OSIPP Discussion Paper: DP-2019-E-009

Intergenerational Conflict Over Consumption Tax Hike: Evidence
from Japan
September 19, 2019

Ryosuke Okazawa*
Graduate School of Economics, Osaka City University

Katsuya Takii**
Osaka School of International Public Policy (OSIPP), Osaka University【Keywords】Consumption Tax, Fiscal Consolidation, Pension, RDD【JEL Codes】E6, H2, H31, H63【Abstract】This paper analyzes the determinants of voter preferences on
consumption tax hike using an opinion survey of Japanese citizens. We findrobust evidence that the older voter is more likely to support consumption
tax hike. We also find that the most of inter-generational difference toward
consumption tax policy is explained by the gap between citizens under sixty
and over sixty. We investigate how individual economic environment changes
in 60 years old as a result of mandatory retirement system and pension
system and find that the hours of work do not change but their degree of
dependence on the pension in household income increases at the age of 60.
Utilizing these facts, we conjecture that individuals may realize theimportance of consumption tax in order to save the value of their assets.
We would especially like to thank Real Arai for valuable discussions. We are also grateful to Nobuo Akai, Yu Awaya,
Shunichiro Bessho, Takero Doi, Makoto Hasegawa, Hirokazu Ishise, Masayuki Kudamatsu, Nobuyoshi Kikuchi,
Syuhei Kitamura, Stephan Litschig, Tetsuya Matsubayashi, Kazuki Onji, Shinpei Sano, Kimiko Terai, Eric Weeseand the participants of the seminar in Osaka University, Kochi University of Technology, Tokyo Metropolitan
University, GRIPS, Kansai Public Economics workshops. Of course, we alone are responsible for both the content
and any errors. Authors are grateful to a financial support from SPS KAKENHI [grant numbers JP25245040,
JP17H02516, JP18H03636, JP18K01658, and JP19K01698].
* Email: okazawa@econ.osaka-cu.ac.jp** Email:takii@osipp.osaka-u.ac.jp

1

Introduction

Since the outbreak of ﬁnancial crisis, many developed countries are suﬀering from enormous
government debt. Figure 1 illustrates the recent amounts of general government liabilities per
GDP in selected OECD countries. It shows that many countries have experienced government liabilities per GDP after ﬁnancial crisis. Although ﬁscal consolidation is one of urgent
macroeconomic issues for most developed countries, the processes of ﬁscal consolidation do
not seem to continue well in many countries. Why is ﬁscal consolidation so diﬃcult?
[Figure 1 here]
The political process is often considered as a cause of persistent government deﬁcit. In
the classical work, Buchanan and Wagner (1977) argue that ﬁscal consolidation policies,
such as tax increases or cuts in government spending, tend to be postponed in democraticsocieties because they burden the current electorate although they are beneﬁcial for future
generations. Since future generations have no political inﬂuence on current policy decisions,ﬁscal policies in democratic countries often cause enormous accumulation of government
debt.1 Figure 2 shows that the median age of voters consistently increases in advanced
countries in periods when government debt expansion is observed. Taking the changes in
the age distribution of the electorate in recent years seriously, the recent government debt
expansion might be explained by intergenerational conﬂict in policy preference. 2[Figure 2 here]
This paper analyzes the determinants of voter preferences for consumption tax hike,which is considered as one of the most important key instruments for ﬁscal consolidationplans in Japan, using an opinion survey conducted among Japanese citizens. To assess therole of the intergenerational conﬂict on delay of ﬁscal consolidation policy, we examine how
age of voters inﬂuences preferences for consumption tax hike. As Figure 1 and 2 show, Japan
experiences a rapid increase in the median age of voters as well as that in government debt
per GDP. Moreover, several attempts to reduce ﬁscal deﬁcits have been postponed mainly
due to political unpopularity among Japanese citizens. There are some arguments thatregard an increase in the political inﬂuence of older generations as a serious obstacle in thepolitical situations. 3 From these facts, we believe that Japan is an ideal country for our
research purpose.
1 There is also substantial literature that analyzes the debt management policies of the government froma positive perspective (a excellent survey is provided by Alesina and Passalacqua 2016). Intergenerational
conﬂict over ﬁscal policies is often noted in the literature (e.g. Cukierman and Meltzer 1989, Tabellini 1991,
Song et al. 2012, Müller et al. 2016).
2 Since aging populations typically place a ﬁnancial burden on the government through an increase in
medical spending or pension beneﬁt payments, we cannot simply regard the observed co-movement of anaging population and the accumulation of government debt is caused by a surge in political power of elderly
citizens. However, the standard political economic theory predicts that politicians in democratic countries
would heed the interests of older voters as the median age of the voters increases.
3 The political stance that gives substantial consideration to the opinions of the elderly is called “silver
democracy” and is often noted as the reason why the government fails to achieve reduction in its large
budget deﬁcit. (e.g. Ihori 2016 and Kato and Kobayashi 2017). Ihori (2016) argues that “As the diﬀerence1

Contrary to the prevailing view that older voters oppose an increase in consumption tax
to escape from the current ﬁscal burden, we ﬁrst provide robust evidence that the older
voter is more likely to support consumption tax hike. This result does not change evenif we control diﬀerences in education, income, and family structure. Interestingly, we also
ﬁnd that the relationship between support for consumption tax hike and age are non-linear
and the most of inter-generational diﬀerence of policy preference can be explained by thegap between citizens under sixty and over sixty. This indicates that there might have somemechanisms that make senior people to support consumption tax hike after 60s.
In order to uncover the reason why the old citizens tend to support consumption tax hike,we closely investigate this gap in the latter part of the paper. Knowing that many people facemandatory retirement and start to obtain the part of pension at the age of 60, we examine
whether there is a discontinuous change in the political opinion about consumption tax hikeat the age of 60 by adopting a regression discontinuity design. We ﬁnd that the supporters of
the consumption tax hike discontinuously jump up at the age of 60. The share of supporters
for consumption tax hike among citizens who just turned 60 is about 4-7% higher than thatamong slightly younger citizens. Given that the total share of support for consumption tax
is less than 40%, the estimated magnitude is large and not negligible. This indicates thatchanges in economic environments that individuals encounter at the age of 60 can be themain candidate mechanism that make senior people to change their political attitude.
Investigating institutional regularities in Japan, we identify main changes in economic
environments which many Japanese might encounter at the age of 60s as a result of Japanesemandatory retirement system and pension system: changes in employment status and changes
in the amount and the component of household income. We investigate the economic significance of these changes by adopting a regression discontinuity design.
We show that while there is a discontinuous reduction of the share of regular worker at
the age of 60, because many ﬁrms reemploy or extend the period of employment, the hours
of work and the share of employment do not show any large changes in 60 years old. As aresult, we also ﬁnd that the time allocation to leisure or home production does not show any
drastic changes in 60 years old. Moreover, we ﬁnd that a large drop in household income
at the age of 60 probably due to changes in employment status. The share of pensioner
household also jumps up at the age of 60 because many Japanese are eligible to receive apart of their pension at the age of 60. This indicates not only that people reduce total
household income, but also that their degree of dependence on the pension increase at theage of 60.
Although we cannot derive deﬁnite conclusion about mechanism from these ﬁndings,
we propose a promising hypothesis on the reason why senior people changes their political
attitude to support consumption tax hike in 60 years old. The elderly citizens would turnto support consumption tax hike after they reach age of 60 because they come to realize thein preference by age increases, the current beneﬁciary tends to hope for an increase in beneﬁt payments but isreluctant to bear their costs, and the reforms tend to be postponed. As a result, the ﬁscal burden is imposedon the future beneﬁciary. If the policy is determined by “silver democracy,” it causes the accumulation ofﬁscal deﬁcits and an increase in social security beneﬁts. (pp. 246)”.

2

importance of ﬁscal sustainability to preserve the value of property that they have gained.
The hypothesis that motives of the old voters to preserve the value of their assets cause
support of ﬁscal consolidation policy is consistent with the prediction of previous theoreticalresearch and we believe that our evidence can be considered as a valuable ﬁrst step to reﬁne apossible candidate mechanism to understand why senior people support ﬁscal consolidation
policy.
Related Literature The intergenerational conﬂict in the politics of government debt ispointed out in the previous studies that theoretically analyze the political economy of government debt. They show that the old voters generally are more likely to prefer the accumulationof the government debt to tax increase than the young voters. For instance, by building aoverlapping generation model with taxes and private intergenerational transfers from parent
to child, Cukierman and Meltzer (1989) show that low tax policy ﬁnanced by accumulationof debt is supported by the majority as long as there are citizens who want to leave negative
bequests to their oﬀsprings but negative bequests are forbidden. Song et al (2012) develop
a dynamic model where voters choose level of public good provison, taxes, and debt in eachperiod. Under the assumption that there is no risk of default, their model predicts that old
agents support high spending, high taxes, and large debt but the young wants to avoide debt
accumulation since it reduces public good provision in the near future. On the other hand,
Tabellini (1991) considers a situation where the government cannot commit to repaymentof the debt. Since the debt repudiation cause redistribution from creditors to debtors, issuing debt itself creates a coaliton of voters who support of repaying it. In particular, debt
reputation reduces welfare of the old, hence the old voters support debt repayment.
This study is also related to several studies that analyze the determinants of ﬁscal policy
preference using survey data. Many studies analyze the determinants of preference on redistributive policy (e.g., Corneo and Gruner 2002, Alesina and La Ferrara 2005, Alesina andFuchs-Schündeln 2007, Alesina and Giliano 2011, Giuliano and Spilimbergo 2013).4 However, only a few studies analyze preferences for ﬁscal consolidation policies (e.g., Blinder andKrueger 2004, Heinemann and Hennighausen 2012, Stix 2013, Hayo and Neumeier 2017).
Among them, some research reports the tendency that the old is more likely to support ﬁscal consolidation, which suggests that Japan would not be the only country that old support
ﬁscal consolidation more (Blinder and Krueger 2004, Heinemann and Hennighausen 2012,
Hayo and Neumeier 2017, Walter et al. 2018). 5
4 While several studies analyze ﬁscal policy preferences (e.g., Ohtake and Tomioka 2004, Hayo and Ono

2010, Yamamura 2012, 2014) using survey data from Japanese citizens, there is no empirical research thatanalyzes Japanese citizens’ preferences for ﬁscal consolidation.
5 Blinder and Krueger (2004) investigate the process of public opinion formation using a telephone surveyof a sample of the US population. Although they do not address ﬁscal consolidation policies directly, theauthors show that older respondents are more likely to consider the ﬁscal deﬁcit a serious problem while they
are less likely to consider raising tax an appropriate way to reduce the deﬁcit. Heinemann and Hennighausen(2012) and Hayo and Neumeier (2017) also ﬁnd that older citizens are more likely to demand public debt
reduction using German Survey data. Walter et al. (2018) also ﬁnd that older voters tend to agree withausterity programs rather than young people using the original survey data in Greece.

3Although these authors ﬁnd evidence that the old is more likely to support ﬁscal consolidation, intergeneratinal conﬂict is not main concern of these research. Hence they neither
analyze the reason why the old supports consolidation policy nor provide persuasive explanations. 6 This paper contributes the literature by going further ahead. We also ﬁnd that the
supporters of the consumption tax hike discontinuously jump up at the age of 60, the timingthat many people face mandatory retirement and start to obtain pension beneﬁt. Moreover,
we provide evidence which allows us to infer a plausible candidate mechanism behind theage eﬀect: the preserving the value of asset hypothesis. To the best of our knowledge, there
is no previous study that discuss the mechanism behind the age eﬀect. 7
Given that the arguments that the aging electorate causes political bias toward the interests of the older electorate are commonly observed in many advanced countries, our ﬁnding
would be informative for thinking about politics of ﬁscal consolidation policies generally.
Like Japan, loose ﬁnancial administration is also attributed to political rule by the older
generation in countries where the accumulation of sovereign debt is outstanding, such as
Italy and Greece. For instance, in an article in the Financial Times, the common view of
the young Italian toward “gerontocracy”, politics ruled by the old, is described as follows“(young people) feel stiﬂed by Silvio Berlusconi’s older generation of politicalleaders who drove Italian public debt to crippling levels and kept the top jobs tothemselves for decades.”8
On the contrary to such the view, our ﬁndings suggest that the political inﬂuence of old
citizens would not necessarily be obstacle for ﬁscal consolidation even if they only careabout their self interests.
The remainder of the paper is organized as follows. In Section 2, we explain the back6 The intergenerational conﬂict over policy preference is studied more substantially in research that an-alyzes demand for government spending. Much research examines the diﬀerences in opinion between generations over public education spending. The empirical research using survey data typically conﬁrms thatthe older voter is less likely to support spending on public education, which is consistent with the standard
economic theory since government spending on public education is considered redistribution from older toyounger generations (e.g., Bruner and Baldson 2004, Cattaneo and Wolter 2009, Rattsøand Sørensen 2010,
Sørensen 2013, Bruner and Johnson 2016).
7 Our research is also related with studies analyze how pension eligibility aﬀects household decision using
regression discontinuity approach. Edmonds et al. (2005) investigate how an increase in household incomechanges their living arrangement by exploiting the institutional feature that pension eligibility discontinuously
changes at age 60 in South Africa. They estimate the impact of turning age of 60 on household size andinterpret it as causal eﬀect of pension eligibility. By adopting a similar approach, Edmonds (2006) estimate
the impact of presence of a pension eligible person in household on schooling and labor supply of children
in South Africa. Although we also estimate the impact of turning the pension eligible age, we should be
careful to interpret the estimated change as causal eﬀect of receipt of pension since the pension eligibility
could not be the only diﬀerence between over and below age of 60 among Japanese citizens. Hence we takea more deliberate approach. After estimating impact of turning age of 60 on support for consumption tax
hike simply, we provide additional evidence and discuss about the reason why citizens changes their attitude
toward tax policy at age of 60.
8 “Italy’s Generation X hopes to loosen grip of gerontocracy” Financial Times, December 2, 2016.
Accessed at https://www.ft.com/content/e1075190-b7d6-11e6-961e-a1acd97f622d?mhq5j=e5 (March 5,
2018)

4

ground of the recent ﬁscal consolidation policies in Japan. In Section 3, we explain our data
and the deﬁnitions of the variables in our estimate. Section 4 provides the basic empiricalresults. In Section 5, we provide the results from our RDD and show that there is a discrete jump in support consumption tax hike at the age of 60. In Section 6, we discuss how
Japanese mandatory retirement system and pension system can change economic environment of senior people at the age of 60 and provide evidence from which we can potentiallyinfer a candidate mechanism that that make senior people to change their political attitude
to support consumption tax hike. In section 7, we provide additional evidence exploiting
the diﬀerence by subgroup. In section 8, we discuss possible candidate mechanism that isinferred from our evidence and propose the preserving the value of asset hypothesis. In ﬁnal
section we conclude.

2

BackgroundIn this section, we provide the background history of ﬁscal policy in Japan. It demonstrates
that consumption tax hike is always considered as one of the most important instruments
for ﬁscal consolidation policy in Japan.
It is well-known that the amount of government debt of has been sharply increased during
the recent decades in Japan. The gross liability of the general government exceeds 220% of
GDP in 2016, which is highest number among advanced countries.
In response to accumulation of the public debt and the severe ﬁscal situation, the government has attempted to implement ﬁscal consolidation since the mid 1990s. In 2001, thegovernment developed the basic plan for ﬁscal policy (Basic Policies for Economic and Fiscal
Policy Management and Structural Reform), also called “Big-Boned Policy” (honebuto no
ho-shin), and established the two targets of ﬁscal policy to restore the sustainability: (i) The
government restricts the issue of new government bonds to a maximum of 30 trillion yen.
(ii) The government will transform the primary balance of the budget into a surplus.9
Although the ﬁscal balance gradually improved in the mid-2000s, the primary balanceagain deteriorated due to the ﬁnancial crisis in 2008. After the change in the government on
September 9 in 2009, the administration of the Democratic Party of Japan formulated theﬁscal plan (Basic Frame for Fiscal Consolidation: Medium-term Fiscal Plan) in 2010 andemphasized the aim of improving the primary balance and persistently reducing the amountof government debt to GDP ratio. In the plan, the government aimed to reduce the primarydeﬁcit of national and local governments to GDP ratio by half from 2010 to 2015 and bring
the primary balance of the budget into surplus by 2020. 10
The comprehensive reform of tax systems have played a key role in the ﬁscal consolidation plans of the government since 2011. The comprehensive reform of tax systems have
9 “Basic policies for economic and ﬁscal policy management and structural reform 2001” approved by thecabinet. Accessed at https://www.kantei.go.jp/jp/kakugikettei/2001/honebuto/0626keizaizaisei-ho.
html (Febrary 21, 2019)10 “The strategy of ﬁscal policy management” approved by the cabinet. Accessed at https://www.kantei.
go.jp/jp/kakugikettei/2010/100622 zaiseiunei-kakugikettei.pdf(Febrary 21, 2019)5

played a key role in the ﬁscal consolidation plans of the government since 2011. For instance,
the IMF report also indicates that it was necessarily to raise the government revenue giventhat an aging population made diﬃcult to reduce government expenditure, and raising consumption tax rate should be the key measure for that purpose (Keen et al. 2011). The
numerical studies also indicate that the government must adjust its ﬁscal policy to maintainthe ﬁscal sustainability (e.g., Imrohoroglu and Sudo, 2011; Arai and Ueda, 2013; Hansen
and Imrohoroglu, 2016; Imrohoroglu et al; 2016).
The reform proposal in 2011 planed that the consumption tax rate would be raised
gradually to 10% by the middle of 2010.11 On the other hand, the government limited theusage of the revenue from consumption tax to the expenditure related with social security,
health care, and countermeasure against decline in birth rate to win public support for tax
increase. In 2012, the government revised the Consumption Tax Act and stipulated the useof the consumption tax revenue.
The consideration of economic conditions, however, have allowed discretion and made theimplementation of ﬁscal consolidation politically diﬃcult. In 2014, the consumption tax rate
was raised from 5% to 8% as planned. However, in 2014, a further increase in the consumption
tax rate from 8% to 10%, which was scheduled in October 2015, was postponed to April
2017 by the political decision of the prime minister Shinzo Abe. Moreover, it was postponed
again to October 2019 in June 2016 because of economic stagnation and sluggish domestic
demand. Political consideration underlies delays in ﬁscal consolidation. The consumption
tax is unpopular with voters and, hence, it is necessary to avoid tax increases to win theelection. The opposition to tax increases remains strong at present, and there are concernsof a further delay in ﬁscal reform.
In sum, consumption tax hike was considered as one of the most important instruments forﬁscal consolidation policy in Japan. While the government has tried to increase consumption
tax to make public ﬁnance sustainable, the implementation of consolidation policy was always
postponed because it is unpopular policy among Japanese people.

3

Data

In this section, we describe our data and the measurement of preferences for the consumption tax rate and variables to investigate intergenerational diﬀerences in attitude toward
consumption tax hike.
We use survey data from the Japanese General Social Survey (JGSS) and opinion poll
data from the University of Tokyo/Asahi Shimbum Survey (UTAS). The JGSS is a Japaneseversion of the General Social Survey and nationallly representative data including demographic characteristics such as age, sex, family structure, education, and income. 12 The
11 The consumption tax was introduced in Japan in 1988.

Then, the tax rate was 3%. In 1998, theconsumption tax rate was raised from 3% to 5%.
12 The Japanese General Social Surveys (JGSS) are designed and carried out by the JGSS Research Centerat Osaka University of Commerce (Joint Usage / Research Center for Japanese General Social Surveys
accredited by Minister of Education, Culture, Sports, Science and Technology), in collaboration with the

6

JGSS also collects opinions, preferences, and data on the sense of values of a wide rangeof respondents. While the survey has been conducted periodically since 2001, we use thedata from 2010 (JGSS2010) and 2012 (JGSS2012) because these surveys investigate opinions
on the desirable consumption tax rate because public discussions on the consumption tax
increase attracts much attention at the time when the two surveys were conducted. Ourdata contain citizens’ opinions on the desirable level of consumption tax at the time before
the government eventually decided on the consumption tax increase.
While the JGSS contains cross-sectional data, and respondents are not the same in the2010 and 2012 surveys, these two surveys use the same method and contain many overlapping
question items. We pool the data from the two surveys and analyze preferences for ﬁscal
consolidation using the pooled data.
As secondary data source, we use data from the University of Tokyo/Asahi Shimbum
Survey (UTAS), which has jointly conducted public opinion polls since the 46th Lower House
general election in 2012.13 The survey was conducted nationwide and questionnaires weresent to 3,000 voters; responses were received from 1,900 voters, and data on the attitudes
toward various policy dimensions including diplomatic issues, political reform, trade policies,
and ﬁscal policies were obtained. We use the UTAS to back up our ﬁndings obtained in the
JGSS.
Preferences for the Consumption Tax Rate Let us ﬁrst discuss how to measure thepreferences for consumption tax hike using the JGSS survey data. We measure preferences
for consumption tax hike using the following question on the consumption tax rate: “At
what level do you think the consumption tax rate should be?” This question was posed
to 2,507 respondents in the JGSS 2010, approximately half of the respondents in the JGSS
2010, and 4,667 in the JGSS 2012. The respondents were asked to choose their answers fromsix alternatives, which are composed of two categories with the tax rate less than 5 %, onewith a tax rate of exactly 5%, and three with tax rates higher than 5%. 14 We focus onwhether the respondents choose a tax rate higher than 5%, which is the actual consumption
tax rate when each survey is conducted and construct a binary variable that takes a valueof 1 if the respondents choose alternatives that indicate tax rates higher than 5% and 0
otherwise. In the following analysis, we regard those who choose tax rates higher than 5%
as supporters of the consumption tax increase and empirically analyze the determinants.
Institute of Social Science at the University of Tokyo. The project is ﬁnancially assisted by the Japanese
Ministry of Education, Culture, Sports, Science and Technology and Osaka University of Commerce. The
JGSS adopts both interview and detention methods using a questionnaire to collect survey data. The
questions on subjects that would relate to social justice or morals are posed using the detention method.
The survey population is composed of men and women from 20 years old to 89 years old. The survey subjects
are selected using a stratiﬁed two-stage sampling method.
13 The UTAS is conducted by Masaki Taniguchi at the University of Tokyo and the Asahi Shimbun.
14 Although the questions were the same for the JGSS 2010 and 2012, there was a slight diﬀerence in theiralternatives. While the six alternatives were (1) 0%, (2) 1 to 4%, (3) 5%, (4) 6 to 7%, (5) 8 to 9%, and (6)more than 10% in the JGSS 2010, The alternatives in 2012 were (1) 0%, (2) 1 to 4%, (3) 5%, (4) 6 to 9%, (5)10 to 14%, and (6) more than 15%. To control any possible inﬂuence caused by the diﬀerences in the answer
categories between the JGSS 2010 and 2012, we include a survey year dummy in the following analysis.

7

In the UTAS, the respondents are also asked to provide their opinion of the consumption tax increase using the following statement: “In the long run, it is inevitable that theconsumption tax rate will be higher than 10%.” The respondents are required to choose
their answers from ﬁve alternatives: agree, somewhat agree, cannot say (between agree anddisagree), somewhat disagree, and disagree. We use each respondent’s response to thesequestions as their preference for the consumption tax increase.
Control Variables Following the literature, we control demographic variables such as sex,
marital status, number of children, education, employment status, and annual householdincome in our analysis. According to their terminal education record we classify respondents
into the following four categories elementary and junior high school, high school, some college,
and university. Employment status is classiﬁed into four categories in the JGSS data: regular
employment (seiki-koyo), part-time employment (hiseiki-koyo), self-employment, and notworking. In the UTAS data, we created two diﬀerent categories, public servant and student,
in addition to the four categories. These variables are designed to control for demographic
characteristics among citizens that might inﬂuence their preference for ﬁscal consolidation.
However, there is no information on household income, marital status, family structure in
the UTAS data.15
We also use the following indicators as additional controls in some speciﬁcations. (1)living in a large city, (2) bad health, (3) house ownership,16 (4) trust in politicians.17 (5)experience of charity, and (6) will to volunteer. The last two variables are included only in
JGSS 2012, which was conducted in the year following the Great East Japan Earthquake.
We use these two variables as a proxy for respondent altruism.
Policy Preference JGSS contains several questions about policy preference of respondents. In order to conﬁrm whether a similar tendency is observed in preference on otherkinds of policies, we use the opinion toward government’s responsibility to provide life security, health care for the elderly and redistribution policy and investigate how the age of
respondents is related with their preferences on these policies.
Receipt of pension We identify the respondent who receives pension beneﬁt by exploiting
a question about the source of household income in JGSS. We deﬁne receipt of pension as
an indicator for whether household of respondent reveives a pension beneﬁt. Note that the
respondents not eligible to pension can be included the category of pension recipients if theirspouse or family in the household receive a pension.
Time Use As working time, we use the average hours worked per week which is asked
to respondents in JGSS. We also use information about lifestyle of respondents. The re15 We provide rigorous deﬁnition of variables in Appendix.
16 Stadelmann and Eichenberger (2012, 2014) show that public debts capitalize into prices of property.

House ownership might aﬀect policy preference through the capitalization eﬀect of public debt.
17 Stix (2013) shows that the credibility of ﬁscal consolidation matters with regard to attitudes towardﬁscal consolidation policies.

8spondents are asked the frequency of shopping, cooking dinner, cleaning, and washing ina typical week. From these questionaries, we deﬁne indicators for whether respondents dothese activities almost everyday. Although we have only limited information on leisure of
respondents, we also use average daily hours of watching TV as proxy of leisure time.
Summary Statistics We drop observations if the data of demographic variables is missing.
Table 1 and 2 provide the summary statistics for our sample. Table 1 shows that 39% of
respondents of the JGSS support a consumption tax hike.
[Table 1, 2 here]
Table 3 shows how opinions of respondents of JGSS toward desirable consumption tax
rates vary among diﬀerent demographic groups. It shows that approximately half of all
respondents prefer the status quo. There is a tendency that the elderly citizens are more
likely prefer tax increase than younger citizens. While 46% of those aged in their 60s support
a consumption tax increase, only 29% of those aged in their 20s support a consumption tax
increase. Probably due to general perception about serious ﬁscal situation in Japan, few
people hope for a reduction in consumption tax rate though a certain fraction of young
respondents hopes for a reduction in consumption taxes. Panels B and C in Table 3 compare
the gender diﬀerences. The results show that female respondents are less likely to support a
consumption tax increase. The tendency that the fraction of tax hike supporters increases
with age is observed both in the male and female sample, although it is less obvious in thelatter. These ﬁndings contradict the standard argument that the older generation would
postpone the implementation of consolidation policies and impose greater ﬁscal burden on
future generations.
[Table 3 here]

4

Basic FactsFirstly, we provide robust evidence that the older voter is more likely to support consumption
tax increase.

4.1

Japanese General Social Survey

Following the literature on ﬁscal policy preferences, we control several demographic variables
to isolate the impact of age on support for a consumption tax increase, which cannot be
explained by the correlation between age and other demographic variables. We use thefollowing regression model to clarify how tax policy preferences are related to age and othervariables,
Yit = β0 + β1 Ageit + β2 Xit + δt + ϵit(1)where Yit refers to whether the respondent i supports the consumption tax increase. The
subscript t refers to the survey year. The control variables Xit include the demographics
9

of the respondent i such as sex, marital status, number of children, education, employment
status, and annual household income. Moreover, we always include the survey year ﬁxed
eﬀect δt , which captures any diﬀerences between the survey years. 18 Our main concern iswhether the coeﬃcient of age, β1 , is positive or negative.
Table 4 provides the estimation results from our basic speciﬁcation. The importantﬁnding is that older individuals are signiﬁcantly more likely to support a consumption tax
increase even if we control the demographic variables. In all speciﬁcations, the impact of age
is signiﬁcantly positive, and the estimated coeﬃcient is approximately 0.5 to 6%. Therefore,
aging 10 years increases the probability that the respondent will support a consumption tax
increase by approximately 5%, indicating that the intergenerational diﬀerence in preference
for the consumption tax should not be negligible.19[Table 4 here]
The positive relationship between age and support for a consumption tax increase isrobust even when we include the additional control variables. Column (2) in Table 4 showsthat estimation result when we control residential area, house ownership, and health status.
Whether the respondent lives in a large city, house ownership and the subjective healthstatus are not related to support for a consumption tax increase. More importantly, theestimated impact of age barely changes even if we control these variables. Column (3) showsthat support for a tax increase is also not signiﬁcantly related to trust in politicians, and theintergenerational diﬀerence in preferences for a consumption tax increase do not disappear
even if we control trust in politicians. Column (4) reports the results when we include theproxies of altruism as additional control variables. There is a tendency for individuals who
have experience with donating or volunteering to be more likely to approve of a consumption
tax increase, which would be beneﬁcial for future generations. However, the estimated eﬀectof age barely changes even if we control proxies of altruism.
While the estimation in Table 4 assumes a linear relationship between age and preference
for a tax increase, we also estimate a model that includes dummies of age group of respondents instead of their age to allow a non-monotone relationship between age and policy
18 Even if we measure preferences for a tax increase more precisely by dividing the respondents into (i)those who choose a tax rate less than 5%, (ii) those who choose a tax rate equal to 5%, and (iii) those whochoose more than 5%, our qualitative result does not change. In this case, Yit is the ordered variable thatrefers to the degree of preference for the consumption tax increase, and we estimate (1) using an ordered
probit. The result is available upon request.
19 Table 4 also shows that family structure has an impact on preferences for a consumption tax increase.
Compared with single individuals, those who are married are more likely to support a consumption tax
increase although the estimated impacts are not signiﬁcant in all speciﬁcations. The existence of children,
however, has no signiﬁcant impact on preferences for a consumption tax increase, which is contrary to
the results in the previous literature. This result is robust when we allow the nonmonotone relationshipbetween number of children and policy preference as Table 5 shows. The relationship between education andpreference for the consumption tax increase is roughly consistent with that of previous research. There is atendency that more educated individuals are more favorable toward a consumption tax increase. Additionally,
household income is a key determinant of preference for a consumption tax increase; rich individuals are
signiﬁcantly more likely to support a consumption tax increase, which might be because of the regressivityof the consumption tax.

10

preference, Figure 3 shows that the number of supporters of the consumption tax increases
consistently with age although individuals 65-69 years old are more likely to support the tax
increase than individuals over 70.
[Figure 3 here]
The ﬁnding that older individuals tend to prefer a consumption tax increase seems to berobust but not consistent with the standard view that older individuals would place ﬁscal
burden on future generations. More importantly, the impacts seem to be much larger after
they reach 60s.

4.2

Opinion Poll by the University of Tokyo and Asahi Shimbum
SurveyTo conﬁrm the robustness of our ﬁndings, we reexamine the relationship between age andconsumption tax increases using the UTAS data. As the dependent variable is orderedvariables, and a higher number corresponds to stronger support for ﬁscal consolidation or
the consumption tax increase, we estimate using ordered probit models.
[Table 5 here]
Table 5 shows that older individuals are signiﬁcantly likely to approve of the consumption
tax increase in the long run compared to younger individuals. Strikingly, only the coeﬃcients
after 60s are signiﬁcant. That is, it suggests that the major part of age eﬀects comes fromafter 60s dummies. Overall, the estimation results in Table 5 are consistent with the ﬁndings
using the JGSS.
In sum, we ﬁnd robust evidence that, on the contrary to the standard view about intergenerational conﬂict with ﬁscal consolidation policy, older voters tend to support a consumption tax hike. We also ﬁnd that the most of age eﬀects is explained by the 60-year-old
later dummy. These results can be supported in diﬀerent data set.

5

Changes in Political attitude at Age 60

In the previous section, we ﬁnd not only that older voters tend to support a consumption
tax increase, but also the major part of inter-generational diﬀerence in the support for
consumption tax hike is explained by whether respondents are over sixty or not. As we will
discuss later, the most of Japanese citizens faces large changes in their economic situationand life style at the timing when they turn 60 because of the age requirement for national
pension system and common practices concerning elderly employment in many ﬁrms. In
order to clarify the cause of inter-generational conﬂict about consumption tax policy, we pay
special attention to change in political preference around age of 60 and examine whether
policy opinion of citizens toward consumption tax policy largely changes when they turn 60.

11

5.1

Regression Discontinuity Design

We examine change in support for consumption tax hike around age 60 by using the regression discontinuity design (RDD). Our concern here is whether being sixty sharply changes
opinions of citizens toward consumption tax policy. In terminology of RDD, the treatment
is whether the respondents is over sixty or not. By deﬁnition, assignment of the treatment isperfectly determined by the age of respondents, which is the running variable in our design.
Therefore, our approach can be regarded as sharp regression design.
Under assumption that the probability that the respondent support consumption tax
hike is function of age of respondent and continuous at age of 60, the treatment eﬀect canbe deﬁned by
T E = lim E(Yit |Ageit = a) − lim E(Yit |Ageit = a).
a↓60

a↑60

(2)

The age of respondent is only recorded in years in JGSS, hence our running variable isdiscrete. Following the procedure of Lee and Card (2008) for RD design where runningvariable is discrete, we adopt a global polynomial method to estimate the treatment eﬀect.
Speciﬁcally, we assume the following regression function:
Yit = α + γDit + f (Ageit ) + ϵit(3)where Dit is a dummy variable which takes 1 if and only if the age of respondent is 60 or overand the function f (Ageit ) is continuous at Ageit = 60. We approximate function f by highorder polynomials and allow the parameter of polynomial to vary on either side of the cutoﬀ
age. Moreover, we assume that the speciﬁcation error is random and orthogonal to age of
respondents. Under assumption of random speciﬁcation error, the least squares estimate of
the parameter γ will be consistent estimator of the average treatment eﬀect at the age of 60.
Following the suggestion of Lee and Card (2008), we use standard errors that are clusteredby the running variable. 20

5.2

Results

Our main result is presented in Figure 4, which plots the share of supporters for consumption
tax hike by age and the solid lines denote quartic ﬁt on each side of age cutoﬀ. We can see
a discontinuous break in support for tax hike at the age cutoﬀ. This evidence suggests thatthe probability that respondents prefer tax increase is larger for citizens just has turned 60
compared with the slightly younger citizens. Table 6 reports the corresponding coeﬃcients
estimates. Taking column (4) as our preferred speciﬁcation, the estimated coeﬃcient implies
that citizens just has turned 60 are 7.4 percentage points more likely than the slightly
younger citizens to support consumption tax hike. Given that the total share of support
for consumption tax is less than 40%, the estimated magnitude is large and not negligible.
The sign and magnitude of estimated eﬀec are not so sensitive to variations in the degree
20 We also report conventional heteroskedasticity robust standard errors since clustered standard errors by
the running variable have poor coverage properties (Kolesár and Rothe 2018).

12

of polynomial of the regression function. The estimation results are also robust to including
predetermined covariates, which conﬁrms the validity of the design.
[Figure 4 here][Table 6 here]
We also apply a local polynomial method by using restricting sample to respondents
around age of 60 to conﬁrm the robustness of our baseline estimates. Speciﬁcally, we estimate
the equation (2) using sample of respondents who satisfy Ageit ∈ [60 − h, 60 + h] and adopt
low-order polynomial approximation. 21 Figure 5 shows that estimated coeﬃcient when weuse only restricted sample of respondents whose age are closely to 60. Panel A and B depict
the coeﬃcients obtained using local linear and quadratic regressions for several bandwidthfrom 5 to 20, respectively, and the associated conﬁdence intervals are also reported.22 Theyshow that the magnitudes of coeﬃcients are similar to those in Table 7 and relatively stableas bandwidth changes.
Overall, these results indicate that there is a sharp change in attitude toward consumption
tax hike at age of 60 among Japanese citizens. 23[Figure 5 here]

5.3

Validity Check

The validity of RD design depend on the comparability of respondents who recently hasturned age of 60 and those who are going to be sixty. We provide two types of tests to
examine the validity of our research design.
First, we investigate the distribution of age of respondents around the age cutoﬀ. Although the respondents are not able to manipulate their age, running variable in our design,
the distribution of respondents’ age can be distorted if response rate to survey discontinuously changes at age of 60. Figure 6 shows that there is no such the break around age of
60. The more rigorous manipulation test statistically conﬁrms that there is no signiﬁcantdiﬀerence in size of respondents by age around the cutoﬀ. 24[Figure 6 here]
Second, we examine whether there are discontinuities of predetermined covariates aroundthe age cutoﬀ. Figure 7 plots the fraction of female respondents (panel A), fraction of married
respondents (panel B), mean number of children (panel C), and average years of schooling by
21 Table A.1 reports the estimator of γ for local linear and quadratic regressions.
22 We use robust standard errors to calculate these conﬁdence intervals.
23 We can ﬁnd the discontinuity at age of 60 both in sample using only respondents of JGSS2010 and JGSS
2012 though signiﬁcance of coeﬃcients are reduced (See Table A.3). While we cannot distinguish between
the eﬀect of age of respondents and cohort eﬀect precisely, there is no evidence that supports the claims thatthe observed diﬀerence in policy preference is caused by the diﬀerence in birth year.
24 The p-value of the manipulation test of the discrete running variable proposed by Frandsen (forthcoming)
is 0.922 for k = 0, which does not reject the smoothness condition.

13

age (panel D). These ﬁgures show that there are no remarkable diﬀerence in marital status,
number of children, years of education between the respondents who recently has turned ageof 60 and those who has not yet. 25[Figure 7 here]
The fraction of female respondent discontinuously decreases at age of 60, which could
cast doubt on the validity of our research design. However, we think that it would not be
a serious problem by the following reasons. First, the change in sex ratio in our sample atage 60 is not caused by discontinity of age distribution of either male or female respondents.
Panel A and Panel B in Figure A.1 show the age distribution of male and female respondents,
respectively. They show that there is no break in sample size around age of 60 both for maleand female sample and the manipulation tests do not reject the smoothness of distribution
at cutoﬀ age. Second, the magnitude of change in sex ratio at age of 60 is too small to
explain magnitude of our estimated eﬀect. In fact, the magnitude of estimated eﬀect almost
unchanged even if we control predetermined covariates (Table 6).
In summary, we cannot ﬁnd strong evidence that suggests the possibility of manipulationfrom these tests.

5.4

Other policy preference

The results in Table 6 indicate that Japanese citizen suddenly come to support for the
consumption tax hike when they reach 60-years-old. One concern is whether such changes
in support for the consumption tax hike reﬂect changes in more general political preferences.
In order to examine whether there is a discontinuity at age of 60 in general policy preference,
we conduct the same regression discontinuity design for political attitudes to other kinds ofpolicies.
We test whether there is also changes in the attitudes about the role of government forsocial security and health care for the elderly around age of 60. We also examine the general
attitude toward redistribution policies and trust in politicians.
[Figure 8 here]
Panel A , Panel B, and Panel C in Figure 8 plot the preference for health care policy, life
security for the old, and redistributive policy, by age, respectively. We can see that there are
no clear discontinuities in the measure of preference on these variables. 26 Panel D in Figure
8 shows that there is also no discontinuity in trust in politicians at age of 60. These results
indicate that it is less likely that the change in attitude toward tax policy is caused by ashift in policy preference on the role of government and trust in politicians. A discontinuouschange in political attitude is observed only about attitude toward consumption tax policy.
25 Table A.2 reports regression results which examines discontinuities in predetermined covariates. We
estimate the similar model to equation (3) with predetermined covariate as the dependent variable. Table
A.2 shows that all coeﬃcients except for female dummy are insigniﬁcant and not robust to the choice oforder of polynomial and bandwidth.
26 Table A.4 conﬁrms that change in policy preference around the age of 60 is small and not statisticallysigniﬁcant.

14

6

Why Do Citizens Suddenly Change Their Attitudes
toward Tax Policy?

In the previous section, we ﬁnd that there is a discontinuous increase in the support for
consumption tax hike at the age of 60. Importantly, the major part of our puzzling ﬁndingthat the old citizens are more likely to accept ﬁscal consolidation through tax increase canbe explained by a change in policy preference at the age of 60. In the following sections,
we attempt to understand the reason why the support for consumption tax hike jumps at
the age of 60. As we mentioned above, Japanese pension system and retirement practice
cause several changes in life style after people turn 60 in Japan. The natural conjecture isthat these institutional arrangements would inﬂuence changes in political attitude. We ﬁrst
discuss institutional arrangements of pension system and retirement in Japan.

6.1

Institutional Arrangements

The national pension system The Japanese public pension system consists of the National Pension System (Kokumin Nenkin) and the Employees’ Pension Insurance (EPI) System (Kosei Nenkin). 27 All Japanese citizens must be covered by the National Pension
System and can receive the Old-age Basic Pension (rorei kiso nenkin) when they reach ageof 65 if they have paid required contribution. The monthly full amount of Old-age Basic
Pension beneﬁt is about 65,000 yen. Even before the eligible age for the Old-age Basic Pension, the qualiﬁed recipients can receive reduced amount of pension whenever they reach ageof 60. 28
The workers in a ﬁrm with more than 5 employees are also covered by EPI. The eligibility
age for the employees’ pension has been 60 until 2001, though it started to be raised gradually
since 2001. While the old citizens who have a coverage period under EPI ststem can receive
the Old-age Employees’ Pension (rorei kousei nenkin) from the age of 65, qualiﬁed recipientsfor EPI in their early sixties can receive the specially-provided (tokubetsu shikyu) Old-age
Employees’ Pension during the transition period from 2001 to 2025. The specially provided
employees’ pension consists of the constant part (teigaku bubun) and the proportional part(hosyu-hirei bubun), and eligibility ages for each part are diﬀerent. The eligibility age for the
specially provided is currently rising in stages. The eligibility age of men for the constantpart started to rise by one year for every three years since 2001 until it reaches 65 years in
2013. That for the proportional part started to rise since 2013 by one year for every three
years and it is planned that eligibility age for all part of pension beneﬁt reach age 65 in 2025.
The eligibility age for women also started to rise in ﬁve years later from that for men. For
the constant part, the eligibility age started to rise since 2006 by one year for every three
27 There was Mutual Aid pension for public servants (Kyosai Nenkin) prior to 2015, which was integrated
into Employees’ Pension Insurance.
28 The amount of receivable beneﬁt at the age of 60 is 70 % of that for age 65. On the contrary, by delaying
the timing when they start to receive beneﬁt, the qualiﬁed recipients can also receive increased amount ofpension. If they choose to start to receive basic pension from the age of 70 or older, the amount of receivablebeneﬁt gets 142 % of that for age 65.

15years until 2018 and that for the proportional part is planned to rise since 2018 by one year
for every three years.
Table 7 summarizes the eligibility age for each part of pension beneﬁt from 1986 to 2014.
In 2010 and 2012, when the survey which we analyze has been conducted, both of male andfemale qualiﬁed recipients can receive proportional part of specially-provided Employees’
Pension from age of 60 though they cannot receive the constant-part. They also can receiveneither of basic pension beneﬁt and employees’ beneﬁt until they reach age of 65.
[Table 7 here]
The amount of beneﬁt from proportional part depends on both of number of months
covered by EPI and the past earnings of recipients. 29 Hence there is a large diﬀerence inamount of pension between men and women at age of 60. According to Ministry of Health,
Labor and Welfare (2013a), the average monthly amount of pension beneﬁts at age of 60 are
97,681 yen for men and 47,733 yen for women in 2010. The corresponding numbers in 2012
and are 96,584 yen and 48,864 yen, respectively. 30
It is important for our research that the most of Japanese citizens start to receive pension
benﬁt when they reach 60. The average monthly amount of pension beneifts that persons of
sixty can receive is smaller than the average of beneﬁts for those above 65, but they are notneligible. 31
The retirement of old workers in Japan Most of Japanese ﬁrms set retirement ageof workers in advance and can terminate an employment contract when workers reach theretirement age (teinen system). Typically, the retirement age has been set at 60 because it
had been prohibited to set retirement age to under 60 years of age by the law (the Elderly
Employment Stabilization Law, EESL)
While the retirement at age 60 has been common practice of Japanese old workers, thegovernment revised the EESL in 2006 and mandated ﬁrms to provide opportunities for
employees to work until 65 in response to rise in the eligibility age for the full pension
beneﬁt. If the mandatory retirement age is set to below 65, the ﬁrm must take any one of
the following ways to secure employment of old workers until they reach age of 65; (i) raising
the mandatory retirement age, (ii) introducing a continuous employment system (keizoku
koyoseido), and (iii) abolition of the mandatory retirement age. When the ﬁrms introduce
the continuous employment system, they can make old workers retire at once and reemploy
them on new employment contract, or they can extend their employment contract until ageof 65. According to Ministry of Health, Labor and Welfare (2006), about 84% of ﬁrms takes
29 The amount of beneﬁt from constant part is determined by the date of birth and number of months

covered by EPI of recipients. Although the working recipient can receive specially provided employees’
pension, the amount of beneﬁt is reduced or suspended if the total of monthly pension beneﬁt and monthly
remuneration from work exceeds 280,000 yen.
30 The gender gap becomes relatively small for citizens who are 65 years old and more because they canreceive both of Old-age Basic Pension and Old-age Employees’ Pension.
31 The average monthly amount of beneﬁts of Old-age Employees’ Pension are about 190,000 yen for men
and 110,000 yen for women.

16one of the above measures and more than 85% of them introduces the continuous employment
system. 32 There are very few ﬁrms that abolish the mandatory retirement age.
After the revision of EESL in 2006, the employment rate for individuals in their sixties has
risen. Kondo (2014) compares the employment rate by age between the cohort born in 19431945, which was not inﬂuenced by revision of EESL, with those born in 1946-1948, which
was inﬂuenced by revision. She ﬁnds that employment rate decreases by about 10% after age
60 in the former cohort whereas it decreases by 6-7% after age 60 in the later cohort. Kondo
and Shigeoka (2017) show that EESL revision signiﬁcantly increases the male employment
share in their early 60s but the eﬀect is only observed for workers in large-sized ﬁrms. 33
Although the revision of EESL has increased employment of early 60s, the average wagesof 60-64 year old are lower than those of 50s probably because EESL does not prohibit ﬁrms tooﬀer substantially lower wages for workers who reach mandatory retirement age. Ministryof Health, Labour and Welfare (2009) reports that about 35% of ﬁrms that introduces
continuously employment system set wages of reemployed old workers roughly 60-70% of
those at their retirement age. The decrease in wage of workers whose employment contracts
are extended at retirement age is relatively small. However, about 30% ﬁrms reduce wageof these workers by more than 10%.
The large amount of retirement allowance is the other prominent feature of retirement
system in Japan. It is usual that workers receive retirement allowance when they reach theirmandatory retirement age. According to Ministry of Halth, Labor, and Welfare (2013b),
about 75% of Japanese ﬁrms have retirement allowance plans in 2012. The fraction ispositively correlated with size of ﬁrm, 93.6% of large ﬁrms with more than 1,000 employees
have retirement allowance plan whereas only 72.0% of ﬁrms with 30-99 employees have plan.
The amounts of retirement pay depends on several factors such as the size of ﬁrm and tenureof workers. For typical worker with 35 or longer years of tenure, it is roughly 10-15 million
yen. When workers are reemployed or continuously employed after they reach the mandatory
retirement age, their timing of receiving retirement allowances depends on the case.34 While
it is said that workers generally receive retirement allowances at the timing when they reachthe mandatory retirement age, that is 60, some workers receive them at the timing when
they actually retire after reemployment.
In sum, we expect that many Japanese encounter the following changes in employment
status, the source of income and the amount of total asset at the age of 60. (i) As many
Japanese workers encounter mandatory retirement while they are reemployed, there may
32 Among large ﬁrms with more than 300 employees, 94.4% of them adopt a way to secure employment of
old workers.
33 Stephens and Unayama (2012) also ﬁnd a similar pattern using data from the 1986-2005 survey. This isprobably because the reemployment after age 60 has been already common in small ﬁrms and the employment
share of male workers in small ﬁrms does not sharply decrease at age of 60 both before and after the EESL
revision. In fact, a certain share of small ﬁrms does not set mandatory retirement age at 60 in the ﬁrst place.
According to Ministry of Health, Labour and Welfare (2009), about 30% of plants with 5 to 29 employees
did not have the mandatory retirement age and about 20% of them set it above age of 60 in 2008.
34 If workers choose to take early retirement, they can receive retirement allowance even if they do notreach mandatory retirement age.

17

be changes in working hour, employment status and the use of time. (ii) Because many
Japanese experience a decrease in wage payment as a result of reemployment and receive thepart of pension after they turn 60, both the amount and the component of household income
drastically changes. (iii) Because many Japanese receive the large amount of retirement
allowance at the age of 60, the total amount of asset increases.
We investigate the possibility of each changes in data and provide evidence from which
we can infer the mechanism of a discontinuous increase in the support for consumption tax
hike at the age of 60.

6.2

Changes in Outcome Variables at Age of 60

In this subsection we provide evidence on changes in outcome variables such as working hour,
employment status, time-use, household income, and pension reciption at the age of 60 byusing the same method as above.
Employment Status First, we look at the changes in employment status of old citizens.
Panel A in Figure 9 plots the share of respondents who does not work by age. It shows that
there is no clear discontinuity in working population around age of 60 though the share of
not working citizens is clearly increasing in age. Panel B shows that the similar pattern isalso observed in transition of hours worked per week around age 60. While average hours
worked declines with age, there is no sharp reduction around age of 60.
Panel A in Table 8 conﬁrms that there are no signiﬁcant changes in the share of working
population and work hours around the age of 60. 35 Regardless of the fact that mandatory
retirement age is set at 60 in the most of ﬁrms, there is no strong evidence that many old
workers do not stop working immediately after they turn 60. Even if the old workers continue
to work after they reach the mandatory retirement age, it necessarily does not imply that
there are no changes in their economic situations. While the EESL demands ﬁrm to provide
employment opportunities for old workers who have turned 60, it does not force them to treat
these workers in the same way as before. Therefore, there could be change in employment
contracts of workers who reach mandatory retirement age. Panel C in Figure 9 shows thatthe share of regular employed workers slightly decreases at age 60. The corresponding point
estimate in Table 8, however, is small and not statistically signiﬁcant.
[Figure 9 here][Table 8 here]
In summary, these evidence indicates that the most of citizens in our sample continue towork after the age of 60. In addition, there is not large change in employment status, suchas decrease in regular employment at age 60.
35 We provide results for several speciﬁcation in Table A. 5 in Appendix. While the coeﬃcients are signiﬁcant in some speciﬁcations, the magnitude is small and the sign of coeﬃcient is not robust to order ofpolynomial.

18

Time Use Second, we examine whether the workers change their time-use after they reachthe mandatory retirement age. The literature on consumption of households over life cycle
suggests that the substitution from market activities to home production occurs after theretirement. One possible explanation for the support of old citizens for consumption tax
increase is that the burden of consumption tax becomes relatively light for the elder generation since they substitute away from market consumption by increasing home production.
36
Although we cannot directly test this hypothesis because our dataset does not containany consumption data, we provide evidence about changes in time-use at the age of 60.
Panel A - D in Figure 10 plot the fraction of respondents who answer that they conduct
shopping, cooking dinner, cleaning, and washing every day. While it seems that the frequency
of cooking dinner slightly decreases at age of 60, there are no clear discontinuities of timeuses at age of 60. The point estimates in Panel B in Table 8 conﬁrm that there are no
signiﬁcant increases of frequency of home works at age of 60.37[Figure 10 here]
Panel E in Figure 10 provides change in time of watching TV, which we regard one proxyof leisure time. Although it shows that there is a tendency that the old citizen spends moretime to watching TV, there is no discontinuity of time spending to watch TV at age of 60.
Panel F in Figure 10 shows that there is also no drastic change in size of household, which
would aﬀect incentive of shopping and home production, at age of 60.
Overall, we cannot ﬁnd any evidence that people immediately increase their time spendingfor home production and leisure at the age of 60. This would be consistent with the ﬁndingthat the hours of worked does not change at the age of 60.
Changes in the Amount and Component of Income As we discuss before, because
many Japanese experience a decrease in wage payment as a result of reemployment andreceive the part of pension after they turn 60, we expect that both the amount and thecomponent of household income largely changes. In order to investigate this possibility, we
also provide evidence on changes in the amount and the component of household income at
the age of 60.
[Figure 11 here]

36 There are many studies that ﬁnd people reduce their consumption after the retirement (e.g.,

Hurst2008). The previous studies show that the reduction in consumption expenditure are limited to two kinds of
categories, work related goods and food expenditure (Hurst 2008). Moreover, the substitution of households
from market activities to home production is often pointed out as the reason why food expenditure declinewith age. Aguiar and Hurst (2005) show that time spending for shopping and preparing meal increases at
the timing of reduction of food expenditure, which makes the quality and the quantity of food intake roughly
unchanged. Aguiar and Hurst (2007) ﬁnd that the price paid for a particular good decreases after middle
age and it is mainly because that old people reduces food expenditure by the frequent shopping.
37 The impact on the frequency of cooking dinner is negative and statistically signiﬁcant in some speciﬁcations.

19Panel A in Figure 11 indicates that there is a sharp reduction in household income aroundthe cutoﬀ age. Panel C in Table 8 shows that the reduction is statistically signiﬁcant andimplies a decrease of more than one million yen.
Panel B in Figure 11 shows that the fraction of pension recipients discontinuity increases
at age 60. The estimated coeﬃcient in Panel C in Table 8 is statistically signiﬁcant andimplies that the fraction of pension recipients increases by more than 20% at age of 60. As
we have argued, citizens who have work experience in ﬁrms with more than 5 employees
can receive proportional part of specially-provided Employees’ Pension after they turn 60.
However, they can receive neither of the constant-part of specially-provided Employees’
Pension nor Old-age Basic Pension until they reach age of 65. Hence, the most part ofestimated increase of pension recipients at age of 60 would be caused by the respondents’
reception of proportional part of specially-provided Employees’ Pension.
In sum, these results suggest not only that people reduce total household income, butalso that their degree of dependence on the pension increase at the age of 60.

7

Heterogeneity of Eﬀect

In the previous section, we argue that many Japanese encounter changes in the employment
status and the source of income and ﬁnd that while there are no signiﬁcant discontinuities inthe employment status, hours worked, and time use, the amount and component of householdincome largely changes after citizens reach the age of 60. In particular, we ﬁnd that the
average household income sharply decreases but the probability of receipt of pension beneﬁt
signiﬁcantly increases at the age of 60. While we also discuss that many Japanese are likely
to increase the amount of total asset due to retirement allowance at the age of 60, as we haveno information about the amount of asset of respondents in our data, we cannot provide any
evidence that the asset discontinuously changes at the age of 60. 38
In this section, we conduct subsample analyses to provide further evidence that can
assist us to discuss plausible mechanisms. We exploit two dimensions of heterogeneity in
our sample. First, we compare the policy preference between male and female respondents.
Second, we investigate diﬀerence in change of policy preference of respondents by size ofﬁrms in which that have been employed.
Let us ﬁrst explain several important gender diﬀerences of working condition and economic situation in old age in Japan. Given that majority of Japanese working women does
not take regular jobs, the inﬂuence of mandatory retirement system would be relatively small
among women. Moreover, since the amount of pension beneﬁt at the age of 60 strongly depends on the past work experience of recipients, many female citizens can receive only small
amount of pension beneﬁt at the age of 60. For instance, housewives with little work experience can only receive negligible amount of pension beneﬁt even when they reach the age
38 About half of respondents in JGSS2012 are asked whether they hold ﬁnancial assets such as bond or
stock. From the analysis of the limited sample, we cannot ﬁnd evidence that indicates there is upward jumpon the share of bond or stock holders at the age of 60.

20

of 60 and get eligible for employee’s pension. Therefore, if the change in policy preferenceat the age of 60 is caused by the change in either their life style, income or asset, we expectthat change in attitude toward consumption tax policy among females would be weaker thanthat among males.
Column (1) and (2) in Table 9 shows diﬀerences in change of economic situations at theage of 60 between male and female respondents. The decrease in household income of male
respondents at age of 60 is much larger than that of female respondents and statisticallysigniﬁcant. The share of regular employment of male respondent also signiﬁcantly decreases
at the age of 60 while that of female respondent does not. On the other hand, the proportionsof pension recipients are signiﬁcantly decreased at the age 60 for both of male and female
respondents. Hence, while our data supports our arguments that men and women encounter
diﬀerent changes in employment status and, therefore, the amount of income at the age of60, it does not support the argument that there are gender diﬀerences in the share of thepension receipts. We consider that gender diﬀerences are more likely to occur at the amountof pension, which our data does not include the information about.
[Table 9 here]
The size of ﬁrms in which that have been employed might also inﬂuence the retirement
practices and the recipients of pension. As we have argued, the retirement practices of oldworkers signiﬁcantly diﬀer between large and small ﬁrms. The mandatory retirement at age
60 is relatively uncommon in small ﬁrms both of before and after the revision of EESL in2006. Therefore, if the change in policy preference at the age of 60 is caused by the distinctive
retirement practice, changes in attitude toward consumption tax policy should be stronger
among respondents who have been employed in large ﬁrms.
Unfortunately, we cannot identify the size of ﬁrm that respondent has been employed atage 60 precisely since respondents of JGSS are asked about only the current employment
status. Hence, we use the size of the ﬁrm in which respondents are employed for the ﬁrst
time as proxy of the size of a ﬁrm in which they have been employed at the age of 60. As
the frequency of job turnovers is low in Japan compared with other advanced countries, theﬁrm size of initial jobs could predict the employment status of workers in their old age fairly
well.
[Table 10 here]
According to their initial jobs, we categorize respondents into two groups: those who has
not employed at all or worked at a ﬁrm with less than 99 employees as the ﬁrst job andthose who has worked at a ﬁrm with more than 100 employees or public authorities as theﬁrst job. Table 10 shows the relationship between the ﬁrm size of initial jobs and current
employment status among respondents aged 50 to 59. It indicates that only 23.1 percent of
individuals who have initially worked at a small ﬁrm work at a large ﬁrm or public sector in
their ﬁfties. Hence, we expect that the sample of citizens the initial job is in a small ﬁrm or
not working is a good proxy of the sample in a small ﬁrm or not working at the age of 60.
21

Column (3) in Table 9 shows that reduction in income at the age of 60 is less common andthe fraction of working population does not decrease among respondents who have started
their career with small ﬁrms.39 These results are consistent with the argument that theretirement at the age of 60 is less common in small ﬁrms. On the other hand, the signiﬁcant
increase in proportions of pension recipients can be observed among both of respondents
who have started their career with small ﬁrms and those who with large ﬁrms.
[Figure 12 here][Table 11 here]
Let us ﬁrst investigate the policy preference between male and female respondents. Panel
A and B in Figure 12 show the relationship between attitude toward consumption tax policy
and age of respondent for male and female sample, respectively. In line with our prediction,
they show that the drastic change in policy preference at age of 60 can be observed only
among male respondents. Table 11 indicates that the estimated eﬀect of reaching age of
60 for males is about 10% and statistically signiﬁcant. For female respondents, the sign ofeﬀect of being sixty on the support for consumption tax hike is neither robust to speciﬁcation
nor statistically signiﬁcant in speciﬁcation with higher order polynomial. These results are
consistent with the prediction that male change of political preference at the age of 60 would
be larger than that of females.
On the other hand, there is little support the claim that change in preference for tax
policy is larger among respondents who have been employed in large ﬁrms. The panel C andD show that discontinuities of attitude toward consumption tax policy at age of 60 can beobserved regardless of size of initial job of respondents. 40 While the reduction of sample
size makes our estimation less precise, Table 10 indicates there is not large diﬀerence of
estimated coeﬃcients of reaching age of 60 between respondents who have been employed inlarge ﬁrms and small ﬁrms.

8Discussion

From a series of observed facts, we would like to make some speculative arguments on themechanism on why many elderly people suddenly support consumption tax hike at the ageof 60.
First, it seems hard to explain the observed change in political preference at age of
60 by changes in life styles, home production, and leisure time of elderly citizens. The
literature of the retirement consumption puzzle (e.g., Hurst 2008) argues that the retirement
increases the intensity of home production, which makes people to reduce the purchase of
consumption goods. If this argument is correct, the reduction can lower the cost of an increase
39 The fraction of not working respondent is signiﬁcantly increases at the age of 60 among them. However,the sign of coeﬃcient is not robust to speciﬁcation (Table A.11).
40 Table 10 reports that coeﬃcients in large ﬁrm sample is larger than that in small ﬁrm size, though Table
A.8 shows that this result does not robust to speciﬁcation.

22

in consumption tax for retired senior persons. However, our evidence indicates no distinct
changes in working hours, the intensity of home production, and time use of respondents at
the age of 60. Moreover, Stephens and Unayama (2011) found that there is no immediate
reduction in consumption at retirement, on average, in Japan. Taken together, these ﬁndings
do not support the hypothesis that reduction in consumption due to substitution from market
consumption into home production causes support for consumption in elderly citizens.
Second, we think that explanation that reduction in income at the age of 60 causeschanges in support for consumption tax hike also would not be promising. While householdincome and the share of regular workers drops at the age of 60, these changes should be
negatively related with support for consumption tax hike since poor respondents or nonregular employed workers tend to oppose to tax hike. In fact, household income is positively
correlated with support for consumption tax hike although coeﬃcient of regular employment
is not signiﬁcant (Table 4). Moreover, we can still observe a discontinuous increase in support
for consumption tax hike even if we restrict sample to the workers not initially employed
in a large ﬁrm, who do not experience large change in household income and employment
status at the age of 60. Hence, we think that it is less likely to ﬁnd a plausible mechanism
from this line of argument.
As a plausible explanation, we propose the hypothesis that elderly people change theirpolitical attitude to consumption tax policy by receiving pension beneﬁt. As shown in Table
8, many Japanese start to receive pension at the age of 60 and rely on it to maintain theirlives. If the state ﬁnancial risk is expected to undermine sustainability of the social security
system, the recipients of pension would support consumption tax hike in order to protect
their vested interests. Our evidence suggests that while a reduction in income at age of 60 isless common and the fraction of working population does not decrease among respondents
who have started their career with small ﬁrms, the signiﬁcant increase in both the support
for consumption tax hike and the proportions of pension recipients can be observed among
both of respondents who have started their career with small ﬁrms. This indicates that the
motive to preserve the value of pension is more promising than other explanations.
To be fair, we also ﬁnd the evidence that appears not to be consistent with this hypothesis.
While we ﬁnd that the proportions of pension recipients are signiﬁcantly increased at age 60
for female respondents, the support for consumption tax hike does not change at the age of
60 for female respondents. We consider that this is probably because females are likely tohave substantially lower pension in Japanese employment system. Because our dataset does
not include the information about the amount of pension, the validity of this argument isleft for the future research.
The similar and somewhat diﬀerent explanation is that the severance payment would
sharply change political opinion of elderly people through by increasing their amount ofﬁnancial assets. If the risk of debt crisis would involve devaluation of ﬁnancial assets, theelderly citizens would turn to support ﬁscal consolidation in order to preserve value of theirassets when they receive retirement pay. In fact, the previous research ﬁnds evidence that net
ﬁnancial asset is larger in 60s than in 50s. Ichimura et al. (2009) shows that, from 50s to 60s,

23the average share of deposits holders increases 2.7 percent, the average share of bonds holders
increases 2.1 percent, the average share of stock holder increases 1.6 percent and the average
share of non-mortgage liabilities holder decline 7.6 percent. It shows the large decline in
non-mortgage liabilities holder and increases in ﬁnancial asset holder, in particular, deposit
holders and bond holders. However, Ichimura et al. (2009) do not provide any information
whether this diﬀerence discontinuously occurs at the age of 60. Hence, it is diﬃcult tojudge the validity of this explanation without further information. We leave it as a possible
hypothesis to be tested. 41
Although we are not able to separate preserving the value of pension from preserving
the value of ﬁnancial asset, our argument suggests that the motive of elderly citizens topreserve their value of assets, stepping back from the issue that these assets are public
or private, can be the promising explanation to cause their support for consumption tax
hike. The possibility that the old voters support ﬁscal consolidation policies to preserve
the value of their assets is pointed out in the theoretical literature on the political economy
of social security and government debt (e.g. Tabellini 2000, Persson and Tabellini 2002).
Since pension can be regarded as redistribution from the young to the old, the old generally
accpet increase in tax to maintain generous pension beneﬁts. Similary, the debt holder
also has incentive to raise tax rate if the government cannot commit to repayment of thegovernment debt (Tabellini 1991, Dixit and Londregan 2000, Gruembel and Sussman 2009)
Our hypothesis about observed fact is that the older citizen could be more likely to support
ﬁscal consolidation policy if such the motive of elderly citizens to preserve value of theirassets is strong enough. While this is on the contrary to the prevailing view, we think it
shuold be worth pursuing.

9

Conclusion

This paper analyzes the determinants of voter preferences on consumption tax hike using an
opinion survey of Japanese citizens. We ﬁnd robust evidence that the older voter is more
likely to support consumption tax hike. We also ﬁnd that the most of inter-generational
diﬀerence toward consumption tax policy is explained by the gap between citizens undersixty and over sixty. We discuss a possible mechanism about the discontinuous jump basedon the following additional ﬁndings: the hours of work do not change but their degree of
dependence on the pension in household income increases at the age of 60. We argue thatthe motive of the elderly citizens to preserve the value of their asset would lie behind theirsupport for consumption tax hike.
Our hypothesis that the old citizens are more likely to support consolidation policy fromworry about the serious impact on their asset value could be applied in diﬀerent situations.
In the Greek crisis, some citizens voted for austerity because they feared that their assets
41 If we take the tendency that practices of retirement payment at age of 60 are enforced more often inlarge ﬁrms seriously, the observed shift of political opinion at age of 60 among respondents employed in smallﬁrms would be less consistent with this argument, while the lack of shift of political opinion at the age of 60
among female can be consistent.

24

would be devalued. Vicky Pryce, the chief economic adviser at the Centre for Economics
and Business Research, explains the reason why she supported the yes vote as follows:42“It [no vote] would almost certainly mean banks becoming insolvent, an exitfrom the euro and a much faster decline in economic activity with hyperinﬂation
following as the drachma that is introduced instantly devalues.”
If there is considerable risk of devaluation of domestic assets when standard consolidation
policy fails, the prevailing view of intergenerational conﬂict over ﬁscal policy might not hold.
Finally, we brieﬂy discuss the direction of future research. On the mechanism that yields
correlation between age and support for a consumption tax, furthur investigation is required.
In particular, we need richer data to provide deﬁnitive evidence concerning the relationshipbetween ﬁnancial asset holdings and preferences on ﬁscal policy. The empirical research that
identiﬁes the causal eﬀect of ﬁnancial asset holdings on ﬁscal policy preference is left for
future study.43

42 “Greek referendum: how would top economists vote?” The Guardian, July 3, 2015.
Accessed at https://www.theguardian.com/world/2015/jul/03/greek-referendum-what-the-experts-say(March 18, 2018)
43 Tere are some reserch that analyzes impact of asset holding on political preference (e.g. Jha 2015,
Kaustia et al. 2016). To the best of our knowledge, however, there is no previous research that analyzes
eﬀect on preference for ﬁscal consolidatioin policy.

25

References
Aguiar, M., and Hurst, E. (2005). Consumption versus expenditure. Journal of political
Economy, 113(5), 919-948.
Aguiar, M., amd Hurst, E. (2007). Measuring trends in leisure: the allocation of time overﬁve decades. The Quarterly Journal of Economics, 122(3), 969-1006.
Alesina, A., and Fuchs-Schündeln, N. (2007). Good-Bye Lenin (or Not?): The Eﬀect ofCommunism on People’s Preferences. American Economic Review, 97(4), 1507-1528.
Alesina, A., and Giuliano, P. (2011). Preferences for Redistribution. In Handbook of Social
Economics, Vol. 1, pp. 93-131.
Alesina, A., and Passalacqua, A. (2016). The Political Economy of Government Debt. In
Handbook of Macroeconomics, Vol. 2, pp. 2599-2651.
Arai, R., and Ueda, J. (2013). A numerical evaluation of the sustainable size of the primarydeﬁcit in Japan. Journal of the Japanese and International Economies, 30, 59-75.
Blinder, A. S., and Krueger, A. B. (2004). What Does the Public Know about Economic
Policy, and How Does It Know It? Brookings Papers on Economic Activity, (1), 327.
Brunner, E. J., and Balsdon, E. (2004). Intergenerational conﬂict and the political economy
of school spending. Journal of Urban Economics, 56(2), 369-388.
Brunner, E. J., and Johnson, E. B. (2016). Intergenerational conﬂict and the political economy of higher education funding. Journal of Urban Economics, 91, 73-87.
Buchanan, J. M., and Wagner, R. E. (1977). Democracy in Deﬁcit. Acad. Press.
Cattaneo, M. A., and Wolter, S. C. (2009). Are the elderly a threat to educational expenditures? European Journal of Political Economy, 25(2), 225-236.
Cukierman, A, and Meltzer, A.H. (1989). A political theory of Government debt and deﬁcits
in a neo-ricardian framework. American Economic Review, 79(4), 713-732.
Corneo, G., and Gruner, H. P. (2002). Individual preferences for political redistribution.
Journal of Public Economics, 83(1), 83-107.
Dixit, A., and Londregan, J. (2000). Political power and the credibility of government debt.
Journal of Economic Theory, 94(1), 80-105.
Edmonds, E. V., Mammen, K. and Miller, D. (2005). Rearranging the Family? Income
Support and Elderly Living Arrangements in a Low-Income Country. Journal of Human
Resources, 40(1), 186-207.
Edmonds, E. V. (2006). Child Labor and Schooling Responses to Anticipated Income inSouth Africa. Journal of Development Economics, 81(2), 386-414.
26

Giuliano, P., and Spilimbergo, A. (2013). Growing up in a Recession. Review of Economic
Studies, 81(2), 787-817.
Guembel, A., and Sussman, O. (2009). Sovereign debt without default penalties. The Review
of Economic Studies, 76(4), 1297-1320.
Hayo, B., and Ono, H. (2010). Comparing public attitudes toward providing for the livelihoodof the elderly in two aging societies: Germany and Japan. The Journal of Socio-Economics,
39(1), 72-80.
Hayo, B., and Neumeier, F. (2017). Public Attitudes toward Fiscal Consolidation: Evidence
from a Representative German Population Survey. Kyklos, 70(1), 42-69.
Hansen, G., and Imrohoroglu, S. (2016). Fiscal Reform and Government Debt in Japan: A
Neoclassical Perspective, Review of Economic Dynamics, 21, 201-224.
Heinemann, F., and Hennighausen, T. (2012). Understanding public debt preferences. FinanzArchiv: Public Finance Analysis, 68(4), 406-430.
Hurst, E. (2008). The retirement of a consumption puzzle. National Bureau of Economic
Research, No. w13789.
Ichimura H, Hashimoto H, Shimizutani S. (2009) Japanese Study of Aging and Retirement:
JSTAR First Results 2009 Report. RIETI Discussion Paper Series 09-E-047.
Ihori, T. (2016) Why consumption tax hike is correct from the view point of economics?
(Syohi Zouzei ha Naze Keizaigakuteki ni Tadashiinoka?), Daiyamondo-Sya (in Japanese).
Imrohoroglu, S., Kitao, S. , and Yamada, T. (2016). Achieving Fiscal Balance In Japan,
International Economic Review, 57, 117-154.
Imrohoroglu and Sudo, N. (2011). Will a Growth Miracle Reduce Debt in Japan? Economic
Review, 62(1), 44-56.
Jha, S. (2015). Financial asset holdings and political attitudes: evidence from revolutionary
England. The Quarterly Journal of Economics, 130(3), 1485-1545.
Kato, S. and Kobayashi, K. (2017) Public Finance and Democracy, (Zaisei to Minsyu-Syugi),
Nihon Keizai Shinbun Syuppan Sya (in Japanese).
Kaustia, M., Knupfer, S., and Torstila, S. (2016). Stock Ownership and Political Behavior:
Evidence from Demutualizations. Management Science, 62(4), 945-963.
Keen, M., Pradhan, M., Kang, K., de Mooij, R., (2011). Raising the consumption tax inJapan: why, when, how? IMF Discussion Note No. 11/13
Kolesár, M., and Rothe, C. (2018). Inference in regression discontinuity designs with a discrete running variable. American Economic Review, 108(8), 2277-2304.

27

Kondo, A. (2014) Does mandatory employment protection increase elderly employment?
(Koyo Kakuho Sochi no Gimuka niyotte Koureisya no Koyo ha Fuetanoka?) The Japanesejournal of labour studies (Nihon Rodo Kenkyu Zasshi), 642, 13-22 (in Japanese).
Kondo, A. and Shigeoka, H. (2017) The Eﬀectiveness of Demand-Side Government Intervention to Promote Elderly Employment: Evidence from Japan. Industrial and Labor
Relations Review, 70 (4), 1008-1036.
Lee, D. S., and Card, D. (2008). Regression discontinuity inference with speciﬁcation error.
Journal of Econometrics, 142(2), 655-674.
Ministry of Health, Labour and Welfare. (2009). Survey on employment conditions of older
persons, (Konenreisya Shugyo Jittai Chosa) (in Japanese). Accessed at https://www.
mhlw.go.jp/toukei/list/3-20c.html (Febrary 21, 2019).
Ministry of Health, Labour and Welfare. (2013a). Overview of employees’ pension insurance and national pension system, (Kosei Nenkin Hoken, Kokumin Nenkin Zigyou no
Gaikyo) (in Japanese). Accessed at https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000106808 1.html (Febrary 21, 2019).
Ministry of Health, Labour and Welfare. (2013b). General survey on working conditions,(Syuro Joken Sogo Chosa) (in Japanese). Accessed at https://www.mhlw.go.jp/toukei/
itiran/roudou/jikan/syurou/13/index.html (Febrary 21, 2019).
Müller, A., Storesletten, K. and F. Zilibotti, F. (2016). The Political Color of Fiscal Responsibility. Journal of the European Economic Association, 14(1), 252-302.
Ohtake, F., and Tomioka, J. (2004). Who supports redistribution?. The Japanese Economic
Review, 55(4), 333-354.
Persson, T., amd Tabellini, G. (2002). Political economics and public ﬁnance. In Handbookof public economics (Vol. 3, pp. 1549-1659). Elsevier.
Rattsø,J. and Sørensen, R.J. (2010). Grey power and public budgets: Family altruism helps
children, but not the elderly. European Journal of Politic
Song, Z., Storesletten, K., and Zilibotti, F. (2012). Rotten Parents and Disciplined Children:
A Politico-Economic Theory of Public Expenditure and Debt. Econometrica, 80(6), 27852803.
Sørensen, R. J. (2013). Does aging aﬀect preferences for welfare spending? A study ofpeoples’ spending preferences in 22 countries, 1985-2006. European Journal of Political
Economy, 29(1), 259-271.
Stadelmann, D., and Eichenberger, R. (2012). Consequences of Debt Capitalization: Property Ownership and Debt versus Tax Choice. Southern Economic Journal, 78(3), 976-998.

28

Stadelmann, D., and Eichenberger, R. (2014). Public debts capitalize into property prices:
empirical evidence for a new perspective on debt incidence. International Tax and Public
Finance, 21(3), 498-529.
Stephens Jr, M., and Unayama, T. (2012). The impact of retirement on household consumption in Japan. Journal of the Japanese and International Economies, 26(1), 62-83.
Stix, H. (2013). Does the Broad Public Want to Consolidate Public Debt? - The Role ofFairness and of Policy Credibility. Kyklos, 66(1), 102-129.
Tabellini, G. (1991). The Politics of Intergenerational Redistribution. Journal of Political
Economy, 99(2), 335-357.
Tabellini, G. (2000). A positive theory of social security. Scandinavian Journal of Economics,
102(3), 523-545.
Walter, S., Dinas, E., Jurado, I., and Konstantinidis, N. (2018). Non-cooperation by popular
vote. expectations, foreign intervention and the vote in the 2015 Greek bailout referendum.International Organization, 72(4), 969-994.
Yamamura, E. (2012). Social capital, household income, and preferences for income redistribution. European Journal of Political Economy, 28(4), 498-511.
Yamamura, E. (2014). Trust in government and its eﬀect on preferences for income redistribution and perceived tax burden. Economics of Governance, 15(1), 71-100.

29

Table 1: Summary statistics (JGSS)
Variable
Dependent variable
Support for consumption tax hike
Demographic variables
Age
FemaleMarriedNumber of children
Household income (million yen)
Education
High schoolSome college
University
Employment status
Regular employment
Part-time employment
Self-employedControl variables
Living in a large city
House ownership
Bad health status
Trust in politiciansExperience of charity
Will to volunteer
Policy preferenceLife security for old (ﬁve grade)
Health care for old (ﬁve grade)
Redistribution (ﬁve grade)
Pension beneﬁt
Receipt of pension
Time use
Average hours worked per week
Cooking dinner everyday
Washing everyday
Shopping everyday
Cleaning everyday
Hours of watching TV per day

Mean

Std. Dev.

Number of obs.

0.399

0.49

5140

53.642
0.513
0.759
1.712
5.59

15.879
0.5
0.428
1.074
3.793

5140
5140
5140
5140
5140

0.478
0.149
0.23

0.5
0.356
0.421

5140
5140
5140

0.349
0.183
0.1

0.477
0.387
0.3

5140
5140
5140

0.488
0.775
0.142
0.342
0.866
0.671

0.5
0.418
0.349
0.474
0.341
0.47

5140
5125
5135
2856
3297
3363

3.637
3.931
3.714

1.15
1.014
1.032

5091
5091
5129

0.405

0.491

5137

23.021
0.486
0.399
0.204
0.24
3.6

20.783
0.5
0.49
0.403
0.427
2.335

4995
5110
5105
5122
5117
5114

Notes: The table presents summary statistics for JGSS sample (Source: JGSS 2010 and JGSS 2012). The
number of observation in JGSS 2010 is 1,732 and that in JGSS 2012 is 3,408. Detailed deﬁnition of eachvariable is presented in Appendix. Experience of charity and will to volunteer is only asked to the respondents
in JGSS 2012. Trust in politicians is only asked to about half of repondents in JGSS 2010 and 2012.

30

Table 2: Summary statistics (UTAS)
Variable
Dependent variable
Support for consumption tax hike (ﬁve grade)
Demographic variables
Age 30s
Age 40s
Age 50s
Age 60s
Age 70 overFemaleEducation
High schoolSome college
University
Employment status
Regular employment
Part-time employment
Self-employed
Public servant
Student

Mean

Std. Dev.

Number of obs.

2.681

1.266

1821

0.137
0.169
0.199
0.194
0.212
0.501

0.344
0.375
0.399
0.396
0.409
0.5

1821
1821
1821
1821
1821
1821

0.407
0.205
0.242

0.491
0.403
0.428

1821
1821
1821

0.283
0.136
0.13
0.049
0.016

0.45
0.343
0.337
0.217
0.125

1821
1821
1821
1821
1821

Notes: The table presents summary statistics for UTAS sample. In UTAS, respondents report their age bychoosing a category from six alternatives, 20s, 30s, 40s, 50s, 60s, and 70 over. There is no question abouthousehold income and family structure in UTAS.

31

Table 3: Preferece on consumption tax by age group (JGSS)Age group
Panel A. All sample
20-29
30-39
40-49
50-59
60-69
70TotalPanel B. Male only
20-29
30-39
40-49
50-59
60-69
70TotalPanel C. Female only
20-29
30-39
40-49
50-59
60-69
70TotalTax cut
Obs.
Fraction

Status quo
Obs.
Fraction

Tax increase
Obs.
Fraction

Total
Obs.

49
98
104
82
91
78
502

14.41
11.69
10.84
8.84
8.05
8.26
9.77

191
441
513
481
515
448
2589

56.18
52.63
53.49
51.83
45.53
47.46
50.37

100
299
342
365
525
418
2049

29.41
35.68
35.66
39.33
46.42
44.28
39.86

340
838
959
928
1131
944
5140

26
53
45
36
49
36
245

16.88
13.25
9.98
8.07
8.73
7.36
9.80

74
182
200
202
214
189
1061

48.05
45.50
44.35
45.29
38.15
38.65
42.42

54
165
206
208
298
264
1195

35.06
41.25
45.68
46.64
53.12
53.99
47.78

154
400
451
446
561
489
2501

23
45
59
46
42
42
257

12.37
10.27
11.61
9.54
7.37
9.23
9.74

117
259
313
279
301
259
1528

62.90
59.13
61.61
57.88
52.81
56.92
57.90

46
134
136
157
227
154
854

24.73
30.59
26.77
32.57
39.82
33.85
32.36

186
438
508
482
570
455
2639

Notes: The table presents frequency distribution of opinion toward consumption tax policy by age group.
According to answers to desirable consumption tax rate, we classify the respondents in JGSS into three
categories, tax cut, status quo, and tax increase. The category of tax cut includes respondents who prefertax rates less than 5 %, that of status quo includes respondents who prefer tax rate of exactly 5%, and thatof tax increase includes respondents who prefer tax rates higher than 5%.

32

Table 4: Estimation results of benchmark model (JGSS)
Age
FemaleMarriedHave children
High schoolSome college
University
Household income
Regular employed
Part-time empployed
Self-employed(1)
0.0051∗∗∗(0.0005)-0.1140∗∗∗(0.0151)
0.0370∗∗(0.0182)-0.0097(0.0207)0.1178∗∗∗(0.0204)
0.1468∗∗∗(0.0259)
0.2804∗∗∗(0.0247)0.0109∗∗∗(0.0020)-0.0134(0.0195)-0.0370∗(0.0195)-0.0755∗∗∗(0.0239)(2)
0.0052∗∗∗(0.0005)-0.1142∗∗∗(0.0151)0.0404∗∗(0.0183)-0.0099(0.0208)
0.1175∗∗∗(0.0206)
0.1458∗∗∗(0.0261)
0.2779∗∗∗(0.0249)
0.0112∗∗∗(0.0020)-0.0138(0.0197)-0.0361∗(0.0197)-0.0772∗∗∗(0.0240)0.0111(0.0134)-0.0160(0.0170)-0.0213(0.0191)(3)0.0054∗∗∗(0.0007)-0.1055∗∗∗(0.0202)
0.0368(0.0252)-0.0023(0.0282)
0.1014∗∗∗(0.0290)0.1342∗∗∗(0.0362)
0.2694∗∗∗(0.0341)0.0092∗∗∗(0.0027)-0.0130(0.0259)-0.0330(0.0275)-0.0994∗∗∗(0.0321)-0.0046(0.0182)-0.0264(0.0231)-0.0366(0.0253)
0.0377∗(0.0192)

0.080
5140

0.081
5120

0.079
2847

Living in a large city
House ownership
Bad health status
Trust in politician
Experience of charity
Will to volunteer
R2
N

(4)
0.0058∗∗∗(0.0011)-0.0794∗∗∗(0.0302)0.0104(0.0367)-0.0121(0.0420)0.1105∗∗(0.0440)0.1440∗∗∗(0.0541)0.2471∗∗∗(0.0517)0.0124∗∗∗(0.0040)-0.0094(0.0393)-0.0136(0.0410)-0.0726(0.0467)
0.0035(0.0273)-0.0199(0.0344)-0.0004(0.0382)
0.0344(0.0302)0.0701∗(0.0417)0.0895∗∗∗(0.0308)
0.075
1297

Notes: The table shows estimate for a linear probability model. The dependent variable is a binary variable
that equals one when the respondent supports consumption tax hike. Survey year dummy is included inestimation model. Robust standard errors in parentheses.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

33

Table 5: Estimation results of benchmark model: UTAS
(1)Ordered probit
Age 30s
0.0392(0.1202)
Age 40s
0.0226(0.1189)
Age 50s
0.0226(0.1155)
Age 60s
0.3601∗∗∗(0.1195)
Age 70 over
0.3118∗∗∗(0.1264)
Female-0.1445∗∗(0.0551)
High school
0.1137(0.0815)
Some college
0.1630∗(0.0961)
University
0.5024∗∗∗(0.0959)
Regular employment
0.1554∗∗(0.0779)
Part-time employment
0.0008(0.0831)
Self-employed
0.1120(0.0820)
Public servant
0.2169∗(0.1263)
Student
0.5530∗∗(0.2387)
Cutoﬀ 1-0.3997∗∗∗(0.1430)
Cutoﬀ 20.2599∗(0.1428)
Cutoﬀ 30.9125∗∗∗(0.1442)
Cutoﬀ 4
1.7897∗∗∗(0.1503)
N
1821
R2

(2)
OLS
0.0637(0.1379)
0.0417(0.1361)
0.0377(0.1325)
0.4240∗∗∗(0.1370)0.3600∗∗∗(0.1445)-0.1757∗∗∗(0.0650)0.1266(0.0942)0.1827∗(0.1109)
0.5859∗∗∗(0.1109)0.1815∗∗(0.0903)0.0007(0.0953)
0.1242(0.0970)0.2525∗(0.1514)0.6465∗∗(0.2752)

1821
0.055

Notes: The table shows estimation result for ordered probit model and that for OLS. The dependent variable
is a binary variable that equals one when the respondent supports consumption tax hike. Survey year dummy
34 in parentheses.
is included in estimation model. Robust standard errors∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Table 6: Regression discontinuity estimates (JGSS)Age 60 overCovariates
No

Age 60 over

Yes

Order of Polynomial
Observation(1)
0.0557∗∗(0.0243)[0.0253]
0.0769∗∗∗(0.0245)[0.0249]
1
5140

(2)
0.0602∗(0.0349)[0.0357]
0.0696∗(0.0353)[0.0349]
2
5140

(3)
0.0422(0.0424)[0.0463]
0.0461(0.0417)[0.0453]
3
5140

(4)
0.0737∗(0.0387)[0.0573]
0.0662∗(0.0389)[0.0565]45140

Notes: The table reports coeﬃcient of the age-above-60 indicator controlling for a polynomial of age. We
allow the parameter of polynomial to vary on either side of the cutoﬀ. The covariates is demographic variables
such as gender, marital status, education, household income, and employment status. Standard errors are
clustered at age in parentheses. Robust standard errors are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Table 7: The eligibility age of pension beneﬁt
Fiscal Year1986 - 2000
2001 - 2003
2004 - 20052006
2007 - 200820092010 - 201120122013 - 2014

Specially-provided Employees’ Pension
Constant-part
Proportional-part
60
60
61 for men, 60 for women
60
62 for men, 60 for women
60
62 for men, 61 for women
60
63 for men, 61 for women
60
63 for men, 62 for women
60
64 for men, 62 for women
60
64 for men, 63 for women
60
63 for women
61 for men, 60 for women

35

Basic Pension and
Employees’ Pension
65
65
65
65
65
65
65
65
65

Table 8: Jumps of outcome variables at age of 60 (JGSS)
Dependent Variables
Panel A: Work related variables
Not working

Regular employment

Weekly hours worked

Panel B: Home production and leisure
Shopping everyday

Cooking dinner everyday

Washing everyday

Cleaningg everyday

Time of watiching TV

Size of household

Panel C: Amount and content of household income
Household income

Receipt of pension

Jump at Age of 60

Number of Obs.

-0.0446(0.0296)[0.0519]-0.0339(0.0593)[0.0549]
2.8136(2.1102)[2.4414]5140

0.0442(0.0269)[0.0470]-0.0758(0.0492)[0.0581]0.0007(0.0287)[0.0574]-0.0491(0.0348)[0.0479]-0.0931(0.1435)[0.2632]-0.1065(0.1170)[0.1472]5122-1.2165∗∗(0.5000)[0.4898]
0.2248∗∗∗(0.0240)[0.0509]

5140

4995

5110

5105

5117

5114

5139

5140

5137

Notes: The table reports coeﬃcient of the age-above-60 indicator on each dependent variables controlling for
4th order polynomial of age with no covariates. We allow the parameter of polynomial to vary on either sideof the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported
in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

36

Table 9: Jump of outcome variables: By Subgroup

Dependent variables
Not working

Number of Obs.
Weekly hours worked

Numboer of Obs.
Regular employment

Number of Obs.
Household income

Number of Obs.
Receipt of pension

Number of Obs.

By gender
Male
Female(1)(2)
0.0061-0.0586(0.0455)(0.0548)[0.0599][0.0780]2501
2639
2.47680.8621(2.7740)(3.0992)[3.1767][3.0326]2423
2572-0.1369∗∗
0.0125(0.0543)(0.0609)[0.0797][0.0638]
2501
2639
∗∗∗
-1.7296-0.8346(0.5336)(0.7715)[0.7403][0.6517]
2501
2639
∗∗∗
0.22100.2458∗∗∗(0.0524)(0.0288)[0.0550][0.0709]2498
2639

By ﬁrm size at the initial job
Small ﬁrm
Large ﬁrm
(3)
(4)
-0.1248∗0.0425(0.0686)(0.0501)[0.0772][0.0705]2471
2669
2.4768-1.6310(2.7740)(2.7839)[3.1767][3.1543]2423
2605
0.0412-0.0990(0.0685)(0.4945)[0.0808][0.6899]2501
2669-0.3966-1.7048∗∗∗(0.6387)(0.7715)[0.6401][0.6517]
2471
2669
∗∗∗
0.16500.2744∗∗∗(0.0530)(0.0375)[0.0766][0.0684]
2469
2668

Notes: The table reports coeﬃcient of the age-above-60 indicator on each dependent variables controlling for
4th order polynomial of age with no covariates. We allow the parameter of polynomial to vary on either sideof the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported
in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

37

Table 10: The relationship between ﬁrm size at the initial job and current employment
among respondents from 50 to 59 years old (JGSS)
Firm size at the initial job
Small ﬁrm
Large ﬁrm
PublicTotal

Small ﬁrm
175
(54.69)136(31.41)
15(16.3)
331(38.58)Current employment
Large ﬁrm
Public6212(19.38)(3.75)
189
24(43.65)(5.54)
1944(20.65)(47.83)275
80(32.05)(9.32)

Not working
71(22.19)84(19.4)
14(15.22)172(20.05)

Total
320
(100)
433
(100)
92
(100)
858
(100)

Notes: The table presents frequency distribution of current emplotment status among respondents from 50
to 59 years old by ﬁrm size at their initial job. The deﬁnition of each categories are presented in Appendix.
The numbers in parentheses mean fraction of each cell.

Table 11: Regression discontinuity estimates by subgroups (JGSS)Age 60 overNumber of Obs.

By gender
Male
Female(1)(2)∗∗
0.13130.0090(0.0514)(0.0412)[0.0841][0.0776]2501
2639

By ﬁrm size at the initial job
Small ﬁrm
Large ﬁrm
(3)
(4)
0.05130.1183(0.0528)(0.0755)[0.0844][0.0779]
2471
2669

Notes: The table reports coeﬃcient of the age-above-60 indicator controlling for a polynomial of age without
covariates. We allow the parameter of polynomial to vary on either side of the cutoﬀ. Standard errors are
clustered at age in parentheses. We arso report robust standard errors in blacket.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

38

General GovernmentGrossLiability/ GDP(%)

250

200

150

100

50

0
1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

Year

FranceGermany

GreeceItaly

J apanSpain

United Kingdom

United States

Figure 1: Gross ﬁnancial liabilities in advanced countries
Notes: The graphs show transitions of gross ﬁnancial liabilities across advanced countries. Data comes from
OECD Economic Outlook.

Germany

Greece

Italy

Japan

Spain

SwedenUnited Kingdom

United States of America

Meidan Age

30 40 50 60

30 40 50 60

30 40 50 60

France1980

2000

Graphs by Country

2020

20401980

2000

2020

20401980

2000

2020

2040

Year

Figure 2: Median age of the total population in advanced countries
Notes: The graphs show transitions of median age across advanced countries. Data comes from World
Population Prospects 2017 of United Nation.

39

.4
.3
Coefficient.2.1025−29 30−34 35−39 40−44 45−49 50−54 55−59 60−64 65−69

70−

Age
coefficient

90% CI

Figure 3: The coeﬃcients of dummies of each group for non linear speciﬁcation (JGSS).2

Support for consumption tax increase
.3
.4
.5

.6

Notes: The ﬁgure plots coeﬃcients of dummies of age groups, age 25-29, age 30-34, age 35-39, age 40-44, age
45-49, age 50-54, age 55-59, age 60-64, age 65-69, and age 70 over when we regress support fot consumption
tax hike on sex, marital status, education, household income, employment status, and a series of age dummies
using JGSS sample. The excluding category is age 20-24. We also report conﬁdence intervals of coeﬃcientsusing robust standard errors.

20

40

60
Age

80

100

Figure 4: The fraction of supporters for consumption tax hike by age (JGSS)
Notes: The ﬁgure plots fraction of supporters for consumption tax hike for each age in JGSS sample. The
solid line is quartic ﬁts on each side of age of 60. The vertical line represents age of 60.

40

Panel B: Quadratic

−.1

0

0

.05

Coefficient.1

Coefficient
.1

.2

.15

.2

.3

Panel A: Linear

20

15

10

bandwidthcoefficient

5

20

15

90 %CI

bandwidthcoefficient

10
90 %CI

Figure 5: The local estimator by bandwidth (JGSS)

0.01

Fraction.02.03

Notes: The graphs show the coeﬃcients of the age-above-60 indicator and associated conﬁdence intervals
for each bandwidth. Panel A uses the local linear method and Panel B uses the local quadratic method toestimate coeﬃcients. The conﬁdence intervals are calculated by using robust standard errors.

20

40

60
Age

80

100

Figure 6: The distribution of age of respondents (JGSS)
Notes: The graph shows the fraction of respondents for each age in JGSS sample. The vertical line represents
age of 60.

41

5

Panel B: The fraction of married

0

.4

.2

.5

Female.6

Married
.4

.6

.7

.8

.8

Panel A: The fraction of female

20

40

60
Age

80

100 20Panel C: Years of schooling

40

60
Age

80

100

80

100

10

0

11

.5

Years of schooling12
13

Number of children
1
1.5

14

2

15

2.5

Panel D: Number of children

20

40

60
Age

100 20

80

40

60
Age

Figure 7: The mean of demographic variables by age (JGSS)
Notes: The ﬁgure plots average of predetermined variables such as sex, marital status, years of schooling,
and number of children for each age in JGSS sample. The solid line is quartic ﬁts on each side of age of 60.
The vertical line represents age of 60.

42

Panel B: Life security for old

2.5

2.5

3

Life security for old
3
3.5

Health care for old
3.5

4

4

4.5

Panel A: Health care for old

20

40

60
Age

80

100 20

40

60
Age

80

100

80

100

Panel D: Trust in politician

0

3.2

.2

3.4

Redistribution
3.6
3.8

Trust in politicians
.4
.6

.8

4

1

4.2

Panel C: Redistribution

20

40

60
Age

80

100 2040

60AgeFigure 8: The policy preference by age (JGSS)
Notes: The ﬁgure plots the average of policy preference related variables such as demand for health care forold, demand for life security for old, support for redistributive policy, and trust in politician for each age in
JGSS sample. The solid line is quartic ﬁts on each side of age of 60. The vertical line represents age of 60.

43

Panel B: Average hours worked per week

0

0

.2

10

Not working.4.6

Weekly hours worked
20
30

.8

1

40

Panel A: The share of not working citizens

20

40

60
Age

80

100 20

40

60
Age

80

0

.2

Regular employed
.4

.6

.8

Panel C: The share of regular employedworkers

20

40

60
Age

80

100

Figure 9: The work related variables by age (JGSS)
Notes: The ﬁgure plots average of work related variables such as fraction of not working, average hours
worlked per week, and share of regular employment for each age in JGSS sample. The solid line is quarticﬁts on each side of age of 60. The vertical line represents age of 60.

44

100

Cooking dinner everyday
.2
.4
.6
0

0

.1

Shopping everyday
.2
.3

.8

Panel B: The frequency of cooking dinner.4

Panel A: The frequency of shopping

20

40

60
Age

80

100

20

60
Age

80

100

Panel D: The frequency of cleaning

0

0

.1

Washing everyday.2.4

Cleaning everyday
.2
.3

.4

.6

.5

Panel C: The frequency of washing

40

20

40

60
Age

80

100

20

Panel E: Time of watching TV

40

60
Age

80

100

2

1.5

3

2

Size of household
2.5
3Time of watching TV
4
5

3.5

6

4

Panel F: Size of household

20

40

60
Age

80

20

100

40

60
Age

80

100

Figure 10: Home production and leisure related variables by age(JGSS)
Notes: The ﬁgure plots average of home production and leisure related variables such as frequency of shopping, cooking, washing, cleaning, time of watching TV, and size of household for each age in JGSS sample.
The solid line is quartic ﬁts on each side of age of 60. The vertical line represents age of 60.

45

Panel B: Receipt of pension

0

2

.2

Household income
46

Reception of pension
.4
.6

.8

8

1

Panel A: Household income

20

40

60
Age

80

100 20

40

60
Age

80

Figure 11: Household income and receipt of pension beneﬁt by age (JGSS)
Notes: The ﬁgure plots average of household income and receipt of pension for each age in JGSS sample.
The solid line is quartic ﬁts on each side of age of 60. The vertical line represents age of 60.

46

100

Panel B: Female only

.2

.1

Support for consumption tax increase
.2
.3
.4

Support for consumption tax increase
.4
.6
.8

1

.5

Panel A: Male only

20

40

60
Age

80

100 20

40

60
Age

80

100

Panel D: Start career with large ﬁrm

00

Support for consumption tax increase
.2
.4
.6
.8

Support for consumption tax increase
.2
.4
.6

1

.8

Panel C: Start career with small ﬁrm

20

40

60
Age

80

100 20

40

60
Age

80

Figure 12: The fraction of supporters for consumption tax hike by subgroup (JGSS)
Notes: The ﬁgure plots fraction of supporters for consumption tax hike for each age in JGSS sample bysubgroup. The solid line is quartic ﬁts on each side of age of 60. The vertical line represents age of 60.

47

100

Appendix
A.1 Deﬁnition of Variables
Demographic Varibles
Education. We classify respondents into the following four categories according to their terminal education record: elementary and junior high school, high school, some college, anduniversity. Both the JGSS and UTAS ask respondents for their terminal education record.
The category of some college includes colleges of technology and junior colleges. Graduate
school is included in the category of university.
Household Income. Only JGSS asks responrents about pre-tax household income that includes wages and pension beneﬁts, yields on shares, and income from real estate. The
respondents are asked to choose their answers from among several income categories. We
record the median value of the category that the respondent chooses as household income.
We assign 350 thousand yen for the respondent who chooses the lowest category, less than
700 thousand yen for the next lowest category, and 25 million yen for the respondent whochooses the highest category of more than 23 million yen.
Employment Status. Employment status is classiﬁed into four categories in the JGSS data,
regular employment (seiki-koyo), part-time employment (hiseiki-koyo), self-employment, andnot working. Managers and directors are included in category of regular employment while
part-time and temporary workers are included in category of non-regular employment. In
the UTAS data, we add two diﬀerent categories, public servant and student, to the above
four categories.
Control Variables (only JGSS)
Living in a large city. An indicator variable that shows whether a respondent lives in a citywith a population over 200,000.
Bad health. JGSS asks respondents about subjective evaluation of their health status in
ﬁve grades. Bad health is a dummy variable that indicates whether subjective evaluation isworse than the third in the ﬁve stage evaluation
House ownership. An indicator variable that shows whether the respondent has their own
house.
Trust in politicians: In JGSS, there are questions concerning trust in members of Congress asfollows: “How much do you trust members of Congress?” We regard those who respond with“trust a lot” or “trust a little” as having trust in politicians. Since half of the respondents
in the JGSS 2012 are not asked about trust toward members of Congress, the sample size
substantially decreases when we include trust in politicians in our analysis.
Experience of charity: Whether the respondent donated during the past year.
Will to volunteer: JGSS 2012 asked respondents, “Would you like to participate in volunteer
activities if there is an opportunity to from now on?” We regard those who respond with
“I’d like to participate” or “I’d like to participate if I could” as having the will to participate48

in volunteer activity.
Policy Preference (only JGSS)
Health care for the old. In JGSS, there is a following question on life security of the elderly,“Is the life security of the elderly the responsibility of individuals or families? Or is it the
responsibility of the state or local government?” The respondents provided responses from
1 to 5, where “5” corresponds to “responsibility of the state or local government” and “1”corresponds to “responsibility of individuals or families.” We use this ﬁve grade variable asdegree of demand for health care for the old.
Life security for the old. In JGSS, there is a following question on health care, “Is healthcare for the elderly the responsibility of individuals or families? Or is it the responsibilityof the state or local government?” The respondents provided responses from 1 to 5, where“5” corresponds to “responsibility of the state or local government” and “1” corresponds
to “responsibility of individuals or families.” We use this ﬁve grade variable as degree of
demand for health care for the old.
Redistribution. JGSS asks for opinions on redistributive policies in the following statement,“Are you in favor of the statement that the government should adopt policies to reduce theincome gap between the rich and the poor?” The respondents must choose their answer fromﬁve alternatives, from 1 to 5, and the larger number means more positive attitude toward
the government intervention.
Receipt of pension (only JGSS)
Receipt of pension. In JGSS, there is a question about the source of ﬁnancial support asfollows: “What are your sources of ﬁnancial support? Choose all items that apply”. We
deﬁne the respondent who answer “pension” is included in the source of ﬁnancial support tothis question as pension recipients.
Time Use (only JGSS)
Average hours worked per week. We use question about normal hours worked per week. The
hours worked for respondent who does not work is recorded as zero.
Home production related variables (Cooking dinner everyday, Washing everyday, Shopping
everyday, and Cleaning everyday). In JGSS, there is quesions about time use as follows:“How often do you do the following activities ?” The respondents are asked about thefrequency of activity such as preparation of dinner, cleaning, washing, and shopping. They
choose answer from six categories, “almost everyday”, “several times in a week”, “about
once in a week”, “about once in a month”, “several times in a year”, and “about once in ayear”. We deﬁne respondents who answer to do these activities almost everyday as one dothese activities everyday.
Hours of watching TV per day. We use question about time of wathing TV “How many
hours do you watch TV in a day on average?”49

Firm size of the initial job (only JGSS)JGSS asks respondents about the content of ﬁrst job in detail, including the number of employees in the ﬁrm. According to the ﬁrm size of their initial jobs, we categorize respondents
into two groups: those who has not employed at all or worked at a ﬁrm with less than 99
employee as the ﬁrst job and those who has worked at a ﬁrm with more than 100 employees
or public authorities as the ﬁrst job.

A.2 Additional Graphs and Tables
Panel B: Female respondents

0

0

.005

.01

.01

Fraction

Fraction
.015

.02

.02

.03

.025

Panel A: Male respondents

20

40

60
Age

80

100 20

40

60
Age

80

Figure A.1: The distribution of age of respondents by sex (JGSS)
Notes: The graph shows the fraction of respondents for each age by sex in JGSS sample. The vertical line
represents age of 60.

50

100

51

(2)
0.0602∗(0.0349)[0.0357]
No
0.0696∗(0.0353)[0.0349]
Yes
2
∞
5140

(3)
0.0422(0.0424)[0.0463]
No
0.0461(0.0417)[0.0453]
Yes
3
∞
5140

(4)
0.0737∗(0.0387)[0.0573]
No
0.0662∗(0.0389)[0.0565]
Yes
4
∞
5140

(5)
0.0476(0.0319)[0.0304]No
0.0625∗(0.0323)[0.0297]
Yes
1
20
3790

(6)
0.0759∗(0.0408)[0.0450]No0.0759∗(0.0409)[0.0440]
Yes
2
20
3790

(7)
0.0526(0.0417)[0.0419]No
0.0584(0.0422)[0.0411]
Yes
1
10
2158

(8)
0.0794∗∗(0.0373)[0.0654]
No
0.0738∗(0.0361)[0.0647]
Yes
2
10
2158

(9)
0.1043∗∗(0.0417)[0.0589]
No
0.0986∗∗(0.0399)[0.0583]
Yes
1
5
1222

Notes: The table reports coeﬃcient of the age-above-60 indicator controlling for a polynomial of age. We allow the parameter of polynomial to vary on either sideof the cutoﬀ. The covariates is demographic variables such as gender, marital status, education, household income, and employment status. Standard errors are
clustered at age in parentheses. Robust standard errors are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Covariates
Order of Polynomial
Bandwidth
Observation

Covariates
Age 60 overAge 60 over(1)
0.0557∗∗(0.0243)[0.0253]
No
0.0769∗∗∗(0.0245)[0.0249]
Yes
1
∞
5140

Table A.1: Regression discontinuity estimates (JGSS)

52

(2)
-0.0118(0.0277)[0.0363]0.0865∗∗(0.0363)[0.0280.0365]-0.4180∗∗∗(0.1166)[0.1527]
0.0953∗(0.0537)[0.0712]
2
∞
5140

(3)
-0.0586∗(0.0304)[0.0470]-0.0153(0.0266)[0.0451]-0.1269(0.1190)[0.1974]
0.0066(0.0600)[0.0929]
3
∞
5140

(4)
-0.0611∗∗(0.0302)[0.0584]0.0306(0.0377)[0.0241]0.0375(0.1151)[0.2437]-0.0512(0.0710)[0.1157]
4
∞
5140

(5)
-0.0199(0.0250)[0.0309]0.0406∗∗(0.0193)[0.0357]-0.5068∗∗∗(0.1167)[0.1302]-0.0646(0.0466)[0.0612]
1
20
3790

(6)
-0.0418(0.0312)[0.0457]
0.0102(0.0260)[0.0330]-0.0776(0.1057)[0.1921]0.0449(0.0530)[0.0915]
2
20
3790

(7)
-0.0639∗∗(0.0293)[0.0425]
0.0363(0.0263)[0.0515]-0.2021∗(0.1076)[0.1780]0.0014(0.0434)[0.0850]
1
10
2158

(8)
-0.0597∗∗(0.0271)[0.0666]
0.0309(0.0438)[0.0463]0.0792(0.1204)[0.2767]
0.0481(0.0499)[0.1348]210
2158-0.1319(0.0796)[0.2503]
0.0314(0.0482)[0.1217]
1
5
1222

(9)
-0.0657∗(0.0295)[0.0600]
0.0215(0.0340)

Notes: The table reports coeﬃcient of the age-above-60 indicator on each predetermineed variables controlling for a polynomial of age. We allow the parameterof polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Order of Polynomial
Bandwidth
Observation

Number of children

Years of schooling

MarriedFemale(1)-0.0281(0.0223)[0.0258]-0.0320(0.0362)[0.0209]-0.5430∗∗∗(0.0978)[0.1082]-0.2529∗∗∗(0.0699)[0.0506]
1∞
5140

Table A.2: Jumps of predetermined variables at age of 60 (JGSS)

53

0.0652∗(0.0359)[0.0444]3408
0.0491(0.0572)[0.0600]
1732
No
2
∞

0.0505∗(0.0257)[0.0314]3408
0.0628(0.0404)[0.0429]
1732
No
1
∞

(2)

0.0348(0.0551)[0.0758]
1732
No
3
∞

0.0416(0.0473)[0.0583]3408(3)0.0262(0.0506)[0.0920]
1732
No
4
∞

0.1021∗∗(0.0443)[0.0730]3408(4)0.0752(0.0477)[0.0512]
1284
No
1
20

0.0323(0.0350)[0.0378]2506(5)0.0396(0.0586)[0.0740]
1284
No
2
20

0.0947∗∗(0.0418)[0.0566]2506(6)0.0439(0.0569)[0.0690]
740
No
1
10

0.0554(0.0427)[0.0527]1418(7)0.0318(0.0594)[0.1043]
740
No
2
10

0.0998∗∗(0.0416)[0.0839]1418(8)0.0612(0.0650)[0.0940]
420
No
1
5

0.1264∗∗∗(0.0357)[0.0755]802(9)Notes: The table reports coeﬃcient of the age-above-60 indicator controlling for a polynomial of age without covariates. We allow the parameter of polynomial tovary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Covariates
Order of Polynomial
Bandwidth

Observation
Panel B. JGSS2010 only
Age 60 over

Panel A. JGSS2012 only
Age 60 over(1)

Table A.3: Regression discontinuity estimates by survey year (JGSS)

54

(1)
-0.0890(0.0543)[0.0533]5091-0.1666∗∗∗(0.0555)[0.0607]5091
0.1048∗∗(0.0515)[0.0523]5129-0.0100(0.0272)[0.0326]
2856
1
∞

(2)
-0.0089(0.0686)[0.0757]5091-0.0844(0.0676)[0.0853]5091-0.0391(0.0635)[0.0743]5129-0.0082(0.0372)[0.0459]
2856
2
∞

(3)
0.1246(0.0936)[0.0979]
5091
0.0130(0.0899)[0.1097]5091
0.0225(0.0671)[0.0973]5129
0.0033(0.0391)[0.0588]
2856
3
∞

(4)
0.0895(0.1014)[0.1198]5091-0.0212(0.1098)[0.1345]5091-0.0104(0.0675)[0.1216]5129-0.0092(0.0523)[0.0721]
2856
4
∞

(5)
-0.0351(0.0603)[0.0635]3753-0.0982(0.0595)[0.0723]3749
0.0304(0.0548)[0.0628]3781-0.0320(0.0339)[0.0390]
2091
1
20

(6)
0.1166(0.0843)[0.0947]3753-0.0221(0.0838)[0.1068]3749
0.0515(0.0654)[0.0942]3781-0.0112(0.0385)[0.0571]
2091
2
20

(7)
0.0670(0.0773)[0.0882]2137-0.0351(0.0877)[0.0994]2136
0.0354(0.0712)[0.0873]2153-0.0183(0.0391)[0.0529]
1219
1
10

(8)
0.0320(0.1010)[0.1349]2137-0.1314(0.1065)[0.1520]2136
0.0221(0.0552)[0.1374]2153
0.0533(0.0390)[0.0819]
1219
2
10

(9)
-0.0091(0.0784)[0.1233]1210-0.0674(0.0886)[0.1390]1211-0.0526(0.0766)[0.1240]1219
0.0678(0.0392)[0.0740]703
1
5Notes: The table reports coeﬃcient of the age-above-60 indicator on policy preference controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Trust in politician

Observation
Redistribution

Observation
Life security for the old

Health care for the old

Table A.4: Jumps of policy preference at age of 60 (JGSS)

55

(2)
0.0612∗∗(0.0261)[0.0322]5140-0.1324∗∗∗(0.0370)[0.0327]5140-3.1614∗∗(1.3532)[1.4873]
4995
2
∞

(3)
0.0019(0.0260)[0.0420]5140-0.1460∗∗∗(0.0478)[0.0435]5140-1.5490(1.4738)[1.9614]
4995
3
∞

(4)
-0.0446(0.0296)[0.0519]5140-0.0339(0.0593)[0.0549]5140
2.8136(2.1102)[2.4414]
4995
4
∞

(5)
0.1367∗∗∗(0.0319)[0.0273]3790-0.2153∗∗∗(0.0379)[0.0278]3790-7.1660∗∗∗(1.7597)[1.2488]
3681
1
20

(6)
-0.0079(0.0219)[0.0406]3790-0.1061∗∗(0.0461)[0.0426]3790-1.1245(1.4501)[1.8989]
3681
2
20

(7)
0.0091(0.0191)[0.0377]2158-0.1011∗∗(0.0476)[0.0395]2158-1.2564(1.4027)[1.7545]
2093
1
10

(8)
-0.0034(0.0270)[0.0583]2158-0.1222∗∗(0.0541)[0.0635]2158-0.6048(1.3045)[2.7499]
2093
2
10

(9)
0.0145(0.0166)[0.0542]1222-0.1274∗∗(0.0517)[0.0572]1222-1.1338(1.0031)[2.5285]1184
1
5

Notes: The table reports coeﬃcient of the age-above-60 indicator on work related variables controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Weekly hours worked

Observation
Regular employment

Not working(1)0.2055∗∗∗(0.0340)[0.0227]5140-0.2602∗∗∗(0.0354)[0.0224]5140-9.5755∗∗∗(1.8477)[1.0241]
4995
1∞

Table A.5: Jumps of work related variables at age of 60 (JGSS)

56

(2)
-0.0091(0.0234)[0.0296]5122-0.0158(0.0328)[0.0361]5110
0.0340(0.0260)[0.0356]5105
0.0335(0.0296)[0.0305]5117-0.0871(0.0961)[0.1622]5114-0.0110(0.1009)[0.0929]
5139
2
∞

(3)
0.0167(0.0282)[0.0383]5122-0.0784∗∗(0.0391)[0.0468]5110
0.0255(0.0280)[0.0463]5105-0.0304(0.0287)[0.0390]5117-0.2042(0.1353)[0.2096]5114
0.2650∗∗(0.1272)[0.1203]
5139
3
∞

(4)
0.0442(0.0269)[0.0470]5122-0.0758(0.0492)[0.0581]5110
0.0007(0.0287)[0.0574]5105-0.0491(0.0348)[0.0479]5117-0.0931(0.1435)[0.2632]5114-0.1065(0.1170)[0.1472]
5139
4
∞

(5)
-0.0131(0.0240)[0.0255]3775-0.0331(0.0272)[0.0309]3766
0.0052(0.0223)[0.0306]3759
0.0411(0.0273)[0.0264]3771
0.1660∗(0.0952)[0.1361]3771-0.2037∗(0.1051)[0.0800]
3789
1
20

(6)
0.0127(0.0293)[0.0376]3775-0.0542(0.0397)[0.0458]
3766
0.0253(0.0268)[0.0454]3759-0.0215(0.0319)[0.0385]3771-0.2425∗(0.1262)[0.2019]3771
0.1309(0.1016)[0.1168]
3789
2
20

(7)
-0.0101(0.0292)[0.0349]2152-0.0815∗∗(0.0374)[0.0425]2153
0.0072(0.0243)[0.0422]2140-0.0104(0.0319)[0.0356]2150-0.0850(0.0998)[0.1871]2149
0.0206(0.1011)[0.1083]
2158
1
10

(8)
0.0397∗(0.0212)[0.0538]2152-0.0787(0.0458)[0.0665]2153-0.0478(0.0408)[0.0659]2140-0.0231(0.0230)[0.0551]2150
0.1390(0.1361)[0.2961]2149
0.0521(0.1315)[0.1658]
2158
2
10

(9)
0.0414(0.0245)[0.0484]1220-0.0757(0.0430)[0.0599]1221-0.0237(0.0432)[0.0592]1213-0.0341(0.0255)[0.0499]1218-0.0183(0.0888)[0.2649]1216-0.0681(0.1178)[0.1489]1222
1
5

Notes: The table reports coeﬃcient of the age-above-60 indicator on home production and leisure related variables controlling for a polynomial of age without
covariates. We allow the parameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors
are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Size of household

Observation
Time of watiching TV

Observation
Cleaning everyday

Observation
Washing everyday

Observation
Cooking dinner everyday

Shopping everyday(1)-0.0593∗∗(0.0226)[0.0211]5122-0.0613∗∗(0.0239)[0.0257]5110-0.0686∗∗(0.0272)[0.0253]5105
0.0217(0.0237)[0.0219]5117
0.5894∗∗∗(0.1325)[0.1170]5114-0.6531∗∗∗(0.1420)[0.0683]
5139
1∞

Table A.6: Jumps of home production and leisure related variables at age of 60 (JGSS)

57

(2)
-2.0432∗∗∗(0.4383)[0.3005]5140
0.3727∗∗∗(0.0313)[0.0305]
5137
2
∞

(3)
-1.0974∗∗(0.4170)[0.3923]5140
0.2757∗∗∗(0.0241)[0.0407]
5137
3
∞

(4)
-1.2165∗∗(0.5000)[0.4898]5140
0.2248∗∗∗(0.0240)[0.0509]
5137
4
∞

(5)
-2.2000∗∗∗(0.3837)[0.2590]3790
0.4655∗∗∗(0.0445)[0.0252]
3787
1
20

(6)
-1.2033∗∗(0.4469)[0.3864]3790
0.3049∗∗∗(0.0273)[0.0394]
3787
2
20
1
10

(7)
-1.2823∗∗(0.4638)[0.3670]2158
0.3191∗∗∗(0.0264)[0.0366]2
10(8)-0.8768(0.5121)[0.5723]2158
0.2211∗∗∗(0.0237)[0.0586]15(9)-1.2036∗∗(0.4681)[0.5261]1222
0.2609∗∗∗(0.0271)[0.0542]

Notes: The table reports coeﬃcient of the age-above-60 indicator on household income and receipt of pension controlling for a polynomial of age without covariates.
We allow the parameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also
reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Receipt of pension

Household income(1)-2.6531∗∗∗(0.3184)[0.2071]5140
0.5358∗∗∗(0.0456)[0.0203]
5137
1∞

Table A.7: Jumps of work related variables at age of 60 (JGSS)

58

0.0258(0.0374)[0.0369]2501

0.0886∗(0.0527)[0.0521]2501(2)0.0513(0.0528)[0.0844]2471
0.1183(0.0755)[0.0779]
2669
No
4
∞

-0.0108(0.0791)[0.0634]
2669
No
3
∞

0.0090(0.0412)[0.0776]2639-0.0217(0.0380)[0.0625]2639
0.0979∗∗(0.0468)[0.0678]2471

0.1313∗∗(0.0514)[0.0841]2501(4)0.0971(0.0606)[0.0679]2501(3)0.0413(0.0565)[0.0420]
1965
No
1
20

0.0579∗(0.0315)[0.0441]
1825

0.0280(0.0285)[0.0410]1924

0.0653(0.0495)[0.0444]1866(5)0.0557(0.0736)[0.0613]
1965
No
2
20

0.0907∗∗(0.0412)[0.0663]1825

0.0375(0.0394)[0.0607]1924

0.1105∗(0.0605)[0.0662]1866(6)0.0479(0.0731)[0.0566]
1141
No
1
10

0.0524(0.0395)[0.0618]1017

0.0087(0.0354)[0.0566]1098

0.0842(0.0610)[0.0613]1060(7)0.0693(0.0739)[0.0885]
1141
No
2
10

0.1079∗(0.0530)[0.0962]1017-0.0191(0.0400)[0.0889]1098

0.1749∗∗∗(0.0469)[0.0957]1060(8)0.1218(0.0731)[0.0797]
654
No
1
5

0.0910∗(0.0479)[0.0873]568-0.0057(0.0445)[0.0799]631

0.2093∗∗∗(0.0485)[0.0864]591(9)

Notes: The table reports coeﬃcient of the age-above-60 indicator controlling for a polynomial of age without covariates. We allow the parameter of polynomial tovary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported in brackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Panel B. Female only
Age 60 over0.0751∗∗∗0.0357(0.0260)(0.0323)[0.0342][0.0482]
Observation
2639
2639
Panel C. Start career with small ﬁrm
Age 60 over0.0689∗∗0.0758∗∗(0.0289)(0.0375)[0.0360][0.0515]
Observation
2471
2471
Panel D. Start career with large ﬁrm
Age 60 over0.05550.0391(0.0462)(0.0611)[0.0357][0.0496]
Observation
2669
2669
Covariates
No
No
Order of Polynomial
1
2
Bandwidth∞∞

Panel A. Male only
Age 60 over(1)

Table A.8: Regression discontinuity estimates by subsample (JGSS)

59

(2)
0.0289(0.0344)[0.0378]2501-0.1808∗∗∗(0.0411)[0.0478]2501-1.0025(1.9804)[1.9463]2423-2.2182∗∗∗(0.5479)[0.4493]2501
0.3557∗∗∗(0.0388)[0.0427]
2498
2
∞

(3)
0.0584(0.0444)[0.0489]2501-0.2409∗∗∗(0.0444)[0.0638]2501-2.3347(2.0902)[2.5626]2423-1.2461∗∗(0.5916)[0.5913]2501
0.2613∗∗∗(0.0444)[0.0567]
2498
3
∞

(4)
0.0061(0.0455)[0.0599]2501-0.1369∗∗(0.0543)[0.0797]2501
2.4768(2.7740)[3.1767]2423-1.7296∗∗∗(0.5336)[0.7403]2501
0.2210∗∗∗(0.0524)[0.0711]
2498
4
∞

(5)
0.1538∗∗∗(0.0416)[0.0317]1866-0.3409∗∗∗(0.0425)[0.0397]1866-8.7069∗∗∗(2.6224)[1.6162]1805-2.4030∗∗∗(0.4734)[0.3857]
1866
0.4635∗∗∗(0.0571)[0.0354]
1863
1
20

(6)
0.0449(0.0385)[0.0464]1866-0.1973∗∗∗(0.0402)[0.0619]1866-2.1559(1.9224)[2.4468]1805-1.4711∗∗(0.5912)[0.5902]1866
0.2969∗∗∗(0.0416)[0.0550]
1863
2
20

(7)
0.0546(0.0346)[0.0433]1060-0.1989∗∗∗(0.0443)[0.0573]1060-2.3188(1.8613)[2.2561]1024-1.3899∗∗(0.5855)[0.5555]1060
0.3255∗∗∗(0.0404)[0.0508]
1058
1
10

(8)
-0.0114(0.0494)[0.0663]1060-0.2128∗∗∗(0.0568)[0.0910]1060
1.1068(2.4338)[3.5465]1024-0.8613(0.6425)[0.8936]1060
0.1925∗∗∗(0.0459)[0.0814]
1058
2
10

(9)
-0.0090(0.0405)[0.0610]591-0.2309∗∗∗(0.0493)[0.0841]591
0.7656(2.0330)[3.2382]574-1.1627∗(0.5351)[0.8326]591
0.2237∗∗∗(0.0370)[0.0746]590
1
5Notes: The table reports coeﬃcient of the age-above-60 indicator on main outcome variables controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Receipt of pension

Observation
Household income

Observation
Weekly hours worked

Observation
Regular employment

Not working(1)0.2284∗∗∗(0.0478)[0.0283]2501-0.4608∗∗∗(0.0521)[0.0328]2501-12.8064∗∗∗(2.9111)[1.4043]2423-2.7050∗∗∗(0.3820)[0.3060]2501
0.4972∗∗∗(0.0558)[0.0291]
2498
1∞

Table A.9: Jump of outcome variables at age of 60 (JGSS): Male sample

60

(2)
0.0989∗(0.0514)[0.0482]2639-0.0987∗∗(0.0386)[0.0377]2639-5.9886∗∗(2.2634)[1.8297]2572-1.8941∗∗∗(0.5201)[0.4020]2639
0.3966∗∗∗(0.0373)[0.0422]
2639
2
∞

(3)
-0.0212(0.0473)[0.0626]2639-0.0852(0.0522)[0.0502]2639-2.5323(2.5493)[2.4162]2572-1.0686∗(0.5937)[0.5237]2639
0.3041∗∗∗(0.0304)[0.0565]
2639
3
∞

(4)
-0.0586(0.0548)[0.0780]2639
0.0125(0.0609)[0.0638]2639
0.8621(3.0992)[3.0326]2572-0.8346(0.7715)[0.6517]2639
0.2458∗∗∗(0.0288)[0.0709]
2639
4
∞

(5)
0.1325∗∗∗(0.0476)[0.0411]
1924-0.1136∗∗∗(0.0344)[0.0318]
1924-6.7567∗∗∗(2.0090)[1.5560]
1876-2.0445∗∗∗(0.4625)[0.3468]
1924
0.4739∗∗∗(0.0420)[0.0349]
1924
1
20

(6)
-0.0325(0.0456)[0.0608]
1924-0.0454(0.0510)[0.0486]
1924-1.5950(2.5681)[2.3486]
1876-1.0450(0.6278)[0.5086]
1924
0.3298∗∗∗(0.0343)[0.0546]
1924
2
20

(7)
-0.0027(0.0429)[0.0566]
1098-0.0576(0.0456)[0.0453]1098-2.4920(2.4605)[2.1794]1069-1.2705∗(0.6574)[0.4873]1098
0.3265∗∗∗(0.0314)[0.0510]
1098
1
10

(8)
0.0398(0.0616)[0.0884]1098-0.0761(0.0509)[0.0745]1098-4.6700(2.7686)[3.4430]1069-0.9751(0.9667)[0.7331]1098
0.2688∗∗∗(0.0360)[0.0824]
1098
2
10

(9)
0.0735(0.0417)[0.0817]631-0.0808(0.0521)[0.0665]631-5.3424∗(2.4219)[3.1515]610-1.3212(0.9650)[0.6629]631
0.3142∗∗∗(0.0399)[0.0766]631
1
5

Notes: The table reports coeﬃcient of the age-above-60 indicator on main outcome variables controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Receipt of pension

Observation
Household income

Observation
Weekly hours worked

Observation
Regular employment

Not working(1)0.1938∗∗∗(0.0422)[0.0334]2639-0.0865∗∗∗(0.0295)[0.0258]2639-7.4031∗∗∗(1.6697)[1.2543]2572-2.6356∗∗∗(0.3686)[0.2793]2639
0.5756∗∗∗(0.0446)[0.0278]
2639
1∞

Table A.10: Jump of outcome variables at age of 60 (JGSS): Female sample

61

(2)
-0.0216(0.0435)[0.0474]2471-0.0112(0.0473)[0.0470]2471
0.7658(2.6219)[2.2634]2390-1.3915∗∗∗(0.5058)[0.4166]2471
0.3051∗∗∗(0.0419)[0.0450]
2469
2
∞

(3)
-0.0595(0.0530)[0.0624]2471-0.0517(0.0541)[0.0632]2471
1.0314(2.7957)[3.0294]2390-0.2996(0.4726)[0.5336]2471
0.1956∗∗∗(0.0421)[0.0610]
2469
3
∞

(4)
-0.1248∗(0.0686)[0.0772]2471
0.0412(0.0685)[0.0808]2471
6.9167∗(3.9512)[3.8017]2390-0.3966(0.6387)[0.6401]2471
0.1650∗∗∗(0.0530)[0.0766]
2469
4
∞

(5)
0.0697(0.0460)[0.0409]1825-0.1072∗∗(0.0434)[0.0403]1825-4.5120∗(2.5738)[1.9274]1765-1.4100∗∗∗(0.4154)[0.3598]
1825
0.3979∗∗∗(0.0522)[0.0378]
1823
1
20

(6)
-0.0766(0.0549)[0.0615]1825-0.0064(0.0584)[0.0623]
1825
2.4954(3.3096)[2.9787]1765-0.4661(0.5377)[0.5174]1825
0.2388∗∗∗(0.0392)[0.0597]
1823
2
20

(7)
-0.0759(0.0533)[0.0572]1017-0.0019(0.0603)[0.0583]1017
2.0874(3.2758)[2.7608]981-0.4273(0.5153)[0.5027]1017
0.2390∗∗∗(0.0313)[0.0559]
1016
1
10

(8)
-0.0774(0.0711)[0.0870]1017-0.0749(0.0559)[0.0938]1017
1.4148(2.8508)[4.3087]981
0.0791(0.5797)[0.7025]1017
0.1355∗∗(0.0633)[0.0882]
1016
2
10

(9)
-0.0927(0.0578)[0.0810]568-0.0535(0.0574)[0.0844]568
2.6029(3.0836)[3.9662]544-0.2765(0.5224)[0.6508]568
0.1829∗∗∗(0.0413)[0.0820]568
1
5

Notes: The table reports coeﬃcient of the age-above-60 indicator on main outcome variables controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Receipt of pension

Observation
Household income

Observation
Weekly hours worked

Observation
Regular employment

Not working(1)0.1582∗∗∗(0.0445)[0.0333]2471-0.1603∗∗∗(0.0391)[0.0320]2471-7.6048∗∗∗(2.4556)[1.5524]2390-1.7529∗∗∗(0.3422)[0.2908]2471
0.4747∗∗∗(0.0523)[0.0300]
2469
1∞

Table A.11: Jump of outcome variables at age of 60 (JGSS): Start career with small ﬁrm

62

(2)
0.1335∗∗∗(0.0462)[0.0443]2669-0.2372∗∗∗(0.0411)[0.0450]2669-6.7103∗∗∗(2.0156)[1.9679]2605-2.4774∗∗∗(0.4644)[0.4182]2669
0.4358∗∗∗(0.0422)[0.0413]
2668
2
∞

(3)
0.0374(0.0583)[0.0572]2669-0.2023∗∗∗(0.0498)[0.0591]2669-3.0872(2.6057)[2.5583]2605-1.6810∗∗∗(0.4805)[0.5464]2669
0.3501∗∗∗(0.0416)[0.0546]
2668
3
∞

(4)
0.0425(0.0501)[0.0705]2669-0.0990(0.0630)[0.0740]2669-1.6310(2.7839)[3.1543]2605-1.7048∗∗∗(0.4945)[0.6899]2669
0.2744∗∗∗(0.0375)[0.0684]
2668
4
∞

(5)
0.1941∗∗∗(0.0395)[0.0371]1965-0.2965∗∗∗(0.0433)[0.0376]1965-9.4627∗∗∗(1.9687)[1.6387]
1916-2.7201∗∗∗(0.4345)[0.3595]
1965
0.5317∗∗∗(0.0489)[0.0334]
1964
1
20

(6)
0.0451(0.0496)[0.0547]
1965-0.1837∗∗∗(0.0451)[0.0574]1965-4.0323∗(2.2568)[2.4629]1916-1.7174∗∗∗(0.4804)[0.5411]1965
0.3694∗∗∗(0.0429)[0.0521]
1964
2
20

(7)
0.0763∗(0.0427)[0.0507]1141-0.1772∗∗∗(0.0500)[0.0530]1141-4.0931∗∗(1.8674)[2.2699]1112-1.8452∗∗∗(0.5029)[0.5092]1141
0.3947∗∗∗(0.0438)[0.0481]
1140
1
10

(8)
0.0585(0.0592)[0.0789]1141-0.1427∗∗(0.0664)[0.0846]1141-2.3784(2.8609)[3.5419]1112-1.4320∗∗(0.5404)[0.8274]1141
0.2982∗∗∗(0.0515)[0.0783]
1140
2
10

(9)
0.1029(0.0604)[0.0734]654-0.1759∗∗∗(0.0509)[0.0766]654-4.3218(2.7843)[3.2709]640-1.7754∗∗∗(0.4797)[0.7587]654
0.3325∗∗∗(0.0563)[0.0721]653
1
5

Notes: The table reports coeﬃcient of the age-above-60 indicator on main outcome variables controlling for a polynomial of age without covariates. We allow theparameter of polynomial to vary on either side of the cutoﬀ. Standard errors are clustered at age in parentheses. Robust standard errors are also reported inbrackets.
∗ signiﬁcant at 10 percent, ∗∗ signiﬁcant at 5 percent, ∗∗∗ signiﬁcant at 1 percent

Observation
Order of Polynomial
Bandwidth

Observation
Receipt of pension

Observation
Household income

Observation
Weekly hours worked

Observation
Regular employment

Not working(1)0.2432∗∗∗(0.0385)[0.0313]2669-0.3194∗∗∗(0.0391)[0.0307]2669-11.0092∗∗∗(1.9062)[1.3555]2605-3.1815∗∗∗(0.3782)[0.2883]2669
0.5944∗∗∗(0.0474)[0.0273]
2668
1∞

Table A.12: Jump of outcome variables at age of 60 (JGSS): Start career with small ﬁrm