the effects of fiscal transparency on municipal bond issuances · criteria. the lower the fti is,...

25

The Effects of Fiscal Transparency on Municipal Bond Issuances Tiankai Wang, Patricia Shields, and Yangmei Wang*

This study examines the infl uence of institutional mechanisms of state fi scal transpar-ency on municipal bond issuance borrowing costs. It tests two hypotheses drawn from David Heald’s (2003) tradeoff: (1) fi scal transparency brings the value of “sunlight” and (2) the risk of “overexposure.” The hypotheses are tested using the fi scal transparency index (FTI), a measure widely used in political science, and true interest costs (TICs) for a sample of states (1986–2012). The results reveal that initially, as fi scal transparency increases, borrowing costs fall. There is a point, however, where additional transparency leads to increased borrowing costs.

INTRODUCTION

This study examines the relationship between fi scal transparency and borrowing costs, using primary-market state-level municipal bond issuance data. In theory, transparency decreases transaction costs,

which are the issuance borrowing costs in the primary market, and refl ects trade prices in the secondary market (Harris and Piwowar, 2006). Fiscal transparency has two dimensions: information disclosure and institutional arrangements (Kopits and Craig, 1998, p. 1). The Municipal Finance Journal has devoted considerable attention to the information disclosure dimensions of fi scal transparency (Pope, 2013; Robbins and Simonsen, 2010; Scott et al., 2006).

In addition, scholars have examined the effect of information disclosure on borrowing costs. For example, in the stock market, fi nancial disclosure

*Tiankai Wang is an assistant professor in the Health Information Management Department at Texas State University, San Marcos, TX. He can be reached by email at [email protected]. Patricia Shields is a professor in the Political Science Department at Texas State University. She can be reached at [email protected]. Yangmei Wang is an instructor in the Accounting/MIS Department at the Dillard School of Business, Midwestern State University, Wichita Falls, TX. She can be reached at [email protected].

26 MUNICIPAL FINANCE JOURNAL

is negatively related to the cost of capital (Dhaliwal et al., 2009; Leuz and Wysocki, 2008). In the municipal bond market, information disclosure signifi cantly reduces the trade prices in the secondary market (Green et al., 2010; Schultz, 2012). Further, accessibility of fi scal information disclo-sure, such as online budget reports, can decrease issuers’ borrowing costs (Wang, 2012).

The study of institutional arrangements, the second dimension of fi scal transparency, is less well developed. Institutional arrangements include the administrative policies, processes, and regulations designed to enhance information disclosure. These institutional arrangements can be more or less transparent. For example, fi scal information can be found in multiple budget appropriation bills, making monitoring more diffi cult and thus diminishing transparency. Transparency is also infl uenced by the frequency of the budget cycle. Biannual budgets disseminate information less often and are thus less transparent. This study focuses on the neglected infl uence of institutional transparency on borrowing costs.

INSTITUTIONAL TRANSPARENCY AND POLICY OUTCOMES

Although no studies examine the infl uence of institutional fi scal trans-parency on state borrowing costs, institutional fi scal transparency has been linked to different kinds of governmental effectiveness such as scale of government (Alt et al., 2002), per capita income (Baldrich, 2005) and debt ratio (Alesina et al., 1999). Within this context, David Heald (2003) pro-poses a colorful metaphor to describe the relationship between fi scal trans-parency and effective government. He draws upon Supreme Court Justice Brandeis’ (1865–1941) famous remark: “Sunlight is the most powerful of disinfectants” (Heald, 2003, p. 725). That is, transparency is a powerful stimulus for ethical behavior and more effective governance. Heald (2003, p. 729) proposes a tradeoff between “the value of sunlight” and “danger of overexposure.” In other words, there is a point where more transparency can reduce governmental effectiveness.

The “value of sunlight” has been widely studied. For example, Baldrich (2005, pp. 7, 13) found a positive relationship between fi scal transparency and per capita income. He notes that economies operate within a structure set by government. Transparency reduces the likelihood of corruption, which adversely affects economic activity. At the state level, Geraats (2000) and Faust and Svensson (2002) argue that fi scal transparency reduces the col-lective action problem because it increases credibility, thereby improving investment payoffs and stabilizing the economy. At the international level, the Organisation for Economic Co-operation and Development (OECD) studies (2002, 2003) indicate that international investment fl ows are higher

FISCAL TRANSPARENCY AND MUNICIPAL BOND ISSUANCES 27

1 “Closed-ended” appropriations are the opposite of “open-ended” appropriations, i.e., published fi gures are fi xed without subsequent updates. Hence, they are closer to ultimate outcomes (Alt et al., 2002).

and that investments tend to be of higher quality in countries with more transparent policy environments. Alt and Lassen’s (2006a, 2006b) studies show that fi scal transparency reduces public debt and the negative effects of tax increases. Finally, Bernoth and Wolff (2008) demonstrate that fi scal transparency lowers risk premiums in government borrowing by reducing uncertainty in European Union countries.

Although the positive infl uence of fi scal transparency is well understood and documented, Heald offers the intriguing suggestion that there are lim-its or negative impacts (overexposure) to transparency. Many scholars offer arguments consistent with Heald’s conjecture.

First, the data collection requirements of fi scal transparency can lead to “extra administrative expenses” (Glennerster and Shin, 2008, p. 206).

Second, revenue transparency can also be counterproductive because it leads to increases in wasteful spending (Gavazza and Lizzeri, 2009), and higher transparency produces “overexposure,” which leads to a loss in effec-tiveness through high levels of taxpayer transaction costs (Heald, 2003).

Third, the more transparent closed-ended appropriations decrease bud-get fl exibility. 1 The reduced fl exibility makes governments less respon-sive and thereby reduces effectiveness (Alt et al., 2002). In addition, the decreased budget fl exibility can infl uence the timeliness of an issuance, which impairs investors’ confi dence.

Finally, “too much” transparency increases the political risk of unsustain-able policies due to increasing power sharing in government (Glennerster and Shin, 2008; Kopits and Craig, 1998). Hood (2001) stressed that trans-parency obstructs the formation of political coalitions in circumstances where there are seemingly irreconcilable confl icts. Thus, transparency of the political system may enhance disputes that undermine effectiveness. Therefore, the effect of fi scal transparency depends on when and in what situations it is employed (Andersen and Nielsen, 2010).

RESEARCH QUESTION AND HYPOTHESES Heald’s (2003) conjecture is graphically illustrated in Figure 1. Line

A 0 -A

1 -A

2 represents an optimistic view—that more transparency leads to

greater governmental effectiveness. Alternatively, line A 0 -A

1 -A

3 repre-

sents Heald’s sunlight/overexposure tradeoff. Initially, the positive infl u-ence of fi scal transparency dominates. Eventually, however, the benefi ts of transparency peak and then decline. Scholars such as Alt et al., (2006) and Bastida and Benito (2007) agree with the optimal fi scal transparency


2 The term “municipal bonds” is also used for state government bonds. In this article, all “municipal bonds” are state-issued government bonds.

opinion. Unfortunately, an empirical study has yet to provide supportive evidence.

We apply Heald’s hypotheses to the case of state municipal bond costs and ask how fi scal transparency infl uences state borrowing costs. We propose alternative hypotheses, which take into account the two views depicted in Figure 1. The fi rst hypothesis represents the optimistic model. The second hypothesis represents Heald’s sunlight/overexposure tradeoff .

• Hypothesis 1 (line A 0 -A

1 -A

2 ): Higher fi scal transparency results in

lower municipal bond issuance cost.

• Hypothesis 2 (line A 0 -A

1 -A

3 ): Initially, when fi scal transparency in-

creases, borrowing costs fall; however, beyond an optimal point, higher transparency leads to increased borrowing costs.

METHODOLOGY In the introduction, we distinguished between fi scal transparency as dis-

closure and institutional arrangements. Our goal is to test the above hypoth-eses using institutional transparency as our independent variable and state municipal borrowing costs as the dependent measure. 2 Although measures of borrowing costs are well established, institutional fi scal transparency is a concept, by its nature, that is less easily quantifi ed and isolated from

Figure 1: Relationship Between Transparency and Effectiveness

Effectiveness

A2

A1A3

A0

T0 T1 Transparency

Source: Adapted from Heald (2003).


other policies. Previous studies on fi scal transparency, such as Alesina et al. (1999) and Baldrich (2005) surveyed Latin American budget directors about their budget processes. Their “nation-oriented” measures are not applicable at the subnational level. Further, measures operationalized as surveys are dependent on the respondents’ knowledge and recall and thus suffer from reliability threats.

Alt et al. (2002) developed an institutional fi scal transparency index (FTI) for the 50 states using data on budget processes available from the publica-tions of the National Association of State Budget Offi cers (NASBO) and the National Conference of State Legislatures (NCSL). They then road-tested the measure using the FTI to study the effects of fi scal transparency on political outcomes, such as the scale of government and gubernatorial approval (Alt et al., 2002; 2006; Alt and Lowry, 2010).

Each component of the nine-item FTI scale measures aspects of budget process transparency. The items in the scale are coded 0 or 1, with 1 indi-cating more transparency. For example, if a state’s budget revenue esti-mates are binding, the process is considered more transparent (and coded 1) because misleading the public would be more costly. Box 1 presents the components of the scale and their coding.

Table 1 applies the index for the 50 states for the period from 1986 through 2012. During the 2000s, Alabama’s FTI score is 2 because only two items in Alabama’s budget process qualify as “more transparency.” In Table 1, we can see that the national average FTI is 4.01, which means that, on average, the states qualify about four items out of the total nine criteria. The lower the FTI is, such as 1 for Maine in 2008, the lower fi s-cal transparency the state has. High values on the FTI (8 for Delaware in 2008) indicate high levels of fi scal transparency. Please note that no state qualifi es on all nine criteria.

Before the FTI is applied, we test its theoretical connection to municipal bond borrowing costs. Reviewing the nine items constructing the FTI (Box 1), we can fi nd the connections. As Ang and Green (2011, p. 5) note:

Information in the municipal bond market is limited, decentralized, and non-standard. . . . Reducing information-gathering and verifi ca-tion costs helps to level the playing fi eld for all participants, encour-aging participation by a broad range of investors.

FTI items 2 and 3 make it easier for the public to access information and hence reduce information gathering costs. FTI items 1 and 4 through 9 measure transparency policies and processes ensuring information acces-sibility and integrity, thus reducing verifi cation costs.

Furthermore, the FTI also measures the potential hindrances of trans-parency. Divided governments may induce disarray in public fi nances (Prud’homme, 1995), tend to have larger defi cits, and hence be subject


to costlier fi nancing (Bohn and Inman, 1996; Lowry and Alt, 2001). FTI items 5 and 7 depict governmental power-sharing and control arrange-ments that infl uence transparency. In summary, the FTI incorporates many processes or institutional arrangements that ensure better information

Box 1: Fiscal Transparency Index Components The nine items, which are considered by Alt et al. (2002) in develop-

ing an FTI for each state, include:

1. Is the budget reported on a Generally Accepted Accounting Prac-tice (GAAP) basis? (Yes = more transparent, because shared lan-guage facilitates communication);

2. Are there multi-year expenditure forecasts? (Yes = more trans-parent, because more information about plans and the expected consequences of action are disseminated);

3. What is the frequency of the budget cycle (Annual = more trans-parent than biennial, because more frequent action means more up-to-date information);

4. Are the revenue estimates binding? (Yes = more transparent, because binding estimates increase the costliness of being misleading);

5. Does the executive branch have primary responsibility for the rev-enue forecast? (No = more transparent, because the legislature, which consists of many elected offi cials, is less likely to be mis-leading or manipulative);

6. Are there multiple appropriations bills (No = more transparent, because a single location facilitates monitoring);

7. Does a nonpartisan staff write appropriations bills? (Yes = more transpar-ent, because these staff have less partisan incentive to be misleading);

8. Can the legislature pass open-ended appropriations? (No = more trans-parent, because published fi gures will be closer to ultimate outcomes);

9. Does the budget require published performance measure? (Yes = more transparent, because these create more explicit standards and information for judging politicians’ actions).

Source: Alt et al. (2002). Notes: More transparency is coded 1, otherwise 0. The range of scale is 0

to nine. Information about GAAP, multi-year expenditure forecasts, budget cycle, revenue binding, responsibility for the revenue forecast, and perfor-mance measurement requirement is available from the NASBO report “Budget Processes in the States.” The other information is available in the NCSL report “Legislative Budget Procedure.”


Tabl

e 1:

Sam

ple

of S

tate

FTI

Sco

res

and

Stat

e Av

erag

e TI

C (F

Y 19

86 th

roug

h 20

12)

Stat

eFT

I Sco

res

Avg.

TIC

1986

–198

819

89–1

991

1992

–199

419

95–1

996

1997

–199

819

99–2

001

2002

–200

720

08–2

012

Avg.

FTI

Alab

ama

33

33

32

22

2.54

4.68

28

Alas

ka3

34

33

33

23.

043.

6204

Arizo

na3

34

33

33

33.

13n/

a

Arka

nsas

55

55

55

54

4.92

4.32

03

Calif

orni

a5

54

44

43

44

5.31

52

Colo

rado

66

66

66

66

63.

6427

Conn

ectic

ut6

65

55

44

44.

795.

3012

Delaw

are

77

78

88

88

7.63

4.49

87

Flor

ida

00

11

11

14

1n/

a

Geor

gia

77

77

78

88

7.46

5.37

19

Hawa

ii3

33

33

33

33

5.51

43

Idah

o3

34

42

22

32.

75n/

a

Illin

ois

44

44

44

55

4.33

5.28

59

Indi

ana

22

11

23

34

2.33

n/a

Iowa

55

56

66

66

5.63

n/a

Kans

as4

44

44

44

44

n/a

Kent

ucky

33

33

34

43

3.38

n/a

(Con

tinu

ed)

32 MUNICIPAL FINANCE JOURNALTa

ble

1: S

ampl

e of

Sta

te F

TI S

core

s an

d St

ate

Aver

age

TIC

(FY

1986

thro

ugh

2012

) (Co

ntin

ued

)Lo

uisia

na3

33

44

44

43.

635.

3272

Main

e1

11

12

22

11.

465.

5158

Mar

yland

44

44

44

44

44.

5167

Mas

sach

usett

s3

33

66

66

54.

794.

983

Mich

igan

44

55

55

55

4.75

4.61

3

Min

neso

ta2

22

22

22

32.

084.

8123

Miss

issip

pi3

24

56

66

64.

795.

838

Miss

ouri

44

44

44

45

4.08

5.24

66

Mon

tana

44

44

44

44

45.

1265

Nebr

aska

21

11

22

22

1.67

n/a

Neva

da4

54

44

55

54.

584.

3663

New

Ham

pshi

re1

12

22

22

21.

754.

6759

New

Jers

ey7

77

77

77

77

6.56

15

New

Mex

ico4

43

34

56

64.

584.

3137

New

York

55

44

44

45

4.33

5.42

07

North

Car

olin

a4

45

55

44

64.

46n/

a

North

Dak

ota

44

43

32

23

3n/

a

Ohio

11

11

22

14

1.46

n/a

Oklah

oma

55

44

44

55

4.58

n/a

Oreg

on1

11

22

22

21.

635.

5806


Penn

sylva

nia

55

55

55

55

55.

4127

Rhod

e Isla

nd7

77

77

77

77

5.25

32

Sout

h Ca

rolin

a4

44

43

33

53.

635.

2409

Sout

h Da

kota

55

55

56

66

5.46

n/a

Tenn

esse

e3

33

33

23

32.

885.

8284

Texa

s5

54

44

44

44.

255.

4098

Utah

76

67

77

76

6.67

4.41

46

Verm

ont

22

22

33

34

2.63

4.79

96

Virg

inia

33

33

44

34

3.29

5.05

62

Was

hing

ton

44

44

55

56

4.63

5.38

97

Wes

t Virg

inia

44

45

56

66

5.08

5.37

11

Wisc

onsin

11

11

22

33

1.88

6.08

62

Wyo

min

g5

55

66

66

65.

63n/

a

Natio

nal A

vera

ge3.

83.

763.

783.

944.

084.

124.

164.

444.

015.

3901

Notes

: In

this

pape

r, th

e stat

es’ F

TI sc

ores

are c

ompi

led ac

cord

ing

to th

e eig

ht “B

udge

t Pro

cess

es” r

epor

ts iss

ued

by th

e NAS

BO si

nce 1

986

and

one “

Legi

slativ

e Bud

get P

roce

dure

s” re

port

issue

d by

th

e NC

SL in

199

8. T

he a

vera

ge F

TI is

the

aver

age

of th

e 26

indi

ces

of fi

scal

trans

pare

ncy

from

198

6 to

201

1. T

he a

vera

ge F

TI is

use

d on

ly fo

r gen

eral

analy

sis, n

ot in

the

regr

essio

n m

odels

. Ave

rage

TI

C is

the

weig

hted

arit

hmeti

c m

ean;

n/a

mea

ns th

at th

e sta

te di

d no

t iss

ue G

O bo

nds

durin

g th

e sa

mpl

e pe

riod,

eith

er b

ecau

se th

e sta

te’s

laws

did

not a

utho

rize

GO b

ond

issua

nce

or th

e GO

bon

ds

cap

had

been

reac

hed.


accessibility and integrity (budget processes and power sharing of govern-ment). The FTI is thus well suited to test hypotheses about the infl uence of state institutional transparency on bond issuances.

The FTI is a worthwhile measure of institutional arrangement fi scal transparency because it is accessible, comprehensive, and objective. In addition, it has stood up to scholarly scrutiny in multiple publications in political science (Alt et al., 2002; 2006; Alt and Lowry, 2010). We are taking an existing, tested measure of fi scal transparency and applying it to bond issuances.

Comparatively, it is easy to select a measure for municipal borrowing costs. In municipal bond issuances, the two most popular cost-measurement methods are the net interest cost (NIC) and the true interest cost (TIC). The TIC is proposed by the Bond Market Association (Temel, 2001) and is now the industry standard for expressing the borrowing cost associated with municipal bond issuances (Robbins et al., 2000). We thus employ the TIC as a measure of borrowing costs.

There are two types of municipal bonds: revenue bonds and general obligation (GO) bonds. This study considers only GO bonds issued by state governments because of their direct relation to state fi scal perfor-mance instead of project performance. By doing so, no bond-type variable or bond-purpose variable is required.

STUDY DATA SET The study’s total data sample includes all 562 issuances of state GO

bonds from 1986 to 2012, excluding 33 issuances whose maturities are less than 10 years because short-term notes have very different investment criteria than long-term bonds. This sample period was chosen because of the serious impact of the Tax Reform Act of 1986 on the municipal bond market. Most commercial banks were out of the municipal bond market because commercial banks were unable to take advantage of the tax-exempt status of municipal bonds (Park, 1997). This situation resulted in a signifi cant fall in municipal bond issuances. The municipal bond markets were quite different pre- and post-1986.

CONTROL VARIABLES Previous empirical studies, which examine state municipal bond issu-

ance, have not revealed a consistent set of predictors. There is no unan-imous regression model in municipal bond studies. Models in previous studies vary among four variables (Ewing, 2002), fi ve variables (Filling et al., 2002), 10 variables (Kessel, 1971), 28 variables (Kriz, 2000), and 37 variables (Peng and Brucato, 2003). Controversy over model specifi cation is problematic here. Our goal is not to argue for the absolute best model


3 The White test equals to 144.0, with a p value of 0.0083, while the Breusch Pagan test equals to 56.98, with a p value that is less than 0.0001.

4 In the fi xed effects models, state and issuing year dummy variables are added. None of the dummy variables achieved statistical signifi cance.

but, rather, to explore transparency. As a result, we build from Simonsen and Robbins’ (1996) “standard model” (Marlowe, 2009) of municipal bond cost, which includes size (amount), maturity, call option, sale method, rat-ings, and baseline index. Some variables in the standard model are omitted (such as experience, which has been proven to be not signifi cant in previ-ous studies) or replaced. For example, “baseline index” (Oregon 20-year bond index) has been replaced with “risk-free rate” and “uncertainty of the risk-free rate,” because the models are applicable to the national market, rather than the Oregon market. In addition to the variables in the standard model, some control variables have been added to the model, including insurance, unemployment rate, population, and per capital income (PCI). Finally, the tested target, FTI, is added to complete the model construction. Therefore, the multivariate regression models are:

• (H1) TIC = β 0 + β

1 RiskFree + β

2 Uncertainty + β

3 Amount + β

4 Maturity +

β 5 CallOption + β

6 Insured + β

7 Unemployment + β

8 Population + β

9 PCI

+ β 10

Aaa + β 11

Aa + β 12

A + β 13

CompetitiveSale + β 14

FTI + ε; and

• (H2) TIC = β 0 + β

1 RiskFree + β

2 Uncertainty + β

3 Amount + β

4 Maturity +

β 5 CallOption + β

6 Insured + β

7 Unemployment + β

8 Population + β

9 PCI +

β 10

Aaa + β 11

Aa + β 12

A + β 13

CompetitiveSale + β 14

FTI + β 15

FTI 2 + ε.

The control variables in the above regression models are successfully applied in studying the relationship between online disclosure and munici-pal borrowing cost (Wang, 2012; see Tables 2 and 3).

EMPIRICAL RESULTS We tested the hypotheses fi rst with an ordinary least squares (OLS)

model and found evidence of heteroscedasticity, using the Breusch-Pagan test and the White test. 3 To correct heteroscedasticity, fi xed effects 4 and heteroscedasticity-consistent covariance matrix (HCCM; Long and Ervin, 2000) are tested respectively. The outputs of the models appear in Table 4. The control variables’ outcome matches the expected sign in Table 2.

Both models fi xed the issue of heteroscedasticity, and their outcomes are similar. An evaluation by Long and Ervin (2000) suggests that HCCM is better, because the use of HCCM “allows a researcher to easily avoid the adverse effects of heteroscedasticity even when nothing is known about the form of heteroscedasticity” (p. 217).The empirical results are robust across all three models.


ANALYSIS AND IMPLICATIONS OF FINDINGS The empirical outputs of the fi scal transparency index express an inter-

esting result. When it is assumed that fi scal transparency has a linear relationship with the borrowing cost, the output shows a positive corre-lation between the two. This contradicts both theories proposed by the scholars. When the square of the FTI is included in the model, the results

Table 2: List of Variables and Sources Used to Gather Data

Variable Description Source Expected Sign

Dependent Variable

TIC True interest cost The Bond Buyer

Independent Variables

FTI Fiscal transparency index Alt et al. (2002) ?

FTI2 Square of FTI Calculated from FTI ?

Control Variables

RiskFree Risk free interest rate The Center for Research in Security Price (CRSP) +

UncertaintyStandard deviation of risk-free rate in eight weeks before date of bond issuance

Calculated from CRSP +

Amount Issuance amount of bonds (in log) Calculated from The Bond Buyer _

Maturity Year to maturity of bonds The Bond Buyer +

CallOptionDummy variable for callable bonds. Issuance with call option equals to 1.

The Bond Buyer +

Insured Dummy variable for insured bonds. Insured issuance equals to 1. The Bond Buyer –

Unemployment Unemployment rate U.S. Census, 1986–2012 +

Population Population U.S. Census, 1986–2012 –

PCI Per capita Income http://www.infoplease.com/ipa/A0104652.html –

Aaa Dummy variable for bond credit rating as Aaa http://www.moodys.com –

Aa Dummy variable for bond credit rating as Aa http://www.moodys.com –

A Dummy variable for bond credit rating as A http://www.moodys.com +

— “Not Rated” rating is eliminated to create rating dummies

CompetitiveSale Sale method dummy. Competi-tive sale equals to 1 The Bond Buyer –


Table 3: Sample Descriptive StatisticsVariable Mean Std. Dev. Min. Max.

Dependent variable

TIC 5.39 1.11 1.54 8.89

Independent variables

FTI 4.24 1.84 1 8

FTI2 21.10 16.42 1 64

Control variables

RiskFree 9.75E-04 2.90E-04 1.79E-04 2.14 E-03

Uncertainty 9.03E-05 7.06E-05 5.18E-07 5.08 E-04

Amount (in millions) 184.93 232.18 1 2,050

Maturity 21.07 5.76 10 41

CallOption 0.81 0.39 0 1

Insured 0.18 0.39 0 1

Unemployment 5.14 1.33 2.20 14.00

Population (in thousands) 8,158.31 8,635.63 594 35,484

PCI 119,516.50 1,678,07.46 14,041 30,4703,68

Aaa 0.33 0.42 0 1

Aa 0.29 0.45 0 1

A 0.05 0.21 0 1

CompetitiveSale 0.26 0.43 0 1

confi rm the alternative theory on transparency—that there exists an opti-mal point in fi scal transparency. That confi rms Hypothesis 2 (line A

0 -A

1 -

A 3 in Figure 1). Moreover, because the estimate of the square of the FTI is positive, the

optimal point is a minimal position. By setting ∂TIC/∂FTI = 0, we can get the optimal FTI values when the TIC reaches the minimal value as 3.48 from the OLS model, 3.79 from the fi xed effects model, and 4.70 from the HCCM model. Thus, depending on which model is used, when the fi scal transparency index is between 3 and 5, municipalities will issue bonds at the lowest cost possible. Although the estimated effects vary somewhat, the overall fi nding is robust across models. The relationship is plotted in Figure 2. In the following discussion, the optimal FTI value from the HCCM model, 4.7, is used to present the results.

This result confi rms the alternative theory on transparency and effective-ness, but it would be premature to draw an oversimplifi ed conclusion. It would fi rst be necessary to determine if the quadratic relationship is valid.

38 MUNICIPAL FINANCE JOURNALTa

ble

4: R

egre

ssio

n M

odel

s Ou

tput

s (O

bser

vatio

n nu

mbe

r = 5

62)

Varia

ble

OLS

(Poo

led

Mod

el)

Fixe

d Ef

fect

sHC

CM

Hypo

thes

is 1

Hypo

thes

is 2

Hy

poth

esis

1Hy

poth

esis

2

Hypo

thes

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petiti

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47

Notes

: Fig

ures

in p

aren

thes

es ar

e t-v

alues

; lev

el of

sign

ifi ca

nce (

two-

tail):

* p

< 0.

10; *

* p <

.005

; ***

p <

0.0

1; #

p <

0.0

001.

HCC

M is

the H

etero

sced

astic

ity-C

onsis

tent C

ovar

iance

Matr

ix pr

opos

ed

by L

ong

and

Ervin

(200

0) to

solve

the p

robl

em o

f hete

rosc

edas

ticity

in p

anel

data.

The

re ar

e fou

r mod

els in

HCC

M: H

C0, H

C1, H

C2, a

nd H

C3. I

n th

is pa

per,

all fo

ur m

odels

wer

e run

, but

onl

y the

HC3

re

sult

was r

epor

ted in

the t

able

abov

e, be

caus

e “HC

3 wo

rks w

ell” (

Long

and

Ervin

, 200

0, p

. 217

) and

“for

N =

250

, all

tests

have

nea

rly id

entic

al siz

e pro

perti

es” (

p. 2

20).


Next, a better explanation of the relationship and implications would be helpful for practitioners.

The quadratic relationship between the TIC and the FTI could be valid. Such a relationship matches the alternative theory on “transparency and effectiveness.” Indeed, states with lower FTI scores have to pay higher borrowing costs in municipal bond issuances. For example, Maine’s aver-age FTI is 1.46, and its TIC of 5.52 is higher than the national average TIC of 5.39. On the other end of the curve, higher FTI scores also mean higher borrowing costs. An example that stands out the most is New Jer-sey, whose FTI score has been as high as 7. Municipal bonds issued by New Jersey bear the highest TIC, 6.56, in the country. As the alternative theory suggests, states with FTI scores in the middle range (4.7 in the HCCM output) enjoy a lower borrowing cost. After excluding those states that do not issue GO bonds, seven states’ average FTI scores are between 4.5 and 4.9. Six out of the seven states’ average TICs are lower than the national average.

The result may have implications for states with higher than the national average TICs and lower than the optimal FTI. The result suggests that the reason for high borrowing costs in those states can be their low fi scal transparency. Therefore, increasing fi scal transparency may lower the state borrowing cost.

Reviewing the FTI items, we fi nd that it is not an easy task to improve the FTI score for each individual state because most items are institutional and diffi cult to amend. Some items, however, may be more easily changed, such as publishing performance measures in budgets and following the GAAP rules. Performance measurement has been an available and widely accepted tool in the administrative toolbox. For example, Tennessee holds

Figure 2: Relationship Between FTI and TIC

TIC

0 1 2 3 4 5 6 7 8 FTI


an FTI score of 2.88, which is lower than the optimal score, while its aver-age TIC is 5.8284, which is higher than the national average. The Ten-nessee state budget does not require published performance measures but can be amended to do so. In fact, Tennessee’s state government has used performance data in its Agency Strategic Plans (Bredesen, 2008). Requir-ing published performance measures can easily increase Tennessee’s FTI score from 3 to 4 and may lower its borrowing costs.

Oregon and Wisconsin face a different situation. Both have low FTI scores and high TIC rates, but their budget reports require published per-formance measures. To increase their FTI scores and lower their borrow-ing costs, they can consider adopting GAAP rules in budget preparation. Adopting GAAP rules is more complicated than publishing performance measures but is still feasible.

Another explanation for the quadratic relationship shown in Figure 2 is that it is a temporary relationship. For example, New Jersey has a reputa-tion as the most corrupt state in the United States (Wang, 2003). As part of a government reform effort, the New Jersey government became more open to the public and tried to compensate for its bad reputation. Indeed, New Jersey’s FTI increased according to Alt’s items, but its bad reputa-tion did not improve. This suggests that government reform alone cannot address New Jersey’s fi scal situation and that New Jersey municipal bonds are still prejudiced by underwriters.

An anomaly in the relationship is that some states with high FTI scores enjoy a lower borrowing cost. For instance, Delaware has an FTI score of 7.63, and its average TIC is 4.4987. Heald (2003, p. 728) states that “the rela-tionship between transparency and effectiveness may change through time.” Therefore, it is reasonable to believe that higher fi scal transparency ultimately benefi ts a state. In that case, the implication is clear to all states. Because higher fi scal transparency ultimately lowers the borrowing cost, in the long run all states with low values on the FTI should consider enacting policies that will raise their level of fi scal transparency consistent with the FTI.

One additional issue that relates to fi scal transparency measurement needs to be addressed. There are two assumptions beneath Alt’s measure-ment: (1) each of the components of his method has the same weight and (2) different components are perfect substitutes. In other words, all items are implicitly the same in terms of the overall index. Another disadvantage of such a design is that it results in a discrete index. Fiscal transparency can also be expressed as a continuous index such as the index in www.citizenaccess.org .

Attempting to use the FTI in assessing state municipal bond issuance is a challenge with undeniable limitations. However, the FTI by Alt et al. is the only index designed for the state level and also tested by previous studies. When a better fi scal transparency measurement becomes avail-


able, scholars can retest the relationship between fi scal transparency and municipal bond issuance cost.

CONCLUSION This paper’s main fi nding is suggestive but by no means conclusive. Alt

et al.’s FTI explores an interesting effect. When the FTI is considered alone in the regression model, it contradicts widely held beliefs. For example, the results show that higher fi scal transparency results in higher borrowing cost. However, further studies suggest that the index has a quadratic relationship with the borrowing cost in the GO municipal bond market. As a result, medium fi scal transparency provides the lowest borrowing cost while both high and low fi scal transparencies result in higher borrowing costs.

This study suggests that there may be limits to the value of transpar-ency, at least as it relates to the cost of bond issues. The empirical results are consistent with Heald’s sunlight/overexposure tradeoff theory on fi scal transparency. We found evidence of an optimal level of fi scal transpar-ency. However, although these results support an optimal transparency theory, they do not ensure that the optimal theory will hold over multiple and diverse empirical tests. The empirical study of fi scal transparency at the state level is inchoate in both theory and practice. How best to measure fi scal transparency and how fi scal transparency infl uences borrowing costs are controversial questions. We expect that empirical data will guide fi scal transparency institutions toward a more “sunlit” road instead of providing excuses to hide information. Therefore, determining how to quantify and value fi scal transparency deserves further study.

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