Fiscal Policy Effectiveness in Japan: Experiences from Recent Policies
Tomomi MiyazakiAbstract
This paper examines the effects of Japanese fiscal policy after the 2008 global financial
crisis so called Lehman’s fall. A mixed vector autoregression (VAR)/event study
approach is used for this purpose. We especially focus on the effects of stimulus
packages related to environmental-related policy. The empirical results show that the
program of eco-car tax break and eco-car subsidy was useful to stimulate the productionof automobile industries.

1. Introduction
In the wake of the 2008 global financial crisis, governments in many developed
countries conducted economic stimulus packages. Some countries like the U.S. included
environmental-related policies in the package. Such “green” initiatives play asignificant role in powering economic recovery as well as environmental protection.
On the other hand, the Japanese government also implemented environmental-related

The author would like to thank Akihiro Kawase, Yuji Kawano, Masao Tsuri, and Prateek Goorha for
their insightful comments and suggestions. The delegates of 12th international conference of theJapan Economic Policy Association and the 51th annual meeting of the Public Choice Society This
work has been financially supported by a Grant-in-Aid for Scientific Research (Young Scientist) andfinancial aid from the Zengin-Foundation. The usual disclaimer applies.

Graduate School of Economics, Kobe University. E-mail: miyazaki@econ.kobe-u.ac.jp

1stimulus packages after the crisis. For example, the subsidies for the purchase of energy
conserving home appliances (the so-called Eco-point) was implemented from May 2009
to March 2010. This is the subsidy plan allowing refundable points when purchasingenergy efficient electronic appliances. Further, the program of eco-car tax break andeco-car subsidy were done for the periods of April 2009 to February 2011.1 Under these
programs, if a consumer buys a new car that emits less CO2 or has low-fuelconsumption such as gas-electric hybrid car, the car tax will be lowered and subsidized amoney.2
However, to the author's knowledge, there has been no research which examines thesize and persistence of fiscal policy in Japan after the global financial crisis by drawing
attention on these environmental-related stimulus packages. Morita (2012), Rafiq(2012), and Vu (2012) examine the size and persistence of the Japanese fiscal policy byincluding the periods of the global financial crisis through Vector Autoregression (VAR)
model. However, these paper do not focus on the environmental-related policies. On theother hand, a recent paper Alhulail and Takeuchi (2014) by examines the effects of

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The effective periods of eco-car tax break and eco-car subsidy program were extended after February
2011. However, since this extension was decided by the coalition government of the Democratic Partyof Japan and People’s New Party, it seems to be different from the policy implementation as one of thestimulus packages mentioned above. Therefore, we do not include the extended periods of thesepolicies when we construct a dummy variable to implement estimations by using a narrative approach.
2 For the fiscal policy response after the global financial crisis in Japan, please see Iwaisako (2010)
and Asako (2012). Moreover, for the details of the program of eco-car tax break and eco-car subsidy,
please see Alhulail and Takeuchi (2014).

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eco-car tax break and eco-car subsidy on the sales of ten eco-friendly vehicles in Japan.
However, Alhulail and Takeuchi (2014) do not examine the size and persistency of thepolicy effects.
The purpose of this research is to examine the effects of fiscal policy after the 2008
global financial crisis in Japan. Especially, we give an eye on two environmental-related
stimulus packages such as the subsidies for the purchase of energy conserving home
appliances (hereafter the eco-point) and the program of eco-car tax break and eco-car
subsidy. Here we would like to use the “narrative approach.” This approach enables us
to examine the effects of policy using a time series method in conjunction with an event
study. To capture policy changes, the dummy variables are constructed based on theannouncement or implementation of the monetary and fiscal policy. The advantage ofthis approach is to consider not only the size and persistence of each policy change but
also the effects of different fiscal policies in different periods after the devastating
financial crisis.
Our empirical results show that the program of eco-car tax break and eco-car subsidy
had positive and significant effects on the production of automobile industries. On theother hand, however, the effect of eco-point on electric appliance production is estimatedto be insignificant. Section 2 explains how dummy variables are used for the3

identification of fiscal shocks when we implement a narrative approach. Section 3
provides the empirical results. Section 4 concludes the paper.

2. The Dummy Variables for Fiscal Shocks
We discuss the dummy variables used to identify fiscal policy shocks on the basis of
official documents.
Incidentally, note that we face an identification problem in selecting the dummy
variables. If we allow the dummy associated with each major tax and spending shock tohave its own distributed lag effect, we cannot identify the effects of each individual
fiscal policy because they are too close to each other in terms of the time periods inwhich they were announced and/or implemented. Therefore, the value of the dummy
variable for a policy is changed from 0 to 1 either in the month in which the policy was
implemented, and it continues to take a value of 1 for the time periods in which thepolicy was in effect, as in the case of Blanchard and Perotti (2002) and Miyazaki (2010).
Considering these, we make the dummy variables that capture the effects ofenvironmental-related policies. To do so, we clarify the initial and final period of theimplementation of the environmental-related policies. The first dummy variable is “Eco4Point” that specifies the implementation periods of the eco-point. The other one is “EcoCar” that show the periods that program of eco-car tax break and eco-car subsidy iseffective. “Eco -Point” equal to 1 from May 2009 to March 2010 and “Eco-Car” equal to 1
from April 2009 to February 2011.

3. Empirical Results
3.1. Data Sets
Throughout the paper, monthly data are used. Since the sample periods after the 2008
global financial crisis are very short, it is difficult to set a certain level of lag length
when we use quarterly data. Therefore, we use the monthly data for estimation as in
the case of Miyazaki (2009) and Kozuka et al.(2012).
The variables that captures the production are y tEl , which denotes indicator of electric
appliance production (minsei-yo denki kikai, in Japanese), and y tAuto , which indicatesthe one of automobile production (jou-you sha, in Japanese) (2010=100).3 y tEl covers the
production of air conditioner and refrigerator, which were targeted by the eco-point.4

3

To capture the effects of each policy, it is also assumed that we focus on the production of the items
which are directly affected by the policy such as gas-electric hybrid car, air conditioner, andrefrigerator, etc. However, the data provided by METI cannot be divided into detailed items.
4 Incidentally, the eco-point also targeted the consumption of the liquid crystal television. This iscaptured by the production of electric machine for home use (minsei-yo denshi kikai, in Japanese).

5These data are downloaded from the homepage of the Ministry of Economy, Trade andIndustry (METI) at http://www.meti.go.jp/statistics/. Here we focus on the individual
industries that are assumed to be directly related to each policy. This is why as long as
these subsidies or tax breaks are assumed to intend the increase in production of eachindustries, it would be favorable to examine the effects on each industries.5 Therefore,
as we see later, we run a VAR model by the combination of each policy dummy and theindex of production of each industries.6
Both y tEl and y tAuto are seasonally adjusted using the X12-ARIMA method. The sample
period is from January 1980 to December 2012. We take the logarithm for y tEl and y tAuto .

3.2. Outline of VAR Estimation
The variables grouped under “Case 1” are Eco point and log y tEl . “Case 2” is the casethat consists of Eco Car and log y tAuto . In order to estimate the effects on individual
industries, we estimate two VAR groups.
Throughout the analysis, we follow the recent convention seen in the VAR literature

However, the item targeted by the eco-point of this data is limited to television. Since y tEl covers thebroader items targeted by the policy compared to the production of electric machine for home use, we
use y tEl .
5Harada and Kageyama (2011) and Hayo and Ohno (2011) also examine the effects on the productionof each industry by using VAR model.
6 We estimate our VAR model by using the index of industrial productions instead of y El or y Auto .
ttHowever, the impulse response functions are not estimated to be significant.

6and use levels, rather than the first or second differences, for all series. As Hamilton(1994) argues, a levels specification yields consistent estimates regardless of whether or
not cointegration exists, whereas a difference specification is inconsistent if somevariables are cointegrated. The lag length is set as twelve in all cases, according to thelikelihood ratio test in Sims (1980).
Now we can set up the structural VAR model BL X t   t , where X t  D i , log y tj  ,B L   B 0  B1 L    B p L p is a pth-order lag polynomial of two-by-two coefficient matrix

B k k  0,1,  , p  , and  t   Di ,  y jt

 is vector of serially uncorrelated structural

disturbances with a mean zero and a covariance matrix   . Here Di is a dummy
variable that specify the policy change (“Eco Point” or “Eco Car”) and log y tj is thelogarithm of index of productions ( log y tEl or log y tAuto ).
Structural disturbances are assumed to be orthogonalized, and the recursive
identification procedure implies that B0 in the structural form becomes lower
triangular and the ordering in the VAR determines the degree of exogeneity of thevariables. Here we treat the policy dummy as most exogenous. It takes policy makers
and the legislature more than a month to learn about shocks to economic activity, and it
is very difficult to make discretionary adjustments to fiscal policy within a month.
Therefore, there may be no feedback from the current economic variables to fiscal

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expansion.7 The treatment may be justified from this argument.

3.3. Estimation Results
Figures 1 and 2 shows the results of Case1 and Case 2, respectively. The solid line
indicates the estimated response and the dotted lines represent the 95% confidence
intervals.
Figure 1 tells us that the effect of the eco-point is not estimated to be statisticallysignificant. On the other hand, the response of the program of eco-car tax break andeco-car subsidy on automobile industries is estimated to be positive and significant.
This implies that at least the program of eco-car tax break and eco-car subsidy waseffective to stimulate the production of automobile industries. However, the magnitudeof the effect is very small, and this positive effect becomes insignificant after fourmonths from its implementation.8

7This is followed by the argument shown in Blanchard and Perotti (2002) and Miyazaki (2009).

8 To check the robustness of the results, we conduct some another exercise by adding some policy

variables or changing the specifications. First, we reestimate the model by changing the ordering suchas  X t  log y t j , D i  . Second, we add the real effective exchange rate ( et ) to the system. This is why
the foreign factor strongly affect the production of these two industries. In this specification, theordering in the VAR is  X t  D i , log y t j , log e t  . Third, we reestimate the model by adding two
variables that capture the monetary policy: the call rate ( rt ) and money stock ( M t ). In this case, we
limit the sample periods after January 1986 because the call rate can be obtained after this month.
The ordering in the VAR is  X t  D i , rt , log M t , log y t j  . Finally, we limit the sample periods afterJanuary 1990 because we confirm a structural change after this month by following Christiano (1986)
and Cecchetti and Karras (1994). In spite of these additional test, the results are basically the same
shown in Figure 1 and 2. Detailed results can be obtained from the author upon the request.

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4. Conclusion
This paper examine the effects of fiscal policy after the 2008 global financial crisis inJapan. Especially, we focus on two environmental-related stimulus packages: theeco-point and the program of eco-car tax break and eco-car subsidy. The estimation
results of impulse response functions show that while the eco-point did not positive andsignificant effects, the program of eco-car tax break and eco-car subsidy has a positive
impact on the production of automobile industries. Incidentally, both packages were
implemented by announcing the termination. Thanks to this, the automobile production
might be stimulated by reflecting the consumer's incentive to spend before the end of
the eco-car tax break and eco-car subsidy. However, the same phenomenon might not beapplicable to the electric appliance production.
The program of eco-car tax break or eco-car subsidy is planned to attain both economic
stimulus and the reduction of carbon-dioxide from a car. This policy may be surely
effective for carbon-dioxide reduce in that the number of gas-electric hybrid automobiles
increased after the implementation of the program as shown in Figure 3. This alsosustains that the production of gas-electric hybrid automobiles surely increased thanks

9to the program, and the production of the automobile industries might also increase inaccordance with this increase. However, according to our estimation results, the effectwas not so large, and soon becomes insignificant. Please pay attention that in terms of
the evaluation of Japanese discretionary fiscal policy up after the global financial crisis,
even a policy with a positive effect has generated limited benefits for the economy.
Incidentally, we do not examine the effects on the consumption or investment. To
examine the effects precisely, we should also pay attention pay attention to theindividual items of private demand. Further, more developed techniques such as
Factor-Augmented VAR model as in Fujii et al. (2013) could be employed forinvestigation. These points should be done in future research.

References
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Figure 1. Impulse response function of the index of electric appliance production, y tEl
Eco point→
.02

.01

0

-.01

-.02
0

10

95% CI

2030

Impulse response function

Note: The solid line indicates the estimated response, and the dotted lines represent the 95%
confidence intervals.

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Figure 2. Impulse response function of the index of automobile production, y tAuto
Eco car→
.06

.04

.02

0

0

10

95% CI

2030

Impulse response function

Note: The solid line indicates the estimated response, and the dotted lines represent the 95%
confidence intervals.

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Figure3. The number of gas-electric hybrid automobiles (2005-2012)

2500000

2000000

1500000

1000000

500000

0
2005

2006

2007

2008

2009

2010

2011

2012

Source: The homepage of Automobile Information Center
URL: http://www.autoinfoc.com/hoyu/kokunaihoyu/hy-kokunaiihoyu-15.html

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