11 Abe’s Womenomics Policy
Did It Reduce the Gender Gap
in Management?
nobuko nagase

11.1 Introduction
The underutilization of female human resources is an urgent problem
in East Asian countries that face declining births, aging populations,and expected future declines in their labor forces. Many East Asian
countries, such as Japan and Korea, also have a large gender wage
gap. Prime Minister Abe announced that promoting female labor
force participation would be one of his core growth policies when
he came into ofﬁce in late 2012. However, promoting higher labor
force participation is not enough if family responsibilities keep
women in the low earnings sector. Enabling females to build theircareers is also an important goal. Nagase (2018a) found a signiﬁcanteffect of “Womenomics” on women’s long-term employment position after their ﬁrst childbirth. Long-term employment, or seishain1
in Japan, connects to one’s future higher wage growth; as such, theincrease in work continuation of mothers in long-term employment isa welcome change. This chapter will review developments concerning* The author would like to thank Japan’s Statistics Ofﬁce for providing the Labour
Force Survey microdata. The data was applied for and used based on funding
provided by the Japan Society for the Promotion of Science (JSPS) Grant in Aid
for Scientiﬁc Research (C) No. 15K03503 for a project entitled “East Asia’s
Declining Birthrates, Institutions to Match Spouses, and Labor Markets”(Project Leader: Nobuko Nagase). I would also like to thank the Ministry of
Health, Labor, and Welfare for providing the Basic Survey on Wage Structure
microdata. The data was applied for and used based on funding provided by the
Joint Usage and Research Center Programs of the Institute of Economic
Research, Hitotsubashi University, “Student Loan Burden on Youth
Development and Family Formation” (Project Leader: Nobuko Nagase). I thankDr Takeo Hoshi, Dr Lorrain Dearden, Dr Hiroshi Ono, and participants at the
Seminar at Stanford University in 2018 and 2019 and the Japan Economy
Network at the Bank of Japan in 2019 for their helpful comments. I thank
Dr Elaine McCrate for her helpful comments and her warm support.

310

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

311

Japanese female labor, placing Abe’s Womanomics policy as part oflarger policy developments. It will then closely examine the genderpromotion gap, by employing two governmental micro data sources,
the Labor Force Survey and the Basic Survey on Wage Structure, tosee whether Abe’s policy had any signiﬁcant effect in increasing
women in management.
For the readers who are not familiar with Japanese labor market, thischapter will ﬁrst provide an overview of traditional Japanese employment practice and its effect on the gender gap in the workplace.
Secondly, it will review various measures taken from 1980s up to
today by the government to close the gap and their effects. Thirdly,
the paper will examine developments in the earnings distribution bygender from the late 1990s to the 2010s: though the gap is closing, data
still show a large gap. Finally, this chapter will discuss in more detailAbe’s new policy to increase the number of women in management inJapan. In particular I focus on a major law, Josei Katsuyaku Suisin Hō
(or The Act on Promotion of Women’s Participation and Advancementin the Workplace), proposed in 2014 and passed in the summer of2015, that mandates enterprises with more than 300 employees to takeaction to actively use female employees in management, although themandate is rather weak. The chapter will then investigate whether theperiod of the Abe administration has had a signiﬁcant impact on thenumber of women being promoted to management levels.

11.2 Background: Traditional Japanese Employment Practiceand the Equal Employment Opportunity Law
The gender gap is large in Japan. The World Economic Forumannounced in 2017 November that Japan ranked 114th among 144
countries in the gender gap index. With respect to economics, a large
gender wage gap and a low percentage of females in professional,
engineering, and management professions contributed to the low
ranking.
In this section, I will review the development of female labor inJapan. In 1985, the Equal Employment Opportunity Law (EEOL)
passed. However, despite the law, wage regressions have shown thatthe coefﬁcient gap between the genders increased between 1984 to
1994 at large ﬁrms, even though the endowment difference narrowed(Hori 1998; Abe 2010, 2011).

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

312

Nobuko Nagase

Before the passage of the EEOL, large ﬁrms selectively employed
university graduate males to be on a male-only fast promotion track,
trained them as future managers, and promoted them to chief. Often
then they became section heads and then department managers
through tournament competition. In contrast, females were only
hired in the slow track and given clerical assistant jobs, with the
expectation that women would retire at marriage or childbirth. Afterthe passage of the EEOL in 1985, ﬁrms could no longer explicitly
discriminate in hiring by sex, but in fact they maintained similar hiring
and training practices. They formally renamed the employment trackthat was previously only for university graduate males as the “fast track
course” while also allowing females to apply, and they renamed thefemale hiring track as the “slow track course.” Only a small number offemales were employed along with males in the newly created “fasttrack course” after the passage of the EEOL, and the slow track course
remained dominated by females. Studies found that many of those
women in the fast track course quit work after several years – forexample, Ohuchi (1999).
Still about half of ﬁrms with more than 5,000 employees today havea course-based hiring practice. This ratio has remained stable according to Ministry of Health, Labor, and Welfare’s Basic Survey of Gender
Equality in Employment Management. The percentage of ﬁrms thathave such a practice is increasing among ﬁrms with 300 to 1000
employees, although such practice is most often found in larger
companies.
In June 2008, the Ministry of Health, Labor, and Welfare established
a committee on “The Gender Wage Gap under Changing Wage andLabor Practice.” After the Asian ﬁnancial crisis of 1998, Japaneseemployment practice changed substantially. Hiring of long-term
employees lessened and hiring of ﬁxed-term employees increased.
Females in the slow track course were often replaced by ﬁxed-term
employees and dispatched workers, especially in larger ﬁrms. The
Japan Institute of Labor Policy and Training (JILPT) in cooperation
with the committee conducted a wage regression of full-time workers
using the Basic Survey on Wage Structure of 2000 and 2006. It foundthat the gender wage gap is larger when ﬁrms have “course based
hiring” (JILPT 2009; Fujii 2009) and that the wage gap is closing
mainly due to the shrinking gender age gap among long-term employees. This in turn happened because more women stayed single andhttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

313

worked as long-term employees longer, even though many still quit
when they had children. The analysis also showed that females aremuch less likely to become managers, and this contributed to thegender wage gap (Fujii 2009).
In recent years, the distribution of the gender wage gap has gained
renewed attention internationally. Whether the gap is glass ceiling or
sticky ﬂoor has been newly investigated by using quantile regression
on Swedish and American data (Albrecht et al. 2003). Hara (2018)
conducted a similar distributional gender wage gap analysis in Japan
using selected data on full-time employees from 1980 to 2015 using
the Basic Survey on Wage Structure. Using the Firpo-Fortin-Lemieux
decomposition (Firpo et al. 2009), Hara found that the raw genderwage gap generally decreased from 1980 to 2015 at most points in thewage distribution, especially in recent years, except at the top where
the gap grew substantially after 2010. She also showed that the gap
was larger in the lowest part of the wage distribution among large ﬁrms
presumably due to course-based hiring practices, while the gap waslarger in the highest part of the distribution at smaller ﬁrms in 2015.

11.3 Recent Measures to Close the Gender Wage Gap in JapanThe government has sought to close this large gender gap by threemethods. One is to change the incentives and constraints faced by
women when deciding whether to stay in long-term labor contracts
after marriage and childbirth. In Japan, the wage prospects of longterm employees compared to hourly part-time, ﬁxed-term contract andother non-seishain employees are very different, as will be shown in
Section 11.6. The prospect of higher wages in the latter sector is poor.
Long-term employees are given more training and have a higher probability of promotion. Therefore, promoting work continuation inseishain positions at marriage and at childbearing is a meaningfulmeasure for closing the gender wage gap. Measures of this sort included
increasing the income replacement rate of the childcare leave allowance, allowing seishain mothers to return to their jobs on a part-timebasis after childbirth upon their request, reducing work hours overall,
introducing ﬁve days a year of sick leave for the care of pre-school
children, and reforming the childcare system. Some of these measures
were taken before the accession of the Abe administration in late 2012and some during his administration.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

314

Nobuko Nagase

The second government strategy is to change the incentives of ﬁrms
to promote women to management, through a series of nudges tochange corporate culture. Several measures of this kind have been
adopted during the Abe administration. The government has aimed
to nudge ﬁrms to hire and promote more females through statutory
requirements to disclose their gender gap data, such as the gender ratio
in management and the gender gap in hiring. This may negatively
impact the recruitment of new female hires at companies with poor
records. In addition, the government has argued that ﬁrms in general dobetter with diversiﬁed management boards.
Third, the government also sought to increase the wage of nonstandard workers, who are poorly paid and highly disproportionately
female. There are two policies of this sort. The ﬁrst aims to reducethe incentive of a spouse to keep their income low, by attempting tochange spousal tax deduction rules and to change ﬁrms’ dependent
spouse allowance linked to tax deduction rules, as will be describedlater. The second introduces the new equal-work/equal-wage principle
irrespective of job contract status.
Early measures taken to encourage women to continue work afterchildbirth included the introduction of childcare leave in 1992, theintroduction of a childcare leave allowance in 1995, and an increase in
the leave allowance from 25 percent to 40 percent of base pay in 2001.
However, the introduction of childcare leave increased women’s work
continuation after marriage but had no effect after childbirth (Nagase
1999). Nor did raising the childcare leave allowance of 2001 produce
any change in behavior (Asai 2015). According to my interviews, many
women felt that it was difﬁcult to take the leave unless their bosses,
colleagues, and husbands were supportive. However, corporate culture
was not supportive enough, and husbands came home late.2
This effort to retain women in the long-term labor market did not
succeed for some time. Other problems remained in corporate culture.
Under Japanese employment practice, large ﬁrms internally train newhires in different sections of a ﬁrm by relocation, evaluation, and gradualpromotion to chief, then to section head. Since ﬁrms invest in workers’
ﬁrm-speciﬁc training, hoarding occurs during economic downturns, andovertime occurs during economic booms, compared to more frequentlayoffs and hiring among US ﬁrms (Houseman & Abraham 1993;
Abraham & Houseman 1989). Because of the higher ﬁrm-speciﬁc training, returns to tenure are higher compared to those in the USA

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

315(Hashimoto & Raisian 1985, 1992). However, overtime work andsudden orders by the company to relocate are hard to reconcile withfamily needs. Consequently, many female workers resigned at marriage
in the 1980s and then at pregnancy in the 1990s and 2000s. Some wishedto take care of their own children, but others felt corporate culture madeit difﬁcult to take childcare leave (Teramura 2014; Enmi & Brinton2015). Once women quit their “good jobs” – that is, the seishain jobs
that they had begun upon graduation – they often reentered the labor
force as part-time nonstandard employees at a wage near the minimum
wage. However, the National Fertility Survey of 2002, 2005, and 2010
revealed that there was almost no increase in the average employment
rate of mothers across ﬁve-year birth cohorts of their infants, observed
when the ﬁrst child was one year old. It was 26.8 percent in 2005 to
2009, not much higher than the 24.4 percent in 1990 to 1994.
Eventually, employment of seishain mothers did start to go up around2009 and then accelerated after 2013. The short hour option mandateof 2009 – which allowed workers with a child under three to work six
hours a day, applied to ﬁrms with more than 100 employees from 2010
and to all ﬁrms from 2012 – was key to the rising employment ofseishain mothers. By using time differences in enactment of the law as
a natural experiment, Nagase (2014, 2017) found that the law hada signiﬁcant and powerful effect on both childbirth and labor supply.
The National Fertility Survey of 2015 also showed that new mothers’
employment rate when their ﬁrst child was age one was 29.1 percent for
those who had a child in 2005–2009 but rose to 38.3 percent among
women with ﬁrst births in 2010 to 2014. However, Takeishi (2010) andMatsubara (2012) argue that the short hour option may negatively
affect female careers. In part because of this, increasing women’s promotion is another important feature of Womenomics.
Formal infant care provision was also helpful for maternal work continuation in general (Nagase 2003a; Unayama 2011; Nagase 2018a) – or atleast helpful for work continuation among mothers in nuclear families(Asai et al. 2015) – but the provision was low in metropolitan areas andhigher in rural areas. The Noda administration in 2012 prepared andenforced a signiﬁcant reform concerning both day care and kindergarten,
better coordinating their regulation. Before this reform, the development ofchildcare slots in urban areas was slow until 2008,3 despite the series of“Angel Plans” in 1990s (Nagase 2007) and remained slow till 2012
(Nagase 2018a).

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

316

Nobuko Nagase

In the Japanese type of internal training system, employees are often
trained to become managers. However, according to interviews, even if
women were employed in the fast track course right after the EEOL reform,
they were more likely to be placed in clerical jobs than males (Ohuchi1999). Such different allocation of jobs was reduced after some years, butbosses still often gave women routine tasks, especially after childbirth,while males were given more challenging assignments (Yamaya &Nagase 2012; Nagase & Yamaya 2011). In order to be promoted to
manager, internal valuation accumulation points should exceed those ofcoworkers. Many ﬁrms had grading systems that gave low evaluations tochildcare leave takers and short hour workers. Some of our interviewees
reported that at their ﬁrm, when a woman had a child, her promotion
would come much later than that of comparable males who have no needto take childcare leave. A survey of seishain mothers by 21seiki Shokugyo
Zaidan (2014) found that, on average, the respondents felt that theirbosses’ provision of training and feedback declined after they took childcare leave.

11.4 Abe’s Policy Concerning Female Promotion and Closing
the Wage Gap
Starting in 2013, the Abe administration continued to expand policies toencourage women to continue work as seishain. With strong leadership,
it rapidly increased the number of childcare facilities, and the growth ofchildcare slots accelerated after a reform of childcare in 2012. The
administration again increased the childcare leave allowance in the ﬁrst
six months after birth from 50 percent to 67 percent of base pay.
In Section 11.4.1, I will discuss laws that preceded Abe administrationand then the new legislation that passed during the Abe administration to
encourage ﬁrms to promote women to management. This is primarily theJosei Katsuyaku Suishin Hō of 2015. I will then discuss another important policy concerning women’s wage – that is, policy to close the wage
gap between standard and nonstandard workers – in Section 11.4.2.

11.4.1 Laws That Nudge Firms to Promote Women
to Management
Starting around 2003, the government began to focus attention on thepractices of ﬁrms that may discourage women’s work continuation.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

317

The Law to Support the Next Generation of 2003 mandated that ﬁrms
with more than 300 employees assess their ﬁrm practices for compatibility with family caregiving responsibilities, starting in 2004 as measurement for low birth rate. In addition, the goal of increasing the shareof women leaders to at least 30 percent by 2020 was adopted in 2003 as
the Gender Equality Head Ofﬁce Decision. It was reafﬁrmed in
December 2010 as the Cabinet Decision, when the third Basic Planfor Gender Equality was adopted.4 The “2020–30” target – achievea 30 percent target for females in authoritative positions by 2020 – is an
old policy that has been hard to achieve. The interim report showedthat actual progress was far from the target.5 In the fourth Gender
Equal Participation Basic Plan of 2015, the target was modiﬁed to, forexample, 25 percent women for the lowest managerial category,
kakarichō or section chief, at private enterprises, an increase fromtheir actual representation of 16.2 percent in 2014. Similarly, thePlan established a target of 15 percent women for kachō, or section
heads, by 2020, up from 9.2 percent in 2014. Finally, it set a target
around 10 percent for buchō, or department manager, the highest rank
targeted, which had female representation of 6.0 percent in 2014. This
Basic Plan also set a target of about 5 percent, to be rapidly increasing to10 percent, for women on boards of directors, while the actual percentage was 2.8 percent in 2014. These numbers are calculated from the
Basic Survey on Wage Structure, as the percentage of employees inmanagerial positions among those who have employment contracts
without termination, working at ﬁrms with more than 100 employees.
It seems that even the lower target is still hard to achieve. The White
Paper on Gender Equality (2019) shows that, in 2018, women were18.3 percent of kakarichō, 11.2 percent of kachō, and 6.6 percent of
buchō. This is progress, but it is still short of the revised target.
When Prime Minister Abe came to ofﬁce in 2013, he announced that
he hoped ﬁrms listed on the stock exchange would each appoint at least
one woman on their boards.6 In 2014 June, the Cabinet Decision wasmade to mandate all listed ﬁrms to disclose the number of female
members on their boards, effective in the new ﬁscal year starting in
April 2015. In August 2015, the Abe cabinet also passed the Act
Concerning the Promotion of Women’s Career Activities, Josei
Katsuyaku Suisin Hō, to be implemented in April 2016.
Josei Katsuyaku Suisin Hō nudges enterprises to take actions topromote women. The companies must gather data on the ratio of

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

318

Nobuko Nagase

women among new hires, the gender gap in average years of tenure, theovertime work hours of average workers, and the ratio of womenamong managers. Other types of data, such as the number of womenand men taking childcare leave, must be analyzed, although ﬁrms are
not mandated to disclose more than one of them.7 Large ﬁrms are also
required to make action plans. Speciﬁcally, the law requires ﬁrms withmore than 300 employees to analyze the status of women within theirﬁrms and then to make action plans to increase their active
participation.8 The action plans should have speciﬁc timelines, measures, and the actual targets to be reached. The plan should beannounced to workers and made public. It must also be registered at
the local MHLW ministry ofﬁce.
Those ﬁrms with good performance are given the Eruboshi recognition, which consists of three grades. These ﬁrms can put the Eruboshi
logo on their products.9 In March 2016, the government announced
that the recognized ﬁrms would also be given preferred points in public
procurement.10 In May 2016, the government announced that 46 ﬁrms
got Eruboshi recognition. The number increased to 291 by
March 2017, 579 by March 2018, 837 by March 2019, and 1028 byMarch 2020.

11.4.2 Other Laws That Aim to Change Japanese Labor
Practice and Close the Gender Gap
The more recent Womenomics policies of the Abe cabinet concern
three things. The ﬁrst policy is putting a cap on the long overtime
hours among seishain workers. The second is closing the wage gap
between standard and nonstandard workers, such as so-called parttime workers (arubaito), “dispatched workers,” “ﬁxed term contract
workers” and “shokutaku.” These workers are disproportionately
female. The third is reform of the tax code. Regarding the ﬁrst ofthese, the overtime reform was made into law. From the beginning of
2016, the buzzword of the Abe cabinet was “Hatarakikata Kaikaku” –“Change the Way We Work.” When Abe reorganized the cabinet in2016 August, he said, “The greatest challenge we meet is the
Hatarakikata Kaikaku.” The Hatarakikata Kaikaku Hō was proposedin 2016 and passed the Diet in 2018. Among its contents, it morestrictly regulates overtime work for large ﬁrms starting in April 2019and one year later for smaller ﬁrms.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

319

The Hatarakikata Kaikaku Hō also included guidelines for the principle of “equal work, equal pay,” regardless of whether one has
a standard or nonstandard contract. The guidelines, announced inlate 2018, say that, in principle, if workers engage in the same workand have equal capability, experience, and performance, the pay
should be equal, irrespective of contract types. It is not easy to deﬁnewhat equal work is. Therefore, companies are to explain to workers therational reasons for differences in pay and beneﬁts, as well as fordifferences in training between standard and nonstandard employees
and to remedy any irrational differences. The prefectural labor ofﬁces
are to negotiate disputes between employer and employees. This principle is to be implemented starting in April 2020 for larger ﬁrms andone year later for smaller ﬁrms. The effect of this policy is yet to be seen.
Finally, Japanese tax policy has for a long time worked to support
nonstandard work arrangements that often were for married females,
who hoped to supplement the household budget. Scholars argued thatthey were accepting low wage and short work hours because their work
motive was only to bring in some addition to the household budget
However, in the late 1990s to early 2000s, nonstandard work arrangements increased among young workers who needed to support their own
living. This happened because of a decline in demand by employers forlong-term employment. Moreover, the number of single mothers
increased, who also needed to support their living but many of themalso worked in nonstandard employment. Among these nonstandard
workers, part-time and arubaito are hourly paid workers, whose work
hours can be either short or full-time and are paid near minimum wage.
Higuchi (1995), Nagase (2002, 2003b, 2018a, 2018b), Abe (2002),
Akabayashi (2006), and Abe and Ohishi (2009) point out that the protection for dependent housewives through the spousal tax deduction andsocial security tax exemption is a core mechanism that limits the incomeof married females. Married women increase their labor supply whenchildren grow older, but, when their annual income reaches 1.03 million
yen,11 the threshold for the tax deduction for dependent spouses, or reaches
1.30 million yen, the threshold for the social security tax exemption for
dependent spouses, many of them adjust their work hours to hold theirincome below these thresholds, because otherwise the greater tax burden islarge compared to the increased income achieved by working longer hours.
Takahashi (2010) and Bessho et al. (2014) say that the effect of thetax structure on labor supply is not large. However, the resulting

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

320

Nobuko Nagase

incentives for good workers to limit their hours reduces pressure forhigher wages in the part-time labor market. Through wage arbitration
between married part-time workers and unmarried workers, the conduct of the former, who beneﬁt from such tax provisions, not only
negatively affects their own wage level but also that of unmarried parttime and arubaito workers who do not beneﬁt from keeping income
below the thresholds (Nagase 2018b).
The Abe cabinet repeatedly announced, in 2014 and 2016, that it
would change the rule concerning the spousal income tax deduction
threshold of married females. Abe also urged large companies to change
their own spousal allowance rules so that they would not affect marriedfemales’ work hour choice.12 However, the Abe cabinet in the end did
not abolish the spousal tax deduction threshold. Instead, it surprisingly
increased the spousal tax deduction threshold to 1.5 million yen.
Theoretically this raises the total working hours at which unmarried
workers have to compete with married women who beneﬁt more fromthe national tax spousal deduction and social security tax exemption. It
will increase the work hours of married females who are willing to workwith low earnings, unless those earnings exceed the sum of their social
security tax exemption and their husbands’ spousal allowance.13 The
effect of this last policy is yet to be determined, as it was announced onlyin late 2016 and implemented in 2018.
In subsequent sections, I will use Japanese micro data to illustratechanges and the present situation of gender wage gap in Japan; I will
also show how female promotion differed by cohort and determine
whether Abe’s policy made any difference.

11.5 About the Data Used in this Analysis
The Labor Force Survey, collected by the Statistics Ofﬁce, isa nationally representative monthly survey covering about 40,000
households and about 100,000 individuals over the age of 15.14 The
earlier Labor Force Special Survey (Tokutei Chosa) collected detailed
information on educational attainment, income, and employment
before it was terminated in 2001. From 2002, the Labor Force Survey
incorporated questions previously included in the Labor Force Special
Survey. From January 2002, the survey began to use a longer questionnaire in the fourth visit that asked not only about labor force status but
also about educational attainment, job tenure, and annual income inhttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

321

the previous year for all relevant individuals in the household. It
provides data on about 10,000 households, or 18,000 to 22,000 individuals every month. To look at long-term trends, the analysis of thischapter uses microdata of the Labor Force Special Survey conductedeach February from 1988 to 2001 and data from the January to MarchLabor Force Survey from 2002 to 2018 to make a connected time series
from 1988 to 2017.
Since the LFS series only has categorical data on the previous year’s
annual income, in twelve categories, the hourly wage rate is computed
as the midpoint of the annual income category divided by the productof weekly work hours times ﬁfty weeks.15 One can identify managers in
the LFS by using the variable on occupations.
I will also use another microdata set, the Ministry of Health, Laborand Wealth’s Basic Survey on Wage Structure, 2002–2017. It isa survey of ﬁrms with more than ﬁve employees conducted every July.
It collects data about salary, bonus, overtime pay, and work hours. The
sample includes private enterprises and workplaces with more than ﬁve
standard employees and public enterprises with more than ten standard
employees; the sample size is as large as 1 million or more per year. In
2005, the questionnaire was reformed to be more sensitive to theincreased number of nonstandard workers. Before 2005, it did not
ask full-time workers if they were seishain. From 2005, it revised its
questionnaire sheet and surveyed seishain workers and non-seishain
workers, including those with ﬁxed- term contracts. It also inquires as
to whether one is working part-time. It has questions about managerial
status, but only for those who work at ﬁrms larger than 100 employees.

11.6 Change in the Gender Wage Ratio and Wage Distribution
Figure 11.1 shows the time series average gender wage ratio for workers aged twenty-three to ﬁfty-nine, displayed by educational category,using the LFS. Until 2012, the standard retirement age was sixty, so
that, for the longer time series, excluding those sixty and over will moreclosely standardize the comparison.16“Gender wage ratio, total” represents the average ratio of women’s
to men’s wages among all workers, including both permanent contract
standard workers and nonstandard employees. This ratio is increasingat the aggregate level. The average wage of females was around 50 percent of that of males in 1988, but the ﬁgure increased to aroundhttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

322

Nobuko Nagase

90
85
80
75
70
65
60

50

1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

55

gender wage ratio, total
seishain, or permanent standard employees, total
seishain, high school
seishain, university
seishain, university, age 23–39

Figure 11.1 Female average wage as percent of male average wage, byeducational attainment, age 23–59 when not otherwise speciﬁed
Source: Author’s calculations using the Labor Force Special Survey 1988–2001
and Labor Force Survey 2002–2017 January–March

65 percent in 2017. When the ﬁgure is limited to those who havepermanent seishain contracts, the gender wage ratio is higher, and thefemale wage, which was over 60 percent of the male wage in 1988, wasapproximately 75 percent in 2017. Because more women than men
work as nonstandard workers, and because the average wage of nonstandard workers is low, the overall gender wage ratio is smaller when
considering all workers. Restricting the estimate to permanent standard contract workers thus produces a higher estimate of the genderwage ratio.
Now consider the trends in the gender wage ratio by educational attainment for permanent contract standard workers. The
gender wage ratio was smaller in the late 1980s, especially among
workers with less education. For those with high school educationor less, the wage ratio was a little over 60 percent in 1988 andaround 70 percent in 2017. In contrast, the gender wage ratio
among university graduates who were seishain was higher

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

323

compared to the ratio among less educated workers in 1988. The
average wage of university-educated females was about 70 percentof the corresponding male wage in 1988. However, the subsequent
improvement was small, with the ratio remaining a little over
70 percent in 2017. This may be because female university educational attainment is increasing faster than that of males, so thatthe average age and average experience of female university graduates are lower overall. Therefore, I also calculated the ratio for
university graduate workers aged twenty-three to thirty-nine,
expecting an increase in gender wage ratio. Now the ratio iseven larger, around 80 percent of the male wage in 1988, but it
also stayed the same during this period, around 80 percent of themale wage in 2017. Therefore, the stubborn gap among university
graduates cannot only be due to the average experience gap bygender.
The ﬁgures show that the overall gender wage ratio among seishain
workers is increasing over time. And while it is larger among those with
university education, the gap is closing more slowly for this group thanfor the less educated, among permanent-contract standard workers.
The gap may be caused by difference in promotion.
I will now show the kernel estimation of the wage distributionsof male and female workers in this section using selected years of
the Labor Force Survey, ﬁrst for permanent contract standard
workers and then for nonstandard workers. Comparing Figures
11.2 and 11.3 – that is, the distribution of wages for permanentcontract standard workers, by sex – women’s wage distribution ismuch narrower than men’s: men are more likely than women tohave an hourly wage rate over 3,000 yen. Figures 11.4 and 11.5
show that, for nonstandard workers, the wage distribution is concentrated at the lower end for both males and females, thoughmore so for females.
All the distributions are right-skewed. For both permanent contract standard workers and nonstandard workers, the female wage
is moving to the right over time, and their wages are on averageincreasing. On the other hand, male workers’ wage distribution ismoving to the left and deteriorating. Despite these gap closing
trends, the wage distribution difference between genders continues
to be very large. Difference in promotion may be one of thehttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Nobuko Nagase

0

Density of full-time permanent workers.0001 .0002 .0003 .0004 .0005

324

0

2,000

4,000
Hourly wage rate in yen
Male 1996
Male 2012

6,000

8,000

Male 2003
Male 2017

0Density of full-time permanent worker
.0002
.0004
.0006

Figure 11.2 Wage distribution of males for permanent contract standard
workers

0

2,000

4,000
Hourly wage rate in yen
Female 1996
Female 2012

6,000

8,000

Female 2003
Female 2017

Figure 11.3 Wage distribution of females for permanent contract standard
workers

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

325

0

Density of non-standard employees
.0002
.0004
.0006

Abe’s Womenomics Policy

0

2,000

4,000
Hourly wage rate in yen
Male 1996
Male 2012

6,000

8,000

Male 2003
Male 2017

0Density of nonstandard employees.0002 .0004 .0006 .0008.001

Figure 11.4 Wage distribution of males for all nonstandard workers

0

2,000

4,000
Hourly wage rate in yen
Female 1996
Female 2012

6,000

Female 2003
Female 2017

Figure 11.5 Wage distribution of females for all nonstandard workers

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

8,000

326

Nobuko Nagase

reasons for the large gender wage gap, which I will examine in thenext section.

11.7 Change in the Gender Composition of Managers
11.7.1 Deﬁnition of Managers
In this section, I will analyze the promotion difference by gender in theJapanese labor market. As mentioned in Section 11.4.1, the JapaneseCabinet Ofﬁce had explicit targets for women in managerial positions,for example, to increase the female proportion of kachō, section heads,
to 15 percent by 2020.
We need, however, to be careful about the deﬁnition of managers
and thus about the choice of data to employ. Ohi (2004) extensively
reviewed the Japanese governmental statistics concerning workers inmanagerial positions using publicly available data. She noted two
different deﬁnitions of managers in the Japanese governmental statistics. According to one deﬁnition, workers’ occupations are classiﬁed as“managers” if they manage subordinates. According to the other definition, workers have a managerial title in the ﬁrm’s salary table but
they may not have subordinates. Ohi calls the former “managers innarrow deﬁnition” and the latter “managers in broader deﬁnition.”
The Census and the Basic Employment Survey are household surveys
that use the narrow deﬁnition of managers. Ohi observes that the Basic
Employment Survey classiﬁes about 500,000 persons in total as managers; for ﬁrms with more than 100 employees, the number is 300,000
in 2002, or 2.0 percent of workers. In contrast, the Basic Survey on
Wage Structure collects data from ﬁrms, and, using the broad deﬁnition, it enumerates those who are titled as buchō (department head),kachō (section head), kakarichō (section chief), shokuchō (foremen),and sonota shokkai (other managers), among workers at ﬁrms withmore than 100 employees. Ohi shows from the public data that, in thisdeﬁnition, managers altogether comprised 23.4 percent of all workers
in ﬁrms with more than 100 employees in 2004, or 3.40 million
employees.
The government uses both deﬁnitions when it employs targets toincrease the proportion of female managers. The Cabinet Ofﬁce uses
the narrow deﬁnition in the Labor Force Survey to compare the gender
gap in management internationally. The Cabinet Ofﬁce also uses thehttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

327

Basic Survey on Wage Structure to examine the increase in the proportion of all managers who are women. However, their target is just theoverall proportion of managers who are women. In the following
section, I will look at the percentage of workers who are managers,
separately by gender.

11.7.2 Change in the Ratio of Managers by Gender Using
Different Deﬁnitions
Figure 11.6 was made by the author using the Labor Force Survey.
While the governmental target only speciﬁes the percentage of all
managers who are female, I will examine different indicators – that is,
the ratio of female managers among female workers and the ratio ofmale managers among male workers. In my view, it is important to

8.0%
7.0%
6.0%
5.0%
4.0%
3.0%
2.0%

0.0%

1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

1.0%

All workers, male

All workers, female

Firms over 100 employees, maleFirms over 100 employees, female

Firms over 500 employees, maleFirms over 500 employees, female

Figure 11.6 Ratio of managers in narrow deﬁnition among employees aged
22–59 by gender and ﬁrm size
Source: Made by the author from Labor Force Survey Series

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

328

Nobuko Nagase

compare the proportions of managers by gender, not just the proportion of
all managers who are women, because the number of male workers islarger than the number of females. Ohi shows that the overall proportionof managers in private enterprises with more than 100 employees using the
Basic Employment Survey (using the narrow deﬁnition) was 2.0 percent in2002. The proportion for the same population using the Labor Force
Survey (also using the narrow deﬁnition) was a comparable 2.5 percent
in 2002 by my calculation. The two statistics differ, but the ratio ofmanagers is similar because the deﬁnition of managers are both based on
the Statistics Ofﬁce’s Japanese occupational standard classiﬁcation. I show
a longer time series after Ohi’s study. Figure 11.6 shows the same trend as
found in Ohi: the overall ratio of managers decreased from early 1990s to
1998. Then, as shown in triangle marks, the ratio of male managers
among male employees went up after 2000, plateaued in the mid-2000s,
then declined continuously after then. The decline was more notable forlarger ﬁrms with more than 500 employees. The ratio of male managers tomale workers was once over 7 percent, but it was below 4 percent by 2017.
On the other hand, female managers among female workers, presented incircle marks, show that the ratio is just very low and unchanged, regardlessof the ﬁrm size. Figure 11.6 also shows the ratio of managers of eachgender by controlling ﬁrm size to over 100 employees to compare withbroader deﬁnition shown in next two tables, which show a similar trend.
Table 11.1 was made by the author using the Basic Survey on Wage
Structure, showing ratio of managers in the “broader category,” as Ohi
puts it. The deﬁnition of managers in this data is whether one is given
managerial title in salary payment. It includes those who does not haveany subordinates. The Basic Survey on Wage Structure only asks about
managers for ﬁrms with more than 100 employees. Therefore, I divided
the number of male and female managers by the number of male andfemale workers, respectively, at ﬁrms with more than 100 employees.
We see that the ratio of managers – that is, including all department
heads, kachō, kakarichō, foremen, and other managers – declined formales from 27.9 percent in 2002 to a low of 23.5 percent in 2017, while
for females, the bottom was 3.2 percent in 200 and went up to 4.9 percent in 2017. The decline in ratio of males with managerial titles musthave contributed to the sluggish male income after 2000s. Though ratioof male managers increased somewhat after 2014, it was still lower in2017 than during the Lehman shock of 2008. In contrast, for females,
an increase is evident from around 2013. We see that the increase in

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

27.9%
27.7%
25.5%
26.1%
27.0%
26.1%
25.2%
24.1%
24.6%
23.7%
24.1%
23.7%
23.8%
24.5%
24.3%
23.5%

4.0%
4.2%
3.2%
3.3%
3.8%
3.9%
3.8%
4.0%
3.9%
4.1%
4.0%
4.3%
4.6%
4.6%
4.9%
4.9%

female
3.4%
3.4%
3.2%
3.6%
4.0%
3.4%
3.3%
3.4%
3.5%
3.4%
3.8%
3.3%
3.1%
3.4%
3.2%
3.1%

male
0.1%
0.1%
0.1%
0.2%
0.2%
0.2%
0.2%
0.2%
0.2%
0.3%
0.3%
0.2%
0.3%
0.3%
0.3%
0.3%

FemaleDepartment heads,
or bucho

Source: The Basic Survey on Wage Structure, author’s calculation

2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

male

All managers

7.4%
7.5%
7.4%
8.0%
7.8%
7.8%
7.5%
7.2%
7.9%
7.1%
7.1%
7.1%
7.3%
7.5%
7.6%
7.2%

male
0.6%
0.6%
0.6%
0.6%
0.8%
0.8%
0.8%
0.8%
0.8%
0.9%
0.8%
0.9%
1.0%
1.1%
1.1%
1.1%

femaleSection heads, or
kacho

6.6%
6.6%
5.7%
6.7%
6.7%
6.3%
6.2%
5.8%
6.3%
5.9%
5.5%
5.8%
5.8%
6.2%
6.2%
5.9%

1.3%
1.3%
1.1%
1.2%
1.3%
1.4%
1.3%
1.3%
1.4%
1.5%
1.3%
1.5%
1.5%
1.7%
1.9%
1.7%

femaleSection chiefs, orkakaricho
male

Table 11.1 Ratio of managers in broader deﬁnition (denominator, all workers)

8.1%
7.8%
7.2%
6.0%
6.4%
6.3%
6.2%
5.8%
5.1%
5.3%
5.7%
5.8%
5.8%
5.7%
5.7%
5.7%

male

1.7%
1.8%
1.2%
1.1%
1.4%
1.3%
1.4%
1.5%
1.3%
1.3%
1.5%
1.5%
1.6%
1.5%
1.5%
1.7%

femaleOther managers

330

Nobuko Nagase

female managers, especially for the lowest category of kakarichō,
started around 2010 and for section heads, or kachō, around 2014.
However, the ratio shows a different picture if we limit the denominator to workers with permanent employment contracts as in Table
11.2.17 Now when we look at the ratio of all managers for males, theﬁrst left column in Table 11.2, we do not see any decline in the ratio ofmale managers among permanent employment contract workers: it
was 28.4 percent in 2002 and 29.4 percent in 2017.
The difference comes from the increase of ﬁxed-term contract
workers over years. The percentage of permanent employment contract workers among all workers at ﬁrms with more than 100
employees was 86.3 percent for males and 69.6 percent for females
in 2005. For males, that ratio went down to 77.6 percent in 2017 andfor females to 52.3 percent. When we compare the result of ratio of
female managers among all workers with that among permanent
employment contract workers, the ratio nearly doubles for females
in 2017, 4.9 percent vis-à-vis 9.1 percent. For females, the increase in
the ratio of managers is more evident among permanent contract
workers but not as much when ﬁxed-term contract workers areincluded. Table 11.2 shows that the ratio was 4.4 percent in 2002,
while it rose to 9.1 percent in 2017. The proportion of female
managers for the lowest category of kakarichō or section chief started
around 2010 and for kachō or section heads around 2014, the same
trend shown in Table 11.1.
Due to the continued rise over years of nonstandard employment
among males, the ratio of all males who are managers between Table
11.1 and Table 11.2 differs only by 0.5 percentage points in 2002 but
by 6 percentage points in 2017. For the ratio of male kachō or section
heads, for example, the difference was only 0.1 percentage points in2002 but 2 percentage point in 2017, meaning that in 2002 section
heads managed mostly males who had permanent contracts, but in2017 section heads had more male ﬁxed-term contract workers tomanage (see Figure 11.7).
Takeuchi (1995) investigated the labor practice at a large ﬁnancial
ﬁrm concerning the promotion of male entrants of the ﬁrm in theuniversity graduation year of 1966. He showed that 99 percent ofmale university graduates of 1966 were promoted to section chief
exactly at the ﬁfth year of tenure. Then the tournament promotion tosection heads was made from the age of thirty-four among section

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

28.4%
28.3%
26.4%
29.7%
30.8%
30.3%
29.6%
28.6%
29.3%
28.4%
29.7%
29.1%
29.7%
30.4%
30.5%
29.4%

4.4%
4.6%
3.6%
5.3%
6.3%
6.6%
6.7%
6.9%
7.0%
7.2%
7.5%
8.2%
8.6%
8.7%
9.0%
9.1%

female
3.5%
3.4%
3.3%
4.0%
4.1%
4.0%
3.8%
4.0%
4.1%
3.9%
4.7%
4.0%
3.8%
4.1%
4.0%
3.7%

male
0.1%
0.2%
0.2%
0.3%
0.4%
0.4%
0.4%
0.4%
0.4%
0.4%
0.5%
0.5%
0.5%
0.5%
0.5%
0.5%

FemaleDepartment heads,
or bucho

Source: The Basic Survey on Wage Structure, author’s calculation

2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017

male

All managers

7.5%
7.6%
7.6%
9.1%
9.0%
9.1%
8.9%
8.5%
9.4%
8.6%
8.8%
8.8%
9.1%
9.3%
9.6%
9.1%

male
0.6%
0.7%
0.7%
1.1%
1.2%
1.4%
1.4%
1.4%
1.5%
1.6%
1.6%
1.7%
1.9%
2.0%
2.1%
2.1%

femaleSection heads, or
kacho

6.7%
6.8%
5.9%
7.7%
7.8%
7.3%
7.4%
7.0%
7.6%
7.2%
6.9%
7.3%
7.3%
7.8%
7.8%
7.5%

male
1.5%
1.5%
1.3%
2.0%
2.2%
2.3%
2.3%
2.3%
2.6%
2.7%
2.5%
2.8%
2.9%
3.2%
3.5%
3.2%

femaleSection chiefs, orkakaricho

8.2%
8.0%
7.5%
6.7%
7.4%
7.3%
7.2%
6.8%
6.1%
6.2%
7.0%
7.0%
7.2%
7.0%
7.0%
7.0%

male

1.8%
1.9%
1.3%
1.7%
2.2%
2.2%
2.4%
2.5%
2.2%
2.2%
2.7%
2.9%
3.1%
2.7%
2.7%
3.0%

femaleOther managers

Table 11.2 Ratio of managers in broader deﬁnition by gender (denominator permanent full-time workers)

332

Nobuko Nagase

35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
All managers among permanent contract workers, maleAll managers among permanent contract workers, female
All managers among all workers, maleAll managers among all workers, female

Figure 11.7 Gender ratio of managers among all workers and among
permanent contract workers including non-seishain
Source: The Basic Survey on Wage Structure, author’s calculation

chiefs, but with more variation in promotion age. Among section
heads, promotion to vice department heads started in their forties.
This is very old and anecdotal evidence for the entrants of the class of1966 at a large ﬁnancial ﬁrm. Labor practice may differ by industry.
This type of age-based promotion, however, was also depicted by
Imada & Hirata (1995) in their studies of the 1980s.
To see how such age-based promotion has changed, I looked atpromotion using the Basic Survey on Wage Structure 2002–2017 forthe birth cohort of 1965–1969 and for 1980–1984, for whom I can see
the longest period of promotion by age groups. I added up the ratio of
those in different managerial position for both birth cohorts. For theformer group, they graduated from university around 1987–1994,
about twenty years later than those in Takeuchi’s study.
Figure 11.8 (A) left side shows for the 1965–1969 birth cohort males
and the right side for females. The denominator is the data for those
who are employed at ﬁrms with more than 1,000 employees and foruniversity graduates who are permanent contract employees following

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

333

Takeuchi (1995). Figure 11.8 (B) presents the same information for the
1980–1984 birth cohort, who would have graduated from university
around 2002–2008.
Figure 11.8 (A)’s left-side ﬁgure of male promotion shows that theratio of higher-rank managers such as section heads and department heads increases with age as found in Takeuchi. We see thatthe ratio of section chiefs decreases for males with age as moremales are promoted to higher positions. The right-side ﬁgure offemale promotion ﬁnds that only 25 percent were any kind ofmanager by age forty to forty-four, and only 35 percent by age
ﬁfty to ﬁfty-four. Nearly 70 percent of female university graduatesin permanent employment were in nonmanagerial positions in theirearly ﬁfties. On the other hand, the comparable ﬁgures were
60 percent and 63 percent for male university graduates. Less

Birth cohort 1965–1969, university graduates working at large firms
Males
Females
70%

70%

60%

60%

50%

50%

40%

40%

30%

30%

20%

20%
10%

10%
0%
30–34 35–39 40–44 45–49 50–54

0%
30–34

35–39

40–44

45–49

Department heads (buchō)

Department heads (buchō)

Section heads (kachō)Section heads (kachō)

Other managers

Other managers

Section chiefs (kakarichō)

Section chiefs (kakarichō)

50–54

Figure 11.8 (A) Ratio of those in different managerial positions by age group,birth cohort of 1965–1969, university graduates at large ﬁrms
Note: Among workers without ﬁxed term of contract, including non-seishain
employees, by age and birth cohort, in ﬁrms with more than 1,000 employees.
Source: The Basic Survey on Wage Structure, author’s calculation

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

334

Nobuko Nagase

than 40 percent of males in their early ﬁfties were in nonmanagerial positions. Unlike men, the ratio of section chief does notdecrease with age for women, presumably since promotion tosection chief occurs at varied timing and at later ages for womencompared with men. Note that the birth cohort of 1965–1969 is
the cohort that entered ﬁrms after the enactment of the EEOL;
however, there are still very large differences in promotion bygender.
Figure 11.8 (B) shows the promotion history of the younger birthcohort of 1980–1984. By age thirty-ﬁve to thirty-nine, more than
30 percent of university graduate males were managers of some kind,but the ratio was only 16 percent for university graduate females at age
thirty-ﬁve to thirty-nine. The promotion speed was twice as fast for

Birth cohort 1980–1984, university graduates working at large firms
Males

Females

35%

35%

30%

30%

25%

25%

20%

20%

15%

15%

10%

10%

5%

5%

0%
25–29

30–34

35–39

0%
25–29

30–34

Department heads (buchō)

Department heads (buchō)

Directors (kachō)Directors (kachō)

Other managers

Other managers

Section chiefs (kakaricho)

Section chiefs (kakarichō)

35–39

Figure 11.8 (B) Ratio of those in different managerial positions by age group,birth cohort of 1980–1984, university graduates at large ﬁrms
Note: Among workers without ﬁxed term of contract, including non-seishain
employees, by age and birth cohort, in ﬁrms with more than 1,000 employees.
Source: The Basic Survey on Wage Structure, author’s calculation

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

335

males for the birth cohort of 1980–1984, compared with females. The
promotion gap in gender did narrow for the birth cohort of 1980–1984
compared with that of 1965–1969, not because women’s promotion
sped up but because men’s promotion became slower.
However, changes in policies and labor practice over time also
increased female promotion among younger birth cohorts. Figure 11.9
shows percentage of those in any managerial positions by age and bybirth cohort among large ﬁrms but including all educational groups, notlimited to university graduates. We clearly see from Figure 11.9 that,while the managerial ratio of males at age thirty-ﬁve to thirty-nine islower for the 1980–1984 birth cohort than the 1965–1969 cohort,falling from 41 percent to 32 percent, the female ratio at age thirty-ﬁve
to thirty-nine increased from 7 percent to 11 percent. The 1980–1984

Male

Female

0.5

0.5

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0

0

25

Age groupbirth cohorts
〜1944

25
–2
30 9
–3
4
35
–3
9
40
–4
45 4
–4
9
50
–5
4
55
–5
9
60
–6
4

0.6

–2
30 9
–3
35 4
–3
40 9
–4
45 4
–4
50 9
–5
55 4
–5
60 9
–6
4

0.6

Age groupbirth cohorts

1945–1949〜1944

1945–1949

1950–1954

1955–1959

1950–1954

1955–1959

1960–1964

1965–1969

1960–1964

1965–19691970–1974

1975–1979

1970–1974

1975–1979

1980–1984

1985–1989

1980–1984

1985–1989

Figure 11.9 Percentage of workers in any managerial position at large ﬁrms bygender and by birth cohort
Note: Among workers without ﬁxed term of contract, including non-seishain
employees, by age and birth cohort, in ﬁrms with more than 1,000 employees.
Source: The Basic Survey on Wage Structure, author’s calculation

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

336

Nobuko Nagase

birth cohort was in the twenty-nine to thirty-three age group in 2013,
and thirty-two to thirty-six in 2016 when Josei Katsuyaku Suisin Hō wasenacted, so they may be the target generation for promotion during the
Abe administration. We also see that promotion of women was very
slow up to birth cohort of 1955–59, who were the generation hired
before EEOL, but sped up in the age group of 45–49 after then.

11.7.3 Differences in the Ratio of Managers at
Policy-Affected Firms
Figures 11.10 and 11.11 let us explore whether there is any observable change in the proportion of females in managerial positions attimes when the government nudged ﬁrms to change their practices
concerning women employees. The ﬁrst of these statutory nudges,
the Law to Support the Next Generation of 2003, mandated thatﬁrms with more than 300 employees assess their ﬁrm practices
for compatibility with family caregiving responsibilities startingin 2004. Abe initiated the discussion of the second such nudge in2013. It was adopted as Josei Katsuyaku Suishin Hō, the law in2015 and implemented in 2016, also mandated for ﬁrms with morethan 300 employees. Figure 11.10 depicts the proportion of men
and women who attained section chief or kakarichō, the lowest
16.0%
14.0%
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Male, firmsize
300–499

Female, firmsize
300–499

Male, firmsize
100–299

Female, firmsize
100–299

Figure 11.10 Ratio of section chief among permanent contract employees bygender, comparison of those working at ﬁrms with 100–299 employees tothose with 300–499
Note: Age twenty-seven to forty-three, permanent contract employees only.
Source: The Basic Survey on Wage Structure, author’s calculation

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

337

45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
Male, firmsize
300–499

Female, firmsize
300–499

Male, firmsize
100–299

Female, firmsize
100–299

Figure 11.11 Ratio of section heads among low ranking managers bygender, comparison of those working at ﬁrms with 100–299 employees
to those with 300–499
Note: Age twenty-seven to ﬁfty-four, permanent contract employees only.
Source: The Basic Survey on Wage Structure, author’s calculation

managerial position, by ﬁrm size. The denominator is the numberof permanent employees, since I assumed the change would be
most evident among long-term employees as most human resource
departments target their policy toward such workers. For longest
time series, permanent employee status is only available, which is
close to the seishain deﬁnition. The change should also be moreevident at the lowest managerial position. However, when differentiating between ﬁrms with 300–499 employees and those with
100–299 employees, the changes are not much different by ﬁrm
size. We do see some increase in promotion for females in 2004
and 2013, but we also see a similar trend for males. Moreover, thechange in Figure 11.10 after 2003 only raised the percentages one
time, after which the trend ﬂattened. Casual review of Figure 11.10
does not seem to identify a signiﬁcant effect of the law.
Figure 11.11 illustrates the corresponding data for section heads,
among those who are either section chief or section heads. Here, the impact
for year 2015 to 2016 among females is more notable, and the law could
have impacted female promotion to section heads among section chiefs.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

338

Nobuko Nagase

11.8 Method of Estimation
My central question for this chapter is whether women had a greater
probability of attaining managerial employment during the Abe administration. I will also ask whether females are treated differently comparedwith males in promotion. I will use the broad deﬁnition of managers in the
Basic Survey on Wage Structure. The broad deﬁnition of managers ismore connected to a ﬁrm’s wage table than in managing subordinates, sothat the promotion difference may give an explanation to the large genderwage gap. My dependent variable, Manager, equals 1 if given any type ofmanagerial position, and Manager equals 0 if not. I will estimate two
probit equations for this dependent variable, Equations 1 and 2.
Manageri ¼ a1 þ b1 Educationi þ b2 female  Educationi
þ c1 Agei þ c2 female  Agei þ d1 Tenurei þ d2 female  Tenurei
þ e1 female þ f1 ðyears of policy 2013 to 2017Þþ f2 ðyears of policy 2016 to 2017Þþ f3 female  ðyears of policy 2013 to 2017Þþ f4 female  ðyears of policy 2016 to 2017Þ
þ g2 firmsizei þ h1 seishaini þ h2 female  seishainiþ i1 year dummy þ ui
ð1Þ
In Equation (1), I have a policy period dummy for the years 2013 to2017, interacted with gender, to see if women had a greater probability of
becoming managers during the Abe administration. I also include a 2016–2017 year dummy interacted with gender, as this is when Josei Katsuyaku
Suisin Hō came into effect. The Josei Katsuyaku Suisin Hō was passed in2015 and implemented from April 2016. For this reason, I added the year
dummy 2016–2017 and crossed it with the female dummy. If their
coefﬁcients, f3 and f4, are signiﬁcantly positive, it means that, during the
Abe administration, the probability of a female being a manager
increased, especially after implementation of the law. Gender, and thetwo periods of the Abe administration, are also tested for direct effects.
Other coefﬁcients are also important. We know from previous casestudies of promotion policies in various large ﬁrms (Imada & Hirata
1995; Takeuchi 1995; Hanada 1987) that being male, accumulating
tenure, reaching a certain age, and being a university graduate areimportant for attaining managerial positions. Being seishain isa prerequisite. Then lower-level managers compete for the next highest

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

339

rank. Thus I will also see whether educational degrees, age, a seishain
contract, and tenure affect males and females differently. Finally, I willcontrol for individual years in this period, ﬁrm size, and year.
Manageri ¼ a1 þ b1 Educationi þ b2 female  Educationi þ
c1 Agei þ c2 female  Agei þ d1 Tenurei þ d2 femaleTenurei þ e1 female þ f1 ðyears of policy 2013 to 2017Þþ f2 female  ðyears of policy 2013 to 2017Þþ g1 ðfirmsize100  299Þ þ g2 ðfirmsize100  299Þ  femalei
þ g3 ðfirmsize100  299Þ  ðyears of policy 2013 to 2017Þþ g4 ðfirmsize100  299Þ  ðyears of policy 2013 to 2017Þ  femaleiþ h1 seishaini þ h2 female  seishaini þ i1 year dumy þ ui
ð2Þ
In Equation (2), I use variation in ﬁrm size to see if Abe’s policy Josei
Katsuyaku Suisin Hō had a statistically signiﬁcant effect on increasing theprobability of female managers at targeted ﬁrms. The term that tests forthis effect is a cross term with ﬁrm size 100–299, the policy period, andgender. (The dataset does not include information on ﬁrms with fewer
than 100 employees.) If Abe’s policy was effective for increasing female
promotion, then g4 should be negative and signiﬁcant, since the law did
not require ﬁrms of size 100–299 to make the gender statistics public or to
make scheduled plans for active participation of female employees. The
policy was actually enacted in 2015 and implemented in 2016, but there
were talks about this policy from 2013 and a proposal to the Diet in 2014;
therefore, I made a policy dummy spanning the years 2013 to 2017.
Finally, I estimated Equations 1 and 2 for seishain workers only,
while dropping the terms seishain and seishain*female.

11.9 Results of the Estimation
11.9.1 Promotion of Females, Long-Term Employment
Practice, and the Effect of Abe’s Policy
The ﬁrst set of results in Table 11.3, on the left-hand side, shows theestimated marginal effects of Equation 1 for all workers. We can say thatthe promotion of females went up signiﬁcantly by 1 percent during the
2013–2017 Abe administration period and additionally by 0.5 percent
during the 2016–2017 period when Josei Katsuyaku Suisin Hō was
implemented.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

340

Nobuko Nagase

However, this progress must be considered in the context of traditional Japanese employment practice. While higher education andhigher age both increase the probability of promotion to managerial
positions, the effects of education and age for females are signiﬁcantly
less than those for males. The probability of becoming managers
strongly increases with age and peaks at ages forty-ﬁve to ﬁfty-four,
but the effect is also around 10 percent lower for females.
As shown in on the left side of Table 11.3, being in a seishain position
greatly increases the probability of promotion. Comparing the estimates
for all workers and for seishain only, the gender difference in advancement to manager by age and education is even more pronounced amongseishain, especially in their forties and ﬁfties. Males in their ﬁfties arenearly 60 percent more likely to be a manager than males in their teens orin early 20s, but the effect is 13 percent less for females in their ﬁfties.
Tenure effect shows that if women stay in the ﬁrm for a long period,
tenure square term shows that females tenure will be compensated inpromotion a little higher than males.
The long-term employment practice of seishain evidently negatively
affects the allocation of ﬁrm speciﬁc human capital investment tofemales. Firms may be concerned that females will quit their workwhen they form families, while such conduct is less likely for males.
This in turn generates statistical discrimination against females inhiring and promotion. According to the results, females were more
rewarded only after staying with the ﬁrm for a long period, only after
many males surpassed them in promotion.
Interesting results include the marginal effects of ﬁrm size, whichshow that promotion is less likely at larger ﬁrms compared to smallerﬁrms when other factors are controlled for. The year dummies revealthat promotion was slow during the recession of 2002 to 2006 for both
sexes relative to 2012. These were years of bad macroeconomic performance, with the economy in deep recession in 2003. Additionally,
from 2002 to around 2010, females were clearly less likely to bepromoted to managers than males after considering age, education,
tenure and other variables. However, the sign on the coefﬁcient offemales shifted to positive in 2011 and became signiﬁcantly positive
during Abe’s cabinet, 2013–2017, as compared with 2012.
In summary, the ﬁrst column of Table 11.3 shows that education,
tenure, and age are signiﬁcantly less valued for females for promotion
in long-term employment. However, there are more forces to pushhttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

341

Table 11.3 Probit analysis of being a manager, marginal effects
All employees, ﬁrm
size over 100

FemaleEd 14 yrs
Ed 16 yrs or more
Ed 14 yrs* female
Ed 16 yrs or more* female
Age 21–24
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 21–24* female
Age 25–29* female
Age 30–34* female
Age 35–39* female
Age 40–44* female
Age 45–49* female
Age 50–54* female
Age 55–59* female
Age 60–64* female
tenuretenure^2tenure* female
tenure^2* female
year2002
year2003
year2004
year2005
year2006
year2007
year2008
year2009
year2010
year2011

Seishain employees,
ﬁrm size over 100

Coefﬁcientt values

Coefﬁcientt values-0.00960.07510.1476−0.0105−0.02070.04120.16290.34300.47710.56100.5966
0.59840.55220.5104−0.0122−0.0386−0.0681−0.0893−0.0997−0.1028−0.1051−0.1047−0.1073
0.0130−0.0002−0.00070.0001−0.0085−0.0105−0.0205−0.0037
0.00550.01360.00890.00300.0030−0.0052−1.2
148.1 ***
501.9 ***
−13.5 ***
−28.0 ***
7.5 ***
26.6 ***
49.4 ***
65.4 ***
75.5 ***
79.6 ***
79.6 ***
73.0 ***
65.4 ***−1.5−5.3 ***−10.5***−15.3***−18.2***−19.3***−20.2***−20.2***−21.4***
266.2***−144.2***−6.3***
17.9***−13.0***−16.3***−32.4***−5.3***
7.9***
18.9***
12.4***
4.2***
4.2***−7.3***−0.0099
0.09120.1763−0.0135−0.0252
0.04650.18880.38240.51600.59450.62470.62310.57430.4839−0.0153−0.0500−0.0868−0.1138−0.1268−0.1295−0.1315−0.1301−0.1326
0.0155−0.0002−0.00020.0000−0.0110−0.0135−0.0256−0.0067
0.00500.01550.00960.00220.0023−0.0070−1.0
148.0 ***
497.8 ***
−13.8 ***
−26.9 ***
7.0 ***
26.2 ***
49.0 ***
64.8 ***
74.7 ***
78.4 ***
78.0 ***
70.8 ***
57.3 ***−1.5−5.5 ***−10.4***−15.0***−17.7***−18.4***−18.9***−18.7***−19.2***
248.4***−124.8***−1.3
10.1***−13.7***−16.8***−32.5***−7.8***
5.8***
17.4***
10.8***
2.5***
2.6***−8.0***

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

342

Nobuko Nagase

Table 11.3 (cont.)
All employees, ﬁrm
size over 100

Seishain employees,
ﬁrm size over 100

Coefﬁcientt values

Coefﬁcientt values

year2002* female
year2003* female
year2004* female
year2005* female
year2006* female
year2007* female
year2008* female
year2009* female
year2010* female
year2011* female
year2013−2017year 2013–2017* female
year2016−2017year 2016–2017* female
ﬁrm5000−
ﬁrm1000−4999
ﬁrm500−999
ﬁrm 100–299
seishainseishain * female−0.0230−0.0160−0.0237−0.0156−0.0117−0.0130−0.0017−0.0041−0.00300.0017−0.00430.0119−0.0033
0.0056−0.0429−0.0290−0.0149
0.00890.12530.0034−14.3***−9.8***−14.7***−9.5***−7.1***−8.0***−1.0−2.4**−1.8*
1.0−7.6***
8.7***−7.6***
5.6***−114.6***−76.2***−34.4***
22.4 ***
249.9 ***
2.5 ***−0.0291−0.0200−0.0298−0.0193−0.0161−0.0166−0.0031−0.0060−0.00350.0012−0.0051
0.0131−0.0035
0.0072−0.0538−0.0362−0.01850.0114−14.5***−9.9***−14.8***−9.3***−7.7***−8.0***−1.4−2.8**−1.6
0.5−7.2***
7.6***−6.4***
5.7***−114.2***−76.0***−34.3 ***
23.1 ***

Pseudo r2

9,893,284

8,528,542

observation

0.26430.2325

Note: statistically signiﬁcant *** 1 percent, ** 5 percent, * 10 percent.

women into managerial positions after 2013 and even more so in
2016–2017 compared to 2013–2014, although the marginal effectwas small.

11.9.2 Using Variation in Firm Size to Assess Abe’s Policy
Table 11.4 shows the effect of Abe’s policy by using Equation 2, which
examines differences in ﬁrms’ response to the policy change by ﬁrm
size. Josei Katsuyaku Suisin Hō did not mandate ﬁrms with 100–299
employees to make action plans. However, ﬁrms with more than 300

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

343

Table 11.4 Estimate of Abe’s policy on female promotion by ﬁrm size
All employees, ﬁrm
size over 100

FemaleEd 14 yrs
Ed 16 yrs or more
Ed 14 yrs*female
Ed 16 yrs or more* female
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 25–29* female
Age 30–34* female
Age 35–39* female
Age 40–44* female
Age 45–49* female
Age 50–54* female
Age 55–59* female
Age 60–64* female
tenuretenure^2tenure* female
tenure^2* female
year2002
year2003
year2004
year2005
year2006
year2007
year2008
year2009
year2010
year2011
year2002* female
year2003* female

Seishain employees,
ﬁrm size over 100

Coefﬁcientt values

Coefﬁcientt values−0.01650.07880.1478−0.0136−0.02210.11370.28610.42050.50730.54500.54870.50300.4608−0.0294−0.0615−0.0845−0.0959−0.0994−0.1021−0.1021−0.1060
0.0130−0.0002−0.00070.00005−0.0084−0.0102−0.0200−0.0029
0.00640.01420.00940.00330.0036−0.0047−0.0216−0.0147−6.0 ***
154.4 ***
502.4 ***
−17.4 ***
−29.7 ***
68.4 ***
153.9 ***
211.6 ***
246.8 ***
260.4 ***
260.8 ***
237.7 ***
195.5 ***
−13.2 ***
−31.5 ***
−47.7 ***
−57.4 ***
−60.8 ***
−63.4 ***
−62.6 ***
−57.5 ***
263.9 ***
−146.1 ***−6.0 ***
18.0 ***−12.8 ***
−15.7 ***
−31.4 ***
−4.2 ***
9.1 ***
19.6 ***
13.1 ***
4.6 ***
5.1 ***−6.6 ***−13.3 ***
−9.0 ***−0.0199
0.09550.1763−0.0173−0.0268
0.13640.32670.46380.54680.57990.58020.53150.4378−0.0384−0.0781−0.1072−0.1213−0.1245−0.1270−0.1261−0.13070.0154−0.0002−0.0001
0.00004−0.0108−0.0131−0.0250−0.0058
0.00590.01620.01020.00250.0030−0.0065−0.0273−0.0184−6.5 ***
154.4 ***
498.1 ***
−17.8 ***
−28.5 ***
68.7 ***
153.7 ***
210.5 ***
244.5 ***
256.8 ***
255.7 ***
230.4 ***
163.0 ***
−13.8 ***
−31.4 ***
−46.7 ***
−55.3 ***
−57.5 ***
−59.1 ***
−57.5 ***
−48.6 ***
246.1 ***
−127.1 ***−1.0
10.4 ***−13.4 ***
−16.3 ***
−31.6 ***
−6.7 ***
6.9 ***
18.1 ***
11.4 ***
2.8 ***
3.4 ***−7.4 ***−13.5 ***
−9.0 ***

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

344

Nobuko Nagase

Table 11.4 (cont.)
All employees, ﬁrm
size over 100

Seishain employees,
ﬁrm size over 100

Coefﬁcientt values

Coefﬁcientt values

year2004* female
year2005* female
year2006* female
year2007* female
year2008* female
year2009* female
year2010* female
year2011* female
year2013–2017
ﬁrm 100–299
year 2013–2017* femaleﬁrm100−299* femaleﬁrm100–299* year2013–2016
ﬁrm100–299* female*year2013–2017
seishainseishain*female−0.0226−0.0143−0.0114−0.0133−0.0012−0.0041−0.00300.0016−0.00310.04260.0140−0.0084−0.0094
0.0023−14.0 ***
−8.6 ***−6.9 ***−8.1 ***−0.7−2.4 **−1.8 *
0.9−5.5 ***
119.1 ***
10.2 ***−10.3 ***
−16.0 ***
1.7 *−0.0285−0.0177−0.0157−0.0169−0.0025−0.0060−0.00350.0011−0.00310.05310.0157−0.0106−0.0126
0.0033−14.1 ***
−8.4 ***−7.6 ***−8.1 ***−1.2−2.8 ***−1.6 *
0.5−4.4 ***
120.7 ***
9.2 ***−10.4 ***
−17.1 ***
1.9 *

0.12620.0022251.3 ***
1.6

Pseudo r2
observation

9,893,284
0.2644

8,528,542
0.231

Note: statistically signiﬁcant *** 1 percent, ** 5 percent, * 10 percent.

employees were mandated to do this. The law was implemented in2016, but it was discussed in 2014 and passed in 2015, so I chose to
examine the effect of the law throughout the 2013–2017 period.
If the cross term of the ﬁrm size 100–299, the Abe policy period, andbeing female is positive and barely signiﬁcant, that means that women
working at ﬁrms with 100–299 employees were slightly more likely tobe promoted to manager during 2013–2016 relative to larger ﬁrms –or, to put it differently, that ﬁrms with more than 300 employees did
not have more females promoted to managers during the Abe cabinet.
The results do not show that females had a signiﬁcantly higher
probability of promotion at mandated ﬁrms during the Abe administration period; that is, overall promotion to managers did not accelerate speciﬁcally at ﬁrms with more than 300 employees during thishttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

345

period. This is understandable considering the weak type of the mandate. However, from Table 11.3 we did see that female promotion
accelerated more generally during the Abe administration, though themarginal effects were small. The descriptive statistics is shown in the
Appendix.

11.10 Discussion and Conclusion
This paper has reviewed changes in policies and law in Japan after
1980s to today that aimed to increase the number of women in thelabor force, promote females in management, and close the genderwage gap. We constructed a long-term microdata series using theLabor Force Special Survey (Tokutei Chosa) and Labor Force Survey
to look at long-term trends from 1988 to 2017. Since the LFS only
gives data on managers in narrow deﬁnition, we also used the Basic
Survey on Wage Structure of the Ministry of Health, Labor, andWelfare to look at those in managerial positions in the broad deﬁnition, by gender.
Previous research of myself has shown that, after around 2009, work
continuation of new mothers as seishain started to increase with theintroduction of a short hour option that ﬁrms were mandated to makeavailable for workers with infants. This trend of greater work continuation as seishain accelerated during Abe’s administration and his
Womenomics policy of 2013. New mothers’ continuing labor participation as seishain will help to reduce the gender pay gap in the long run,since, once females quit their permanent standard employment at
marriage or at childbirth, most only re-enter the labor market as poorly
paid hourly nonstandard employees.
However, previous research did not reveal whether those females,
who continued their work as seishain, would be as likely to bepromoted as males. Therefore, this paper has investigated the managerial and career prospects of females. The paper showed that theclosing of the gender gap in managerial positions was still quite
limited, although some improvement was shown during Abe’s policy
period.
We found that the closing of the promotion gap has been slow evenamong the more highly educated seishain workers. This paper showedthat there is a profound gender difference in the evaluation of age,education, and tenure for promotion to manager in Japan. We did ﬁnd

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

346

Nobuko Nagase

some acceleration of women’s accession to managerial positions during
the 2013–2017 period.
Even though a menu of policies was rolled out, most were aimed at
reducing the opportunity cost of having children. They were not targeted at making fundamental changes to the Japanese long-term
employment system.
The results found in this chapter indicates that further drastic change
is required in labor law and labor practice to close this large genderwage gap and the gap in promotion prospects.
Why are the gaps still so large? A substantial proportion of women may
be hired in the slow track but not the fast track, compared to maleuniversity graduates. Another reason may be lack of training, even though
one might be in the same track as males. One can only become manager
through adequate experience and training. If such opportunity is offered
to females only in a limited way, even if the law nudges ﬁrms to promotewomen, ﬁrms will have a harder time ﬁnding adequate candidates. In
addition, often women choose the slow track, as long work hours andcompany expectations of relocation may harm their family life. In addition, more seishain women than men are taking one year of leave atchildbirth and then returning to work as short work-week employees after
the leave. This may also hinder their promotion.
We found that gender-based evaluation is greatly evident in theJapanese long-term employment system, which was once highly praised
as the cause of strong economic performance in Japan in the 1980s. For
more women to make the best of their capacity, the Japanese type of longterm employment system needs to undergo further change.
To conclude, Abe’s policy had a statistically signiﬁcant effect on
increasing women’s representation in management for companies ingeneral. This being said, the gap in gender is still very large. A more
fundamental change in labor practice is needed to close the large genderwage gap and the gender gap in managerial positions. This should
include a change in hiring practice, a change in training, and a change
in relocation practices, as well as reforming the EEOL.

Notes
1. “Seishain” in Japan is sometimes translated as “regular full-time
employment.”

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

347

However, “seishain” is often associated with a work contract without
termination. Moreover, wages are often expected to increase withtenure, and higher work commitment is also expected. The same
workers are also often referred to as “standard” employees. Therefore,
I will use “permanent standard employee,” “standard worker,” or“long-term employee” as translations of “seishain,” as well as using theterm itself.
2. Most of this research is based on interviews that have been publishedonly in Japanese, including my own research, as cited in the sections that
follow.
3. For the ﬁrst time in December 2007, the governmental document gavea speciﬁc target and timeline – 38 percent in ten years – for thepercentage of registered childcare places for infants, in the Report of
the National Council for Pathways to Supporting Children and Families(Kodomo to Kazoku wo Oensuru Nihon Juten Senryaku Kaigi). The
national average of registered childcare places for children below three
years of age was then 20 percent, but lower in most major urban areas.
This report was adopted as a reference material of the National Social
Security Council Report (Shakai Hosho Kokumin Kaigi) of
November 2008 and then recognized 38 percent in ten years as
a national target in the Cabinet Ofﬁce’s Medium Term Plan of
Economy and Finance (Keizai Zaisei no Chuchoki Hoshin to 10 nen
Tembou) of December 2008.
4. The 2020–30 target was initially decided in June of 2003 by the Gender
Equality Promoting Head Meeting, Danjo Kyodo Sanaku Suisin
Honbu. The Council on Gender Equality in 2007 explained that“women leaders” meant representatives at the national and local
congress, managers over the rank of kachō at enterprises, andprofessionals who need high professional knowledge. The percent of
women among private corporate managers was described as still
6.5 percent as of 2009 but was targeted to be 10 percent by 2015 in
the third Basic Plan for Gender Equality.
5. For example, in 2013 the proportion of women was 7.9 percent in theHouse of Representatives and 18.2 percent in the House of Councilors.
Women were 6.9 percent of department managers in private enterprises
in 2011. In 2010, women were 18.9 percent of medical doctors,
5.6 percent of Ministers, and 25.7 percent of new hires of national
bureaucrats in the fast promotion track.
6. The Gender Equality Bureau Cabinet Ofﬁce showed in their White
Paper of 2011 that among the 41,973 board members of 3,608 listed
ﬁrms, only 515 were women, comprising only 1.2 percent. In
manufacturing, construction, ﬁnance, and transportation, womenhttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

348

Nobuko Nagase

board members comprised less than 1 percent. Toyokeiai Yakuin
Shikiho shows the number of women board members among listedﬁrms as of July each year. The number was 538 or 1.2 percent in 2006
and remained at 1.2 percent until 2009. In 2011, it was 585 or
1.4 percent and in 2012, 630 or 1.6 percent. Many large ﬁrms didseem to respond to Abe’s request. In 2013, it was 691 or 1.8 percent;in 2014, it rose to 816 and 2.1 percent; and in 2015, 1,142 and
2.8 percent. For example, among 92 listed banks, there were no
women on the board among 772 executive board members in 2011.
Even when non-executive directors and audit and supervisory board
members are included, among 1,370 members, only 6, or 0.4 percent,were female in 2011. The ﬁgure of female ofﬁcers in listed companies
rose to 4.1 percent as of 2018 according to the Gender Equality Bureau.
7. Firms must collect and publish one type of data among fourteen options.
The options include the female ratio of employees, the gender gap in
average tenure, the gender gap in application to hiring ratio, monthly
overtime work hours, and the gender gap in management. Firms are
asked to analyze the reason for the gender gap. Action plans should havetargets and planned periods, which must be made available to the public
and registered at the local MHLW ofﬁce. The action plan can be, forexample, increasing male childcare leavers and providing a model fordiverse career plans. As many as 12,236 ﬁrms registered their gender
statistics on the MHLW’s database as of May 2020 May. Also 15,288
ﬁrms made open their action plan on the same database: http://positiveryouritsu.mhlw.go.jp/positivedb/. From April 2020, the law was
renewed, and these ﬁrms must disclose at least two, but yet just two.
8. From April 2020, the law was renewed, and ﬁrms with more than 100
employees will be required to publicize their action plans.
9. To be recognized, the hiring ratio and tenure should be about the samefor men and women, average work hours should be less than fewer
hours, the ratio of female managers should be above the industry
average, and the ratio of promotion to kachō or middle managerial
positions from section chief should be about the same by gender. In
addition, ﬁrms should demonstrate the development of diverse career
paths by allowing changes from the slow track to the fast track within
the company or by recruiting seishain from nonstandard employees.
The Eruboshi recognition has three stages, and the recognition may beobtained based on their present status.
10. There will be a budget for preferred procurement of around 5 trillion
yen according to the Cabinet Ofﬁce, even though Eruboshi comprise
one among lists for preferred points.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy349

11. The net decline in after-tax household income due to the dependent
spousal tax deduction when spouses work longer hours becamea political issue, so that, in 1987, a new spousal special deduction was
introduced to prevent the decline in net household income that results
due to the increase of income tax of husbands. Yet many ﬁrms gave
spousal allowances as a supplement to the main income earners, andsince this allowance was often linked to one’s spouse not having taxable
income, that spouses still adjusted their work hours so that income tax
should not be levied.
12. Toyota, for example, announced in 2016 that it would abolish its
spousal allowance step by step in ﬁve years and would instead offset
the decline in salary by increasing the children’s allowance.
13. As to the issue of social security tax for a dependent spouse, thegovernment is not overtly making any changes. However, thegovernment introduced new rules in October 2016 that following parttime workers should be taxed the social security insurance for
employees and also be given rights to the employee pension. This is for
those who earn more than 1.06 million a year, worked twenty hours per
week, and are not students, but it is limited to those who work at ﬁrms
with more than 500 employees. The government, in this way, is hoping
to decrease the fraction of dependent wives who are in the social security
tax category of “dependent spouses” despite that fact that they are shorthour workers. In 2019, Pension Law reform further mandated that therule for part-time workers will be expanded to ﬁrms with more than 100
employees in 2022, and further to those with more than 50 employees in2024.
14. Details of the sampling methods, estimation methods and the sampling
errors of the estimates used for the Labour Force Survey are available in
English: www.stat.go.jp/english/data/roudou/pdf/samplerr.pdf, accessed
September 13, 2017.
15. The question about annual income in the previous year offers respondents
twelve possible answers: 0 yen; >0 yen and less than 0.5 million yen; ≥0.5
yen and <0.99 million yen; ≥1 million yen and <1.49 million yen;
≥1.50 million yen and <1.99 million yen; ≥2.00 million and <2.99 million
yen; ≥3.00 million and <3.99 million yen; ≥4.00 million yen and<4.99 million yen; ≥5.00 million yen and <6.99 million yen; ≥7.00 million
yen and <9.99 million yen; ≥10.00 million yen and <14.99 million yen;
15.00 million yen or over. Because only upper and lower bounds areavailable, the midpoint in each category is used to represent income. For
the top income group, 17.00 million is used. Estimates of the wage rate are
obtained by dividing the annual income by the number of work hours in thehttps://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

350

Nobuko Nagase

last week of the month multiplied by 50. The bottom and top 1 percentilesof the wage data were not used in the analysis.
16. Many ﬁrms still have a mandatory retirement age of sixty. However,a new law in 2012 mandated that, from April 2013, ﬁrms must continue
to offer employment opportunity to their workers until age sixty-four.
This, however, can be in the form of nonstandard employment. The law
passed because of the rise of the standard age of receiving the employee
public pension.
17. A time series of seishain is available from 2005. To include the time seriesof 2002 to 2005, the deﬁnition of workers with permanent contract, thatthose of seishain and nonstandard employees are recommended for use
by the ministry. In 2005, seishain was 81.4 percent of all male workers,
and 44.1 percent of all female workers. Permanent contract nonstandard
workers were 4.7 percent for males and 15.5 percent for females in thesame year. In 2017, the respective seishain ﬁgures by gender were
74.2 percent 43.5 percent, and permanent contract nonstandard
workers by gender, 3.6 percent and 8.8 percent.

Reference
Abraham, K., and S. Houseman. 1989. “Job Security and Work Adjustment:
How Different Are US and Japanese Practices?” Journal of the Japaneseand International Economies 3(4): 500–521.
Abe, Y. 2002. “Does the \1.03 million tax exemption limit depress the hourly
wage of part-time workers?“ Japan Labor Bulletin 41(9): 6–7.
Abe, Y. 2010. “Equal employment opportunity law and the gender wage gap
in Japan: A cohort analysis.” Journal of Asian Economics 21(2):142–155.
Abe, Y. 2011. “Equal employment opportunity law and labor force behaviorof women in Japan.” Journal of the Japanese and International
Economies 25(1): 39–55.
Abe, Y., and A. Oishi. 2009. “The 1.03 million yen ceiling and earnings
inequality among married women in Japan.” Economics Bulletin 29(2):1510–1519.
Akabayashi, H. 2006. “The labor supply of married women and spousal tax
deductions in Japan – a structural estimation.” Review of Economics ofthe Household 4(4): 349–378.
Albrecht, J., A. Börklund, and S. Vroman. 2003. “Is there a glass ceiling in
Sweden?” Journal of Labor Economics 21(1): 145–177.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

351

Asai, Y. 2015. “Parental leave reforms and the employment of new mothers:
Quasi-experimental evidence from Japan.” Labour Economics 36:
72–83.
Asai, Y., R. Kambayashi, and S. Yamaguchi. 2015. “Childcare availability,
household structure, and maternal employment.” Journal of theJapanese and International Economies 28: 172–192.
Bessho, S. I., and M. Hayashi. 2014. “Intensive margins, extensive margins,
and spousal allowances in the Japanese system of personal income taxes:
A discrete choice analysis.” Journal of the Japanese and International
Economies 34: 162–178.
Firpo, S., N. M. Fortin, and T. Lemieux. 2009. “Unconditional Quantile
Regressions.” Econometrica 77(3): 953–973.
Eunmi, M., and M. Brinton. 2015. “Workplace matters: The use of parental
leave policy in Japan.” Work and Occupations 42(3): 335–369.
Fujii, K. 2009. “Research on Gender Wage Gap.” Business Labor Trend,
September 11–16 (in Japanese).
Hanada, M. 1987. “Competition within Human Resource System : The
Human Resource Management of Japanese Firms seen from thePromotion System (Jinji Seido kara mita Nihon Kigho no JInji
Senryaku). Soshiki Kagaku (Organization Science) 21(2): 44–53(in Japanese).
Hara, H. 2018. “The Gender Wage Gap across the Wage Distribution in
Japan: Within and Between Establishment Effects.” Labour Economics
53: 213–229.
Hashimoto, M., and J. Raisian. 1985. “Employment Tenure and Earnings
Proﬁle in Japan and the United States.” American Economic Review 75(4): 721–735.
Hashimoto, M., and J. Raisian. 1992. “Employment Tenure and Earnings
Proﬁle in Japan and the United States: Reply.” American Economic
Review 82(1): 346–354.
Higuchi, Y. 1995. “Sengyoshufu Hogo Seisaku no Keiziteki Kiketsu(Economic Consequence of Social Protection Policy for Housewives).
In “Jakusha” Hogo Seisaku no Keizai Bunseki (Consequence of Social
Protection for the “Vulnerable”), edited by T. Hotta and N. Yashiro.
Tokyo: Nihon Keizai Shinbunsha (in Japanese).
Hori, H. 1998. “Danjo Chingin Kakusa no Shukusho Keiko to sono Yoin
(Decline in Gender Wage Gap and the Factors Contibuting to the
Change).” Nihon Rodo Kenkyu Zasshi No. 456 (in Japanese).
Houseman, S., and K. Abraham. 1993. “Female Workers as Buffer in theJapanese Economy.” American Economic Review 83(2): 45–51.

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

352

Nobuko Nagase

Imada, S., and S. Hirata. 1995. Promotion Structure of White Collar
Workers (Howaito Kara no Shoshin Kozo). Tokyo: Japan Institute ofLabor (in Japanese).
JILPT. 2009. Report on Research for Gender Wage Gap under Changing
Wage and Labor Practices, Surveys on Firm Wage and Employment
Practices, and Survey on Employer and Labor Union Leaders. JILPT
Research Series No. 52 (in Japanese).
Matsubara, M. 2012. “The Impact of Long-term Use of the Short Working
Hour System on Careers” (Tanjikan seishain seido no chokiriyo ga
kyaria ni oyobosu eikyo). Nihon Rodo Kenkyu Zasshi (Japanese
Journal of Labour Studies) 54(10): 22–33 (in Japanese).
Nagase, N. 1999. “Work and childbearing choice of married women in
Japan: The effect of labor practices” (Shoshika no yoin: shugyo
kankyo ka kachikan no enka ka – Kikonsha no shugyo keitai sentaku
to shussan jiki no sentaku). Journal of Population Problems (Jinko
Mondai Kenkyu) 55(2): 1–18 (in Japanese).
Nagase, N. 2002. “Wife allowance and tax exemption behind the low wageof part-time workers.” Japan Labor Bulletin 41(9): 8–9.
Nagase, N. 2003a. “Childcare policy for economic revival ofurbanities” (Toshi saisei to hoiku seisaku).” In Economic Analysis
of Urban Revival (Toshi Saisei no Keizai Bunseki), edited by
F. Yamazaki and Y. Asada, pp.248–278. Tokyo: Toyo keizai
shinposha (in Japanese).
Nagase, N. 2003b. “Standard and non-standard work arrangements, paydifference, and choice of work by Japanese mothers.” In Nonstandard
Work in Developed Economies: Causes and Consequences, edited by
S. Houseman and M. Osawa, pp.267–300. Kalamazoo, MI:
W. E. Upjohn Institute for Employment Research.
Nagase, N. 2007. “Shoshika ni kakawaru Seisaku ha Doredake
Jikkosaretanoka? Hoiku to Jido Ikusei ni kansuru Seisakuno Kadai(How much of the Policy for Childcare and Child Development Has
Been Put into Action?).” Financial Review 87: 3–22 (in Japanese).
Nagase, N. 2010. “Danjo Chingin Kakusa no Kaisho ni Mukete Naniga Sei
CHurituteki na Seido ka (What Is Meant by Gender Neutral Practices, in
Search for Closing Gender Wage Gap).” Rodo Chosa (Labor Research),
February 14–22 (in Japanese).
Nagase, N. 2014. “The effect of a short-hour option mandate on ﬁrst
childbirth, birth intention and work continuation after childbirth:
Evidence from Japan” (Ikujitanjikan no gimukaga daiisshishussan to
shugyokeizoku shussan iyoku ni ataeru eikyou: hokaisei woshizenjikken tosita jisshou bunseki).” Journal of Population Studies(Jinkogaku Kenkyu) 50(1): 29–53 (in Japanese).

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

353

Nagase, N. 2017. “The Effect of Family Friendly Policies on Fertility andMaternal Labor Supply.” Stanford Asia Health Policy Program
Working Paper No. 42.
Nagase, N. 2018a. “Has Womenomics Worked?” Asian Economic Policy
Review 13(1) 68–101.
Nagase, N. 2018b. “Inequality between Standard Employment and
Non-Standard Employment: Policies to Promote Human Resource
Investment among Females and Youth.” Japan Labor Review (Nihon
Rodo Kenkyu Zasshi) Special Issue No. 691: 19–38 (In Japanese).
Nagase N., and M. Brinton. 2017. “Gender division of labor and second
births: Labor market institutions and fertility in Japan.” Demographic
Research 36(11): 339–370.
Nagase, N., and Mana Yamaya. 2011. “Career Prospects of University
Graduate Females in Large Japanese Firms: The Course Based Hiring
Practices, their Anxieties and Possibilities (Daikigyo Kinmu no Daisotu
Seishain Josei no Shugyo Keizoku Fuan – kosu betu jinji ni chumoku
shite).” Kyaria Dezain Kenkyu (Career Design Research) 7: 185–197 (inJapanese).
Nagase, N., and Mana Yamaya. 2012. “Women in Managerial Positionat Private Firms: Labor Practice and Division of Labor within
Households (Minkan Daikigyo no Josei Kanrishoku no Kyaria
Keisei).” Kyaria Dezain Kenkyu (Career Design Research) 8:
95–105 (in Japanese).
Ohi, M. 2004. “Changes in Managers Seen from Statistics, the Numbers, theSpeed of Promotion, and Relative Wage versus Non-Managers (Suji demiru Kanrishokuzo no Henka: Ninzu, Shoshinsokudo, Ippanshoku
tono Sotaichingin).” Nihon Rodo Kenkyu Zasshi (Japanese Journal ofLabour Studies) 545: 4–17 (in Japanese).
Ohuchi, S. 1999. “Daisotsu Howaito Kara no Kigyonai Kyaria Keisei:
Sogoshoku, Ippanshoku no Jittai Chosa yori (Career Development ofWhite Collar University Graduates within Firm: Sogoshoku andIppanshoku).” Nihon Rodo Kenkyu Zasshi (Japanese Journal ofLabour Studies) 471 (in Japanese).
Takahashi, S. 2010. “An estimation of the work disincentive effects of the
spousal deduction and the social security systems on the labor supply ofJapanese married women (Haigusha kojo oyobi shakai hosho seido ga
nihon no kikon josei ni oyobosu roudou yokusei koka no sokutei).”
Nihon Rodo Kenkyu Zasshi (Japanese Journal of Labour Studies) 52(12): 28–43 (in Japanese).
Takeishi, E. 2013. “Measures to shorten working hours: Their current state
and areas of concern (Tanjikan kinmu seido no genjo to kadai).” Shogai
Gakushu to Kyaria Desain 10: 67–84 (in Japanese).

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

354

Nobuko Nagase

Takeuchi, H. 1995. Japanese Meritocracy (Nihon no Meritokurashi).
Tokyo: University of Tokyo Press (in Japanese).
Teramura E. 2014. “The effect of the workplace norm on female
employment and work quit (Josei no ahugyo, rishoku kodo no
jisshou bunseki: Shokuba no funiki ga ataeru eikyo no kensho).”
Kyaria Dezain Kenkyu (Research on Career Design) 10: 175–185 (inJapanese).
21seiki Shokugyo Zaidan. 2014. Ikuji wo shinagara Hataraku Josei no
Shoshin Iyoku ya Mochibeshon ni kansuru Chosa (Study on the
Factors affecting Promotion Motives of Women with Children in Longterm Standard Employement). www.jiwe.or.jp/research-report/2013m
otivation_women_to_work (in Japanese).
Unayama, T. 2011. “Marriage and female labor participation: Evidence
from Japanese prefectural cross-section data” (Kekkon, shussan to
shugyo no ryoritsu kanousei to hoikujo no seibi).” Nihon Keizai
Kenkyu 65: 1–22 (in Japanese).

Appendix Descriptive Statistics for Table
11.3 and Table 11.4
All employees, ﬁrm
size over 100

managers
femaleEd 14 yrs
Ed 16 yrs or more
Ed 14 yrs*female
Ed 16 yrs or more*
femaleAge 21–24
Age 25–29
Age 30–34
Age 35–39
Age 40–44

Seishain employees ﬁrm
size over 100

means

standarddev
min max means

standarddev
min max

0.222
0.299
0.148
0.362
0.083
0.073

0.416
0.458
0.355
0.481
0.275
0.260

0
0
0
0
0
0

1
1
1
1
1
1

0.253
0.263
0.146
0.388
0.077
0.072

0.435
0.440
0.353
0.487
0.266
0.259

0
0
0
0
0
0

1
1
1
1
1
1

0.076
0.131
0.134
0.134
0.131

0.265
0.338
0.340
0.341
0.337

0
0
0
0
0

1
1
1
1
1

0.076
0.133
0.138
0.140
0.136

0.265
0.340
0.345
0.347
0.343

0
0
0
0
0

1
1
1
1
1

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

Abe’s Womenomics Policy

355(cont.)All employees, ﬁrm
size over 100

Age 45–49
Age 50–54
Age 55–59
Age 60–64
Age 21–24* female
Age 25–29* female
Age 30–34* female
Age 35–39 * female
Age 40–44* female
Age 45–49* female
Age 50–54* female
Age 55–59* female
Age 60–64* female
tenuretenure^2tenure* female
tenure^2* female
year2002
year2003
year2004
year2005
year2006
year2007
year2008
year2009
year2010
year2011
year2002* female
year2003 * female
year2004* female
year200 * female
year2006* female
year2007* female
year2008* female
year2009* female
year2010* female

Seishain employees ﬁrm
size over 100

means

standarddev
min max means

standarddev
min max

0.120
0.115
0.100
0.041
0.035
0.050
0.041
0.036
0.035
0.032
0.029
0.024
0.010
13.262300.39
2.825
52.06
0.070
0.068
0.069
0.061
0.062
0.059
0.058
0.057
0.058
0.056
0.018
0.017
0.018
0.019
0.019
0.019
0.017
0.017
0.018

0.325
0.319
0.300
0.197
0.183
0.218
0.199
0.187
0.183
0.175
0.168
0.153
0.099
11.159403.316.640
178.74
0.254
0.252
0.253
0.239
0.242
0.236
0.235
0.231
0.233
0.230
0.132
0.130
0.133
0.136
0.135
0.136
0.131
0.131
0.132

0.330
0.322
0.298
0.133
0.181
0.213
0.191
0.178
0.170
0.160
0.153
0.137
0.069
11.042402.116.777
183.33
0.271
0.268
0.269
0.238
0.240
0.234
0.231
0.228
0.230
0.227
0.140
0.138
0.140
0.125
0.124
0.124
0.118
0.119
0.121

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

1
0.124
1
0.118
1
0.099
1
0.018
1
0.034
1
0.048
1
0.038
1
0.033
1
0.030
1
0.026
1
0.024
1
0.019
1
0.005
49 14.281
2401 325.88
49 2.785
2401 53.69
1
0.080
1
0.078
1
0.078
1
0.060
1
0.062
1
0.058
1
0.057
1
0.055
1
0.056
1
0.054
1
0.020
1
0.019
1
0.020
1
0.016
1
0.016
1
0.016
1
0.014
1
0.014
1
0.015

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

1
1
1
1
1
1
1
1
1
1
1
1
1
49
2401
49
2401
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1

356

Nobuko Nagase(cont.)All employees, ﬁrm
size over 100

year2011* female
year2013–2017year 2013–2017* female
year2016–2017year 2016–2017* female
ﬁrm5000–
ﬁrm1000–
ﬁrm500–ﬁrm100–ﬁrm100–* femaleﬁrm100–* female*year2013–2017
ﬁrm100–* year
2013–2017seishainseishain* female
sample size

Seishain employees ﬁrm
size over 100

means

standarddev
min max means

standarddev
min max

0.017
0.321
0.101
0.133
0.044
0.243
0.245
0.133
0.264
0.083
0.082

0.130
0.467
0.302
0.340
0.204
0.429
0.430
0.339
0.441
0.275
0.275

0
0
0
0
0
0
0
0
0
0
0

1
1
1
1
1
1
1
1
1
1
1

0.015
0.304
0.083
0.127
0.037
0.248
0.246
0.131
0.261
0.073
0.021

0.120
0.460
0.277
0.333
0.188
0.432
0.431
0.337
0.439
0.259
0.145

0
0
0
0
0
0
0
0
0
0
0

1
1
1
1
1
1
1
1
1
1
1

0.082

0.275

0

1

0.078

0.268

0

1

0.862 0.345
0.227 0.419
9,893,284

0
0

1
1

https://doi.org/10.1017/9781108921145.011 Published online by Cambridge University Press

8,528,542