Fiscal Rules in Recessions: Evidence from the American States

Article

Fiscal Rules inRecessions:Evidence from theAmerican States

Sounman Hong1

AbstractThis study explores the impact of balanced-budget rules on states’ fiscal pol-icy outcomes and tests whether this impact depends on the political andeconomic environments in light of the American states’ experience from2004 to 2010. The findings suggest that (1) budget rules are more bindingin recessions as compared with ‘‘normal’’ times; (2) the impact of the ruledepends on the political environment, especially on the party identity of thegovernor; (3) a divided government influences the rule’s impact, particularlywhen one party controls the governorship and another controls thelegislature; and (4) states’ responses, as measured by total budget cuts, tounexpected revenue shocks (such as unexpected decreases in tax revenue)tend to be larger than states’ responses to unexpected expenditure shocks.

Keywordsfiscal policy, state government, economic crisis, balanced-budget rule

1College of Social Sciences, Yonsei University, Seoul, Korea

Corresponding Author:

Sounman Hong, College of Social Sciences, Yonsei University, Room 113-3, Yonhee Hall,

Yonsei University 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea.

Email: [email protected]

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The emergence and persistence of the fiscal crisis in many industrial coun-

tries has generated widespread concern and an interest in fiscal policy.

Many states in the United States are also facing a fiscal crisis unprecedented

in modern American government, with this fiscal situation contributing to

an increase in their perceived risk of default. Nadler and Hong (2011) report

that among the many economic variables of the states, the budget deficit of

real gross domestic product (GDP) was identified as one of the three eco-

nomic variables having the greatest explanatory effect of the increase in the

US state bond yield spread during 2008–2009.1 For this reason, although the

2008 financial crisis might have been caused by reasons having little to do

with poor management of government finances,2 many policy makers are

seeking to introduce a policy solution that can provide their countries (or

states) with more stable fiscal outcomes and can prepare them for the debt

crisis that could follow the financial crisis (Reinhart and Rogoff 2011).

As a solution for effectively managing the fiscal crisis, fiscal rules such

as a ‘‘balanced-budget rule’’ have recently attracted the attention of many

public policy makers of industrial countries as a solution to the unprece-

dented fiscal crisis.3 Research on balanced-budget requirements has been

focused mainly on testing the macroeconomic consequences of the rule:

whether balanced-budget rules amplify business cycles by stimulating

demand during the boom via an increase in expenditures and by reducing

demand during recessions via a decrease in expenditures. For instance,

King, Plosser, and Rebelo (1988) proposed a theory showing that the ampli-

tude of the business cycle may increase when the government follows a

balanced-budget rule. Schmitt-Grohe and Uribe (1997) also show a model

in which market participants’ expectations can make this trend even worse.

This Keynesian notion that a reduction in budget deficits is always

contractionary, a notion regarded as an unquestionable ‘‘stylized fact’’ (Gia-

vazzi and Pagano 1990; Taylor 2011), has not always been clear-cut when it

comes to empirical evidence. A study by Levinson (1998) supports the the-

oretical models by reporting evidence that the stringent balanced-budget

rules enforced in some large US states have exacerbated business cycles

in those states.4 However, Fatas and Mihov (2003, 2006) present evidence

that constraints on fiscal policy may reduce the volatility of the business

cycle, because, with stringent rules, less discretion is given to politicians

in making fiscal policy. Empirical evidence is even more mixed if we focus

on data from times of ‘‘fiscal stress.’’ A number of studies (Perotti 1990; Ale-

sina et al. 1998; Giavazzi and Pagano 1990) show that in times of fiscal stress,

deficit cuts may have very different effects on aggregate demand than during

‘‘normal’’ times and that they may well have an expansionary effect. Parker

2 Public Finance Review



(2011) concludes that during recessions, the effectiveness of fiscal policy in

either stabilizing or destabilizing the economy is highly questionable.

Compared to the attention given to the macroeconomic impact of budget

rules, however, relatively little attention is given to how states respond to

these rules, and whether these responses depend on political and economic

environments. In fact, it is possible that budget rules are often difficult to

enforce (Poterba 1995), as most states have no formal rule for enforcing

their balanced-budget requirements (Gold 1992). The US General Account-

ing Office (US GAO; 1993) also reports that no lawsuits have challenged

state budgets, even when states have failed to balance them. Although a

number of studies (e.g., Alt and Lowry 1994; Bohn and Inman 1996; Hou

and Smith 2010; Mahdavi and Westerlund 2011; Poterba 1994, 1995; Primo

2007; Smith and Hou 2013) have already reported some evidence of the

association between budget rules and fiscal policy outcome, the existing

evidence either is largely outdated or focuses mainly on whether specific

components of fiscal rules have impacts on fiscal policy.

Thus, previous studies have done relatively little to explain how and

whether the impact of state budget rules on fiscal policy outcomes depends

on political institutions or the economic situations of the states. This is an

important omission, because understanding how fiscal rules interact with

political institutions may have important policy implications for the design

and reform of fiscal rules. Further, understanding whether fiscal rules

become more or less binding depending on states’ economic situations may

expand our understanding of the macroeconomic impacts of these rules and

provide important policy implications.

This article provides a new estimate of the role of budget rules as well as

its dependence on political and economic environments. The variation in fis-

cal as well as political institutions across states within the United States pro-

vides a valuable opportunity to test the potential interplay between the budget

rule and political situation. Furthermore, the recent experience of the 2008–

2010 financial crisis provides a unique opportunity to observe how states

adjust their fiscal outcomes in response to a change in economic situations.

Hypothesis

Fiscal rules such as balanced-budget rules, for which there is no formal

mechanism in place to enforce them (Gold 1992; Poterba 1995), are always

present but are generally less binding during normal periods, because they

are overshadowed by other policy issues. During normal periods, fiscal

adjustments are not a major policy issue either for the public or for the

Hong 3



politicians. However, those rules are likely to matter more during a fiscal

crisis, because fiscal adjustments become one of the major interests of the

public, media, and markets.5 That is, during a fiscal crisis, public sentiment

often forces both opposing political parties to work together around fiscal

adjustments that ‘‘need to be done.’’ This is when the ever-present fiscal

rules become highlighted. Therefore, during a fiscal crisis period, I expect

that fiscal rules such as balanced-budget rules will become more binding

and have greater impacts on states’ fiscal policy outcomes.

Hypothesis 1: Fiscal rules that have no formal enforcement mechanism

such as balanced-budget rules will become more binding in times of

recession than in normal times.

Although the public sentiment can force both parties to work together on

a common issue, it cannot guarantee that those opposing parties will reach

consensus as a result of the negotiation. In fact, as the opposing political

parties sit together at the negotiation table and make known their own

preferences, it is more likely that the differences between the two parties

will become increasingly obvious. In other words, the level of political

opposition around the issue of fiscal adjustments, which were inherent

before the crisis, surfaces during fiscal turmoil.

To be more specific, I expect that the costs of reaching political consen-

sus will be higher (1) when the state government is ‘‘divided’’ and (2) when

the executive or legislative branch is controlled by a left-leaning political

party. The latter prediction is because of previous evidence that, in success-

ful fiscal adjustments, a significant part of the spending cuts generally

derives from cuts in government wages and programs such as education,

public assistance, and Medicaid (Alesina et al. 1998; National Association

of State Budget Officers [NASBO] Fiscal Survey of States 2009–11). I

expect that the increased costs of reaching political consensus will be shown

as less binding balanced-budget rules.

Hypothesis 2: Balanced-budget rules will have a smaller impact on

states’ fiscal outcomes under either a divided government or a left-

leaning political party control.

Empirical Framework

This study aims to estimate the impact of budget rules on fiscal policy out-

comes and its dependence on the political and economic environments.




More specifically, I first estimate the association between the budget cuts

made by the US states and the stringency of the balanced-budget rules

adopted by those states. Then, I show whether and how these estimated

associations depend on the political and economic environments. In this

article, I follow Poterba and Rueben (2001) in measuring ‘‘fiscal shocks.’’6

That is, the unexpected revenues should equal the difference between the

revenues that would have been collected with the tax system that was in

effect at the beginning of the fiscal year and the revenues that the tax system

was forecasted to collect at the beginning of the fiscal year. Thus, I subtract

the change in tax revenue and spending during the fiscal year. Unexpected

expenditures are defined in a similar way. Specifically, fiscal shocks are

defined as follows:

Defshockit ¼ Expshockit � Revshockit; ð1Þ

Revshockit ¼ Actual revenueit � DTaxit � Forecast revenueit; ð2Þ

Expshockit ¼ Actual outlaysit � DSpendit � Forecast outlaysit; ð3Þ

where Defshockit in (1) is the unexpected deficit shock in a given fiscal year

t in state i, which is our measure of a fiscal shock. The unexpected deficit

shock equals the difference between unexpected revenue (Revshockit) and

unexpected expenditure (Expshockit). A positive number for Defshockit

refers to either an unexpected increase in expenditure or an unexpected

decrease in revenue. DTaxit and DSpendit are the changes in tax revenue

and spending during fiscal year t that are enacted during that fiscal year.

As noted by Poterba (1994), failure to subtract DTaxit and DSpendit in

defining Defshockit would induce a simultaneity problem, as the dependent

variable is Budgetcutit, which is the sum of the positive component of

DTaxit and the negative component of DSpendit.

I first test whether a state with a more stringent balanced-budget rule

reacts differently to unexpected fiscal shock than a state with a less stringent

rule. To do so, I interact the measured unexpected deficit shock (Defshockit)

with the measured level of the balanced-budget rule stringency (BBRi),

controlling for the economic variables of each state. Thus, the estimated

equation takes the form

Budgetcutit ¼ aþ b1Defshockit þ b2 DefshockitBBRið Þ þ b3BBRi

þ b4Xit þ b5Si þ eit;ð4Þ

Hong 5



where Budgetcutit denotes the amount cut from the budget after the budget

of that fiscal year has passed the legislature. A positive number for Budget-

cutit refers to either a decrease in spending or an increase in taxation. BBRi

is the measured level of balanced-budget rule stringency, as shown in Table

1, and Xit is a set of economic covariates of state i in fiscal year t. Among

various economic variables, I control for the following economic variables

that turn out to have the most significant effect on the dependent variable

Table 1. Balanced-Budget Rule Stringency.

State ACIR GAO State ACIR GAO

Alabama 10 1 Montana 10 1Alaska 6 1 Nebraska 10 0Arizona 10 0 Nevada 4 1Arkansas 9 1 New Hampshire 2 0California 10 1 New Jersey 10 1Colorado 10 1 New Mexico 10 1Connecticut 5 0 New York 3 0Delaware 10 0 North Carolina 10 1Florida 10 1 North Dakota 8 1Georgia 10 0 Ohio 10 1Hawaii 10 1 Oklahoma 10 1Idaho 10 1 Oregon 8 1Illinois 4 0 Pennsylvania 6 0Indiana 10 1 Rhode Island 10 1Iowa 10 0 South Carolina 10 1Kansas 10 1 South Dakota 10 1Kentucky 10 1 Tennessee 10 1Louisiana 4 0 Texas 8 0Maine 9 1 Utah 10 0Maryland 6 0 Vermont 0 0Massachusetts 3 0 Virginia 8 0Michigan 6 0 Washington 8 0Minnesota 8 1 West Virginia 10 1Mississippi 9 1 Wisconsin 6 0Missouri 10 1 Wyoming 8 0

Note: GAO ¼ General Accounting Office; ACIR ¼ Advisory Commission on Intergovernmen-tal Relations. The higher the number, the more stringent the rule is. The ACIR classificationcomes from the ACIR (1987) and Poterba and Rueben (2001). The GAO classification comesfrom US GAO (1993). In California, the voters approved constitutional amendments in 2004that require the Legislature to enact a balanced-budget and prohibit borrowing to manage anend-of-year deficit. Those amendments moved California into the ‘‘most rigorous’’ category(National Conference of State Legislatures [NCSL] 2010).




Tab

le2.

Sum

mar

ySt

atis

tics

.

Mea

nSt

andar

ddev

iation

Min

imum

Max

imum

Unit

Def

icit

shock

0.1

91.5

7�

6.4

817.1

6In

bill

ions

USD

Expen

diture

shock

0.1

20.9

5�

2.8

911.4

5In

bill

ions

USD

Rev

enue

shock

�0.0

71.4

9�

19.2

25.7

4In

bill

ions

USD

Bal

ance

d-b

udge

tru

le(A

CIR

)8.1

62.6

00

10

Stri

nge

ncy

0–10

scal

eBal

ance

d-b

udge

tru

le(G

AO

)0.5

80.4

90

1St

ringe

ncy

0–1

scal

eC

olle

ctiv

ebar

gain

ing

righ

t1.2

60.8

70

21

ifst

ate

has

aduty

tobar

gain

(explic

itor

implic

it),

0oth

erw

ise

Rig

ht

tost

rike

0.1

60.3

70

11

ifst

ate

has

ari

ght

tow

ork

law

apply

ing

topublic

emplo

yees

,0

oth

erw

ise

Rig

ht

tow

ork

0.4

20.4

90

11

ifst

rike

isper

mitte

d(w

ith

qual

ifica

tions)

,0

oth

erw

ise

Par

tyid

entity

ofgo

vern

or

0.5

30.5

00

11

ifD

emocr

ats,

0if

Rep

ublic

ans

Public

sect

or

unio

nm

ember

ship

33.3

018.1

76.2

072.4

Per

centa

gepoin

ts(%

)D

emocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

52.4

115.1

019.2

990.1

2Per

centa

gepoin

ts(%

)

Rea

lG

DP

2.5

33.0

60.2

217.6

9100

bill

ions

USD

Unem

plo

ymen

tra

te6.0

42.3

82.4

913.8

4Per

centa

gepoin

ts(%

)R

ainy-

day

rese

rve

tost

ate

expen

diture

6.3

615.4

70

155.2

3Per

centa

gepoin

ts(%

)

Not

e:G

AO¼

Gen

eral

Acc

ounting

Offic

e;A

CIR¼

Advi

sory

Com

mis

sion

on

Inte

rgove

rnm

enta

l;G

DP¼

gross

dom

estic

pro

duct

.

7



(Nadler and Hong 2011):7 unemployment rate and the overall size of a

state’s economy as measured by real GDP. The set of covariates Xit also

includes the ratio of states’ expenditures covered by states’ ‘‘rainy-day’’

reserves. States usually have rainy-day reserves that allow them to set aside

excess revenue for use in times of unexpected revenue shortfall or budget

deficit,8 and thus, a state’s attempt to balance its budget may have been sig-

nificantly affected by them. Si is a set of unobservables that is specific to

state i but is time invariant. As Si is unobservable, (4) is first differentiated

to get rid of Si and to obtain the following equation:

DBudgetcutit ¼ aþ b1DDefshockit þ b2D DefshockitBBRið Þþ b3DXit þ Deit;

ð5Þ

where D denotes a time-difference operator. By focusing on changes rather

than on the level of the included variables, I can effectively control for the

time-invariant but state-specific unobservables (see Poterba and Rueben

2001). Table 2 provides summary statistics for all the variables used in this

study.

Economic Factors

The central question of this study is to test whether states’ responses to bud-

get rules depend on the political and economic environments. I first check

whether states’ responses to budget rules differ during an economic reces-

sion as opposed to normal times. The data set used in this article covers the

period from 2004 to 2010. The period from 2004 to 2008 is defined as nor-

mal times, and the period from 2008 to 2010 is defined as ‘‘economic reces-

sion.’’ I estimate equation (5) separately for normal times and economic

recession and conduct Chow tests in order to see whether the estimated

coefficients for the two periods are statistically different.

Political Factors

I also test whether the effect of budget rules is moderated by political insti-

tutional variables, such as the party identity of the governor and legislature

and divided control over the government. In this study, I follow Alt and

Lowry (1994) to categorize the level of control over the government as fol-

lows: (1) unified party government in which one party controls executives

as well as both chambers of the legislature, (2) split-legislature government

in which one party controls each chamber, and (3) split-branch government




in which the same party controls both chambers of the legislature, but the

other party holds the governorship. Alt and Lowry (1994) find a significant

effect of the balanced-budget rule in unified government but a smaller effect

or none in divided governments. In this study, to test whether this finding

holds in the recent data, I estimate the following equation:

DBudgetcutit ¼ aþ b1DDefshockit þ b2D DefshockitBBRið Þþ b3D DefshockitBBRiZitð Þ þ b4DZit þ b5DXit þ Deit;

ð6Þ

where Zit is the political variable. Thus, estimating equation (6) examines

whether the association between budget rules and the amount of the budget

cut after the budget is passed is any different among states with different

political institutions.9 The estimated results are reported in tables 3 and 4.

Unexpected Revenue and Expense Shocks

Another interesting point to consider is whether the two different compo-

nents of Defshockit, the expenditure and revenue shocks, have different

impacts on the dependent variable. In order to check this, for equations (4)

through (6), I replaced Defshockit with the right-hand side of equation (1),

Expshockit� Revshockit. That is, I tested the impact of expenditure and rev-

enue shocks separately on fiscal policy outcome in addition to the overall

impact of deficit shock. The estimated results are reported in panel B of tables

3 to 5.

Data

The dependent variable of this study, Budgetcutit, in equations (4) through

(6) is the total amount cut from the budget after the fiscal budget had passed.

This variable comes from the NASBO’s 2004–2010 Fiscal Survey of States.

The fiscal shock variable is constructed as in equations (1) through (3),

and the state revenue and expenditure data also come from the NASBO’s

Fiscal Survey of States.10 The economic variables controlled, state real

GDP, and state unemployment rates, come from the US Bureau of Eco-

nomic Analysis (BEA) and the Bureau of Labor Statistics (BLS), respec-

tively. The rainy-day reserves data comes from the NASBO’s Fiscal

Survey of States. The party identity of the governor and the state legislature

is obtained from state government websites and National Conference of

State Legislatures (NCSL; 2010).

Hong 9



Tab

le3.

The

Bal

ance

d-B

udge

tR

equir

emen

t(B

BR

)an

dPolit

ical

Envi

ronm

ents

,2004–08.

Dep

enden

tva

riab

le:D

Budge

tcut

The

AC

IRC

lass

ifica

tion

ofBBR

The

GA

OC

lass

ifica

tion

ofBBR

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

A.T

est

ofth

eim

pac

tofdef

icit

shock

DD

efsh

ock

0.3

03**

*0.2

00**

*0.1

26**

*0.2

00**

*0.3

03**

*0.2

64**

*0.2

61**

*0.2

25**

*(0

.103)

(0.0

661)

(0.0

463)

(0.0

667)

(0.1

03)

(0.0

581)

(0.0

523)

(0.0

528)

DD

efsh

ock�

BBR

0.1

07**

*0.1

95**

*0.1

05**

*0.4

08**

*0.4

93**

*0.4

14**

*(0

.0356)

(0.0

438)

(0.0

324)

(0.1

04)

(0.1

06)

(0.1

02)

DD

efsh

ock�

BBR�

Par

tyid

entity

ofg

ove

rnor

(1if dem

ocr

at)

�0.2

12**

*�

0.5

66**

*(0

.0460)

(0.1

67)

DPar

tyid

entity

ofgo

vern

or

(1if

Dem

ocr

at)

�0.1

12

�0.0

577

(0.0

748)

(0.0

674)

DD

efsh

ock�

BBR�

Dem

ocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

0.0

207

1.1

24

(0.1

88)

(0.7

31)

DD

emocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

1.6

50

1.3

73

(1.0

65)

(0.8

99)

N290

290

290

284

290

290

290

284

R2

.548

.650

.746

.652

.548

.692

.727

.704

Dep

enden

tva

riab

le:D

Budge

tcut

(1)

(2)

(3)

(4)

B.T

est

ofth

eim

pac

tofex

pen

diture

and

reve

nue

shock

sD

Expsh

ock

0.0

718*

0.0

302

0.0

207

0.0

267

(0.0

425)

(0.0

439)

(0.0

309)

(0.0

374)

10



DR

evsh

ock

�0.3

84**

*�

0.3

01**

*�

0.2

21**

*�

0.2

78**

*(0

.0686)

(0.0

474)

(0.0

334)

(0.0

455)

DExpsh

ock�

BBR

�0.0

0257

0.0

505

0.0

182

(0.0

279)

(0.0

636)

(0.0

306)

DR

evsh

ock�

BBR

�0.0

611**

*�

0.1

35**

*�

0.0

559**

*(0

.0196)

(0.0

234)

(0.0

214)

DExpsh

ock�

BBR�

Par

tyid

entity

ofg

ove

rnor

(1if dem

ocr

at)

�0.1

04*

(0.0

582)

DR

evsh

ock�

BBR�

Par

tyid

entity

ofg

ove

rnor

(1if dem

ocr

at)

0.1

72**

*(0

.0321)

DPar

tyid

entity

ofgo

vern

or

(1if

Dem

ocr

at)

�0.1

18

(0.0

955)

DExpsh

ock�

BBR�

Dem

ocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

�0.2

44*

(0.1

30)

DR

evsh

ock�

BBR�

Dem

ocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

�0.1

80

(0.1

34)

DD

emocr

atic

Par

tysh

are

inst

ate

legi

slat

ure

1.6

08*

(0.8

96)

N290

290

290

284

R2

.733

.776

.828

.794

Not

e:G

AO¼

Gen

eral

Acc

ounting

Offic

e;A

CIR¼

Advi

sory

Com

mis

sion

on

Inte

rgove

rnm

enta

l;BBR¼

bal

ance

d-b

udge

tre

quir

emen

t;G

DP¼

gross

dom

estic

pro

duct

.Robust

het

erosc

edas

tic

stan

dar

der

rors

inpar

enth

eses

.Chan

gein

GD

P,u

nem

plo

ymen

tra

tes,

and

rain

y-day

rese

rves

toex

pen

diture

sar

eco

ntr

olle

d.I

use

dye

arfix

edef

fect

inal

lsp

ecifi

cations.

Bal

ance

d-b

udge

tru

leva

riab

leis

mea

nce

nte

red.

*p<

.10.**

p<

.05.**

*p<

.01.

11



Table 4. The Balanced-Budget Requirement (BBR) and Divided Government, 2004–08.

Dependent variable: DBudgetcut

The ACIR classification of BBR The GAO classification of BBR

(1) (2) (3) (4)

A. Test of the impact of deficit shockDDefshock 0.0957** 0.197*** 0.260*** 0.262***

(0.0475) (0.0669) (0.0543) (0.0578)DDefshock � BBR 0.129*** 0.104*** 0.307*** 0.396***

(0.0332) (0.0335) (0.0815) (0.0985)DDefshock � BBR �

Split branch�0.188*** �0.497***(0.0536) (0.152)

DSplit branch �0.0771 �0.110(0.0787) (0.0745)

DDefshock � BBR �Split legislature

�0.0447 �0.140(0.0452) (0.119)

DSplit legislature 0.0355 0.0535(0.107) (0.0860)

N 290 290 290 290R2 .703 .651 .715 .693

Dependent variable: DBudgetcut

(1) (2)

B. Test of the impact of expenditure and revenue shocksDExpshock 0.0180 0.0321

(0.0270) (0.0442)DRevshock �0.217*** �0.305***

(0.0417) (0.0499)DExpshock � BBR �0.000254 0.000276

(0.0520) (0.0268)DRevshock � BBR �0.0800*** �0.0638***

(0.0205) (0.0193)DExpshock � BBR �

Split branch�0.0343(0.0698)

DRevshock � BBR �Split branch

0.101***(0.0381)

DSplit branch �0.107(0.0920)

DExpshock � BBR �Split legislature

0.0766**

(0.0385)DRevshock � BBR �

Split legislature�0.0468(0.0350)

DSplit legislature 0.0516(0.0920)

N 290 290R2 .786 .778

Notes: GAO¼General Accounting Office; ACIR¼ Advisory Commission on Intergovernmen-tal; BBR ¼ balanced-budget requirement; GDP ¼ gross domestic product. Robust heterosce-dastic standard errors in parentheses. Change in state real GDP, unemployment rates, andrainy-day reserves to expenditures are controlled. I used year fixed effect in all specifications.Balanced-budget rule variable is mean centered.*p < .10. **p < .05. ***p < .01.




Tab

le5.

The

Bal

ance

d-B

udge

tR

equir

emen

t(B

BR

):N

orm

alT

imes

(2004–08)

vers

us

Rec

essi

ons

(2008–10).

Dep

enden

tva

riab

le:D

Budge

tcut

The

AC

IRcl

assi

ficat

ion

ofBBR

The

GA

Ocl

assi

ficat

ion

ofBBR

(1)

(2)

(3)

(4)

(5)

(6)

A.T

est

ofth

eim

pac

tofdef

icit

shock

DD

efsh

ock

0.0

681**

*0.2

05**

0.0

616**

*0.0

712**

*0.3

28**

*0.0

679**

*(0

.0202)

(0.0

956)

(0.0

226)

(0.0

188)

(0.0

550)

(0.0

196)

DD

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BBR

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137

0.1

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0.0

592

0.5

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*0.0

349

(0.0

124)

(0.0

442)

(0.0

135)

(0.0

367)

(0.1

04)

(0.0

465)

DD

efsh

ock�

Cri

sis

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90*

0.2

82**

*(0

.0995)

(0.0

539)

DD

efsh

ock�

BBR�

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sis

0.1

37**

*0.5

14**

*(0

.0463)

(0.0

985)

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/AN

/AF(

2,277)¼

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ue¼

.0000

N/A

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ue¼

.0000

N200

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290

200

90

290

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.809

.770

.360

.874

.843

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enden

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riab

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tcut

(1)

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(3)

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est

ofth

eim

pac

tofex

pen

diture

and

reve

nue

shock

sD

Expsh

ock

0.1

05**

*0.0

790

0.1

12**

*(0

.0296)

(0.0

515)

(0.0

256)

(con

tinue

d)

13



Tab

le5.

(continued

)

Dep

enden

tva

riab

le:D

Budge

tcut

(1)

(2)

(3)

DR

evsh

ock

�0.0

576**

�0.3

65**

*�

0.0

539*

(0.0

290)

(0.0

523)

(0.0

284)

DExpsh

ock�

BBR

0.0

273**

0.0

0965

0.0

235*

(0.0

136)

(0.0

478)

(0.0

122)

DR

evsh

ock�

BBR

�0.0

0384

�0.0

606**

*0.0

0536

(0.0

192)

(0.0

207)

(0.0

182)

DExpsh

ock�

Cri

sis

�0.0

280

(0.0

599)

DR

evsh

ock�

Cri

sis

�0.3

18**

*(0

.0526)

DEx

psho

ck�

BBR�

Cri

sis

�0.0

212

(0.0

461)

DR

evsh

ock�

BBR�

Cri

sis

�0.0

694**

*(0

.0255)

The

Chow

test

N/A

N/A

F(4,273)¼

23.4

1p

Val

ue¼

.0000

N200

90

290

R2

.392

.899

.875

Not

e:G

AO¼

Gen

eral

Acc

ounting

Offic

e;A

CIR¼

Advi

sory

Com

mis

sion

on

Inte

rgove

rnm

enta

l;BBR¼

bal

ance

d-b

udge

tre

quir

emen

t;G

DP¼

gross

dom

estic

pro

duct

.R

obust

het

erosc

edas

tic

stan

dar

der

rors

inpar

enth

eses

.C

han

gein

stat

ere

alG

DP,unem

plo

ymen

tra

tes,

and

rain

y-day

rese

rves

toex

pen

diture

sar

eco

ntr

olle

d.I

use

dye

arfix

edef

fect

inal

lspec

ifica

tions.

Bal

ance

d-b

udge

tru

leva

riab

leis

mea

nce

nte

red.T

he

null

hyp

oth

esis

ofth

eC

how

test

isth

atth

eco

effi-

cien

tsofD

Expsh

ock�

Cri

sis,D

Rev

shock�

Cri

sis,D

Expsh

ock�

BBR�

Cri

sis,

andD

Rev

shock�

BBR�

Cri

sis

are

allze

ro.

*p<

.10.**

p<

.05.**

*p<

.01.

14



The balanced-budget rule, which is our independent variable, comes from

the 1987 Advisory Commission on Intergovernmental Relations (ACIR;

1987), in which the stringency level of balanced-budget rules adopted by

US states are categorized into four groups, depending on the stage in the bud-

get process at which balance is required (Poterba and Rueben 2001).11 Yet, as

in some states, voters have approved amendments that require the legislature

to enact a balanced-budget requirement (NCSL 2010). Thus, I revised the

ACIR data to incorporate these changes. Table 1 shows the estimated strin-

gency of the balanced-budget requirements in US states.

More recently, however, some scholars have questioned the validity of

the ACIR (1987) data as a quantitative measure of the balanced-budget

rules. For instance, Krol and Svorny (2007) propose the GAO classification

of balanced-budget stringency as an alternative measure of balanced-budget

rules. Although it is debatable whether the GAO classification is superior to

the ACIR (1987) classification (e.g., see Levinson 2007), I still present, as a

robustness check of my finding, both the estimates with the GAO classifi-

cation of balanced-budget rules and the estimates with the ACIR classifica-

tion. As will be explained, the estimated coefficients of the two different

classifications yielded similar estimates.

Table 1 shows and compares the two classifications of balanced-budget

rule stringency. The ACIR (1987) classification varies substantially on a

scale of 0 to 10, with 10 representing the most stringent requirement. Only

one state, Vermont, does not have a formal balanced-budget requirement

(Poterba and Rueben 1999). Twenty-seven states have the most rigorous

requirement: a constitutional prohibition against carrying a deficit forward

that requires a balanced budget to be passed by the legislature. The low-

scoring states tend to have only a requirement that the governor submit a

balanced budget or that the legislature enact a balanced budget, without a

prohibition on carrying forward the deficit into the next budget cycle. The

GAO classification has only two groups (0 or 1), with 1 representing the

more stringent requirement. The two classifications showed a highly posi-

tive Pearson correlation (.5365).12

Findings

The main empirical result is presented in tables 3 through 5. Tables 3 and 4

show the results of testing whether the balanced-budget requirement is associ-

ated with the amount the budget is cut after the fiscal budget has passed and

whether the impact of the requirement is moderated by political environments.

The political factor includes the party identity of the governor (table 3), the

Hong 15



Democratic Party share in the state legislature (table 3), and a measure of split

government (table 4), which is either a split-legislature or split-branch govern-

ment. Table 5, along with figure 1, shows whether the association between

the balanced-budget requirement and fiscal policy outcome is any dif-

ferent between normal times and in times of recessions. Tables 3 to 5

have two different panels: the first (panel A of tables 3, 4, and 5) are

the main test results with the ACIR (1987) balanced-budget data, as

well as robust checks with the GAO balanced-budget data; and the sec-

ond (panel B of tables 3 to 5) decomposed the Defshockit variable into two

subparts, Expshockit and Revshockit, to see whether these two parts have

different impacts on fiscal policy outcome.

As can be seen in table 3 (panel A), the amount by which the budget is cut has

a strong positive association with the amount of deficit shock. An increase of 1

billion USD in deficit shock is associated with an approximately 0.3 billion

USD increase in budget cuts (column 1), and this estimated coefficient is greater

when the state has a more stringent balanced-budget rule (column 2). Concern-

ing whether the requirement depends on political environments, the impact of

the requirement is greater in states where a Republican is the governor. As can

be seen in column 3 of table 3 (panel A), in such states, an increase in deficit

shock is associated with an additional increase in budget cuts during the fiscal

year. The party identity of the legislature had no impact on fiscal policy out-

come. Columns 5 through 8 of table 3 (panel A) confirm that the main conclu-

sion of columns 1 through 4 is unaffected even when the ACIR (1987) data are

replaced with the GAO data.

Table 4 (panel A) tests whether the effect of the rule is different in

divided governments. Following Alt and Lowry (1994), two forms of

divided government were tested: divided branches, in which one party con-

trols the governorship and another controls the legislature, and divided leg-

islatures, in which different parties control each legislative chamber. The

estimated result suggests that the rule becomes significantly less effective

in divided branch governments, but not in divided legislatures. This result

is slightly different from Alt and Lowry’s (1994) findings, which showed

a divided government as less able to react to budget deficits, particularly

in divided legislatures. Again, this main result still holds in columns 3 and

4 when the ACIR (1987) data are replaced with the GAO data.

Table 5 (panel A) compares the estimated impact of the balanced-budget

rule during the 2008–2010 crisis with its impact during the precrisis period

of 2004 to 2008. That is, I tested whether budget rules become more or less

binding in times of economic recessions. Columns 1 and 2 of table 5 (panel

A) show that budget rules are clearly more binding in times of economic




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Hong 17



recessions. In fact, the estimated association between the amount of deficit

shocks and fiscal policy outcome is moderated by the stringency of state

budget rules only in times of recessions, and not in normal times. In column

3, I conducted a Chow test to determine whether the estimated coefficients

in columns 1 and 2 were significantly different and discovered that they

were. Here again, the use of the GAO measurement of budget rules in

columns 4 through 6 did not have significant impacts on overall results in

columns 1 through 3.

Results in tables 5 (panel A) are obvious even in the simple scatterplots

shown in figure 1. Figure 1 plots the amount of deficit shocks against fiscal

policy outcome (the amount of budget cuts) separately for two different

groups: states with relatively strict balanced-budget rules and those with rel-

atively lenient rules. States are classified as ‘‘stringent states’’ (the group of

states with stringent rules) if the stringency of the rule is equal to or higher

than eight in terms of the ACIR (1987) measure of budget rules in table 1.

The rest of the states are classified as ‘‘lenient states’’ (the group of states with

lenient rules). Figures 1C and 1D show the association between the two vari-

ables during normal times, while figures 1A and 1B reflect their association

during times of recession. In order to control for the state-invariant omitted

variables, both figures plot changes instead of the levels of the two variables.

Figure 1 shows that the association between balanced-budget rules and bud-

get cuts made by the states is greater during recessions.

In panel B of tables 3 to 5, I decomposed the amount of deficit shock into

two subparts, the expenditure and revenue shocks, to see whether the two

different parts have impacts on fiscal policy. The estimated coefficients

in panel B of tables 3 and 4 show that the amount of revenue shock has

greater impacts on fiscal policy outcome than the amount of expenditure;

that is, the positive association between the amount of deficit shock and fiscal

policy outcome we observed previously is largely driven by the unexpected

revenue shock (e.g., a decrease in tax revenue leads a state government to cut

its expenditures). In addition, the result in table 5 (panel B) shows that the

relative importance of the unexpected expenditure and revenue shocks may

change in normal times and recessions. The finding that governments’ budget

cuts are largely in response to a decrease in revenue (e.g., tax revenue) holds

only in times of recession.

Conclusion

This study seeks to understand how states response to budget rules and

whether the responses depend on the political and economic environments.




The first finding of this study is that ‘‘balanced-budget rules matter’’; that is,

the amount of budget cuts is associated with the measured stringency of the

states’ budget rules. This study also suggests that the impact of budget rules

depends greatly on political environments, especially on the party identity

of the executive power. Budget rules are much more binding when the gov-

ernor is a Republican, but the identity of the party controlling the state leg-

islature did not have a significant impact. Further, the impact of budget

rules also depends on whether the government is divided. Budget rules were

less binding in divided branch government, in which one party controls the

governorship and another controls the legislature, while the impact of the

rules was largely unaffected under divided legislatures, in which different

parties control each legislative chamber. This finding differs slightly from

that of a previous study (Alt and Lowry 1994), which presented evidence

that the rule was not effective, especially in divided legislatures. Another

finding of this study, which has not been reported anywhere so far, is that

balanced-budget rules are much more binding in times of recession than

in normal times. In fact, the estimated impact of balanced-budget rules

on fiscal policy outcome was not statistically significant when I limited

observations to normal times (table 5).

This study also tested whether the estimated results with the two most

widely used measures of budget rules stringency, the ACIR (1987) and

GAO measures, yield different conclusions. Krol and Svorny (2007) pro-

posed the GAO classification of balanced-budget stringency as an alterna-

tive measure and challenged previous studies on budget rules by showing

that the finding by Levinson (1998), which used the ACIR (1987) data, is

not robust with the GAO data. In this study, however, the main results were

largely unaffected by the use of either source as a measure for budget rules

stringency.

This study has explored the impact of balanced-budget rules on fiscal

policy outcomes in the US states, and tested whether this impact depends

on the political and economic environments. The variation in fiscal as well

as political institutions across states within the United States provides a

valuable opportunity to test the potential interplay between the budget rule

and the political situation. Further, the recent experience of the 2008–2010

financial crisis provides a unique opportunity to observe how states adjust

their fiscal outcomes as a response to a change in economic situations. In

sum, the finding of this study suggests that the impact of fiscal rules such

as balanced-budget rules is largely affected by the rules per se, the political

institutions, and the economic situations of the states.

Hong 19



Appendix

Data Sources

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,

authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or

publication of this article.

Notes

1. See also Von Muller, Nadler, and Hong (2012) who reports similar evidence

from Germany.

2. See Taylor (2009) for the cause of the 2008 financial crisis.

3. For instance, in April 2011, Speaker Boehner of the US House of Representa-

tives introduced an amendment to the US Constitution to mandate a balanced-

budget at the federal level. In May 2010, Sweden announced that it would leg-

islate a fiscal rule that requires its budget to be balanced. In August 2011, both

German chancellor Angela Merkel and French president Nicolas Sarkozy

encouraged eurozone countries to adopt a fiscal rule that requires governments

to balance their budgets. A few weeks later, the head of the Spanish government

announced a constitutional amendment to require a balanced-budget and asked

Data Source List of variables

The National Association of State Budget Officers(NASBO), Fiscal Survey of States

Budget cuts made fiscalbudget passed

US Bureau of Economic Analysis (BEA), RegionalEconomic Accounts, Gross Domestic Product (GDP)by State and Metropolitan Area

Real gross domesticproduct

Bureau of Labor Statistics (BLS), Local AreaUnemployment Statistics, Unemployment Rate byState

Unemployment rate

NASBO, Fiscal Survey of States Unexpected budgetdeficit shock

State government websites Party identity of governorNational Conference of State Legislatures (NCSL), Party

Composition of State LegislaturesParty identity of state

legislatures




the political parties to approve it by the end of 2011. France is also planning a

similar revision. In September 2011, the governments of Italy and Korea

proposed bills to enforce a balanced-budget requirement with a constitutional

amendment.

4. See also Krol and Svorny (2007).

5. Another possible explanation for the increased interests in fiscal adjustments by

political parties is the ‘‘market discipline hypothesis,’’ which states that credit

markets provide incentives for state governments to restrain borrowing and

make fiscal adjustments (e.g., Bayoumi, Goldstein, and Woglom 1995).

6. See Poterba (1994) or Poterba and Rueben (2001) for further information.

7. I do not control for state budget deficit to gross domestic product (GDP), as

doing so creates a reverse causality problem.

8. Specific operations for deposits and withdrawals of the reserves differ by states.

For further information, see Tax Policy Center (2009).

9. In order to more easily interpret the estimated coefficients, I ignore

D DefshockitZitð Þ and D BBRiZitð Þ. However, the overall estimates and conclu-

sions are the same when I include the two terms in the model.

10. These states’ revenue and expenditure data are states’ general fund data.

11. Most of the existing studies on balanced-budget requirements (Alt and Lowry 1994;

Eichengreen and Bayoumi 1994; Poterba 1994; Bohn and Inman 1996; Sorensen,

Wu, and Yosha 2001; Fatas and Mihov 2006) rely on a survey conducted by the

1984 Advisory Commission on Intergovernmental Relations (ACIR; 1987).

12. Further information on the stringency level of the balanced-budget requirement

can be found in ACIR (1987), Poterba and Rueben (2001), National Conference

of State Legislatures (NCSL; 2010), Krol and Svorny (2007), and US General

Accounting Office (US GAO 1993).

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icits: Evidence from the States.’’ American Political Science Review 88:

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Bayoumi, Tamim, Morris Goldstein, and Geoffrey Woglom. 1995. ‘‘Do Credit Mar-

kets Discipline Sovereign Borrowers? Evidence from the U.S. States.’’ Journal

of Money, Credit and Banking 27:1046–59.

Hong 21



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Hong 23


http://www.taxpolicycenter.org/taxfacts/displayafact.cfm?Docid=489

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http://www.hks.harvard.edu/pepg/PDF/Papers/PEPG12-01_Nadler_Hong.pdf


Author Biography

Sounman Hong is an assistant professor in the Department of Public Administra-

tion at Yonsei University. He received his PhD in public policy from Harvard

University. Sounman’s research interests include business and government, regula-

tory reform and policy (particularly online, financial, and corporate regulations),

and information science.




Fiscal Rules in Recessions: Evidence from the American States

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