A Comparative Analysis of Social Stratificationin Japan, Korea and Taiwan:
Where is the Locus of Social Inequality?*
Shin ARITA
Institute of Social Science
University of Tokyo

ISS Discussion Paper Series
F-182
February 2017

Abstract
This paper examines the ways in which individual’s income and subjective social status are
determined by one’s work-related and personal factors and studies the ways in which social
contexts shape social stratification in Japan, (South) Korea, and Taiwan from a comparative
perspective. The empirical analysis using the 2005 SSM survey data has revealed that
institutional factors such as Japanese employment practices strongly affect individuals’
remuneration and status and make the stratification structure highly multidimensional in Japan.
While occupation, among work-related factors, is the predominant determinant of one’s income
and subjective social status in Taiwan, employment type and firm size (only for men) also havea considerable independent influence in Japan. Korea appears to be placed between Japan andTaiwan. Among personal factors, the influence of age is striking for men in Japan, although it isslight for women. These results suggest the seniority-based personnel practices and additional
benefits for working at large firms have strong influence on one’s status in Japan, while womenand non-standard workers are institutionally excluded from these benefits. We can conclude thatthe selection of the beneficiaries of the Japanese employment practices is one of the essential
factors generating social inequalities in Japan.
Keywords and Phrases: income, subjective social status, remuneration determination, Japaneseemployment practice, East Asia

* This is a revised version of the paper that originally appeared in Studies of Social Stratification inContemporary Japan: From the Perspective of Micro-Macro Linkages 1 (research report for the
JSPS Grant-in-Aid for Scientific Research (A), No. 20243029) (pp.323-342) edited by Yoshimichi
Sato in March 2011. This paper includes discussions based on newly conducted analysis, in addition
to the analysis in Arita (2008) and Arita (2011).

1. Introduction: Why compare East Asian social stratification?
It has long been considered that social inequalities in Japan, (South) Korea and Taiwan are not as
severe as those in other countries, based on the view that these East Asian societies have achieved
relatively equal distribution of wealth and social goods in the process of rapid economic growth(World Bank, 1993). However, widening social inequalities in recent years have come to light as amajor social problem in these societies, exemplified by the proliferation of ‘social disparity’arguments (e.g., kakusa shakai ron in Japan). Ascertaining the structure of social stratification andthe generating mechanisms of social inequalities has become an important task in these countries, notonly academically but also socially.
Comparison with other societies is a particularly effective approach in attempting toascertain the social stratification structures and the generating mechanisms of inequalities in a society.
A number of studies comparing Japan’s social stratification structure with that of another country(Ishida, 1993, for example) have succeeded in highlighting characteristics of Japan’s stratification
structure that are difficult to find when studying Japanese society in isolation. However, due tolimitations of survey data availability and comparability, most of these earlier studies arecomparisons with Western societies. At present, little comparison between East Asian countries has
been conducted.
Yet, studies in other fields have shown that comparison between East Asian countries
having both similarities and dissimilarities is extremely effective in identifying each society’s
characteristics in more detail (Brinton, 2001; Hamilton and Biggart, 1988). This approach is expected
to be similarly effective for comparative analysis of social stratification. Japan, Korea and Taiwan
have very similar structural conditions of stratification, such as industrialization based on labor
intensive manufacturing, extensive agrarian reform after the Second World War and a universal andrapid expansion of education. Today, all three societies are experiencing rapid globalization,
post-industrialization and a common trend toward ‘flexible employment’. At the same time, however,they have many subtle but very important dissimilarities in institutional conditions such as
employment practices, social security systems and education systems. Comparing societies that are
similar in broad outlines yet different in details can be expected to more clearly reveal thecharacteristics of each society’s stratification structure, especially the effects of social and economic
background conditions on social inequalities.
In this paper, we shall attempt a comparative analysis of social stratification in East Asia
using the data from the 2005 Social Stratification and Mobility surveys (hereafter called ‘SSM
surveys’) of Japan, Korea and Taiwan in line with the above issues. Specifically, we shall focus on
individual income as an objective aspect of social stratification and people’s subjective social status
as a subjective aspect of social stratification. We shall empirically analyze the ways in which these
two aspects are determined by individuals’ work-related and personal factors. In doing so, we shall2carry out a comprehensive examination of the leading factors giving rise to unequal distribution ofsocial resources in each of these societies.

2. Factors of inequalities in remuneration and life opportunities
2.1 Work-related factors
In industrialized societies, the work that an individual is engaged in is the most important
determinant of his or her remuneration and life opportunities. It is therefore common for empiricalstudies of stratification and social class to collect data on social status based on respondents’ work.
There are several criteria for classifying an individual’s work. The present analysis shall use four ofthem: employment status, occupation, firm size and type of employment.
Empirical studies conducted by Western scholars have commonly classified an individual’ssocial class based on his or her employment status and occupation, reflecting the accumulation of
past theoretical work (Goldthorpe, 1980; Wright, 1985). Employment status determines the relationsof production and indicates whether an individual has a means of production, which is an asset initself. Occupation is a variable representing the standards of skills and abilities that determine thevalue of an individual in the labor market and the level of control authority an individual has overmeans of production and economic activity at the workplace. Both are considered to be importantvariables which greatly influence an individual’s remuneration and life opportunities.
In addition, it has been pointed out that, in the case of Japanese society, the nature of thework organization, especially the size of the enterprise which employs the individual, is an importantfactor (Sakamoto and Powers, 1995; Kalleberg and Lincoln, 1988). It has been argued that thedelayed industrialization of Japan has given rise to its two-tier economic structure, which has createdcapital and productivity gaps between modern large corporations and traditional small to medium
firms, resulting in large wage gaps and barriers to labor mobility between different firm-size sectors(Ujihara, 1966; Odaka, 1984). And it is highly likely that these disparities in financial resources andstability based on firm size are linked to disparities in employee benefits provided by Japanesemanagement (Abegglen, 1958), such as seniority-based wage raises and career-long employment1. In
this context, in which pay standards, wage raise potential, income and employment stability andprestige vary greatly depending on the size of a company, firm size has been considered to be the key
variable for properly understanding the stratification structure in Japanese society2 (Seiyama et al
1988; Kanomata, 2001).
Furthermore, disparities brought about by differences in employment type have recently
become a major concern in Japan. Non-standard types of employment such as part-time, fixed-term
1

In addition, these large gaps in remuneration between different sized firms have been maintainedwith hardly any redress thanks to another pillar of Japanese management, enterprise unionism.
2 In fact, Japanese sociologists have devised a unique occupation classification framework
incorporating employment status, occupation and firm size (SSM General Occupation Classification)
to use in studies of Japan’s social stratification structure.
3

and dispatched employment have greatly expanded as part of a trend toward increasing labor
flexibility in Japan. Tarohmaru (2009) has demonstrated disparities between standard employees andnon-standard employees in Japan in wages and subjective status identification. He has also identified
barriers to intra-generational mobility between standard and non-standard employment and suggeststhat non-standard employees should be treated as a separate social class for these reasons. Of course,
non-standard types of employment are expanding world-wide, but it is likely to lead to more serious
disparities in Japan where the employment type determines the availability of the major benefits of
employment provided by Japanese management (Hirata, 2008).
2.2 Personal factors
The explanation above is a type of position determinism in the sense that the characteristics of one’s
position, such as one’s job and work-place, determines one’s remuneration, independently of personal
characteristics. At the other end of the spectrum is an individualistic view which posits that one’s
personal characteristics determines one’s remuneration independently of one’s position (Granovetter,1981). Human capital theories and status attainment models are typical examples of the latter view,attaching great importance to the individual’s education level as a personal characteristic that greatly
influences one’s remuneration. By receiving more education, an individual is able to increase his or
her productivity, which is assumed to be the fundamental determinant of individual earnings inneoclassical economics (Mincer, 1974).
Of course, if we could assume a perfectly functionalistic job matching process in which
individuals find jobs with the exact remuneration amount they are qualified to receive, there would
be no fundamental conflict between position determinism and individual determinism. However,recognizing that wage determination and job matching do not necessarily occur in such a manner inthe real world due to institutional factors, it is worth looking at the effects of personal factors such as
education level independently of work-related factors as the status attainment model does. In fact,
Kikkawa (2006) claims that individual education background functions as an important statusindicator which directly impacts on one’s social consciousness and lifestyle, and is not merely asecondary variable which determines occupational status.
If we think of including personal factors in our analysis independently of work-related
factors, we should also consider a few other individual attributes which may strongly affectremuneration and life opportunities in Japanese and other East Asian societies. One of these factors isage. The effect of age on an employee’s remuneration is considered to be greater in Japanese society,with its seniority-based wage and promotion practices, than in other societies (Kalleberg and Lincoln,1988). While the development of this seniority system, according to orthodox economists, can be
attributed to the fact that continuous service increases experience and skill, many other researchers
attribute it to the fact that companies guarantee employees’ living expenses according to their life
stages. Ono (1989), for example, has demonstrated through empirical analysis that age has a greater
impact on individual wage levels than length of continuous service and length of job experience,4

which serve as proxies for the degree of skill development, and that the effect of age is much stronger
than the effect of individual education levels3.
Gender is another important variable in defining remuneration and occupational status in
East Asia. Labor markets in East Asia are mostly divided along gender lines and the remuneration
determination structure is different between men and women, especially in Japan and Korea. It isperhaps more appropriate to study the effect of the gender variable by analyzing each genderseparately and examining how gender influences the effects of other independent variables, as many
previous studies have done, rather than treating gender as an independent variable.

3. Comparison of background conditions in East Asia and the research question
As discussed, it appears that factors such as firm size, employment type and age have particularly
stronger impacts in Japan’s unique social context than in Western contexts. Do other East Asiansocieties, such as Korea and Taiwan, with relatively similar social structure and historical andcultural contexts, have similar background conditions which amplify the effects of these factors? Let
us briefly look at the background conditions involved in this question.
First, one of the background conditions that amplify the effect of firm size in Japanesesociety is the two-tier structure of its economy (Cole, 1979; Sakamoto and Powers, 1995). It is
generally believed that the two-tier structure comprised of modern large corporations and traditional
small- and medium-sized firms was substantially shaped by the fact that Japan was alate-industrializing society. Korea and Taiwan industrialized even later than Japan, and both have
two-tier economic structures according to firm size in greater or lesser degrees. In these two countries,
the gaps in technology levels, productivity and other aspects between the large companies and small
businesses are considered to be even greater than in Japan, especially in Korea. It can therefore be
hypothesized that firm size has a significant impact on remuneration and life opportunities in thesesocieties as well.
At the same time, however, remuneration gaps based on firm size and employment type areconsidered to be further widening in Japan because of its particular employment practices. In otherwords, because the benefits of Japanese employment practices such as the seniority-based
remuneration system and life-time employment security are provided only to standard employees inmost cases, and the level of these ‘privilege-type’ fringe benefits provided to employees is strongly
defined by a company’s financial resources, which are highly related to size of firm in Japan,
employment type and firm size exert stronger influences on social stratification. If so, the importanceof the effects of firm size and employment type may vary depending on how widely such3

However, we must remember that remuneration gaps according to age differences, large as they
may be, are different from the gaps created by other factors because changes in age are equallyapplicable to all individuals and therefore between-individual differences almost disappear over eachindividual’s lifetime.
5

employment practices are adopted in Korea and Taiwan and how different the adoption rate is
between large and small firms. Jung and Cheon (2004) have considered this question by analyzing thestability of employment and the seniority-based wage system and concluded that Japanesemanagement practices are not very prevalent in Taiwan and are only prevalent in Korea among large
corporations. If this is the case, the effects of firm size and employment type are likely to be more
intense in Japan, and to a lesser extent in Korea, than in Taiwan.
A similar hypothesis can be made with regard to the effects of age and gender. Although
Japan, Korea and Taiwan certainly share the common East Asian cultural and historical context of
valuing elders, the individual effect of the age variable is expected to be stronger in Japan, with its
stronger tendency for seniority-based remuneration distribution within a firm. As discussed earlier,the effect of age may vary depending on firm size and employment type. In terms of gender, theeffects of firm size, employment type and age may be more salient among men than womenconsidering that the aforementioned ‘Japanese employment practices’ are strongly oriented towards
livelihood security based on the male breadwinner model4 (Osawa 2011).
Although Korea and Taiwan share high valuation of education with Japan, the effect ofeducation background may also vary between these societies in view of particular differences, suchas a much stronger sense and greater visibility of educational hierarchy in Korea than in Japan (Arita,
2006).
Based on the above issues, this paper shall investigate the following two research questions
with regard to Japanese, Korean and Taiwanese societies.
1

Among an individual’s work-related variables, how much stronger are the effects of firm
size and employment type, which can be regarded as ‘organizational’ effects, thanemployment status and occupation, which are the usual focus of social stratification
studies?

2

How strong are the effects of personal attributes such as age, education and gender onsocial stratification independently of or through the mediation of other work-related
variables?

4. Method
4.1 Data and variables
In this paper, we focus on individual income and subjective social status in order to figure out anindividual’s position in social strata and analyze the effects of work-related and personal factors on
them. Income is ‘one of the most important indicators of inequality between social strata’ (Hara andSeiyama, 1999: 19), having a crucial influence on an individual’s living standards. Subjective social
4

The exclusion of women from the benefits of ‘Japanese employment practices’ is assumed to be asalient factor that enlarges remuneration gaps between genders in Japan.
6

status is a synthetic judgment about one’s own position in the social strata, based on the current stateof income and other resources. Therefore, it is expected that analyzing determinants of these two
factors can lead to a comprehensive understanding of the social stratification structure in a society.
Dependent variables in the analysis below are the natural logarithm of individual income
and the self-reported subjective social status, with 10 being the ‘highest’ and 1 being the ‘lowest’.
The standard deviation for logarithmic individual income is 0.626 in Japan, 0.728 in Korea and 0.874
in Taiwan for men and 0.857 in Japan, 0.974 in Korea and 0.897 in Taiwan for women. It is highest in
Taiwan for men and in Korea for women. The average value of subjective social status is highest inJapan for both men and women (5.42 and 5.56, respectively), followed by Taiwan (4.99 and 5.19) andKorea (4.88 and 5.09). There is no marked variation in their standard deviations except that it issomewhat higher for Korean women.
Independent variables that are included in the analysis are an individual’s occupation (ISCO
major groups), employment status (employer/self-employed, family employee, employee),employment type5 (non-standard worker, standard worker), firm size (small: up to 29 employees,
medium: 30–299, large: 300 or more and public sector), age (centered on 45 years), the square of age(centered on 45 years), and education level (junior high school or lower, senior high school, juniorcollege, university or higher). Logarithmic work hours are incorporated into all income analysis
models in order to control for variations in income due to differences in work hours.
The data sets used in the analysis are the data collected in the SSM Surveys conducted inJapan, Korea and Taiwan in 2005. They are national representative surveys covering adults aged 20
to 69. The sample population used for this analysis is limited to working income earners. The data
sets are analyzed after probability sampling is adjusted by probability weighting for age andresidence area.
4.2 Analysis methods
The analysis below uses OLS multiple regressions6 with income and subjective social status asdependent variables for separate male and female data sets. Since a majority of independent variablesin this analysis are measured using nominal scales, the strength of each factor’s effect is measured
using dummy variables corresponding to each category. However, this method is unable to express an
overall effect of a (single) variable consisting of multiple categories as a single parameter. Hence, it
makes comparison of the strength of effect between variables difficult (e.g., ‘How much stronger isthe effect of firm size than the effect of occupation?’).

5‘Non-standard workers’ are employees in non-standard jobs while employees in standard jobs,
self-employed and employers and family workers are all included in ‘standard workers’. Accordingly,‘employment status’ and ‘employment type’ have been created by re-categorizing four mutually
exclusive categories (self-employed, family workers, standard employees, and non-standard
employees) in a different way based on their respective criteria.
6 Because an ordered logit analysis of 10-point scale of subjective social status did not produce
greatly different results, we have carried out an OLS regression analysis here for convenience.
7

For this reason, we follow the method used by Wright (1997) in an attempt to express theoverall effect of a variable consisting of multiple categories in a single parameter. More specifically,
we first estimate an OLS equation using original dummy variables in the usual manner, then assign
the unstandardized coefficient of each dummy variable to a corresponding category in order toconstruct a single aggregation variable for each of the multi-category factors such as occupation or
firm size7. Next, we substitute the original sets of dummy variables with these newly constructed
aggregate variables to carry out the same regression analysis. The coefficient of determination for the
new model matches completely with that of the previous model using original sets of dummy
variables, and all of the unstandardized regression coefficients of the newly added aggregate
variables become 1. At this point, the “standardized” coefficients of the newly added variables can beused as indicators of the relative importance of the effects of individual variables after controlling for
all other independent variables.

5. Results
5.1 Impact on individual income
Table 1 shows the effect of each factor on individual income estimated by applying the OLS equation
with original sets of dummy variables. For men, the effects of dummy variables are generally similar
albeit with some variations in their degree or significance depending on the country. In summary, age
exhibits an inverted U-curve effect and occupation provides higher income for managers andprofessionals, followed by technicians, clerks and trade workers. Income is higher for the
self-employed and employers than employees, standard workers than non-standard workers, large
company employees than medium company employees, and medium company employees than small
company employees. People with higher education have higher income.
Do the effects of these variables differ greatly from one country to another? Figure 1 shows
the standardized coefficients of the newly constructed aggregate variables for men using the
aforementioned method in order to examine the relative impacts of these factors. First, comparison of
the effects of work-related factors shows that in Taiwan occupation has an overwhelmingly strong
effect while the effects of the other three factors – employment status, employment type and firm size
– are not very strong. In Japan by contrast, firm size exerts as much influence as occupation does andemployment type also has a substantial effect8. It is possible to say that the effect of one’s work on
one’s income has a multidimensional structure in Japan in the sense that differences in not only
occupation but also firm size and employment type exert substantial effects almost independently.
7

The number 0 is assigned to the reference category of dummy variables for each aggregation
variable. The operation is equivalent to arranging categories on a single line based on the size of the
impact of each category on dependent variables. A similar analysis is carried out on age by creating‘aggregate variables’ combining the effects of the first-order and second-order terms.
8 Considering that firm size and employment type in particular have very small numbers of
categories (three and two respectively), the strength of these effects is worth noting.
8

While Korea appears to be placed somewhere between Japan and Taiwan, it is perhaps closer to Japan
as firm size also has a substantial impact on income.
Besides the work-related factors, there are very clear differences between these three
countries in the relative impact of personal factors. The most notable is the strength of the age effectin Japan. The degree of ‘seniority-based remuneration determination’ appears to be very strong as theeffect of age on income in Japan even exceeds that of occupation. By contrast, the effect of age is notvery strong in Taiwan, and is much weaker than that of occupation. The age effect in Korea is similar
to that in Taiwan but is still much greater than other factors.

Table 1 Regression analysis of individual incomeJapanb
13.641 ***0.010 ***
-0.001 ***

Men
Korea
Taiwanbb
14.631 *** 11.978 ***-0.0050.000***-0.001-0.001 ***Japanb
9.711 ***
0.009 ***
0.000

Women
Korea
Taiwanbb
12.059 *** 11.433 ***-0.004-0.002**-0.001-0.002 ***1.092 ***
0.708 ***
0.448 ***
0.310 **
0.179 *
-0.395 ***0.412 ***
0.289 ***

1.199 ***
0.526 ***
0.282 ***
0.296 ***
0.071
-0.384 **-0.044-0.0450.238
0.053-0.2150.154
0.187-0.2300.031-0.203

1.214 ***
0.605 ***
0.558 ***
0.390 ***
0.314 ***
-0.1790.225 *
0.204 *

0.070
-0.108-0.498 ***-0.061-0.416 ***-0.539 ***-0.038-0.070-0.2100.018-0.055-0.459 ***0.062
0.275 ***

0.148 ***
0.288 ***

0.286
0.148

0.096
0.309 ***

-0.191 ***0.110 *
0.228 ***
0.097
0.386

-0.0640.019
0.059
0.612 ***
0.489

-0.2790.337 *
0.687 ***
0.528 ***
0.282

-0.331 ***0.160 **
0.205 **
0.129
0.398

0.874 ***
0.099
0.359
-0.030
0.074
0.708
0.388

1.170 ***
0.699
0.362
0.026
-1.159-0.637
0.493

0.294
0.160
0.796
1.355
0.372
0.739
0.288

0.633 ***
0.246
0.611 **
0.789 **
0.271
0.345
0.405

Constant
Age
Squared age
Occupation (ref: Elementary)
Senior officials, managers
0.641 *** 0.251
Professionals
0.483 *** 0.305 *Technicians, associate professionals0.258 *** -0.080
Clerks0.252 *** 0.126
Service and sales workers-0.035-0.032Skilled agricultural workers
0.330 *** -0.239
Craft and related trade workers
0.167 **
0.069
Plant and machine operators
0.113 *
0.154
Status and type of employment (ref: Standard employees)
Self-employed, Employers
0.158 *** 0.186 *Family workers-0.294 *** -0.054
Non-standard employees-0.347 *** -0.224 *Firm size (ref: small (-29))
Medium（ 30–299)
0.162 *** 0.208 **Large（300+) and public
0.361 *** 0.379 ***Education (ref: High school)
Middle high school or less-0.111 ** -0.124
Junior colledge-0.0030.221 **
Colledge or more
0.015
0.297 ***
Working hours (log)0.183 *** 0.255 ***R-Square
0.428
0.313
Interaction effects
Age effect (composed)
Medium firm × Age
Large firm × Age
Self-employed, employers × Age
Family workers × Age
Non-standard employees × Age
R-Square

0.873 ***
0.082
0.412 **
0.319
0.468
-0.418 **0.435

1.262 ***
-0.3410.386-0.4324.459-0.3260.317*p<.05 **p<.01 ***p<.001

9

Figure 1 Relative impact on income (men)Second, the effect of education is markedly strong in Korea. The effect of education
background remains great even after controlling for all work-related variables, exceeding the effectsof occupation and firm size and being comparable with the age effect. The effect of education
background is reasonably strong in Taiwan as well. The education effect is very weak in Japan
compared with the other countries. Age and work-related conditions such as occupation and firm size
being equal, income differentials based on the education level are markedly small in Japan comparedwith Korea and Taiwan.
Yet, the weakness of the education effect in Japan is at odds with the general perception ofJapanese society as an ‘education-oriented society’. Theoretically, however, one of the reasons forthis weak education effect in Japan may be that the independent effect of education backgroundmostly disappears after controlling for an individual’s work-related variables because one’s education
background almost completely determines whether one can get a high-paying job or not. In order totest this scenario, estimating the ‘total effect’ of the education level on income, including both of thedirect effect and the indirect effect mediated by an individual’s work, we use an OLS equation withall work-related variables removed.
We carried out a new estimation using a model only with age and education level (and work
hours), and constructed new aggregate variables in the same manner. As a result, the total effect ofeducation level (standardized coefficient) is 0.236, which is still considerably smaller than that of age(0.432) in Japan. The effects of education and age are 0.324 and 0.293 in Korea and 0.405 and 0.312
in Taiwan respectively, demonstrating that the education effect is stronger than the age effect in these10countries. It is possible to conclude that the effect of education is relatively small in Japan even if we
include its indirect effect via work-related factors. While it has been shown in the past that the degree
to which an individual’s education background determines his or her income or occupational status issmaller in Japan than in the US or Britain (Ishida, 2010), this analysis has produced a similar findingby comparison with Korea and Taiwan.
Let us analyze in more detail the effect of age, which is particularly strong in Japan. Basedon the results of extrapolation shown in Table 1, income increases as age increases but the rate ofincrease gradually becomes smaller with advancing age and income itself begins to decrease after
peaking at age 51. A similar inverted U-curve is found in Korea and Taiwan but it peaks several years
earlier at age 43 in Korea and age 45 in Taiwan, indicating that income continues to increase with age
over a longer period in Japan.
In order to see if the age effect varies according to firm size or employment type, we haveadded interaction terms between these variables and the age effect to the equation and shown theestimated coefficients of the newly added interaction terms and the main term for age effect and the
new model’s determination coefficient at the bottom of Table 1. The age effect in this model is anaggregation of the effects of the first-order and second-order terms for each country estimated in theprevious full model, as explained in the note 7 above. By analyzing the interaction effects between
the age variable thus constructed and firm size and employment type, we can determine whether the
age-based income change curve is particularly steep (i.e., greater age effect) or flat (smaller age
effect) for any firm sizes or employment types in each country.
The results of these interaction terms show that neither interaction term has a significant
effect in Korea and Taiwan whereas a significant positive interaction with large firm size and asignificant negative interaction with non-standard employment are found in Japan. In other words,
seniority-based wage increase is particularly strong at large corporations and particularly weak in
non-standard employment. Based on these results, it is considered that wage gaps between different
firm sizes or between standard and non-standard employees are mediated by the slope of theseniority-based wage curve in Japan.
Let us carry out a similar analysis with regard to women. Since we have already done a
detailed analysis of the results for men, we shall focus on differences in results between men andwomen here. Comparing Figure 1 and Figure 2 from this perspective, we notice first that the income
determination structure for women is very similar to that for men in Taiwan and mostly similar in
Korea. The graph shapes for men and women are almost identical in Taiwan except for the relative
strength of the age effect and the occupation effect, and they are generally similar also in Korea
except that the education effect is particularly prominent for women.

11Figure 2 Relative impact on income (women)

In contrast, the results for Japanese women are quite different from those for Japanese men.
In the case of Japanese women, employment type has the strongest effect on income and its effect isconsiderably greater than that of occupation. It is particularly notable that the age effect and the firm
size effect, which are found to be very strong for Japanese men, are very weak in the case of Japanesewomen. A possible interpretation for the overwhelmingly strong effect of employment type is thatwages tend to be suppressed regardless of the characteristics of work itself because part-time jobs
mainly held by married women in Japan are largely secondary employment to supplement householdincome. And the finding that the effects of age and firm size are weak in sharp contrast to the case ofJapanese men implies that the opportunity to enjoy the benefits of the seniority-based wage systemand the wage premiums for large company employees is mostly only accessible to men in practice. In
fact, the interaction terms in Table 1 show no significant interaction effects9 between large firm size
and age and between non-standard employment and age for women whereas they are significant in
the case of men. This demonstrates that women are not necessarily given additional benefits of theseniority-based wage system even if they work for large firms or they are standard employees. Thesefindings can be regarded as evidence showing that livelihood security provided by companies inJapan is heavily reliant on the ‘male breadwinner model’.
Finally, the effect of an individual’s education level is extremely weak among women as
well in Japan. The situation is the same when only age and education background (and work hours)
are included in the model. The effect of education is very small in Japan at 0.195 compared with
0.397 in Korea and 0.485 in Taiwan. Based on these findings, the relative weakness of the effect of

9They are not significant due to the large standard errors.
12education on income in Japan is a common trait for both men and women.
5.2 Impact on subjective social status
Table 2 shows the results of analysis of subjective social status. The model used for the analysis ismostly the same as the model used for income analysis except that logarithm of individual income
has been added and work hours have been removed.

Table 2 Regression analysis of a subjective social status
Men
Japan
Korea
Taiwanbbb-7.935 *** -5.373 *** -2.638 ***0.014 *** -0.014 *0.005
0.001 *** 0.001 **0.001 **

Constant
Age
Squared age
Occupation (ref: Elementary)
Senior officials, managers
0.440 *
0.234
Professionals
0.665 *** 0.186
Technicians, associate professionals0.452 ** -0.148
Clerks0.510 ** -0.077
Service and sales workers
0.218
0.134
Skilled agricultural workers
0.409-0.144
Craft and related trade workers
0.312-0.223
Plant and machine operators
0.172-0.130Status and type of employment (ref: Standard employees)
Self-employed, Employers
0.008-0.060
Family workers
0.524 *
0.827
Non-standard employees-0.284 *-0.310Firm size (ref: small (-29))
Medium（30–299)
0.114-0.127
Large（300+) and public
0.196 *
0.059
Education (ref: High school)
Middle high school or less-0.284 ** -0.143
Junior colledge-0.047-0.035
Colledge or more
0.264 **
0.819 ******
Income (log)0.834
0.595 ***R Square
0.191
0.213

Women
Japan
Korea
b
b
4.193 *** -0.992
0.010 ** -0.025 *-0.001
0.000

Taiwanb
0.790-0.010 *0.000

1.102 ***
1.100 ***
0.703 ***
0.657 **
0.542 **
0.159
0.513 **
0.390 *

0.751
0.329
0.248
0.163
-0.0910.518-0.171-0.052-1.1091.168 *
0.457
0.525
-0.001-0.1300.538
0.394

1.311 ***
1.172 ***
0.827 ***
0.743 ***
0.621 ***
0.188
0.367 *
0.437 *

0.040
0.211
-0.359 *

0.269
0.097
-0.0250.647 *
0.563
-0.217-0.0230.350 *
0.062

-0.112-0.149-0.015
0.025

0.392
0.142

-0.0270.087-0.203 *0.189
0.691 ***
0.534 ***
0.256

-0.353 *0.357 **
0.597 ***
0.089
0.071

-0.412-0.134-0.3370.348 ***
0.220

-0.257 *0.155
0.471 ***
0.285 ***
0.238

*p<.05 **p<.01 ***p<.001

Our analysis has found that the effects of the variables for men are again generally similar
between the three countries. Subjective social status is higher among white-collar workers thanblue-collar workers, the highly educated than the lowly educated, and standard employees thannon-standard employees in all three countries albeit with some variations in the significance orstrength of the effect. Of course, individual income also exerts a positive effect on subjective social
status in all three countries. With firm size, however, a significant positive effect is found amonglarge company employees in Japan alone. This means that subjective social status is significantly
13higher among large company employees than small company employees even after controlling for
current individual income and other factors in Japan. This is attributable to the fact that large
company employees have access to more benefits such as future wage increases and employment
stability.

Figure 3 Relative impact on subjective social status (men)
Next, our analysis of the relative impacts of the factors has found that income exerts anoverwhelmingly strong influence in all three countries (Figure 3). Among other factors, anindividual’s education background has a strong direct effect on his/her subjective social status evenafter controlling for work-related factors or individual income in Korea. It is possible to state that
education background has a considerably strong ‘symbolic effect’ on social status. In Taiwan, while
education background has a strong effect on subjective social status (albeit not as strong as in Korea),occupation has an equally strong effect.
By contrast, the direct effect of education level is considerably smaller in Japan comparedwith the other two countries, indicating that the level of education in itself does not exert a verystrong influence over one’s own social status judgment. Numbers show that the effects of firm sizeand employment status are strongest in Japan among the three but differences are not substantial.
Consequently, it is likely that once the mediated effect by income increase is included into
consideration, the total effects of work-related and personal factors on subjective social status closely
resemble their effects on income, and work-related factors such as occupation, firm size andemployment type have comparable effects in Japan.
For women, we found that although the effect of each variable is generally similar to thatfor men, non-standard employment and large firm size do not have significant impact, suggesting that
non-standard employment and large company employment do not influence women’s subjective
14

social status strongly after controlling for other variables (Table 2 above). The fact that these effects
are significant in the case of Japanese men but not so in the case of Japanese women is likely to bebecause women are not given full additional fringe benefits even if they are employed as standard
workers or by large companies as mentioned above.

Figure 4 Relative impact on subjective social status (women)
Comparison of the relative importance of the factors between men and women using Figure
3 and Figure 4 shows no marked difference in the graph shapes for Taiwan. The graph shapes are
relatively similar between men and women in Korea, too, except for a substantially weakerindependent effect for education and a substantially stronger independent effect for occupation in thecase of women. High education in itself does not appear to increase Korean women’s subjective
social status very much.
For Japanese women, it is notable that the effects of work-related factors are generally
smaller, with the individual income’s effect being particularly small, compared with the othersocieties. However, we must pay special attention to the fact that the coefficient of determination for
the regression model itself (0.071) is very small compared with the other societies, as shown in Table
2. It is assumed that a married woman’s subjective social status is influenced by her spouse’s work or
income more than her own work or income in Japan10. While we have conducted analysis of anindividual’s occupation, education background and income for the purpose of this paper, we will needto include these factors of the spouse in future studies.

10

It is also conceivable that a weak correlation between the wife’s work and the husband’s work ismaking the effects of the wife’s work and income appear smaller in Japan than in Korea and Taiwan.
In fact, the rate of concordance between the wife’s occupation and the husband’s occupation on the
ISCO major group level is 47.8% in Korea and 37.3% in Taiwan whereas it is very low in Japan at
28.2%.
15

6. Conclusion
Based on these analyses, it is possible to summarize the characteristics of the social stratification
structures of Japan, Korea and Taiwan as follows. First, Taiwanese society is influenced
predominantly by the effect of occupation and a large part of the spread of income and subjective
social status can be explained by an individual’s occupation. Taiwan is also characterized by anabsence of major differences between the determination structures for men and women.
While the effect of occupation is also strong in Korea, Korean society is characterized
above all by the strength of the effect of education background. In addition to being as important adeterminant of income as occupation, education background directly exerts a strong impact on
subjective social status, especially for men. High education in itself has the effect of increasing
Korean people’s subjective social status even after controlling for income and work-related factors.
In the case of Japanese men, the effect of age is notably strong. Besides the age effect,
occupation, employment type and firm size exert comparable effects in Japan due to the fact that theeffects of firm size and employment type are more prominent than in the other societies. In the caseof Japanese women, however, the effects of age and firm size on income are weak and the effects ofan individual’s work-related and personal factors on subjective social status are also generally small.
Although the three societies share relatively similar structural conditions such as patterns ofindustrialization, close analysis has found considerable differences in the relative impacts of thesefactors on income and subjective social status. It appears that these differences are well explained byeach society’s institutional conditions, especially the prevalence of Japanese personnel management
practices such as the seniority-based wage and promotion systems and long-term stable employment
and/or accessibility to their benefits. For instance, the seniority-based wage and promotion systems
and the practice of long-term employment are strong in Japan but non-standard workers who are notrecognized as the core members of company organizations are not entitled to benefit from them inmany cases. And since the ability to provide these ‘privilege-type’ benefits depends largely on eachcompany’s financial resources, large company employees have greater access to them. Moreover, due
to the dependence of many companies on the ‘male breadwinner model’, these benefits are mainly
given to men only and additional benefits for large company employees and standard employees (asagainst non-standard employees) are not necessarily available to women. It is considered that becauseof the strength of this organizational mechanism in remuneration determination, variables such as
firm size, employment type and gender have far greater impacts on social stratification in Japan thanin the other societies. In sum, the selection of the beneficiary of the Japanese employment practices isstrongly related to substantial inequalities in Japanese society.
In Taiwan where the labor market is far more fluid and these Japanese employment
practices are less prevalent, this organizational mechanism in remuneration determination is weak,hence the market mechanism manifests more clearly and the effect of occupation, which reflects theextent of technical skills and abilities that are valued in the labor market, becomes relatively strong.
16The situation in Korea, where mainly large corporations have adopted ‘Japanese employment
practices’, is closer to that in Japan than Taiwan but the marked strength of the effect of education
background compared with the other societies signifies its unique contexts. Thus the factors
generating gaps in remuneration and social status and their relative importance vary largely between
Japan, Korea and Taiwan, reflecting differences in their social backgrounds. It is possible to argue
that these characteristics have become evident only when the three East Asian countries werecompared.
Finally, we shall discuss the implications of the analysis in this paper. First, thecharacteristics of stratification structure of Japanese society are likely to be influencing theperception of social inequality in Japan. It is possible to state that Japan’s stratification structure ishighly multidimensional in the sense that large remuneration gaps are generated by factors that are
independent of the level of education or the type of occupation (i.e., firm size and employment type).
The multidimensional nature of social stratification is more prone to obscure the focus of social
inequality compared with a society with one-dimensional stratification. Moreover, the strong ‘age’
effect in Japanese society may also have helped deflect people’s attention from social inequalities
that are generated by structural factors. These background conditions and changes in them may serve
as factors that can better explain the previous high levels of ‘middle-class consciousness’ and therecent sudden rise in the perception of social inequalities in Japanese society.
Second, the fact that institutional factors strongly affect social inequalities suggests that
institutional reforms, especially those concerning the livelihood security system provided bycompanies as well as social security system, are also necessary in order to solve the inequality
problem in Japan. We shall continue to examine these issues in the future.
Acknowledgement
I would like to acknowledge all those who gave helpful comments to the previous version of thispaper. I would like to extend my gratitude to Prof. Satoshi Miwa for his methodological advice.
This research was supported by Grant-in-Aid for Scientific Research (A) (number 20243029) and (B)(numbers 24330148 and 16H03688) and from the Japan Society for the Promotion of Science (JSPS). I thankthe 2015 SSM Survey Management Committee for allowing me to use the SSM data.

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