ECONOMIC RESEARCH CENTERDISCUSSION PAPER
E-Series

No.E13-5

Fiscal Adjustment in Japanese Municipalities
byHikaru Ogawa
Shun-ichiro Bessho

Revised version as of February 2014

ECONOMIC RESEARCH CENTERGRADUATE SCHOOL OF ECONOMICSNAGOYA UNIVERSITY

Fiscal Adjustment in Japanese Municipalities∗
Hikaru Ogawa†Shun-ichiro Bessho‡

Abstract
This study examines how Japanese municipalities restore their fiscal
balance after a budget shock. The results show that these fiscal adjustments mainly occur via subsequent changes in government investment,
accounting for 83-100% of adjustments in permanent unit innovations in
grants and own revenue. The contribution of government expenditure tobalancing local budgets is much larger in Japan than in other countries.
In contrast to the role of expenditure, the municipalities’ own-source revenue and grants from the higher-level government play a limited role inbalancing local budgets. In addition, it is observed that government investment is more volatile in Japan than in other countries. Finally, we
conduct an additional analysis based on population size to study how theadjustment process varies among municipalities of different sizes.

JEL Classiﬁcation. H70; H72; H77
Keywords. Dynamic ﬁscal adjustment, municipal policy∗ An earlier version of this paper was presented at APEA2013.

We would like to thank

Masayoshi Hayashi, Toshihiro Ihori and Yohei Yamamoto for their helpful comments. The
research has been supported by grants from JSPS Grants-in-Aid for Scientific Research (A),Grant-in-Aid for Young Scientists (B) and the Kikawada Foundation.
† School of Economics, Nagoya University, Furocho, Chikusaku, Nagoya 4648601, Japan.
Email. ogawa@soec.nagoya-u.ac.jp‡ Department of Economics, Keio University, 2-15-45 Mita, Minatoku, Tokyo 1088345,
Japan. Email. bessho@econ.keio.ac.jp1

1

Introduction

Regional governments have to cope with various ﬁscal shocks caused by economic
downturns, national ﬁscal reforms, and the disappearance of a tax base owing
to natural disasters. However, only recently, starting with the pioneering workof Buettner and Wildasin (2002, 2006; hereafter, BW), have studies attempted
to quantify the dynamics of regional ﬁscal adjustments. Using a balanced panel
data set, compiled from 1270 cities in the United States between 1972 and 1997,
and a vector error-correction model (VECM), they measured how these cities
adjusted to various exogenous ﬁscal shocks. While the VECM was developed
to describe the dynamic interrelationship between stationary variables, mainly
in macroeconomic ﬁelds, they were the ﬁrst to apply it to analyzing impulseresponse functions at the municipal level. A critical feature when applying
the VECM to municipalities is the substantial grants they receive from theirnational government. These grants may play a crucial role in maintaining amunicipality’s ﬁscal balance. One of the ﬁndings of the BW analysis is that cities
maintain an intertemporal budget balance in the face of shocks in own-source
revenue and grants mainly by adjusting public expenditure. By decomposing
the sample, BW conﬁrmed that the pattern is more or less robust with respect
to city size.
Several subsequent studies have applied the BW approach to other countries.
For example, Rattsø (2004) used a panel data set compiled for the period 19831993 from 25 local governments in the county of Sør-Trøndelag in Norway. He
found that, as with the United States, local public investment is the main shock
absorber in Norway’s local ﬁnance system. In this case, one-third of Norway’s
budget surplus shock is adjusted by investment in the following year. Furthermore, Navon (2006) applied the BW approach to a 1996-2002 panel data set of
193 local authorities in Israel. He showed that a reduction in grants from thegovernment leads to a cutback in services to residents and increased deﬁcits. He
further shows that the adjustment process diﬀers considerably across regions.
For example, the budget adjustment process for the non-Jewish local authorities2

is twice as long as that for the Jewish ones. Buettner (2009) applied the BW
approach to examine how German municipalities adjust to ﬁscal shocks. Usinga sample of 1102 jurisdictions for the period 1974-2000, the study ﬁnds that asubstantial part of ﬁscal adjustment to revenue shocks occurs by oﬀsetting thechanges in grants and equalization transfers. In a recent study, Solé-Ollé andSorribas-Navarro (2012) applied the BW approach to examining ﬁscal adjustments in Spain. Using a panel data set of 258 municipalities in the Catalonia
region for the period 1988-2006, they observed that, as with the German municipalities, government grants play a more important role in the adjustment
process. The results of the preceding studies show that, while the municipalities in some countries cope with exogenous ﬁscal shocks by controlling public
spending, municipalities in other countries do so using grants. This suggeststhat further research is needed to understand the diﬀerences and similarities inthe ﬁscal adjustment processes of diﬀerent countries.
This study adopts the same approach, namely the VECM, to estimate themunicipal ﬁscal adjustments in Japan. We use a sample of 3210 municipalities
for the period 1977-2010, therefore covering more than a quarter of a century.
Our analysis has the advantage of using a richer data than previous studies.
More speciﬁcally, a distinguishing feature of our study is that we separate andcategorize government spending into government investment and government
current expenditure (consumption). Buettner (2009) broke down the revenue
side into grants and ﬁscal equalization transfers and, thus, succeeded in determining the role of interregional ﬁscal equalization in Germany. In contrast,in this study, we divide the expenditure side. The trade-oﬀ faced by regional
governments in allocating public expenditure between investment and current
consumption is subject to intensive study, and the decision has a great impact
on the eﬃciency, welfare, and growth of regions.1 Changes in the composition
1 See Keen and Marchand (1997), Matsumoto (2000), and Borck et al. (2007) for the effects

of changes in the allocation of public spending in the framework of interregional competition,and Lau (1995), Devarajan et al. (1996), Rivas (2003), Chen (2006), and Giovanni and Tervala(2010) for the impact of changes in public spending composition on long-run growth.

3

of public spending have attracted the attention of several researchers because,
while a decrease in public investment may have a negative eﬀect on long-run
regional growth, welfare might increase in the short term owing to an increase ingovernment current expenditure, which replaces public investment. Our analysis thus contributes to clarifying the substitutability/complementarity between
government investment and current expenditure. Furthermore, we try to ascertain which policy instruments are used to adjust ﬁscal imbalances.
In addition, by applying the analysis to Japanese municipalities, we clarify
the similarities and diﬀerences in the adjustment process between unitary andfederal nations, since the Japanese government system is notably diﬀerent to themore decentralized systems of the United States and Germany. In particular,
the local tax laws in Japan places a limit on the free choice of municipal tax
rates, and the central government is involved in local loan programs. Instead,municipalities actively engage in public investment to improve their social infrastructure, since they have faced with the lack of infrastructure developmentin the 1970s and 1980s. Our analysis establishes how these features aﬀect the
dynamic adjustment of local budgets.
Our main ﬁndings are as follows. First, government investment plays themost important role in the adjustment process, with 44-52% of the budget
shocks being adjusted through government investment in the following year.The
ﬁgures explain 83-100% of adjustments in permanent unit innovations in grants
and own revenue. This magnitude is quite large when compared to the magnitude of government current expenditure. For instance, a 1 yen decrease in
own revenue and grants is covered by a reduction in government investmentof 0.446 yen and 0.473 yen, respectively. In contrast, the response of government current expenditure is very low, explaining only 1-11% of budget shock.
From a cross-country comparison, these ﬁgures show that government investment in Japan plays a relatively large role in adjusting local budgets. Second,
government investment is highly volatile. A 1 yen increase in government investment accompanies a reduction in government investment by 1.001 yen in
the following year, which is quite high when compared to those of other coun4

tries. In contrast, the magnitude of volatility in own revenue and grants is small.
This implies that municipalities face restrictions in adjusting their ﬁscal balancethrough own revenue sources and that the higher-level government is rigid inproviding grants. Third, in contrast to the role played by the expenditure side,
the municipalities’ own-source revenue plays a limited role in the adjustment
process of local budget balancing. This is diﬀerent to other countries, such as
the United States, where own revenue is used to adjust ﬁscal imbalances. In
addition, grants from the central government do not play a signiﬁcant role inJapanese municipalities. Again, this is in contrast to other countries. For example, in Spain, inter-governmental transfers help to adjust ﬁscal imbalances
through central grants, and in Germany, inter-governmental transfers are used
to adjust ﬁscal shocks through equalization transfers.
We then break down our sample. We divide our sample based on the population size to establish whether the adjustment process depends on the size ofa municipality. In this additional analysis, we discuss ﬂypaper eﬀects, the softbudget problem, and substitutability/complementarity between government investment and current expenditure, based on the size of the municipality.
The rest of this paper is organized as follows. In Section 2, we introduce
our analytical model and data. In Section 3, we present our preliminary results
to ensure the model is speciﬁed correctly. In Section 4, we show the results.
An international comparison is also presented in this section. In Section 5, we
perform the additional analysis, and the ﬁnal section concludes the paper.

2

Framework and Data

2.1

Analytical framework

The analytical framework employed in this study is the vector error-correction
model (VECM), similar to that used in Buettner and Wildasin (2006), Buettner (2009) and Solé-Ollé and Sorribas-Navarro (2012). Denoting own-source
revenues (mainly tax revenues) as Rit , government capital expenditure (invest-

5

ment) as GIit , expenditures excluding public investment and debt service (hereafter government current expenditures) as GC
it , net intergovernmental transfers
as Zit , debt service as Sit and ﬁscal deﬁcit as Dit , the government’s budget
constraint is represented as
Dit = GIit + GC
it + Sit − Rit − Zit .

(1)

Buettner (2009) considered two types of intergovernmental transfers, namely
ﬁscal equalization transfers and grants. Japanese municipalities receive various
kinds of intergovernmental transfers, some of which are matching grants, whileothers are block grants. Here, we group the various types of intergovernmental
transfers into one component. We explain the reasons for this in the next
subsection. From the government’s budget constraint, we express the VECM(p) of the ﬁve variables as follows:∆Yit = γDi,t−1 +pΓj ∆Yi,t−j + uit ,

(2)

j=1

′
where Yit = (GIit , GC
it , Sit , Rit , Zit ) and b = (1, 1, 1, −1, −1) and thus Dit =b′ Yit . Here, γ and Γj s are the parameter matrices to be estimated. In (2), p
denotes the lag length.
The VECM estimation generates a number of coeﬃcients. To interpret theestimation results, we use these coeﬃcients to compute the present value of theimpulse response for each variable with respect to innovations.2

2.2

Data

We use two panel data sets of Japanese municipalities. The ﬁrst set (PanelA) covers a 25-year period (1977-2001), and the second (Panel B) covers a 34year period (1977-2010). The reason for preparing two data sets is the Heisei
municipal mergers. The number of municipalities was stable during the period

2 See Appendix for more information.

For more detail, see also Appendix C in Buettner(2009).

6

covered by the ﬁrst data set: 3280 in 1971 and 3249 in 2001. The Heisei municipal merger reduced the number of municipalities from 3241 on April 1, 2002
to 1750 on April 1, 2010. Therefore, the ﬁrst set covers a shorter period, but isimmune to the municipal mergers. The second set covers a longer period but
may be contaminated by the mergers.
To purge the eﬀects of municipal mergers, we exclude the municipalities thatwere merged during the period of the ﬁrst data set. This could create a sample
bias, but the bias would be quite small because the number of municipalities wasalmost stable, as mentioned previously. The second data set covers the samemunicipalities included in the ﬁrst set, and we merge the data retrospectively
based on the municipal boundaries as of March 31, 2011.3 There are 3210
municipalities in the ﬁrst data set and 1726 in the second set.
Our data are based on the settlement of ordinary accounts. We aggregate
the ﬁscal data for our analysis into ﬁve variables, consistent with the framework described in the previous section: own-source revenues (Rit ), government
investment (GIit ), government current expenditure (GCit ), net intergovernmental
grants (Zit ), and debt service (Sit ). Fiscal deﬁcit (Dit ) is computed following
equation (1).
We decompose government expenditure into investment, current expenditure, and debt services. We have data on investments and debt services, andcalculate the government current expenditure as expenditure excluding public
investments and debt services. The reasons we diﬀerentiate between government capital expenditure and current expenditure are as follows. First, regional
governments face a trade-oﬀ in allocating funds between capital and current
expenditures, which has been extensively investigated in the literature. Second,
Japanese local governments have implemented the government investments as
3 The Japanese fiscal year runs from April 1 to March 31.

Almost all municipal mergers

were made without dividing the municipalities, but there was one exception. Kamikuisshiki
village was divided into two areas in 2006. The northern area merged with Kofu city andthe southern area merged with Fuji-Kawaguchiko town. We have assumed that the proper
Kamikuisshiki village merged with Kofu city.

7

a part of ﬁscal stimulus packages (e.g., Bruckner and Tuladhar 2010). Local
governments also play a crucial role in implementing the redistributive policy(Joumard and Kongsrud 2003, Hayashi 2010). Third, arguably related to thesecond point, the correlograms of the government capital and current expenditures are very diﬀerent. Table 1 shows correlograms for our ﬁve variables.
As shown, the autocorrelations of the four variables other than government investment decrease slowly as the lag increases. However, government investment
decreases relatively rapidly.

Table 1

We group the various types of intergovernmental grants into one component,
Zit . This includes the central and prefectural government subsidies (CGS), local
transfer tax (LTT) grants, and local allocation tax (LAT) grants. CGS and LTT
grants are matching and purpose-speciﬁc grants, while LAT grants are supposed
to be block and general grants. We group these transfers into one component
for the following two reasons. First, the Japanese central and local governments
are highly integrated (e.g., Muramatsu et al. 2001), and LAT grants are alsoutilized to mobilize the local governments by revising the LAT grants formula.4
As a result, LAT grants are often seen as matching grants. Second is the data
availability. We do not have data on how much CGS and LTT are expended forgovernment investment and consumption at the municipality level.
The other three variables are deﬁned as usual. The own-source revenues(Rit ) include tax revenues, fees, donations, and miscellaneous revenues. The
4 The tendency for high integration between local and central governments in Japan is cap-

tured by the Integrated Model of Muramatsu et al. (2001), in which local governments are
assigned a large range of tasks, competencies of the central and local governments are intertwined, and the central government steers local governments through partnerships. A typicalexample of a highly integrated or closed partnership between the local and central governments is the various public work projects implemented on the initiative of local authorities,
with the central government monitoring day-to-day operations.

8

ﬁscal deﬁcits (Dit ) are calculated as GIit + GC
it + Sit − Rit − Zit . All the variables
are deﬂated and expressed in per capita terms, as in the literature.

3

Specification

Prior to our estimation using the VECM, we need to verify whether the ﬁscal
deﬁcit (Dit ) and the ﬁrst diﬀerences of the other ﬁscal variables (GIit , GC
it ,Sit , Rit , Zit ) are stationary. We employed a panel unit root test developedby Pesaran (2007), which allows for serially correlated errors and cross-section
dependence. The results, shown in Tables 2 and 3, suggest that the ﬁscal deﬁcit
is stationary and that the ﬁrst diﬀerences of the other ﬁscal variables are also
stationary in both data sets.5 The result that the ﬁscal deﬁcit is stationary could
suggest that the ﬁscal deﬁcits of the Japanese municipalities are not explosive,at least in the long run.

Table 2
Table 3

Panel data analyses typically consider municipality ﬁxed eﬀects. The VECM
uses the variables with the ﬁrst-diﬀerence and individual eﬀects diﬀerentiatedout in levels, but we use the ﬁscal deﬁcit variable in levels. Thus, the existenceof municipality ﬁxed eﬀects should be tested. In the literature (e.g., Buettner
and Wildasin 2006), this hypothesis is tested using the likelihood ratio test.
However, when municipality ﬁxed eﬀects exist, the usual ﬁxed eﬀect estimatoris no longer consistent (e.g., Arellano 2003). As such, to check for municipality
ﬁxed eﬀects, we utilize the Durbin-Wu-Hausman (DWH) test, which requires
a consistent estimator, even when municipality ﬁxed eﬀects exist. To obtainsuch estimates, we use the one-step GMM estimation by Arellano and Bond
5 We conduct the same panel unit root test for the sub-samples divided by population size,and obtain the same results.

9

(1991), which is now a standard approach (Bond 2002) when the explanatory
variables include the lagged dependent variables and predetermined variables,
as in our estimation equation (2). The ordinary least squares (OLS) estimator isconsistent and eﬃcient under the null that municipality ﬁxed eﬀects exist, but
not consistent under the alternative, while the GMM estimator is consistentunder both the null and the alternative.
We set the lag length to be 4, considering the time dimension of our data
(25 and 34 years) in this test. Our estimation equation (2) does not include
exogenous variables, so our instrumental variables are all “GMM-style” variables (Roodman 2008 ); in other words, the explanatory variables with 6 to 10
periods lags. To avoid the many-instruments problems caused by the long time
dimension, we “collapsed” our instrumental variable set. We conduct equationby-equation estimations using OLS and GMM, and compare the coeﬃcient vectors. The Hansen’s J statistics support the validity of the instruments. The
DWH test results are shown in Table 4.

Table 4

Although the non-existence of municipality ﬁxed eﬀects cannot be rejected
for some estimation equations, it can be rejected for three equations for Panel A.
In addition, the results of the GMM estimation are implausible, perhaps becauseof weak instruments. Considering similar results in existing literature, we choose
to conduct equation-by-equation estimations using an OLS estimation. The
equations with a time trend are also estimated, but here we report only the
results without the time trend because both estimations generate similar results.
For estimations using the VECM, we need to determine the lag length. Considering the time dimension of our data (25 and 34 years), we begin with a lagof four years. We then use a likelihood ratio test to possibly reduce the numberof lags in all the equations at the same time. The test statistics obtained areshown in Tables 5 and 6. Since a reduction of the lag length is rejected in all

10cases, we use a model with four lags.6

Table 5
Table 6

4

Main Results

Table 7 shows the results of the VECM estimation based on OLS estimation for
Panel A (1977-2001, 3210 municipalities). Table 8 shows the same results forPanel B (1977-2010, 1726 municipalities). We assume a discount rate of 3% tocalculate the present value for both panels.7

Table 7
Table 8The diﬀerence between the results of the two data sets does not seem to belarge. This could indicate that the municipalities did not change their ﬁscal
adjustment behavior with regard to their own revenue, government capital andcurrent expenditures, and debt service before and after the Heisei municipality
mergers. Therefore, we focus on the results of Panel A (1977-2001, 3210 municipalities), which has more data and can avoid the possible bias caused bymunicipal decisions on consolidation.
We summarize the results by referring to previous discussions on evidence
from the United States (Buettner and Wildasin 2006), Germany (Buettner2009), and Spain (Solé -Ollé and Sorribas-Navarro 2012).
6 Buettner and Wildasin (2006) also employed a lag length of four years, while Solé-Ollé

and Sorribas-Navarro (2012) used a lag length of three years. Buettner (2009) employed amodel with six lags, but reports that the estimates of models with four or five lags do notshow major differences.
7 Previous studies also employ a discount rate of 3%, and indicate that the qualitative
results are not sensitive to different discount rates, because most of the fiscal adjustments
occur during the first few years.

11

4.1

Subsequent adjustments

The columns in Table 7 show how innovations in one variable aﬀect subsequentadjustments in both itself and other variables. For example, the ﬁrst column
reveals how a 1 yen change in own revenue in one period aﬀects the subsequentevolution of own revenue, government investment, government current expenditure, grants, and debt service. The ﬁgures show that a 1 yen decrease in own
revenue leads to an increase in future own revenue of 0.462 yen, a decrease ingovernment investment and current expenditures of 0.446 yen and 0.014 yen,respectively, and an increase in grants of 0.085 yen. Grants do not play a significant role in oﬀsetting own-revenue losses; the magnitude is not very large. The
magnitude of the role played by grants in adjusting to a shock in own revenue
is somewhat similar to of the United States, but even larger than observed in
Spain and Germany, where grants do not play a signiﬁcant role in oﬀsetting
negative own-revenue shocks.
The results in all columns show that innovations in the budget components
tend to be partly oﬀset by future changes in the same component. For instance,in response to a 1 yen decrease in own revenue, an adjustment of 0.462 yencomes from an oﬀsetting change in the present value of future own revenue.
Following previous studies, it is therefore instructive to calculate the response
to a permanent 1 yen increase in each variable. These results are displayedin the lower part of Table 7. For example, in the ﬁrst row, the ﬁgures showthat 0.831 yen of the balancing adjustment to a permanent unit change in own
revenue comes from government investment.
The second column shows how a shock to government investment is adjusted.
A 1 yen increase in government investment is followed by a 0.076 yen increasein government current expenditure and a 0.051-yen increase in grants, neitherof which are statistically signiﬁcant. While government current expenditure
works against balancing the budget in response to an innovation in government
investment, own revenue and grants respond have a positive eﬀect on balancing
the budget, although not all that much. The distinctive feature is that a 1 yen

12increase in government investment is followed by a 1.001 yen decrease in future
investment. Thus, future government investment plays an excessively importantrole in oﬀsetting innovations to investments, because own revenue and grants are
not suﬃcient to adjust to local budget shocks caused by changes in government
investment.
A 1 yen innovation in government current expenditure (third column) is
followed by a decrease in future current expenditure of 0.420 yen and in government investment of 0.436 yen. The role of grants in balancing the budget in
response to a change in government consumption is positive, but rather limited(0.147).
An innovation in grants (fourth column) is mainly balanced by investment
and oﬀsetting changes in grants themselves. The response of own revenue is verysmall, explaining less than 5% and explaining 8.9% of the permanent increase.
This suggests the existence of strong ﬂypaper eﬀects, which we discuss later.
The response of own-source revenue is low in Spain as well, explaining 6.6%of the permanent increase. However, in the United States, the response ofown-source revenue to a 1 dollar innovation in central grants is one digit larger
than in the case of Japan and Spain. Here, 0.144 dollars explain 27.3% of thepermanent increase. The responses in the German municipalities resemble thosein Spanish municipalities. In this case, the responses of own-source revenue to a
1 euro innovation in central grants and equalization transfers are 0.02 euro and0.04 euro, explaining 4.3% and 8.8% of the permanent increase, respectively.
The ﬁfth column shows the responses to innovations in debt services. A 1
yen increase in debt services is followed by a 0.366 yen decrease in future debt
services. Grants improve the ﬁscal balance, but play a small role. Here, 9.8%
explains 16.7% of the permanent increase. This ﬁnancial deterioration is covered by signiﬁcant decreases in government investment (-0.526). However, ﬁscal
imbalances are not fully covered by these responses, which aﬀect the primary
surplus. We discuss this in more detail later.

13

4.2

Responsiveness

Each row in Table 7 tells us how responsive that variable is to changes toitself and other variables. The second row is noteworthy in that government
investment responds most signiﬁcantly, adjusting between 0.436 and 0.526 yenof a unit innovation in other ﬁscal variables. The responsiveness of government
investment is relatively larger than that of government current expenditure, andis larger than in the United States, Germany, or Spain. For instance, government
expenditure adjusts about 0.338-0.508 dollars of a 1 dollar change in the UnitedStates. In Germany, the same adjustment is 0.274-0.531 euros, and in Spain,
0.261-0.289 euros.
While government investment is highly responsive to ﬁscal shocks in Japan,
the country’s own revenue is less responsive. The ﬁrst row shows that Japan’s
own revenue does not work to adjust ﬁscal imbalances caused by exogenous
innovations in other variables. Here, the absolute values range between 0.021
and 0.057 yen. Own revenue in other countries plays a more aggressive role,adjusting 0.144-0.162 dollars of innovations in other variables in the UnitedStates, 0.085-0.515 euros in Spain, and 0.020-0.185 euros in Germany. The
eﬀect in Japan is because the country’s municipal tax system is less ﬂexible
than in other countries, as pointed out by Mochida (2001, pp.96-97).8

4.3

Flypaper effect

The fourth column in Table 7 is related to the ﬂypaper eﬀect, according towhich, local government expenditure increases signiﬁcantly. Some estimates
increase by almost 100% when the local government receives a grant from thecentral government.
The study on Spain shows that the response of own-source revenue to a 1
euro innovation in central grants is low (just 0.018 euro, explaining 6.6% of
8 Municipalities appear to have options when setting tax rates and the tax base. However,in practice, this flexibility is limited. For instance, under local public finance law, they cannot
apply for permission for debt financing when they set their tax rates below the standard tax
rate, which means most municipalities apply the same standard tax rate.

14

the permanent increase). In this case, the greater part of changes in grants isabsorbed by public expenditure, providing evidence of the ﬂypaper eﬀect. This
result diﬀers from the United States. There, the response of own-source revenue
to a 1 dollar innovation in central grants is one digit larger than the Spanish case,namely 0.144 dollars, explaining 27.3% of the permanent increase. As explained
previously, the responses of own-source revenue to innovations in central grants
in Germany resemble those of Spain, again showing possible evidence of the
ﬂypaper eﬀect.
Compared to these countries, Japan provides evidence of a relatively strong
ﬂypaper eﬀect.9 The ﬁgures in the fourth column show that the response of ownsource revenue to a 1 yen innovation in central grants is negative, but just -0.041
yen. These ﬁgures are one digit smaller than in the United States, but almost
the same as Spain and Germany. This implies that an increase in grants-in-aid
sticks strongly to government expenditure. Speciﬁcally, the ﬁgures show thatthe responses of government investment and current expenditure explain 100.4%
and 4.1% of the permanent increases, respectively. This indicates that the
response of government investment explains just all of a permanent unit increasein grants. In other words, the grants stick to government investment, but not togovernment current expenditure. This diﬀerence is partly because “mandatory”
expenses, such as personnel expenses and social assistance expenses, account fora large share of current expenditure, while public investment as a capital outlay
can be adjusted more ﬂexibly.

4.4

Soft-budget constraints

The fourth row in Table 7 is related to soft-budget constraints. In the UnitedStates, grants from a higher-level government respond signiﬁcantly to innovations in municipal own-source revenue and expenditure. A 1 dollar innovation in
own-source revenue and public expenditure results in a 0.086 dollar decrease and
9 The flypaper effect has been observed in Japanese municipalities using different methods.

For example, see Nagamine (1995) and Doi (1996, 2000).

15

a 0.082 dollar increase in grants, respectively, from the higher-level government.
The response of grants to innovations in debt services is quite modest, being justhalf of that for the other variables. These results imply that municipalities havethe potential to induce transfers from higher-level governments through theirown-source revenue and local expenditure decisions. Similar evidence of government expenditure is reported in Spain: a 1 euro increase in public expenditure
increases government grants by 0.158 euro. In addition, government grants in
Spain respond quite signiﬁcantly to innovations in debt services: a 1 euro increase in debt services increases grants by 0.229 euro. However, higher-levelgovernment grants do not respond signiﬁcantly to innovations in own-source
revenue. The evidence for Germany gives diﬀerent results: here, government
grants do not respond to innovations in own-source revenue and public expenditure, and the German municipalities do not induce grants from higher-levelgovernments by expanding their expenditure.
The response of government grants in Japan is mixed. On the one hand, theresponse of grants to innovations in government current expenditure has thesame features as Spain and the United States. A 1 yen increase in government
current expenditure leads to a 0.147 yen increase in grants, suggesting that themunicipalities might induce grants by expanding current expenditure. However,a 1 yen increase in government investment yields a 0.051 yen increase in grants,
but this is not statistically signiﬁcant. The change is negative when based on the
Panel B (longer period) data set. Thus, these results do not necessarily support
the existence of a soft-budget problem associated with public investment.
The soft-budget problem in Japan is currently a controversial topic. Whilesome studies suggest the problem exists (e.g., Akai et al. 2003, Doi and Ihori
2006), others do not (e.g., Nishikawa and Yokoyama 2004). Our results indicatethat municipal budgets are hard for capital expenditure, but soft for current
expenditure. This diﬀerence may be due to the autocorrelation of government
investment decreasingly rapidly as the lag increases, while that of current expenditure does not. That is, for municipal governments, government investment
is often once-oﬀ, but current expenditure shocks tend to persist because cur16

rent expenditure includes expenses for personnel and welfare, which are seen as“mandatory” expenses. The central government, understanding this diﬀerence,
may tend to support municipalities hit by current expenditure shocks.

4.5

Primary Surplus

Summing up the ﬁrst four rows in Table 7, we calculate the adjustments in primary surplus to innovations in policy variables. In the United States, a 1 dollar
increase in own-source revenue results in an oﬀsetting change by 0.94 dollars
in primary surplus, showing that the primary balance improves by fractions ofa percentage (0.06 dollars). The adjustments in primary surplus to an innovation in public expenditure and grants are not much: -0.041 dollars and +0.045
dollars, respectively. The changes in primary surplus to innovations in policy
variables in Spain are only half those of the United States and may be negligible; a 1 euro innovation in own revenue, government expenditure, and grants
each changes the primary surplus by +0.023 euro, -0.028 euro, and +0.033 euro,
respectively. The absolute value of changes in Germany is also close to unity;a unit innovation in own-source revenue, government expenditure, grants, andequalization transfers each result in an oﬀsetting change by -0.993, 0.989, -0.986,
and 0.984 euro, respectively.
The size of adjustments in primary surplus in Japan denotes a tendency
similar to that in other countries. From Table 9, obtained by adding the ﬁscal
responses of the ﬁrst four rows of Table 7 and 8, we see that the absolute valuesof the changes are close to unity in all cases except debt services. This implies
that the response of primary surplus is satisfactory-to-negligible.10 However,
the results using Panel B, a longer sample period, show a somewhat diﬀerent
10 From Table 9, it seems that fiscal balance is not restored by innovations in debt services.

However, as Buettner (2009) mentions, this reflects temporal fluctuations in debt services.
With regard to Japan, since the estimate of the present value of future changes in debt
services in response to a 1 yen increase is -0.366 yen, 0.634 yen of a unit innovation in debt
services is permanent. Since the present value of a change in primary surplus is 0.534 yen,
the figures conform closely to the predictions based on intertemporal budget constraints.

17

picture. In this case, the absolute values of the changes in primary surplus are
smaller than in the Panel A data set. This might reﬂect the fact that, while
the average ﬁscal deﬁcit per capita had a tendency to increase until 2003, it
decreased between 2003 and 2008 under the policy, by Koizumi and subsequentadministrations, that capped the issuance of government bonds.

Table 94.6

Volatility

More than 70% of adjustments in Spain are reportedly held by the future valueof the ﬁscal variables that experienced the shock. Of these, public expenditureis the most volatile, with 72.9% of adjustments to public expenditure shocks
being held by the future value of the variable. Much of this is also true forthe volatility of public expenditure in the United States (0.716) and Germany(0.851).
Government investment is the most volatile among the other policy variables
in Japan. However, the band of ﬂuctuations in Japan is much wider, which is
unique to the country. Table 7 shows that government investment is highly
volatile (-1.001).
Government current expenditure is less volatile than government investment(-0.420). Japan’s own-source revenue is less volatile than that of Germany (0.569) and Spain (-0.709), with a value of -0.462, but similar to the UnitedStates (-0.348). The volatility of grants (-0.528) is an intermediate position
among that of the other countries: the United States (-0.473), Spain (-0.726),
and Germany (-0.546).

4.7

Complementarity and substitutability

In our analysis, we divide public expenditure into government capital and current expenditures. This enables us to examine whether government investmentcomplements or substitutes government current expenditure, and vice versa.
18

Evidence shows that the two items constituting government expenditure aﬀect
each other, but that the eﬀect of innovation is asymmetric. On the one hand, a
1 yen increase in government investment increases government current expenditure by 0.076 yen, and on the other hand, a 1 yen increase in government
current expenditure reduces government investment by 0.436 yen.
This might reﬂect the eﬀects of public investment on ﬁscal-revenue expansion. Public investment stimulates the economic activities that make room for
municipalities to increase their current expenditure. However, at the same time,the increase in current expenditure tightens ﬁnancial conditions, thus forcing
municipalities to reduce public investment.

5

Additional Results: Effects of Municipal Size

The process of adjustments may be inﬂuenced by the size of the municipality
associated with the ﬁscal institution. Thus, we replicate our analysis after classifying the municipalities into four categories: cities, including Tokyo’s wards, andtowns/villages with large, medium, and small populations. Cities are deﬁned
as having a population of not less than 50 thousand and are jurisdictions thatsatisfy certain prerequisites; towns/villages are jurisdictions with a populationof less than 50 thousand.11 The ﬁscal institutions associated with the municipalities vary between cities and towns/villages. For instance, unlike towns andvillages, cities are delegated a part of the authority for urban planning and welfare policies. More speciﬁcally, ordinance-designated cities have a broader tax
base and wider authority than towns and villages, including, for example, theright to operate a public lottery.

Table 10

11 Municipality population sizes changed during the sample period, so we divided the sample

municipality sizes by the population size of 1977, the first year of the sample period.

19

We now discuss the diﬀerences and similarities across the four categories.
The clearest feature in Table 10 is that government investment is the main
policy instrument used to adjust to ﬁscal shocks, irrespective of municipality
size. It is therefore not surprising that government investment is highly volatilein all categories. In addition, some of our main results discussed in the previous
section do not depend on the size of municipalities. For instance, own revenue
does not play a signiﬁcant role in adjusting to ﬁscal shocks, and does not respondto an innovation in grants, implying that the ﬂypaper eﬀects seem to exist in
all categories. The same results are evident in the Panel B data set. The
complementarity/substitutability between government investment and current
expenditure is in line with the previous section in that a decrease in government
investment follows an increase in current expenditure.12
However, we do observe some diﬀerences among municipalities of diﬀerent
sizes. First, a notable diﬀerence is the larger ﬂuctuations in own revenue insmaller municipalities. For instance, in response to a 1 yen increase in own revenue, cities and large municipalities decrease their future own revenue by 0.068
yen and 0.108 yen, respectively. However, medium and small municipalities decrease their own revenue by 0.355 yen and 0.413 yen, respectively. This might
be related to the tax items the large and small municipalities rely on. The
revenue share of corporate inhabitant tax, which is levied by the municipality
where a corporation has business establishments, is relatively large in the larger
municipalities. In contrast, smaller municipalities tend to rely on property tax.
It is natural that the business-related tax revenue is more prone to shocks thanproperty tax revenue. Thus, tax revenues are strongly inﬂuenced by short-term
shocks, but make a relatively quick recovery in larger municipalities. For instance, a negative revenue shock will reduce corporate inhabitant tax revenue
12 As shown in the second column, the response of current expenditure to an innovation ingovernment investment is negative in cities and large and medium towns/villages. However,
the response of current expenditure in small municipalities is positive, which seems to havea significant impact on the response of current expenditure to innovations in government
investment, as shown in Table 7.

20

to larger municipalities for a given year, but since this does not last long, they
avoid having to reduce their future own revenue. On the other hand, once a
negative shock hits smaller municipalities, the decrease in own revenue persists.
This is because the share of property tax revenues in their budget is relatively
high and decreases in property tax revenue do not recover promptly.
Second, as shown in the ﬁrst column, an innovation in own revenue induces
larger municipalities to increase government investment and current expenditureby more than in smaller municipalities. While a 1 yen increase in own revenue
increases government investment in small and medium municipalities by 0.350
yen and 0.585 yen, respectively, it increases investment in large municipalities
and cities by 0.633 yen and 0.810 yen, respectively. The response of current expenditure shows the same tendency as government investment. In other words,
larger municipalities show a larger response in current expenditure to innovations in grants. The mechanism behind this ﬁnding can be connected with the
grants scheme. The LAT grants from the central government are reduced byan amount (75% at the municipal level) proportional to the increase in the tax
revenue. Hence, the smaller municipalities, which receive the central grants,
do not increase public expenditure on the same level as the revenue increase
because they recognize that the central government grants will be reduced with
the increase in tax revenue. In contrast, the larger (and richer) municipalities
tend not to receive grants, or receive fewer grants. These municipalities are
not as concerned about the reduction in grants, and thus, they increase theirgovernment expenditure in response to the increase in revenue.
Third, the fourth row in the second column in Table 10 shows little evidence
that larger municipalities can induce grants from a higher-level government by
expanding government investment. However, a municipality with a small population might have an incentive to increase its government investment excessively,
as this increase will be ﬁnanced by the central government. The second column
in Table 10 show that a 1 yen increase in government investment increases the
grants in small municipalities by 0.047 yen. Furthermore, the third column reveals that municipalities in all categories induce grants by expanding current
21

expenditure. Speciﬁcally, in small municipalities, a 1 yen increase in current
expenditure increases the grants from the higher-level government by 0.437 yen.
This observation could be consistent with the standard argument that the central government tends to support small municipalities with a weak ﬁnancialbase, where “mandatory” expenses, such as personnel and welfare, constitutea high percentage of their budgets. In this case, foreseeing central government
aid, these municipalities take opportunistic actions.13
Finally, the last row shows that a 1 yen innovation in all variables has a bigger
inﬂuence on the primary surplus in municipalities with a larger population. For
instance, in cities, a 1 yen increase in grants results in an oﬀsetting changeof 0.906 yen in primary surplus, indicating that the primary balance improvesby 0.094 yen. In contrast, the improvement in the primary balance in small
municipalities is 0.042, which is only half the size of cities. This tendency is also
observed in the Panel B data set, and so it is considered a steady pattern.

6

Concluding Remarks

In this study, we examined the dynamic adjustment of municipal budgets inJapan using the VECM and compared the results to similar results for theUnited States, Germany, and Spain. Our main ﬁndings are summarized below.
First, Japanese municipalities respond to ﬁscal shocks mainly by adjusting
their expenditure. Speciﬁcally, government investment plays a more prominentrole than government current expenditure; 44.6-47.3% of an innovation in own
revenue and grants is adjusted through government investment in the following
year, explaining 83-100% of the permanent increase. In contrast, government
current expenditure plays a limited role in balancing the local budget. Government investment in Japan is highly responsive, which contrasts signiﬁcantlywith the situation in the United States, Germany, and Spain.
Second, in contrast to the role played by the spending side, the municipalities’ own-source revenue plays a limited role in balancing the local budget. This
13 However, this result is weakened to a certain degree in the Panel B data set.

22

is in contrast to the case of the United States, where own revenue is used toadjust ﬁscal imbalances. In addition, grants from the central government do notplay a signiﬁcant role in Japanese municipalities. This contrasts with Spain andGermany, where intergovernmental ﬁscal transfers do play a role in adjustingﬁscal imbalances, through central grants in the former, and through equalizationtransfers in the latter.
Third, government investment is highly volatile compared to that observedin other countries. In contrast, the magnitude of the volatility in own revenue
and grants is relatively small, implying that the municipalities face restrictionsin adjusting ﬁscal balances through own-revenue sources, and that the higherlevel government is relatively rigid in providing grants.
Fourth, the complementarity/substitutability between government investment and current expenditure is somewhat mixed. On the one hand, a 1 yen
increase in government current expenditure leads to a reduction of 0.436 yen
in government investment. On the other hand, a 1 yen increase in government
investment leads to an increase of 0.076 yen in government current consumption.
Fifth, an international comparison shows that municipalities are likely tohave soft budgets, but that this is not the case in Japan. However, an additional
analysis shows that, while larger municipalities have no incentive to expand
their government investment, and therefore induce grants from the higher-levelgovernment, small municipalities might do so. Furthermore, the ﬁgures showthat small municipalities have a strong incentive to expand current expenditure
to induce grants from the central government. This might be because the system
of LAT grants, which aims to close the ﬁscal gap among municipalities, induces
opportunistic behavior in small municipalities.
Finally, the responses of government investment explain almost everything
about permanent unit increases in grants, providing evidence of the ﬂypaper
eﬀect. Speciﬁcally, grants do not stick to government current expenditure, but
are likely to stick to government expenditure, regardless of the size of the municipality.

23Appendix
We compute the present value of impulse responses following Buettner (2009).
Our estimation equations are∆Yit = γDi,t−1 +pΓj ∆Yi,t−j + uit ,

(3)

j=1

′
′
where Yt = (GIt , GCt , St , Rt , Zt ) , bt = (1, 1, 1, −1, −1) and thus Dt = bt Yt . The

transition of the ﬁscal deﬁcit is:
Di,t−1 = b′ ∆Yi,t−1 + Di,t−2(4)Following Bohn (1991) and Buettner (2009), the VECM can be represented asa ﬁrst-order VAR:
Xit = BXi,t−1 + vit
where



Γ1 + γb′
I


B≡
0


0

Γ2 + γb′0Γ3 + γb′0Γ4 + γb′
0

0
0
0

I
0
0

0
I
b′

0





∆Yit
 ∆Yi,t−1 Xit ≡  ∆Yi,t−2  ,
 ∆Y

i,t−3
Di,t−4


γ
0 
.. 

. ,
0 
1




uit
 0 
 . 


vit ≡  ..  .
 . 
 . 
.
0

Based on this rearrangement, the prediction of the k-period ahead value createdby an innovation to period t can be written as:X̂i,t+k = Bk vit .
When we set vit as vk , whose k-th element is unity and others are zero, torepresent a unit innovation, the present value of the impulse response in them-th budget component is:hm ρn Bn vk = hm ρB[1 − ρB]−1 vk ,π̂(m, k) =n≥124

where hm is a selection vector with unity as its m-th element and zeros elsewhere,and ρ is a discount factor.

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27

Lags
Own revenues
Investment
Current expend.
GrantsDebt services

0
1.000
1.000
1.000
1.000
1.000

1
0.975
0.762
0.965
0.976
0.948

2
0.960
0.657
0.951
0.956
0.930

3
0.946
0.596
0.940
0.946
0.907

4
0.929
0.552
0.922
0.933
0.882

Table 1: CorrelogramLag order(p)Own revenues
Expenditures
Investments
Current expend.
GrantsDebt service
Deﬁcit∆ Own revenues∆ Expenditures∆ Investments∆ Current expend.
∆ Grants∆ Debt service

1-2.664-3.177-3.337-2.855-2.573-2.427-3.545-3.933-4.130-4.220-4.095-4.006-3.783

***
***
***
***
**
***
***
***
***
***
***
***

2
-2.204-2.978-3.091-2.667-2.343-2.157-3.152-2.680-3.497-3.746-3.233-3.258-2.873

***
***
***
***
***
***
***
***
***
***

3
-2.285-2.665-2.498-2.554-2.076-2.093-2.740-2.309-3.223-2.949-3.264-3.055-2.743

***
*
**
***
***
***
***
***
***

Table 2: Panel Unit Root Test (1977-2001, 3210 municipalities)
Note.∗, ∗∗, and ∗ ∗ ∗ indicate significant difference at 10, 5 and 1 percent levels, respectively.

28

Lag order(p)Own revenues
Expenditures
Investments
Current expend.
GrantsDebt service
Deﬁcit∆ Own revenues∆ Expenditures∆ Investment∆ Current expend.
∆ Grants∆ Debt service

1-2.322-3.320-3.535-2.891-2.616-2.350-3.270-4.775-5.045-5.147-5.044-4.644-4.380

***
***
***
**
***
***
***
***
***
***
***

2
-2.045-2.973-3.199-2.515-2.243-2.059-2.801-3.746-4.024-4.215-3.812-3.598-3.350

***
***
*
***
***
***
***
***
***
***

3
-2.267-2.805-2.951-2.379-2.094-1.960-2.567-3.200-3.518-3.610-3.374-3.197-2.867

***
***

**
***
***
***
***
***
***

Table 3: Panel Unit Root Test (1977-2010, 1726 municipalities)
Note.∗, ∗∗, and ∗ ∗ ∗ indicate significant difference at 10, 5 and 1 percent levels, respectively.

Own Revenues
Investments
Current expend.
GrantsDebt services

Panel A: 1977-2001
Test statistics p-value
22.36
0.38
28.45
0.13
65.63
0.00
57.40
0.00
20.80
0.47

Panel B: 1977-2010
Test statistics p-value
34.84
0.03
124.93
0.00
79.94
0.00
70.28
0.00
29.16
0.11

Table 4: DWH tests for municipal-ﬁxed eﬀects

Lag order(p)χ2 (16)
Municipality-ﬁxed eﬀects?
χ2 (12836)

4→ 3124231.8 [0.000]
with lag length = 4
20880.4 [0.000]

3→ 2125032.8 [0.000]
with lag length = 320715.6 [0.000]

Table 5: Speciﬁcation Test (1977-2001, 3210 municipalities)
Note. The log-likelihood statistics on cross-equation restrictions are reported. The p-values
are in parentheses.

29Lag order(p)χ2 (16)
Municipality-ﬁxed eﬀects?
χ2 (12836)

4→ 369049.6 [0.000]
with lag length = 411305.4 [0.000]

3→ 269529.4 [0.000]
with lag length = 311338.0 [0.000]

Table 6: Speciﬁcation Test (1977-2010, 1726 municipalities)
Note. The log-likelihood statistics on cross-equation restrictions are reported. The p-values
are in parentheses.

Response of
Own revenue
Investments
Current expend.
GrantsDebt Service
Own revenue
Investments
Current expend.
GrantsDebt Service

Innovation to
Invest. Current Grants Debt Ser.
0.057
0.021
-0.041
0.022(0.023)(0.024) (0.023)(0.036)-1.001-0.4360.473-0.526(0.072)(0.080) (0.076)(0.144)0.076-0.420-0.0180.113(0.047)(0.053) (0.040)(0.069)0.051
0.147-0.5280.098(0.062)(0.059) (0.065)(0.134)0.223
0.224-0.166-0.366(0.076)(0.068) (0.073)(0.113)
Response to permanent increase
2.054
0.036
-0.0890.031(18.888)(0.040) (0.048)(0.053)0.831-0.7521.004-0.831(0.147)(0.114) (0.101)(0.186)0.024
2.516-0.041
0.173(0.135) (27.131)(0.086)(0.090)-0.158
2.927
0.254
0.167
(0.092) (22.326)(0.100)(0.222)-0.2556.618
0.384-0.356(0.113) (61.764)(0.092) (0.162)

Revenue-0.462(0.044)0.446(0.081)0.014(0.073)-0.085(0.050)-0.136(0.058)

Table 7: Present Value Responses (Panel A, 1977-2001, 3,210 municipalities)
Note. Standard errors are in the parentheses.

30Response of
Own revenue
Investments
Current expend.
GrantsDebt Service
Own revenue
Investments
Current expend.
GrantsDebt Service

Innovation to
Invest. Current Grants Debt Ser.
0.092
0.055
-0.083-0.052(0.031)(0.049) (0.030)(0.049)-0.929-0.2840.547-0.669(0.077)(0.118) (0.082)(0.173)0.042-0.291
0.094
0.047(0.047)(0.107) (0.042)(0.076)-0.0220.309-0.219-0.063(0.092)(0.154) (0.098)(0.193)0.122
0.186-0.071-0.326(0.041)(0.064) (0.039)(0.096)
Response to permanent increase-0.4210.078-0.107-0.078(15.206)(0.068) (0.036)(0.070)0.976-0.4030.701-0.991(0.190)(0.161) (0.064)(0.209)-0.012-0.8080.120
0.065(0.144) (12.503)(0.050)(0.102)
0.022
0.755
0.431
-0.089(0.217)(9.109)(0.198)(0.285)-0.312-1.5740.262-0.091(0.094) (25.320)(0.069) (0.051)

Revenue-0.432(0.047)0.552(0.103)-0.006(0.080)0.011(0.120)-0.176(0.048)

Table 8: Present Value Responses (Panel B, 1977-2010, 1,726 municipalities)
Note. Standard errors are in the parentheses.

Panel A
Panel B

Own
Revenue-1.007-0.967

Innovation to
Gov. Current Grants
Invest. Expend.
1.033
1.025
-1.0240.958
0.938-0.943

Debt
Service
0.534
0.507

Table 9: Present Value of Change in Primary Surplus

31Response ofOwn
revenue
Investment

Current
expend.
GrantsDebt
ServicesPrimary
surplusCategoryCity
Large
Medium
Small
City
Large
Medium
Small
City
Large
Medium
Small
City
Large
Medium
Small
City
Large
Medium
Small
City
Large
MediumSmall

Innovation to
Revenue Invest. Current-0.068 -0.208-0.123-0.108 -0.029-0.088-0.3550.003-0.038-0.4130.021-0.0040.810 -1.165-0.454
0.633 -1.067-0.4440.585 -1.082-0.4670.350 -0.974-0.2810.188 -0.162-0.4260.115 -0.066-0.3570.085 -0.096-0.447-0.0360.008-0.3070.122 -0.183
0.191-0.135 -0.096
0.271
0.034 -0.191
0.100-0.2790.047
0.437-0.1850.183
0.205-0.0980.104
0.154-0.1090.111
0.141-0.1560.192
0.252-0.9150.931
0.908-0.9490.970
0.953-0.9480.977
0.954-1.0120.975
0.983

Grants0.069-0.013-0.030-0.008
0.694
0.611
0.678
0.547
0.227
0.182
0.214
0.084
-0.060-0.191-0.062-0.382-0.160-0.062-0.036-0.140-0.906-0.937-0.955-0.958Debt Ser.
-0.165
0.023
0.008
0.007
-0.860-0.535-0.609-0.428-0.113-0.135-0.0430.011-0.240-0.044-0.0460.145-0.345-0.372-0.369-0.376
0.539
0.671
0.758
0.491

Table 10: Present Value Responses (1977-2001)
Note. The first upper row in each cell stands for the response of cities. The figures in thefollowing rows stand for the response of large, medium, and small towns/villages.

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