Discussion Paper No.423
Long-term Trends in Intergenerational Income
Mobility in Japan:
From High Increasing to Lost Decade
Zhi-xiao Jia

Publish date (2020/05/18)

TOHOKU ECONOMICS RESEARCH GROUP
Discussion Paper

GRADUATE SCHOOL OF ECONOMICS AND

MANAGEMENT TOHOKU UNIVERSITY

27-1 KAWAUCHI, AOBA-KU, SENDAI,
980-8576 JAPANLong-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

Long-term Trends in Intergenerational Income Mobility in Japan:
From High Increasing to Lost Decade*Zhi-xiao Jia†
Graduate School of Economics and Management, Tohoku University, Sendai, Japan

Abstract
This paper focuses on how components of intergenerational income mobility (IGM) in
Japan vary with cohorts. Intergenerational income elasticity (IGE) between fathers andsons is estimated using Two Sample Two Stage Least Square (TS2SLS) approach and isdecomposed into several intergenerational transmission pathways. Contribution of eachpathway to IGE is jointly determined by the strength of transmission and income
premiums. How IGE due to these transmission pathways vary with cohorts is analyzed byestimating long-term trends in intergenerational transmissions and income structure. This
paper finds IGE in Japan for sons born from 1935 to 1976 lies around 0.35 to 0.40. What’s*

I would like to thank Midori Wakabayashi, Michio Suzuki and Akira Hibiki. I am also grateful to all theparticipants at the 30th Eurasia Business and Economics Society (EBES) Conference. All the remaining
errors are mine.
†

Email address: jia.zhixiao.s1@dc.tohoku.ac.jpiLong-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

more, although upward educational mobility decreases for sons born after early to mid
1950s, it contributes to an increasing in IGM after considering long-term trends in income
premiums of education. However, it is not the case for upward occupational mobility.

Key words: cohort, decomposition, intergenerational elasticity, intergenerational mobility,
Japan, Two Sample Two Stage Least Square

JEL Classification: D31, J62

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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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1. Introduction and Related Literatures

Intergenerational income elasticity (IGE), which is estimated by regressing logarithm of sons’income on logarithm of fathers’ income, is one of the most standard measurements ofintergenerational income mobility (IGM). It captures the extent to which economic advantages aretransmitted across generations.1 IGE has been widely estimated in different countries by different
approaches (See Gong et al. (2012) and Blanden (2013) for review). However, how IGE varies withcohorts within a certain country is still a somewhat unexplored area. The objective of this study isto provide a new perspective to analyze this issue in Japan.

Japan provides an interesting case to analyze long-term trends in IGE as its economy experienced
enormous changes during the second half of 20th century. Initiated by jinmu boom from 1954 to
1957, Japanese economy experienced nearly 20 years of high growth during which its real GDP
growth rate exceeded 9%. Such prosperity was ended by first oil crisis, after which Japan
experienced roughly two decades of stable growth with real GDP growth rate of 4.2%. After thecollapse of bubble boom from 1986 to 1991 with real GDP growth rate over 5%, Japan entered
its so-called lost decade(s) in 1991 with stagnant economy.

1

For instance, an IGE of 0.3 indicates if father’s income is 100% above the average in his generation, then son’s

income is 30% above the average in his generation. In other words, 30% of income inequality in fathers’ generation istransmitted to sons’ generation. The higher the IGE, the lower the IGM.
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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Previous studies mainly relied on some straight-forward methods to analyze how IGE vibrates
across cohorts. One approach is controlling interaction terms of fathers’ income with sons’ birthcohorts in regression estimating IGE, while another one is separately estimating IGE for sonsfrom each cohort (Nicoletti and Ermisch, 2007; Pekkala and Lucas, 2007; Lee and Solon, 2009;
Ueda, 2009; Lefranc et al., 2014; Lefranc, 2018; Chu and Lin, 2019). These approaches can easily
provide pattern of long-run trends in IGE, although such pattern might be distorted by collinearity
between cohort effect and age effect (See Lee and Solon (2009) for a discussion).2 For instance,
Ueda (2009) and Lefranc et al. (2014) found IGE in Japan remains almost unchanged from 1959
to 1979 cohorts and 1935 to 1975 cohorts, respectively. However, such approaches cannot give amore in-depth understanding of how IGE altering over cohorts.

The main contribution of this paper is to provide a new perspective to analyze how IGE evolves
over cohorts by focusing on how components of IGE, instead of entire IGE, vary throughout
cohorts. Firstly, this study decomposes IGE into several intergenerational transmissions of factors

2

It is difficult to distinguish between cohort effect and age effect since cohort equals observation year minus age.

What’s more, the estimate of IGE is very sensitive to age selection. Income in early (resp., late) stage of career
underestimates (resp., overestimates) life-time income. Such non-classical measurement error induces so-called lifecycle bias (Grawe, 2006; Haider and Solon, 2006). For instance, IGE will be underestimated if sons’ (resp., fathers’)
income is observed at early (resp., late) ages. Such problem is more serious in Japan, since in currently available datasets,
seniority-wage system and life-time employment system, which ensure income to increase stably with age, are common
practices for most of males respondents in prime working ages. Lee and Solon (2009) isolated age effect by elaborately
controlling sons’ ages and estimating IGE at age 40, and its specification was followed by, for instance, Lefranc (2018).
2

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia(e.g., intergenerational transmission of education). These factors might induce intragenerational
income inequality and might be transmitted across generations. Contribution of each transmission
pathway to IGE is jointly determined by strength of intergenerational transmission of that factor
as well as returns to that factor in both sons’ generation and fathers’ generation. Similar
decomposition frameworks were also proposed in Österbacka (2001), Lefranc and Trannoy (2005)
and Blanden (2013).3 Next, this study analyzes how IGE due to these transmission pathways varywith cohorts by estimating long-term trends in returns to these factors and intergenerationaltransmissions of these factors. Similar procedures were also presented in Pekkala and Lucas (2007)
and Lefranc (2018). They extracted the effect of parental investment in children’s education from
IGE and analyzed trend in that effect. However, these papers only considered one pathway, i.e.,
education. Moreover, intergenerational transmission of education was not taken into consideration
directly in those papers (See Section 2 for a detailed discussion).

Decomposition framework in this study is based on IGE estimator obtained by Two Sample Two
Stage Least Square (TS2SLS). In many IGM studies in which fathers’ income cannot be observedin primary sample, an auxiliary sample in which both income and characteristics (education,
occupation, etc.) of individuals whom are assumed to be representative of fathers are observable
is used to impute fathers’ missing income.4 TS2SLS has been widely applied in IGM studies since3

As mentioned in Lefranc and Trannoy (2005), this framework is a special case of Bowles and Gintis (2002)’s model.

4TS2SLS is asymptotically the same as 2SLS. Its statistical properties were reviewed in, e.g., Inoue and Solon (2010).
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

Björklund and Jäntti (1997)’s first attempt (See Jerrim et al. (2016) for a review), including Japanese
ones (Ueda, 2009; 2015; Lefranc et al., 2010; 2014) due to lack of datasets in which information
on fathers’ income is suitable for analyses.5 In this study, both primary sample and supplementary
sample are extracted from Survey of Social Stratification and Social Mobility (SSM), one of themost traditional and large-scale Japanese social surveys covering six decades since 1955 with richinformation on respondents’ income, personal background and family background.

Previous Japanese IGM studies found IGE between fathers and sons in Japan lies around 0.30 to
0.35 (around 0.30 in Lefranc et al. (2010) and Ueda (2015), around 0.35 in Lefranc et al. (2014)),6
which is at intermediate level in developed world. It implies Japan is a relatively equal society as
suggested by The Great Gatsby Curve which summarizes the positive relationship between IGE
and intragenerational inequality (Blanden, 2013; Corak, 2013). On the other hand, however, once
equal Japan characterized by its solid middle class has been experiencing an increasing in income,or wage inequality since 1980s, especially for males (Lise et al., 2014; Yamada and Kawaguchi, 2015).

5

Ueda (2009) used Japanese Panel Survey of Consumers (JPSC) in which parents’ income is observable. However,parental income in JPSC is too poorly measured to be used when estimating IGE (See Lefranc et al. (2014) for a moredetailed discussion), which leads Ueda (2009) to rely on 2SLS and TS2SLS to impute parental income in most of its
specifications. Kubota (2017) used Parent and Children Survey (PCS) in which both children’s wealth and parents’
wealth can be observed. However, in most of its specifications, sample size is smaller than 300. In addition, wealth is
not a commonly used measurement of economics status in IGM studies. Kubota (2017) also reported 2SLS results.
6

Besides these studies, Ueda (2009) found IGE between parents and married sons is above 0.40 from 2SLS and

TS2SLS. Kubota (2017) found IGE between parents and children is around 0.35 from 2SLS.
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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In recent years, some scholars have argued that Japan has become a society of disparity to someextent (Moriguchi, 2017). Since IGE captures the transmission of income inequality overgenerations, therefore decomposing IGE and analyzing how components of IGE evolve withcohorts can deepen our understanding on long-term patterns of income inequality.

Estimation results show that IGE in Japan for sons born from 1935 to 1976 is around 0.35 to 0.40.
Intergenerational transmission of tertiary education is one of the most important and stable
pathways through which income inequality is transmitted from fathers to sons throughout 1935 to1976 cohorts. Upward educational mobility contributes to an increasing in IGM since early-mid
1950s cohorts generally after considering long-run variations in returns to education, although
upward mobility of education itself decreases.

The rest of this paper is organized as follows. Section 2 shows conceptual framework ofdecomposing IGE. Section 3 presents empirical specifications. Section 4 introduces SSM survey,
variables and sample selection. Section 5 discusses estimation results. Section 6 concludes.

2. Conceptual Framework

The logarithm of sons’ income and that of fathers’ income is supposed to be expressed as

5Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia!! = #! + ∑#"$% &!" '!" + (!

(1)

and

!& = #& + ∑#'$% &&' '&' + (&(2)

respectively. &% to &# refer to ) factors affecting income, and '’s are returns to &’s. ( iserror term, and it is often referred as luck in related studies (Lefgren et al., 2012). TS2SLS IGE
estimator *+ is obtained by regressing sons’ income !! on fathers’ imputed income !+& by OLS:-()*+, ,," 0*+ = 123+,!- 0(3)!

In which !+& = #,& + ∑#,&' refers to fathers’ imputed income based on &’s. Since sons’'$% &&' 'income !! equals #,! + ∑#,!" + -̂! in which -̂! equals !! − #,! − ∑#,!" , therefore"$% &!" '"$% &!" '*+ can be expressed as

5 ! 67!# 8
5 !# ,4
5 " 67"$ 8
5"$ 69:" 0
5!# 8
5"$ +()*+7!# ,7"$ 0;123+7!# 00123+7!# 0
8# ()*+4∑#∑#*+ = ∑#=+"$% ∑'$%"$%'$%
123+, 0123+,- 0
!

5
8

!#
∑#
'$%

()*+7!# ,9:" 0123+,-! 0!

(4)

Right-hand side of Equation (4) divides *+ into two parts. First part is explained byintergenerational transmissions of &’s from fathers to sons. Second part is uninterpretable part.7

7

Same decomposition can also be performed in 2SLS since it follows the essentially same procedure as TS2SLS with6

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

In most of empirical IGM studies using TS2SLS, income is imputed based on at least two &’s.
Commonly used &’s include education, occupation, and so on (See Jerrim et al. (2016) for areview). 8 If ) & ’s are incorporated in this framework, then first part consists of )<intergenerational transmission pathways, within which ) pathways are intra-factor transmission(e.g., intergenerational transmission of education from fathers to sons), while other )< − )pathways are inter-factor transmission (e.g., intergenerational transmission from fathers’ education
to sons’ occupation). This framework indicates that the contribution of intergenerationaltransmission from fathers’ &' to sons’ &" to overall IGE is determined by four elements
simultaneously: (1) return to &' in fathers’ generation ('&' ); (2) return to &" in sons’ generation('!" ); (3) variance of &' in fathers’ generation (0123&&' 4) and (4) strength of intergenerationaltransmission from &' to &" ( 5673&&' , &!" 490123&&' 4 ≝ ;! ), in which < = = refers to
intra-factor transmissions, while < ≠ = refers to inter-factor transmissions. '&' , '!" and0123&&' 4 capture the labor market structure in fathers’ generation and sons’ generation. Basedon this framework, this study analyzes how '!" and ;! vary with sons’ birth cohorts, and how
these variations contribute to an overall variation in IGE.

This framework has following advantages. Firstly, it directly relates IGE with intergenerational
the exception that TS2SLS combines two separate samples due to unavailability of fathers’ income in primary sample.
8

If fathers’ income is imputed based only on education, then TS2SLS IGE estimator might be upwardly biased too

much due to small R2 of first step equation as well as strong direct effect of fathers’ education on sons’ income. See
Nicoletti and Ermisch (2007), Jerrim et al. (2016) and Section 3 for discussion.
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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capital transmissions compared with Blanden et al. (2014)’s model in which capital is only served
as a mediator (e.g., parental investment in children’s education) between income of fathers andincome of sons as well as methods similar to or following Blanden et al. (2014) (Pekkala and Lucas,
2007; Gong et al., 2012; Kubota, 2017; Lefranc, 2018; etc.). Secondly, it considers both intra-factor
transmissions and inter-factor transmissions. Rare studies consider inter-factor transmissions.
Besides Österbacka (2001) and Lefranc and Trannoy (2005) using similar frameworks, Bevis andBarrett (2015) provided a framework incorporating both intra-factor transmissions and inter-factor
transmissions among education, health and land. Thirdly, it better captures the effect offluctuations in income structure between fathers’ generation and sons’ generation on IGE since
returns to &’s in both fathers’ generation and sons’ generation are considered compared withBlanden et al. (2014)’s and related methods in which only returns to capitals in sons’ generation are
considered and Lefgren et al. (2012)’s and Miller and Mclntyre (2020)’s methods which only
considere the explanatory ability of capitals in fathers’ income inequation.

3. Empirical Specifications

The basic specification for estimating IGE by TS2SLS in this paper takes the form of!! = *= + *% !+& + (!

(5)

8Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

In which !! refers to the logarithm of sons’ annual income, !+& refers to the imputed value of thelogarithm of fathers’ income at age of 40 (See below). *% refers to IGE in the context of TS2SLS.

Three empirical issues should be emphasized when estimating *% . The first one is classicalmeasurement error on fathers’ income when using short-term income or annual income to measure
father’s income, which attenuates *+% (Solon, 1992; Zimmerman, 1992). TS2SLS is immune toattenuation bias since it follows essentially the same procedure as 2SLS with the exception that
TS2SLS combines two separate samples.

The second one is life-cycle bias (Grawe, 2006; Haider and Solon, 2006), which arises when using
current income as a proxy for permanent income (See footnote 3). TS2SLS cannot overcome thiserror since it correlates with permanent income, which implies that it is non-classical type ofmeasurement error. Based on Haider and Solon (2006)’s conclusion that life-cycle bias is relatively
small around the age of 40 (i.e., income at early 40s is a better approximation for life-time orpermanent income), this paper deals with this issue by two ways. Firstly, ages of sons andindividuals whom are assumed to be representative of fathers in auxiliary sample are restricted to[30, 59], i.e., around the prime working age (early 40s). Secondly, fathers’ income is imputed at ageof 40 following Lefranc et al. (2014)’s and Lefranc (2018)’s specifications (See Equation (6)).

The third one is imputation bias due to Two Sample approach. Firstly, since fathers’ characteristics
are reported ex post by sons, therefore sons may misreport their fathers’ characteristics (Björklund
9Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

and Jäntti, 1997). This paper assumes such bias is small if not nil since recall of fathers’ education,
occupation and other characteristics is much more reliable than recall of fathers’ income whensons were teenagers. Secondly, individuals in auxiliary sample may not be representative of fathers.
This paper solves this problem through following strategy. In this paper, fathers’ average age isabout 76 in 1995 and 2005. It implies it was roughly 30 years ago when fathers were at prime
working ages. Therefore, supplementary sample is extracted from 1965’s and 1975’s surveys. Since
SSM spans over six decades, therefore such selection is possible. Similar strategy was also used in
Chu and Lin (2019). Thirdly, fathers’ characteristics would directly affect sons’ income, therefore
IGE might be biased upwardly (See footnote 9). Although this problem is unavoidable when using
TS2SLS, this paper tries to reduce such bias by using four categories of variables, i.e., type of
employment, firm size, occupation and education (See Section 4.1) to impute fathers’ income basedon Jerrim et al. (2016)’s suggestion that use a detailed first step specification. In the end, the firststep equation takes the form of##<!> = #> + ∑#'$% &>' '>' + ∑'$% &>' (1@A> − 40)E%>' + ∑'$% &>' (1@A> − 40) E<>' + (>(6)

In which subscript F refers to individuals in supplementary sample. They are referred as pseudo
fathers henceforth to simplify expression. !> refers to the logarithm of annual income of pseudo
fathers. &> ’s refer to factors affecting !> . Specifically, '> ’s refer to returns to &> ’s at age of 40.
Fathers’ imputed income at age 40 is10Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia!+& = #,> + ∑#,>''$% &&' '(7)

Then Equation (5) can be estimated. In order to perform decomposition, the logarithm of sons’annual income !! is regressed on their characteristics &! ’s following the same specification as
Equation (6):##<!! = #! + ∑#"$% &!" '!" + ∑"$% &!" (1@A! − 40)E%!" + ∑"$% &!" (1@A! − 40) E<!" + (!

(8)

In which '! ’s refer to returns to &! ’s at age of 40. Since !! can be rewritten as !! = #,! +∑#,!" + -̂! after Equation (8) is estimated as shown in Section 2, therefore *% can be"$% &!" 'decomposed based on the framework in Section 2.

In order to analyze how components of IGE vary with cohorts, this study allows returns to &’s
in sons’ generation ('! ’s) and intergenerational transmissions of &’s from fathers to sons (;! ’s) tovary with sons’ birth cohorts. Sons in this study were born from 1935 to 1976. In order to relax
assumptions on cohort trends (e.g., quadratic cohort trend or piecewise linear cohort trend), thispaper divides all the sons into 8 broad cohorts in which each group consists of 5 to 6 years: 1935
to 1940 cohorts, 1941 to 1945 cohorts, …, 1966 to 1970 cohorts and 1971 to 1976 cohorts. '! ’s
and ;! ’s are allowed to vary with these eight broad cohorts.

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4. Data

4.1

Survey of Social Stratification and Social Mobility (SSM)

This paper uses data from Survey of Social Stratification and Social Mobility (SSM), a decennial
repeated cross-sectional survey. SSM was firstly conducted in 1955, and it has six waves available
at present (SSM 1955, 1965, …, 2005). The latest wave was conducted in 2015, however, it has notbeen released yet. SSM is representative of Japanese people aged 20 to 70, and from the fourthwave (1985), females were taken into consideration. SSM focuses on social classes, inequality andsocial mobility, education, and attitudes towards life and society, etc. The most appealing featureof SSM is that it currently covers five decades, which makes choosing the suitable periods during
which fathers were at prime working ages within one survey when applying TS2SLS possible.

SSM has three measurements of income: personal income, spouse’s income and household’s
income, where income refers to pre-tax gross annual income in the past year. Personal income isused in this study. Incomes in SSM are coded in interval form except SSM 1965, and mid-value ofeach interval is used. Meanwhile, extremely high incomes are also coded continuously in somewaves. Income equations (Equation (6) and (8)) are regressed on type of employment, firm size,
occupation and education. Type of employment is divided into two groups: (1) irregular

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employment and self-employment (TE0) and (2) regular employment (TE1).9 Firm size is divided
into three categories: (1) working in small- or medium-sized firms (FS0); (2) working in big firms(FS1) and (3) working in public sector (FS2). 10 Occupation is divided into six groups: (1)agricultural workers (O0); (2) professional workers (O1); (3) administrative and managerial workers(O2); (4) clerical workers (O3); (5) sales workers (O4) and (6) manual workers (O5).11 Education
is divided into three levels based on Kondo (2000)’s classification: (1) lower secondary educationor less (E0); (2) upper secondary education (E1) and (3) tertiary education (E2).12

SSM 1995 and 2005 are used in this paper. Since SSM does not ask for fathers’ income, but only
their education, occupation, job characteristics, etc. reported ex post by respondents, based on

9

SSM provides detailed classifications of employment type. In this study, company president or executive and regularfull-time employee are classified as regular employment. Temporary or part-time employee, employee dispatched by atemporary employment agency and contract employee or employee on a short-term contract are classified as irregular
employment. Self-employed or freelance worker and family worker are classified as self-employment. In first threewaves of SSM, irregular employment is not included in options of questions for type of employment, which reflectsthat irregular employment became an important component in employment structure since 1980s.
10

Big firm is defined as a firm with more than 999 employees.

11

Skilled manual workers, semi-skilled manual workers and unskilled manual workers are merged into one category(O5) in order to simplify specification.
12

SSM distinguishes between old school system and new school system since Japanese education system changed afterWorld War II. In this study, lower secondary school, elementary school (old system) and upper elementary school (oldsystem) are classified as lower secondary education or less. Upper secondary school, middle school or girls’ high school(old system), vocational school (old system) and normal school (old system) are classified as upper secondary education.
Junior college / technical college, university, graduate school, high school (old system), technical school (old system),higher normal school (old system) and university in old system are classified as tertiary education.
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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which fathers’ income can be imputed, therefore SSM 1965 and 1975 are used as supplementary
datasets to impute fathers’ income by TS2SLS.

4.2

Primary Sample and Supplementary Sample

Primary sample is extracted from SSM 1995 and 2005. There are 2,490 and 2,660 male respondents
in SSM 1995 and SSM 2005, respectively. Those whose age are older than 59 or younger than 30
are dropped. Those who do not report their income, characteristics, and those who have no jobs
(unemployment, students, etc.) are dropped. 13 Those who do not report their fathers’
characteristics and birth year are also dropped. In the end, there are 1,828 male respondents, andtherefore 1,828 father-son pairs in primary sample. The top panel of Table 1 shows the descriptive
statistics for primary sample.

Supplementary sample is extracted from SSM 1965 and 1975. There are 2,158 and 2,724 male
respondents (i.e., pseudo fathers) whom are assumed to be randomly drawn from the sameunderlying population as fathers of SSM 1995 and 2005’s respondents in SSM 1965 and SSM 1975,
respectively. Pseudo fathers in SSM 1965 and 1975 whose age are older than 59 or younger than
30 are dropped. Moreover, those who do not report their income, characteristics, and those whohave no jobs are dropped. In the end, there are 2,893 pseudo fathers. The bottom panel of Table

13

Those who have no income are therefore automatically dropped.
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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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1 shows the descriptive statistics for supplementary sample.

[Insert Table 1 here]

5. Results

Estimation result of Equation (5) is shown in column (1) Table 2. As it shows, IGE between fathers
and sons in Japan for sons born from 1935 to 1976 lies around 0.367.

[Insert Table 2 here]

In column (2) of Table 2, IGE is re-estimated following common specifications (e.g., Lefranc, 2018
and Chu and Lin, 2019). A quadratic function of sons’ age and interaction terms of this function
with fathers’ imputed income are also controlled, in which sons’ age is centered at 40. The resulting
outcome, i.e., the estimate of IGE at sons’ age of 40 is 0.403. This paper finds IGE between
fathers and sons in Japan lies around 0.35 to 0.40, which is comparable to, although a little bit
higher than previous Japanese studies using TS2SLS as reviewed in Section 1. It is reasonable tobelieve estimation results in this paper are relatively reliable due to following reasons. Firstly, lifecycle bias is carefully controlled by imputing fathers’ income at age 40 and restricting sons’ age to[30, 59]. Secondly, imputation bias due to TS2SLS is expected to be reduced by choosing pseudo

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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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fathers who are representative of fathers’ population and using a first step specification with richvariables for imputing income. To sum up, this study finds IGE in Japan lies at intermediate levelcompared with other developed countries together with most of previous Japanese IGM studies.

5.1

The Estimate of Income Equations

5.1.1 Main Results

Estimation results of Equation (6) and Equation (8) are shown in columns (1-1) to (1-3) andcolumns (2-1) to (2-3) of Table 3, respectively. Column (1-1) and (2-1) shows returns to type of
employment, firm size, occupation and education of pseudo fathers and sons at age 40, respectively.
Fathers’ missing income is imputed based on results in column (1-1).

[Insert Table 3 here]

Results in columns (1-1) to (1-3) and in columns (2-1) to (2-3) are estimated in supplementary
sample and primary sample, respectively. Three results are notable. Firstly, in 1965 and 1975, returnto regular employment is negative (-0.187 log points (lp)) compared with return to other types of
employment. In 1995 and 2005, however, return to being regular staffs become positive (0.116 lp).
This can be explained by rapid increasing in irregular employment and that in wage gap between
regular and irregular staffs. Based on Employment Status Survey (ESS), the ratio of irregular
employment had increased to 31.9% in 2002. Moreover, average annual wage of regular staffs was
16Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
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348,100 Yen in 2005, while that of irregular staffs was 221,300 Yen as Basic Survey on Wage
Structure (BSWS) shows. Secondly, in 1965 and 1975, return to being agricultural workers at age
40 is significantly less than all other occupations. In 1995 and 2005, however, being sales or manual
workers earns significantly less than being agricultural workers at age 40. One possible reason isthat irregular employment is more prevalent in sales and manual occupations than in professional,
managerial and clerical occupations. In this paper, roughly 15.75% of sons working as sales or
manual workers are irregularly staffs, while that ratio is only 3.79% for sons working as processional,
managerial or clerical workers. 14 Thirdly, there is a decrease of 0.111 lp in return to upper
secondary education from 1965 and 1975 to 1995 and 2005, and return to upper secondary schools
becomes insignificant. It might be explained by increasing in senior high school enrollment in Japan
during the second half of 20th century. Based on School Basic Survey (SBS), enrollment rate of
middle school graduates to high school in Japan increased dramatically from 51.5% in 1955 to over
96% in 1995, which implies compared with 1965 and 1975, upper secondary education degree may
no longer be such valuable in 1995 and 2005 due to its prevalence.

14

Another possible reason for these results is seniority-wage system in Japanese firms. Since agricultural workers areless likely to be employed with such system, which indicates age-income profiles of agricultural workers should bemuch flatter than those of other occupations, therefore returns to other occupations at age 40 might be smaller thanreturn to agricultural occupation. After dropping all age controls, return to professional occupation (0.21 lp) and return
to managerial occupation (0.45 lp) are significantly higher than that to agricultural occupation. Although return to sales
occupation (-0.05 lp) and manual occupation (-0.14 lp) are lower than that to agricultural occupation, these estimates
are insignificant. Similar patterns can also be found in 1965 and 1975.
17

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

5.1.2 Long-term Variations in Japanese Income Structure

As discussed in Section 2 and Section 3, this paper allows returns to type of employment, firm size,
occupation and education to vary with sons’ birth cohorts. Figure 1 summarizes estimation results.

[Insert Figure 1 here]

Three results are worth noting. Firstly, from 1935 cohort to 1976 cohort, regular employees as wellas those being employed in big firms and public sector move to the center of Japanese labor market.
This can be seen from Panel A of Figure 1. From 1935 cohort to 1950 cohort, income premiumof staffs other than regular staffs (mainly self-employed staffs in these early cohorts) keeps
decreasing from 0.19 lp to 0.05 lp. Similar patterns were also documented in Genda andKambayashi (2002) and Lefranc et al. (2014). From 1951 cohort, return to regular employment
becomes positive (0.04 lp) and keeps increasing to 0.25 lp, which can be explained by the same
reason as mentioned in Section 5.1.1. Meanwhile, returns to working in big firms and public sector
also increase from 1935 cohort to 1976 cohort, although those increases are not as monotonous
as regular employment. Secondly, returns to all the occupations at age 40 decease compared with
agricultural occupation from 1935 cohort to 1976 cohort and such trends are almost monotonous.
For occupations other than agricultural ones, income gap between top and bottom group generally
decreases from 1935 cohort to 1960 cohort (from 0.56 lp to 0.36 lp). However, it raises again

18

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

afterward to 0.50 lp.15 Thirdly, although returns to upper secondary and tertiary schools declinewith fluctuation from 1935 cohort to 1960 cohort, they increase again from 1961 cohort, especiallyfor tertiary education. Similar patterns were also found in Tachibanaki (2009) and Lefranc et al.
(2014). To sum up, this paper finds for sons born after mid 1950s, income inequality increases. Thisfinding is consistent with Lise et al. (2014) and Yamada and Kawaguchi (2015) in which a stable
increasing in income or wage inequality was found from mid 1990s to 2000s, during which
individuals born after mid 1950s were at their prime working age.

5.2

The Estimate of Intergenerational Transmissions

5.2.1 Main Results

Next, strengths of intergenerational transmissions (i.e., ;! ’s) are estimated. This paper considers
10 factors which might induce income inequality and might be transmitted from fathers to sons.
Therefore, there are 100 transmission pathways within which 10 pathways are intra-factor
transmissions, while remaining 90 are inter-factor transmissions. Table 4 shows estimation results.

[Insert Table 4 here]

Each cell of Table 4 refers to a simple Linear Probability Regression (LPR) regressing a sons’

15

In this section, top occupational group and bottom occupational group are defined based on returns at age 40.
19

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

characteristic &!" on a fathers’ characteristic &&' . All the diagonal elements refer to intra-factor
transmissions (= = <), while others refer to inter-factor transmissions (= ≠ <). As shown in Table
4, all the intra-factor transmissions are significantly positive except intergenerational transmissionof upper secondary education. This can be explained by the rapid expansion of upper secondary
education as mentioned in Section 5.1.1, which equalized opportunities for senior high schools
regardless of sons’ family backgrounds.

What mechanisms underlie these transmissions is still an open question. Lefgren et al. (2012) andMiller and Mcintyre (2020) proposed similar models which identified two structural parameters
captured by IGE. Based on these models, intergenerational transmissions occur through bothfinical investment (e.g., parental investment in human capital) and direct transmission (e.g.,inheritance of preference through daily interaction and specific family culture). It is still ambiguousthat which of above two mechanisms prevails, but one should believe both of them play a role.
For instance, this paper finds if sons are raised by fathers with tertiary degree, then the probability
that they become professional workers is 20.9% higher than sons whose fathers do not have tertiary
degree. On the other hand, the corresponding probability that these sons become managerial
workers is only 3.8% higher than other sons. College income premium is considerably high infathers’ generation (0.292 lp, see Table 3), which implies these fathers would have more finicalresources to invest in their sons for generously salaried jobs. However, the probability that thesesons become managerial workers whose income are higher than professional ones is pretty low.
20

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

This result implies there must be something else besides monetary matters.

5.2.2 Long-term Variations in Intergenerational Transmissions

Following the discussion in Section 2 and Section 3, this paper analyzes how ;! ’s vary with sons’birth cohorts. This paper has 100 ;! ’s and it is inefficient to consider all of them. Besides 10 intrafactor transmissions, only upward educational mobility and upward occupational mobility arefocused on. Upward occupational mobilities are defined based on Occupational Prestige Score(OPS) provided by SSM.16 This paper identifies four upward mobilities and they are allowed tovary with sons’ birth cohorts. Estimation results are summarized in Figure 2.

[Insert Figure 2 here]

Panel A to Panel C show how intra-factor transmissions vary with cohorts. As they show,intergenerational transmission of tertiary education is the most important and stable pathway. In
most of cohorts, the probability that sons with fathers holding tertiary degrees also have tertiary
degrees is 40% higher than sons whose father do not have tertiary degrees. In 1951 to 1955 cohorts
and 1961 to 1965 cohorts, this probability exceeds 50% and even reaches 60%, respectively. Thismight reflect the fierce competition for admissions to universities, which forces parents to invest

16

SSM gives each occupation an OPS. The average OPS of professional occupations, managerial occupations andmanual occupations is 61.6, 68.3 and 37.9, respectively.
21

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

in children’s education, like tutoring schools. Another important finding is that from 1935 cohort
to 1976 cohort, the probability that sons are at managerial positions if their fathers are also
managerial workers (transmission of managerial occupation) decreases from over 50% to almost
zero. This reflects the development of seniority-wage system and life-time employment system,
which ensures that promotion depends on tenure in (informally, the loyalty to) a certain firm. Suchsystem significantly dilutes the effect of family background when pursuing for a managerial title.

Panel D to F show how upward educational and occupational mobilities evolve with cohorts. The
general pattern is that, from 1935 to mid 1950s cohorts, these upward mobilities generally increase,which corresponds to high-increasing period before early-mid 1970s since most of individuals
born from 1935 to mid 1950s enter the labor market during this period. After mid 1950s cohorts,
these upward mobilities decline with fluctuations generally, especially for 1971 to 1976 cohortsconsists of those who were more likely to enter the labor market after the collapse of bubble
economy. One intuitive reason of such pattern might be that during prosperous times, it is easierfor children to climb the social ladder from their families of origin. This hypothesis can be
reinforced by 1966 to 1970 cohorts consist of those who were more likely to enter the labor market
from late 1980s to early 1990s, i.e., in bubble boom during which Japanese economy reaches its
peak of the 20th century. It can be seen from Panel D to F that upward mobilities slightly increase
for these cohorts.

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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

5.3

Decomposition of IGE

5.3.1 Main Results

Lastly, IGE is decomposed based on the framework shown in Section 2. Table 5 shows
decomposition results. Each cell of Table 5 presents IGE attributed to one transmission pathway.17
The diagonal cells refer to IGE due to intra-factor transmissions, while other cells refer to IGE
due to inter-factor transmissions.

[Insert Table 5 here]

As Table 5 shows, intergenerational persistence of income inequality is likely to occur at both ends
of distributions of education and occupation. For instance, intergenerational transmissions among
tertiary education, managerial occupation and manual occupation. Take intergenerationaltransmission from fathers’ managerial occupation to sons’ tertiary education as an example. IGE
due to this pathway is roughly 0.069. The high contribution of this pathway to IGE can be
explained by high income premiums of managerial positions in fathers’ generation and tertiary
education in sons’ generation as well as strong intergenerational transmission of this pathway.
Moreover, if the sign of income premium changes from fathers’ generation to sons’ generation17

For instance, the number in the first row and first column refers to IGE due to intergenerational transmission of

being regularly employed.
23

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia(e.g., income premium of regular employment) or intergenerational transmission is negative (e.g.,transmission of upper secondary education to tertiary education from fathers to sons), then IGE
due to related pathways might be negative, i.e., such pathways would increase IGM.

To sum up, this papers finds IGE due to intergenerational transmissions of occupation (0.100) is
higher than IGE due to that of education (0.042). This is consistent with Österbacka (2001)’s
Finnish study and Lefranc and Trannoy (2005)’s French study. The difference between contributionof occupation and education in this study (0.058) is much lower than that in Lefranc and Trannoy(2005) (over 0.11). One important reason might be different specifications. In Lefranc and Trannoy(2005), occupation was measured by social classes whose income premiums are much more stable
than occupation in the long-run. For instance, this papers finds income premiums of 4 out of 5
occupational groups at age 40 compared with reference group (agricultural occupation) change
from positive to negative from 1965 and 1975 to 1995 and 2005. Another reason might becompetitive education system in Japan, which makes parental investment in children’s education
more important and therefore plays a more important role in IGE.

5.3.2 Long-term Trends in Components of IGE

Next, long-term variations in income structure and intergenerational transmissions are combined
together to analyze how these variations contribute to variations in components of IGE. Results
are summarized in Figure 3.
24

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia[Insert Figure 3]

Panel A to C present how IGE due to intra-factor transmissions vary with cohorts. Following
patterns are notable. Firstly, throughout all the cohorts, IGE due to intergenerational transmissionof tertiary education almost remains above 0.04. In 1935 to 1940 cohorts and 1966 to 1970 cohorts,
IGE due to this pathway even approaches 0.08 and 0.10, respectively. The stable high contributionof this pathway to IGE is due to strong intergenerational persistence of tertiary education andhigh return to it. It is worth noting that although both variations in intergenerational transmission
and income premium contribute to this final trend, this trend is much more similar to long-term
trend in return to tertiary education, instead of that in intergenerational transmission. Secondly,
IGE due to intergenerational transmission of regular employment decreases from 0.016 in 1935
to 1940 cohorts to -0.030 in 1971 to 1976 cohorts. In other words, from 1935 cohort to 1976
cohort, intergenerational transmission of being regularly employed increases IGM. The reason isthat from 1935 cohort to 1976 cohort, return to regular employment keeps increasing and changes
from negative to positive. Moreover, intergenerational transmission of regular employment keeps
positive throughout all the cohorts. Lastly, IGE due to transmission of occupations keep
decreasing with cohorts, which is very similar to long-term trends in returns to occupations asshown in Panel B of Figure 1.

Panel D to F show how IGE due to upward educational and occupational mobilities vary with25

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

cohorts. As panel D shows, From 1935 cohort to 1950 cohort, IGE due to upward educational
mobility increases from -0.006 to 0.021 with fluctuations. Since 1951 cohort, this trend is reversed
and IGE due to this pathway decreases to almost zero with the exception that IGE due to thispathway reaches 0.034 in 1966 to 1970 cohorts. It implies upward educational mobility contributes
to an increasing in IGM generally since 1951 cohort. Similar pattern can be observed from Panel
F. From 1935 cohort to 1955 cohort, IGE due to upward mobility from fathers’ occupation tosons’ education increases monotonously from -0.108 to -0.015. Since 1956 cohort, however, IGE
due to this pathway decreases monotonously to -0.055. Different patterns are shown in Panel E.
As it shows, IGE due to intergenerational transmission from fathers’ manual occupation to sons’managerial occupation decreases from 0.050 to -0.016 from 1935 cohort to 1965 cohort. However,it increases again to 0.050 from 1966 cohort to 1976 cohort. As for IGE due to transmission fromfathers’ manual occupation to sons’ professional occupation, it keeps fairly stable around zerothroughout 1941 to 1970 cohorts. However, it also increases to 0.047 for 1971 to 1976 cohorts. To
sum up, these upward occupational mobilities do not contribute to an increasing in IGM.

6. Conclusions

This paper has estimated IGE in Japan using TS2SLS and finds IGE in Japan lies around 0.35 to
0.40 for sons born from 1935 to 1976. How components of IGE vary with sons’ birth cohorts is
26

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

analyzed by estimating long-term trends in income structure and intergenerational mobilities of
education, occupation, etc. This paper finds income inequality in Japan increases for sons bornafter early-mid 1950s and upward educational mobility and upward occupational mobility decrease
for these recent cohorts of sons. Although upward mobility of education itself decreases for sonsborn after early-mid 1950s, it contributes to an increasing in IGM for these sons after considering
long-term trends in income premiums of education. However, it is not the case for upward
occupational mobility. Moreover, income premium of regular employment keeps increasing withthe establishment of life-time employment system and seniority-wage system in Japan after WorldWar II, which provides a channel for sons born from 1935 to 1976 to improve their economic
status compared with their fathers (See discussion in Section 5.3.2).

This paper indicates both the strength of intergenerational transmissions of factors which might
induce income inequality (e.g., education) and long-term trends in income premiums of thesefactors (e.g., return to education) underlie intergenerational persistence of income inequality.
Which of these two mechanisms prevails is an open question for further researches. Using Japanesedata, this study finds changes in income premiums might be more important. For instance, thepatterns of long-run variations in IGE due to intergenerational transmission of tertiary educationand that of occupations are highly coincided with long-run trends in returns to tertiary educationand occupations (See discussion in Section 5.3.2). All in all, it seems that long-run trends in income
inequality might be more important in shaping intergenerational persistence of income inequality.
27

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

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Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

Table 1 Descriptive Statistics
primary sample(extracted from
SSM 1995 and2005. n=1,828)

auxiliary sample(extracted from
SSM 1965 and1975. n=2,893)

variablelog (sons’ income)sons’ birth year
sons’ age
type of employment (sons)regular employment
firm size (sons)
big firms
public sector
occupation (sons)professional
administrative and managerial
clericalsales
manualeducation (sons)
upper secondary education
tertiary education
fathers’ birth year
fathers’ age
type of employment (fathers)
regular employment
firm size (fathers)
big firms
public sector
occupation (fathers)
professional
administrative and managerial
clericalsales
manualeducation (fathers)
upper secondary education
tertiary educationlog (pseudo fathers’ income)pseudo fathers’ birth year
pseudo fathers’ age
type of employment (pseudo fathers)
regular employment
firm size (pseudo fathers)
big firms
public sector
occupation (pseudo fathers)
professional
administrative and managerial
clericalsales
manualeducation (pseudo fathers)
upper secondary education
tertiary education

mean
15.48
1954.31
45.16

s.d.
0.56
9.44
8.26

80.03%

0.40

17.45%
12.20%

0.38
0.33

14.50%
11.65%
20.02%
12.96%
36.71%

0.35
0.32
0.40
0.34
0.48

50.44%
38.18%
1923.10
76.42

0.50
0.49
11.87
10.61

52.83%

0.50

12.20%
12.04%

0.33
0.33

7.77%
11.82%
10.45%
11.60%
33.42%

0.27
0.32
0.31
0.32
0.47

27.63%
15.48%
13.92
1928.38
42.26

0.45
0.36
0.95
9.52
8.22

66.92%

0.47

15.62%
10.68%

0.36
0.31

7.50%
10.75%
15.21%
11.30%
38.47%

0.26
0.31
0.36
0.32
0.49

30.87%
15.31%

0.46
0.36
32

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

Table 2 Estimation results of IGE between fathers and sons in Japan

fathers’ imputed incomesons’ agesons’ age2
fathers’ imputed income×sons’age
fathers’ imputed income×sons’age2
year dummy

Dependent variable: logarithm of sons’ annual income (n=1,828)(1)(2)
0.367***
0.403***(0.046)(0.056)○○○○○

Note: sons’ age is centered at 40. Robust standard errors are in parentheses. *** p<0.01, ** p<0.05,* p<0.1.

33

Sons’ income equation (Equation (8))
Dependent variable: logarithm of sons’ annual income (n=1,828)
(2-1)
(2-2)
TE0
Ref
0.116**-0.002TE1
TE1×age
TE1×age2(0.054)(0.007)
FS0
Ref
0.205***
0.011***
FS1
FS1×ageFS1×age2(0.032)(0.004)
0.023
0.006
FS2
FS2×ageFS2×age2(0.038)(0.005)O0
Ref-0.058-0.031*O1O1×ageO1×age2(0.162)(0.019)0.045-0.054***O2
O2×ageO2×age2(0.161)(0.020)-0.126-0.033*O3O3×ageO3×age2(0.158)(0.018)-0.267*-0.042**O4
O4×ageO4×age2(0.162)(0.018)-0.391**-0.035**O5O5×ageO5×age2(0.154)(0.018)
E0
Ref
0.117
0.008
E1
E1×ageE1×age2(0.090)(0.015)0.230**
0.014
E2
E2×ageE2×age2(0.093)(0.016)0.000(0.001)-0.001(0.001)0.004***(0.002)0.006***(0.002)0.004**(0.001)0.004***(0.001)0.004***(0.001)-0.001**(0.000)0.000(0.000)0.001(0.001)(2-3)

Zhi-xiao Jia

of variables are introduced in Section 4.1.

34

Note: age, age2, year dummies and constant terms are controlled. age is centered at 40. Robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Definitions

Pseudo fathers’ income equation (Equation (6))
Dependent variable: logarithm of pseudo fathers’ annual income (n=2,893)
(1-1)
(1-2)
(1-3)
TE0
Ref
-0.187***-0.0040.002***TE1
TE1×age
TE1×age2(0.053)(0.006)(0.001)FS0
Ref
0.244***
0.010***-0.001*
FS1
FS1×ageFS1×age2(0.032)(0.003)(0.000)0.024
0013***
0.000
FS2
FS2×ageFS2×age2(0.040)(0.005)(0.001)O0
Ref
0.492***
0.021-0.002O1
O1×ageO1×age2(0.089)(0.014)(0.001)0.775***
0.020*-0.002O2
O2×ageO2×age2(0.082)(0.011)(0.001)0.417***
0.005-0.001O3
O3×ageO3×age2(0.080)(0.010)(0.001)0.290***
0.003
0.001
O4
O4×ageO4×age2(0.073)(0.009)(0.001)0.267***-0.0050.000
O5O5×ageO5×age2(0.068)(0.008)(0.001)E0
Ref
0.228***-0.0020.001
E1
E1×ageE1×age2(0.038)(0.004)(0.001)0.292***-0.0100.002**
E2
E2×ageE2×age2(0.051)(0.007)(0.001)

Table 3 Estimation results of income equations

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost DecadeFS1s
0.053***(0.018)0.143***(0.032)0.008(0.028)0.002(0.033)0.023(0.029)0.062**(0.032)-0.021(0.027)0.043**(0.019)-0.006(0.020)0.053**(0.026)FS2s
0.035**(0.015)0.014(0.024)
0.109***(0.029)0.059*(0.033)0.024(0.025)0.074**(0.029)-0.063***(0.019)-0.026*(0.016)-0.015(0.017)0.027(0.022)O1s
0.071***(0.016)0.019(0.026)0.161***(0.032)0.370***(0.043)0.040(0.028)0.049(0.030)-0.036(0.024)-0.048***(0.027)0.019(0.019)0.209***(0.029)O2s
0.069***(0.015)0.092***(0.028)-0.014(0.022)-0.050**(0.023)0.183***(0.031)0.034(0.027)-0.025(0.022)-0.013(0.016)0.017(0.017)0.038*(0.023)O3s
0.051***(0.019)0.048(0.030)0.072**(0.031)-0.011(0.034)0.083***(0.032)0.116***(0.035)-0.056**(0.027)-0.045**(0.019)-0.009(0.021)
0.031(0.027)O4s-0.003(0.016)-0.040*(0.021)-0.023(0.023)-0.026(0.027)-0.005(0.024)-0.034(0.023)0.291***(0.034)-0.052***(0.016)
0.064***(0.019)0.018(0.023)O5s-0.121***(0.023)-0.081**(0.033)-0.164***(0.031)-0.253***(0.031)-0.259***(0.027)-0.118***(0.034)-0.127***(0.032)0.211***(0.024)-0.089***(0.024)-0.263***(0.024)E1s-0.117***(0.023)-0.059*(0.036)-0.201***(0.034)-0.341***(0.035)-0.241***(0.033)-0.096**(0.038)-0.058(0.036)0.184***(0.024)0.004(0.026)-0.342***(0.028)E2s
0.230***(0.022)0.147***(0.036)
0.269***(0.035)0.426***(0.037)0.365***(0.033)0.170***(0.038)0.096***(0.036)-0.192***(0.023)0.083***(0.026)
0.464***(0.028)Zhi-xiao Jia

each of these 100 regressions. Robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Definitions of variables are introduced in Section 4.1.

35

Note: Each cell refers to a simple Linear Probability Regression (LPR) regressing a sons’ characteristic "!" on a fathers’ characteristic "#$ . Constant term is controlled in

E2f

E1f

O5f

O4f

O3f

O2f

O1f

FS2f

FS1f

TE1f

TE1s
0.177***(0.019)0.125***(0.022)0.129***(0.022)0.033(0.033)0.100***(0.024)0.100***(0.025)-0.164***(0.034)0.052***(0.019)0.024(0.020)0.044*(0.024)

Table 4 Intergenerational transmission (!! ’s)

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade

TE1s-0.01078
0.005290.000410.00157
0.00954
0.00731-0.00720
0.004610.00171
0.00239FS1s-0.00575
0.010710.00005
0.000140.00379
0.00805-0.00166
0.00674-0.00073
0.00507

FS2s-0.00042
0.000120.000070.00055
0.000460.00107-0.00055-0.00046-0.00021
0.00029O1s
0.00217-0.00040-0.00026-0.00875-0.00192-0.00177
0.00079
0.00215-0.00066-0.00568

O2s-0.00163
0.00151-0.00002-0.00092
0.006740.00095-0.00043-0.00044
0.000460.00080O3s
0.00334-0.00219-0.00025
0.00056-0.00853-0.00916
0.00266
0.004370.00065-0.00181

O4s-0.00049
0.003930.000170.002840.001150.00566-0.02947
0.01072-0.01047-0.00225

O5s-0.02492
0.011530.001770.04035
0.08283
0.02892
0.01886-0.06341
0.02109
0.04816E1s
0.00720-0.00250-0.00065-0.01627-0.02311-0.00703-0.00259
0.016560.00025-0.01873

E2s-0.02769
0.012340.001700.03997
0.06873
0.02459
0.00841-0.03407
0.01157
0.04998

Zhi-xiao Jia

employment). Definitions of variables are introduced in Section 4.1.

36

Note: Each cell refers to IGE due to one transmission pathway (e.g., -0.01078 in first row and first column refers to IGE due to intergenerational transmission of regular

TE1f
FS1f
FS2f
O1f
O2f
O3f
O4f
O5f
E1f
E2f

Table 5 Intergenerational income elasticity attributed to each transmission pathway

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost DecadeLong-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade
Zhi-xiao Jia

Figure 1 Long-term trends with cohorts in income premiums
(A)
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
-0.15
-0.20
-0.25
1930

1935

1940

1945

1950

1955

TE1

1960

FS1

1965

1970

1975

1980

1970

1975

1980

FS2

(B)
1.50
1.25
1.00
0.75
0.50
0.25
0.00
-0.25
-0.50
-0.75
-1.00
-1.25
1930

1935

1940

1945

O1

1950

1955

O2

1960

O3

1965
O4

O5

(C)
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
-0.15
-0.20
-0.25
1930

1935

1940

1945

1950

1955
E1

1960

1965

1970

1975

1980

E2

Note: Definitions of variables are shown in Section 4.1. Returns refer to returns at
the age of 40.
37

1930

1930

1950

FS1

1960

1950

1960

1970

FS2

1970

Prob (son has E2 | father has E1)

1940(D) Upward mobility (I)

TE1

1940

1980

1980

0.10
0.05
0.00
-0.05
-0.10
-0.15
-0.20

0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-0.05

1930

1930

O4

O1

1950

O5

O2

1960

1950

1960

1970

O3

1970

Prob (son is O2 | father is O5)

Prob (son is O1 | father is O5)

1940(E) Upward mobility (II)

1940

(B)

1980

1980

-0.05
-0.10
-0.15
-0.20
-0.25
-0.30
-0.35
-0.40

0.60
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.10
-0.15

1930

1930

E1

1950

1960
E2

1950

1960

1970

1970

Prob (son has E2 | father is O5)

1940(F) Upward mobility (III)

1940

(C)

1980

1980

Zhi-xiao Jia

38

Note: Definitions of variables are shown in Section 4.1. Take Panel (D) as an example. It shows how upward educational mobility (Prob (son has tertiary degree | father
only has upper secondary degree)) varies with sons’ birth cohorts.

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

-0.05

0.00

0.05

0.10

0.15

0.20

0.25

0.30

(A)

Figure 2 Long-term trends in intergenerational transmissions

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade

1930

1930

1950

FS1

1960

1950

1960

1970

FS2

1970

Prob (son has E2 | father has E1)

1940(D) Upward mobility (I)

TE1

1940

1980

1980

0.05
0.03
0.00
-0.03
-0.05
-0.08
-0.10
-0.13
-0.15

0.65
0.55
0.45
0.35
0.25
0.15
0.05
-0.05
-0.15
-0.25
-0.35

1930

1930

O4

O1

1950

O5

O2

1960

1950

1960

1970

O3

1970

Prob (son is O2 | father is O5)

Prob (son is O1 | father is O5)

1940(E) Upward mobility (II)

1940

(B)

1980

1980

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.10
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
-0.01
-0.02

1930

1930

E1

1950

1960
E2

1950

1960

1970

1970

Prob (son has E2 | father is O5)

1940(F) Upward mobility (III)

1940

(C)

1980

1980

Zhi-xiao Jia

39

Note: Definitions of variables are shown in Section 4.1. Take Panel (D) as an example. It shows how IGE due to upward educational mobility (Prob (son has tertiary
degree | father only has upper secondary degree)) varies with sons’ birth cohorts.

-0.02

-0.01

0.00

0.01

0.02

0.03

0.04

-0.04

-0.03

-0.02

-0.01

0.00

0.01

0.02

(A)

Figure 3 Long-term trends in components of IGE (i.e., IGE due to transmission pathways)

Long-term Trends in Intergenerational Income Mobility in Japan: From High Increasing to Lost Decade