municipal bond market

interest rates.

(3) Bond characteristics:

a. Ln(amount): the natural logarithm of the par amount (in millions) of a bond issue.

Issue amount is expected to be inversely related with the TIC, because of increasing

economies of scale. However, the relationship is expected to be nonlinear, so the

logarithmic form is used.

b. Ln(maturity): the natural logarithm of the average life (in years) of all series of the

bond. This variable is expected to be positively related to the TIC, as the yield

curve of municipal bond interest rates generally leans upward. Because the rela-

tionship is expected to be nonlinear the logarithmic form is used.

c. GO_bond: a dummy variable for the bond issue being a GO bond. GO bonds are

secured with issuers’ full faith pledge of their tax power, and thus are considered

less risky. As a result, GO bonds have lower interest rates than revenue bonds.

d. Tax-exempt: a dummy variable that is coded as one if the interest of a bond issue is

exempt from federal income tax and zero otherwise. A tax-exempt bond has a lower

interest rate (higher price). Thus, this variable is expected to have a negative sign.

e. Competitive: a dummy variable for the method of sale being via competitive bid. A

negative relationship is expected between competitive bidding and TIC, as the

competition among bidders would increase bond prices and lower the interest costs.

Empirical findings about this relationship, however, are inconclusive.21

f. Callable: a dummy variable indicating that a bond is callable, being coded as one if

the bond is callable and zero otherwise. Because investors may lose interest income

if the bond issuer calls back the bond when the market interest rate is low, they

require a premium for the call option. Thus, it is expected that callable bonds have

higher yields.

g. Credit rating: a set of dummy variables indicating the credit rating assigned by

Standard and Poor’s or Moody’s.22 Credit rating categories are AAA, AA, and A.

Unrated bonds and those bonds rated BBB or lower serve as the reference group for

this set of credit rating dummy variables. Bonds with higher credit ratings are less

risky and thus expected to have lower TICs.

21. See, for example, Paul A. Leonard, ‘‘Competitive Bidding for Municipal Bonds: New Tests of the

Underwriter Search Hypothesis,’’ Municipal Finance Journal 19, no. 4 (1999): 18–37; Mark D. Robbins and

Daehwan Kim, ‘‘Do State Bond Banks Have Cost Advantages for Municipal Bond Issuance?’’ Public

Budgeting and Finance 23, no. 3 (2003): 92–108.

22. No bonds in the sample have letter level split ratings from Standard & Poor’s and Moody’s.


h. Insured: a dummy variable for private bond insurance. A bond that is enhanced by

private bond insurance is coded as one and zero otherwise. Because natural AAA-

rated bonds have lower interest costs than enhanced AAA-rated bonds,23 there

should be a positive relationship between the insured dummy variable and the TIC,

all else being equal.

i. Issue purpose: a set of dummy variables specifying the use of bond proceeds. This

classification follows that of SDC platinum, and includes dummy variables for the

top four largest categories: education, general purpose, transportation, and utility. To

be consistent with the sample of SIB loans, bonds with proceeds for airport-related

purposes are included in the transportation category. The reference group is other

types of bonds, including economic development, industrial development, health

care, multiple family housing, etc. Bonds in these four largest categories have been

found to have lower interest rates, due to their lower risks.24

(4) Issuer type: a set of dummy variables for the type of bond issuer. Dummy vari-

ables for five types of government entities are included in the model: state gov-

ernment, state authority, county, municipality, and local authority. The reference

group for this set of variables is school and special districts. Previous empirical

studies have provided evidence that the market may associate issuer type with a

certain risk level, affecting the risk premium demanded by investors.25

(5) Year dummy: a set of dummy variables representing the year the bond was

issued.

Table 3 provides descriptive statistics for the sample of municipal bonds used to

generate the predictive model. Compared with the pool of SIB loans (see Table 1), the

sample of municipal bond issues has a higher mean repayment period or years to ma-

turity and are issued for larger amounts. However, the years to maturity and issue

amount do contain the range of those in the SIB borrowing sample.

Table 4 presents the regression results for the predictive model. The R2 value suggests

that overall the model is able to explain about 83 percent of the observed variation in

bond interest rates. All coefficients of bond characteristic variables have the expected

signs. Most bond characteristics, with the exception of the GO bond dummy, insured

dummy and ‘‘A’’-rated dummy variables, are statistically significant at the 10 percent or

higher level.

23. Peng.

24. See Michael H. Hopwell and George G. Kaufman, ‘‘Commercial Bank Bidding on Municipal

Revenue Bonds: New Evidence,’’ The Journal of Finance 32, no. 5 (1977): 1647; Peng.

25. See, for example, Earl D. Benson, ‘‘Municipal Issue Interest Cost and Issue Purpose,’’ Municipal

Finance Journal 8, no. 1 (1987): 45–58; Lisa M. Fairchild and Timothy W. Koch, ‘‘The Impact of State

Disclosure Requirements on Municipal Yields,’’ National Tax Journal 5, no. 4 (1998): 733–753; Jun Peng

and Peter F. Brucato, ‘‘Do Competitive-Only Laws Have an Impact on the Borrowing Cost of Municipal

Bonds?’’ Municipal Finance Journal 22, no. 3 (2001): 61–76; Solano.


Step 2: Predicting the Interest Rate Spread between Municipal Bonds and SIB Loans

The model predicted in the previous section is used to estimate the interest rates of the

alternative market offerings for SIB loans, assuming that bonds are issued with similar

characteristics as SIB loans.26 While the values of some independent variables can be

TABLE 3

Descriptive Statistics for the Municipal Bond Sample (N5 286)

Mean Standard deviation Min Max

TIC 4.538 0.935 1.896 8.680

BBI20 5.135 0.431 4.270 6.120

Bond characteristics

Amount (in millions) 29.359 52.516 0.053 513.970

Years to maturity 17.496 7.855 0.748 42.247

GO_bond 0.469 0.500 0 1

Tax-exempt 0.958 0.201 0 1

Callable 0.748 0.435 0 1

Competitive 0.381 0.487 0 1

Insured 0.479 0.500 0 1

Rating

AAA 0.584 0.494 0 1

AA 0.252 0.435 0 1

A 0.084 0.278 0 1

Issue purpose

Education 0.238 0.426 0 1

Transportation 0.171 0.377 0 1

Utility 0.122 0.328 0 1

General purpose 0.329 0.471 0 1

Issuer type

State government 0.042 0.201 0 1

State authority 0.049 0.216 0 1

County 0.143 0.351 0 1

Municipality 0.451 0.498 0 1

Local authority 0.028 0.165 0 1

26. Selection bias is present if unmeasured factors affecting the use of SIB and RSIB are correlated with

unmeasured factors affecting Rm, or if Rm directly causes RSIB. This study controls for a number of factors

affecting both Rm and RSIB and assumes that the remaining correlation is small. Note that, as discussed in

the previous section on the predictive Rm model, over 83 percent of the variance of Rm is explained by the

model and that RSIB is often constrained by operating rules such as fixed rates for a period of time.

Therefore, it is plausible that remaining unobserved factors are uncorrelated.


determined based on the available information on SIB borrowings, others must be made

based on certain assumptions.

The values of issue amount, years to maturity, and issuer type are all known from the

SIB loan data. All SIB bonds are assumed to be callable, as the Ohio SIB allows early

retirement of its outstanding loans. The Ohio SIB requires collateral or credit enhance-

ment for funded transportation projects, so it is assumed that these infrastructure pro-

jects would acquire credit enhancement if they were financed through municipal bonds.

Thus, in the prediction, all SIB-funded projects are assumed to be insured. The insured

status automatically grants an AAA rating to the bonds. The assumed AAA rating is

consistent with the previous rating of borrowers in the sample, because out of the 20

TABLE4

Regression Results for the Predictive Model of Municipal Bond Interest Rate (Rm)

TIC (N5 286) Coefficient Standard error T P value

BBI20 1.076 0.116 9.300 0.000

Bond characteristics

Ln(Amount) � 0.040 0.018 � 2.180 0.030

Ln(maturity) 0.406 0.058 6.990 0.000

GO_bond � 0.050 0.055 � 0.910 0.366

Tax-exempt � 1.307 0.142 � 9.210 0.000

Callable 0.428 0.087 4.940 0.000

Competitive � 0.142 0.065 � 2.170 0.031

Insured 0.061 0.091 0.680 0.499

Rating

AAA � 0.745 0.162 � 4.590 0.000

AA � 0.676 0.151 � 4.490 0.000

A � 0.187 0.171 � 1.090 0.275

Issue purpose

Education � 0.677 0.132 � 5.140 0.000

Transportation � 0.540 0.102 � 5.300 0.000

Utility � 0.550 0.100 � 5.500 0.000

General � 0.501 0.093 � 5.370 0.000

Issuer type

State government 0.043 0.155 0.280 0.780

State authority � 0.146 0.159 � 0.920 0.360

County � 0.243 0.136 � 1.780 0.076

Municipality � 0.261 0.127 � 2.060 0.040

Local authority � 0.466 0.192 � 2.430 0.016

Constant 0.486 0.680 0.710 0.476

Adjusted R2 0.831

Year dummyffip


government entities in the SIB loan sample that were rated by Standard & Poor’s or

Moody’s only two were rated below AAA.

Making assumptions about the other three variables, however, is more problematic.

For example, there is insufficient information to determine whether an issue would be a

GO bond or a revenue bond. In Ohio, issuing a local GO bond, which is secured by the

pledge of the tax power and the credit of the local government, requires the authorization

by a majority of all qualified voters.27 Predicting whether a proposition to finance a

transportation project with a GO bond could pass the needed local referendum is difficult.

The tax status of municipal bonds is regulated by a body of complicated rules, re-

strictions, and Internal Revenue Service guidelines.28 While interest earnings from GO

bonds are always exempt from federal income tax, those from revenue bonds may be

subject to regular federal income tax or AMT. Determining whether a revenue bond is

taxable typically requires bond counsel expertise and detailed information about the

project and bond issue.29

There is also no theoretical underpinning for determining which bond sale method

local governments would use in issuing their municipal bonds. Unlike some states, Ohio

does not require its municipal bonds be sold in a specific way. Issuers can choose either

competitive bidding or negotiated sale.Scenario analysis. Accounting for unobserved bond characteristics that cannot be easily

assumed involves a sensitivity or scenario analysis of best- and worst-case scenarios thatencompass the different bond type, tax status, and sale method assumptions. The as-sumptions underpinning the two scenarios are summarized in Table 5.

The worst-case scenario encompasses assumptions associated with generating the lowestmunicipal bond interest rate, and therefore the smallest interest rate yield spread betweenmunicipal bonds and SIB loans. Under this scenario, the assumptions involve municipalbonds issued as tax-exempt GO bonds and sold competitively. The best-case scenario, onthe other hand, involves assumptions that generate the highest possible municipal bondinterest rate, and subsequently the largest interest rate spread. The municipal bonds areassumed to be issued as taxable revenue bonds on a negotiated sale basis.

Interest rate spread ðD ~RÞ. With the dependent variable values discussed above, thealternative interest rates of SIB-funded projects in the municipal bond market,

_Rm,

27. James M. Poterba and Kim S. Rueben, Fiscal Rules and State Borrowing Costs: Evidence from

California and Other States (San Francisco: Public Policy Institute of California, 1999).

28. T. J. Atwood, ‘‘Implicit Taxes: Evidence from Taxable, AMT, and Tax-exempt State and Local

Government Bond Yields,’’ Journal of the American Taxation Association 25, no. 1 (2003): 1–20.

29. The tax exempt status of revenue bonds first depends on whether or not the projects tied to the

bonds can pass the private activity test. If they pass the test, then the bonds will be categorized as private

activity bonds and their interests may consequently be taxable. A private activity bond is subject to regular

federal income tax if it fails to meet some requirements regarding the use of bond proceeds, volume,

maturity, etc. A private activity bond is subject to AMT, with some exceptions, if it meets all these

requirements. For more information, see Bartley W. Hildreth and Kurt C. Zorn, ‘‘The Evolution of the

State and Local Government Municipal Debt Market over the Past Quarter Century,’’ Public Budgeting

and Finance 25, no. 4S (2005): 127–153.


are predicted. Given the predicted municipal bond interest rates and the observed SIBloan rates, the interest rate spread between the two can be calculated (see Table 6). For theentire sample, the average spread was 34 basis points for the worst-case scenarioðD ~R ¼ R̂m � RSIB ¼ 3:630� 3:292 ¼ 0:338Þ, while for the best-case scenario the averagespread was 184 basis points ðD ~R ¼ 5:128� 3:292 ¼ 1:836Þ. Therefore, borrowing costsavings ranges from 34 basis points at the low end to 184 basis points at the high end.

Table 6 presents the descriptive summary for instances where debt financing results in ahigher alternative bond market interest rate compared with the SIB loan rate, representingsituations where a cost savings is realized. Under the worst-case scenario, 44 (about 83%)infrastructure projects would have saved on interest costs through SIB loans. On average,they were able to save 55 basis points, compared with financing through the alternativemunicipal bond market. The savings is more pronounced under the best-case scenario, inwhich all but one SIB loan had a lower interest rate than the alternative financing methodand saved about 188 basis points on average.

Table 6 also summarizes those instances where the SIB loan rate was higher than thepredicted municipal bond interest rate, and therefore no subsidies were realized. Under theworst-case scenario, nine SIB-funded transportation projects would have resulted in alower borrowing cost if the local governments had chosen to finance through the municipalbond market instead. With the alternative financing method, on average they would havea saving of 69 basis points in interest rate over the SIB loan rate. Under the best-casescenario, only one SIB loan had a higher interest rate than its alternative financing method.Financing through the municipal bond market instead of the SIB loan would have savedabout 27 basis points.

T-tests indicate that the SIB loan rate is significantly lower than the alternative municipalbond borrowing rate in both scenarios (see Table 6). Thus, financing transportation pro-jects through SIB borrowing does save local governments in terms of borrowing costs. Thissuggests that the SIB program does, in fact, represent an intergovernmental transfer fromthe federal and state governments to local governments for transportation investment.

Several comments must be made about the interest savings determined in this study. Thisstudy does not consider transactions cost savings from issuing bonds in the municipal bondmarket or in the instances where the local governments receiving the loans do not havewell-established credit ratings or lack experience in capital financing. These issuance costsand other costs related to the debt burden, while not being factored into this study’s costsavings, do play a role in the decision by local entities of which financing method to use.This might explain why some local governments make what may appear to be suboptimal

TABLE5

Assumptions Underpinning the Best- and Worst-Case Scenarios

Best case

(highest interest rate spread)

Worst case

(lowest interest rate spread)

Bond type Revenue bond General obligation bond

Tax-exempt status Taxable Tax-exempt

Sales method Negotiated sale Competitive bidding


financing choices by using SIB loans with higher interest rates than municipal bonds. Inthis study, under the worst-case scenario, in 17 percent of the cases SIB loan rates werehigher than municipal bond interest rates. That the local government would obtain fi-nancing via SIB loans rather than through the municipal bond market could be explainedby considering factors such as high bond issuance costs, lack of bond market experience, orlack of debt capacity.

CONCLUSION AND POLICY IMPLICATIONS

SIBs were developed to serve as a financing mechanism through which federal and state

governments can provide localities with access to lower cost borrowing. This study

provides evidence that they are successful in achieving this purpose. By making below-

TABLE 6

Interest Rates and Interest Rate Spreads under Different Scenarios

Variable Observations Mean Standard deviation Min Max

Whole sample

Worst-case scenario R̂m 53 3.630 0.603 1.984 5.368

RSIB 53 3.292 0.874 0.000 6.000

D ~R 53 0.338 0.663 � 1.769 2.368

H0 : D ~R)0

t5 2.400 Pr(T4t)5 0.00

Best-case scenario R̂m 53 5.128 0.603 3.483 6.867

RSIB 53 3.292 0.874 0.000 6.000

D ~R 53 1.836 0.663 � 0.270 3.867

H0 : D ~R)0

t5 10.731 Pr(T4t)5 0.00

Observations with D ~R > 0 (observations with savings by SIB financing)


RSIB 44 3.034 0.575 0.000 4.000

D ~R 44 0.546 0.468 0.024 2.368

Best-case scenario R̂m 52 5.117 0.603 3.483 6.867

RSIB 52 3.240 0.795 0.000 6.000

D ~R 52 1.877 0.600 0.516 3.867

Observations with D ~R < 0 (observations with no savings by SIB financing)


RSIB 9 4.556 1.014 3.000 6.000

D ~R 9 � 0.684 0.514 � 1.769 � 0.043

Best-case scenario R̂m 1 5.730 . 5.730 5.730

RSIB 1 6.000 . 6.000 6.000

D ~R 1 � 0.270 . � 0.270 � 0.270


market loans to local governments, SIBs are able to provide indirect subsidies to the

localities receiving loans. The empirical analysis of loans made by the Ohio SIB suggests

that, for most local level transportation projects, SIB financing represents potentially

significant cost savings over debt financing through the municipal bond market.

Policy Implications

While this study’s analysis determined that SIBs can and do offer borrowing cost sav-

ings, the extent of this savings depends on how SIB loan rates are determined. In Ohio,

loan rates are required by policy to be at most three-fourths of the prime rate. However,

actual loan rates were consistently set at much lower than this maximum level and rarely

varied according to project type and level of risk, indicating that there is little pricing of

loans according to risk.30 This raises the question of whether this policy is a wise strategy

for the Ohio SIB, and if so what are the trade-offs of such a policy? The fixed rate

structure simplifies the administration of the SIB, particularly when the SIB lacks the

expertise needed to assess risk and incorporate measures of risk into the interest rate or

when such risk assessment is not cost effective. However, this policy could potentially

damage the revolving nature of SIB funds. When riskier loans are not compensated for

with higher interest rates, the Ohio SIB loan policy of a fixed rate structure discriminates

against less risky projects and potentially reduces the corpus of funds available for future

loans.

Another important question is whether the Ohio SIB is targeting the right transpor-

tation projects. With a policy that assigns a fixed interest rate regardless of risk, the SIB

advantages higher risk projects, resulting in adverse selection. SIB loans become more

attractive to high-risk borrowers who may otherwise face higher borrowing costs or who

may not be able to raise capital through alternative means.

Limitations of the Study

This study provides only a conservative estimate of the cost savings associated with SIB

loans. This limitation is attributed to two factors. First, the study examines only the

interest rate savings resulting from SIB loans. However, given the financing alternative of

issuing bonds in the municipal bond market, SIB loans are unencumbered by significant

transaction costs, as loan applications are not as extensive as those required for bond

issuances, and typically do not involve costs associated with legal counsel, credit rating

reviews, insurance premiums, and the like. For example, borrowers with a relatively

low natural credit rating would also pay an insurance premium in exchange for credit

30. To test that the loan interest rates are not priced according to risk or other characteristics of the

loan, borrower, or project being funded by the loan, we regressed the loan interest rate on characteristics of

the loan, borrower, and project. None of these variables were statistically significant in the regression

model, providing evidence that the loan interest rate is invariant to the type of project and the associated

level of risk.


enhancement and an AAA rating.31 This premium is not included in the analysis and

thus the results underestimate the actual spread between SIB loan rates and the costs to

the issuer. In addition, this study’s cost savings do not include any measures of the

financial advantages of SIB loans as an alternative source of funding for communities

that have reached their debt capacity or debt limits.

Second, selection bias, while not posing significant problems for the analysis, also

contributes to underestimation of the cost savings. As discussed earlier, the data suggest

that the bond sample and the SIB loan sample are different in some respects. For

instance, local governments with higher borrowing needs and longer-term borrowing

plans tend to elect bonds over SIB loans (see Tables 1 and 3). While loan amount and

years to maturity have been controlled for in the prediction model, other unobserved

factors such as the project’s underlying risk may introduce bias. It is reasonable to expect

that those who are the most creditworthy and needing to raise large amounts of capital

would be most likely to finance through the municipal bond market. Those facing the

highest costs on the bond market, on the other hand, would be more inclined to finance

using SIB loans. The result is a conservative prediction of Rm relative to the actual Rm,

producing a predicted DR that is less than the actual DR.

Future Research

SIBs were originally created with multiple goals in mind, including accelerating trans-

portation project completion, increasing state and local investments in transportation,

and increasing private investment in transportation infrastructure.32 Future research

could investigate the extent to which SIBs, through their loans and other financing

activities, have achieved these goals. For example, an examination of the leveraging

effect of SIB loans on private investment in transportation could determine the extent to

which SIB loans and the emphasis on private sector contributions in repaying loans have

actually stimulated private participation in public infrastructure investments.

31. Kidwell, Sorensen, and Wachowicz observed that for GO bonds issued from 1975 through 1980 by

MBIA’s optional bidding program, one dollar par value insurance costs 10.0 basis points for Aa-rated

issues and 12.7 basis points for Baa-rated issues, per year. Smith and Harper documented that in the early

1990s, insured Florida bonds included an insurance premium of around 6.6 basis points per dollar par value

every year. See David S. Kidwell, Eric H. Sorensen, and John M. Wachowicz, ‘‘Estimating the Signaling

Benefits of Debt Insurance: The Case of Municipal Bonds,’’ Journal of Financial and Quantitative Analysis

22, no. 3 (1987): 299; Stephen D. Smith and Richard B. Harper, ‘‘Private Insurance of Public Debt:

Another Look at the Costs and Benefits of Municipal Insurance,’’ Economic ReviewFFederal Reserve Bank

of Atlanta 78, no. 5 (1993): 27–38.

32. According to the 1997 U.S. DOT report to Congress, SIBs were intended to achieve 4 goals: (1)

accelerating project construction and attracting additional funds for transportation projects, (2) lowering

the debt burden of local governments for pursuing transportation projects, (3) improving local access to

external debt financing, and (4) reducing the cost of capital for local governments. See U.S. Department of

Transportation, An Evaluation of the U.S. Department of Transportation State Infrastructure Bank Pilot

ProgramFSIB Report to Congress (Washington, DC, 1997); available from: http://www.fhwa.dot.gov/

innovativeFinance/contoc.htm: accessed July 16, 2007.


Future research could also investigate the question of how institutional factors of the

SIBs matter and how states should balance the subsidy with due diligence to the public

purse. Such a study would contribute needed knowledge about trade-offs associated with

SIB funding for local transportation projects and would have interesting implications for

the design and administration of SIBs.

NOTES

We would like to thank Lenahan O’Connell of the Kentucky Transportation Center who provided

the seeds for the research idea behind this study. Melinda Lawrence of the Ohio State Infrastructure

Bank was also of great assistance in clarifying the technical details of the Ohio SIB loan policies and

practices. This study also benefited from comments and suggestions from Merl Hackbart and Dwight

Denison, in addition to two anonymous reviewers.


Documents

State Infrastructure Banks and Intergovernmental Subsidies for Local Transportation Investment