Disparity Society Theory and Social Stratification Theory:
An Attempt to Respond to Challenges by Disparity Society Theory *Yoshimichi Sato
(Tohoku University)
Abstract
This paper explores the empirical validity of two important issues recently highlighted bydisparity society theory in Japan. The first is income disparity and disparity between regular andnon-regular workers. It is clear that social stratification theory has not yet analyzed these issues
seriously. It has studied occupations rather than income; it has implicitly assumed that workers
have regular jobs. The second issue is recent cross-strata increases in disparity. This paper
studies the effect of employment status – regular employment versus non-regular employment –on income by analyzing data produced by Japan’s Social Stratification and Social Mobility
Surveys. A regression analysis is applied to the data, with logarithmic income as the dependent
variable, and occupation and employment status as independent variables. The result shows t hat
employment status has stronger explanatory power than that of occupation, as argued bydiscrepancy society theory. To check the empirical validity of the claim that cross -strata
disparity is on the increase, this paper compares partial regression coefficients of two regression
models using the survey data from 1995 and 2005. The result of the comparison shows that thecoefficient of regular employment had become smaller from 1995 to 2005. This means that
income disparity between Japanese regular and non-regular workers had shrunken over the
decade. It would be risky to argue that income disparity is on the decline based only on thisresult. A fruitful dialog between disparity society theory and social stratification theory isneeded to better comprehend income disparity.
Keywords and phrases: Income disparity, employment status, growing disparity

1

Challenges against Social Stratification Theory by Disparity Society
TheoryIn recent years, a large number of books and papers on the widening disparities in society
have attracted much public attention. But for a few exceptions including Sato (2000) andKariya (2001), researchers specializing in social stratification theory and social mobility
analysis have not very often debated social disparities. For these researchers, theexistence of disparities in society is so self-evident that it is difficult to understand why*

This paper was originally published in Political Economy Quarterly, vol. 44, no. 1 in Japanese. It isreprinted in English with permission from the Japan Society of Political Economy. Academic support
from the Center for the Study of Social Stratification and Inequality at Tohoku University isgratefully appreciated.
44

disparity society theory attracts so much attention from the general public. However,arguments by disparity society theory do deserve interest. In this paper, I take thesearguments as challenges to conventional social stratification theory and social mobility
analysis and attempt to respond to some of the hotly debated issues.

2Social Stratification Theory and Social Mobility Analysis

The crux of social stratification theory and social mobility analysis highlights majordifferences between them and disparity society theory. Social stratification theory
assumes that socially desirable resources are distributed unequally among several socia lgroups. Put succinctly, the fundamental questions in social stratification theory consistof: a descriptive question of ‘how unequal the distribution is’; and an explanatory
question of ‘why such inequality exists’. While economists assume that money is themain desirable resource and tend to focus on the Gini coefficient and other tools tomeasure income inequality, specialists in social stratification study use such concepts as
occupational strata and educational strata, and focus more on occupation and education
than on income. Although occupation is a means to make income, there are desirability
ratings of occupations themselves. In social stratification theory, the desirability ofoccupations is expressed using the concept of occupational prestige. The theory also
assumes that each person attempts to get a job with higher prestige. The index formeasuring occupational prestige is calculated based on social surveys. Specifically,various occupations (such as president of a large company, carpenter, or k indergarten
teacher) are presented to respondents, who are requested to state their evaluations ofthese occupations (very high, fairly high, moderate, fairly low, or very low). These
answers are quantified and aggregated to calculate the index of occupational prestige.
Needless to say, there are a large number of different occupations in the world.
This has prompted the construction of occupational classification that categorizes
occupations according to occupational prestige, lifestyle, and so on. An exa mple ofoften-used categorization is the one that classifies the population into eight groups:
professional (physicians, teachers, musicians, etc.); managerial (members of the national
assembly, company presidents, postmasters, etc.); clerical (general/pla nning clerks,
reception/desk clerks, accounting clerks, etc.); sales (shopkeepers, restaurant managers,
shop assistants, etc.); skilled (automobile assemblers/mechanics, cooks, shipbuilders,etc.); semi-skilled (train drivers/locomotive engineers, conductors, metal welders, etc.);
45

unskilled(roadworkers,

freight

workers,

cleaners,etc.);

andfarming(agricultural/silk-raising farmers, forestry workers, fishery workers, etc.) (Tominaga1979). Certainly, this is not the only way to stratify society. Other st ratification theories
can include the schema with two major classes – the working class and the capitalistclass – proposed by the classical Marxist class theory, and Wright’s (1978) schema thatincorporates white-collar workers as an intermediary position in the Marxist’s schema.
Why, then, are socially desirable resources distributed unequally? A Marxist
response to this question focuses on the relationship between the classes. The basic idea
is that the ruling class exploits the ruled class, and this exploitation results in the unequal
distribution of wealth. Meanwhile, Becker’s (1993) human capital theory, one of thetheories of modern economics, maintains that difference in wages between two workers
results from their contrasting differences in human capital, including education and work
experience. Differences in human capital result in differences in productivity, which inturn result in differences in wages. In addition, in Doeringer and Piore’s (1971) internal
labor market analysis and Odaka’s (1984) dual labor market theory, even in the same
occupation whether a worker is at the core or in the periphery of the labor market would
make differences in wages, fringe benefits, and job security. Within sociology, social
stratification theory uses these ideas in analysis of social stratification and social
mobility but differs from these theories in its attempts to answer the following questions
from the viewpoint of intergenerational mobility: ‘Why do some people enter theworking class while others enter the capitalist class?’, ‘Why do some people go on to
university while others do not?’, and ‘Why can some people enter the internal labormarket while others cannot?’.
Intergenerational mobility references stratum mobility across generations. For
instance, in terms of the aforementioned eight occupational categories if a teacher’s childbecomes a company president, this would mean a shift from the professional to the
managerial stratum. If the child becomes an automobile assembler, this would mean ashift from the professional to the skilled stratum. The child may of course enter the
professional stratum. He/she may enter the professional stratum not just as a teacher but
also as a lawyer or photographer. In legal terms, freedom of choice in employment isguaranteed to all. This is, however, a guarantee only in the eye of the law. In reality,
disparities of opportunity exist in intergenerational mobility. Put simply, a child is more
likely to enter the same stratum as his/her parent(s) than any other stratum. In past, mostof these cases were attributable to family business succession which occurred directly
46

from parents to their children. However, with increasing numbers of workers having
become employees and the self-employed sector having reduced in size, the effect ofeducation has become more powerful. In other words, under the current status attainment
process, any given parents’ social stratum affects their children’s stratum througheducation.
Modernization theory, on the other hand, argues that as society becomesmodernized, people should come to obtain employment based not on their origin but on
their performance. This is because if a company selects its employees based on theirparents’ social stratum, not all of them would be of superior quality, resulting in reduced
competitiveness of the company. Even a person from a low stratum should be able toenter a higher stratum if he/she can attain advanced education by his/her own talent andeffort. One of the major objectives of social mobility analysis is to empirically verify this
meritocratic argument. Contrary results, however, have been found in international
comparisons and time-series analyses of intergenerational mobility conducted by anumber of researchers. Observation of the mobility patterns (pure mobility) has beenobtained after controlling for the effect of industrial and occupational structures andchanges to them. This has revealed no difference in the level of pure mobility among
societies that have achieved a certain level of industrialization. For sociologicalmodernization theory, higher levels of pure mobility should be found in more
modernized societies. Yet empirical evidence shows this is not the case. One possible
reason for this is the disparities in educational attainment among different social strata.
Hara and Seiyama (1999) calculated high school advancement rates and university
advancement rates by stratum of origin and showed that, while the disparities in highschool advancement rates were rapidly reduced, the disparities in university advancement
rates by stratum were not reduced. Thus, different stratum origins are associated withdifferent levels of educational attainment which, in turn, would affect occupational
attainment.
Social stratification theory and social mobility analysis have therefore focused
mainly on a person’s stratum or class, based on his/her current occupation, and haveinvestigated the level of association between his/her own stratum/class and his/herparent’s stratum/class. These researchers have analyzed the process of his/her entry to
his/her own stratum/class on the basis of quantified empirical data. This research strategy
has several limitations, which seem to have been the focus of attention of disparity
society theory. The following section will provide a detailed analysis of this point.
47

3

Two Challenges by Disparity Society Theory

While disparity society theory has a number of variations, it has challenged theabove-described social stratification theory and social mobility analysis in two common
respects. First, disparity society theory has pointed out the significance of income
disparity. Second, it has focused on disparities between regular and non-regular
employment. Other significant points raised by disparity society theory include age
disparities, regional disparities, and increasing non-regular employment. However, age
disparities are related to the disparity between regular and non-regular employment.
Similarly, from the viewpoint of social stratification theory, regional disparities areabsorbed into other factors determining inequality. Furthermore,, increasing non-regular
employment would pose no problem to society if workers in non-regular employment
were given equal treatment to those in regular employment. It would be a social problem
only if significant disparities in wages, fringe benefits, etc. existed between regular andnon-regular employees.
In this regard, social stratification theory, particularly social mobility analysis,
has sought to elucidate the processes through which a person moves from his/her parent’s
stratum to his/her own stratum (particularly occupational stratum). This is true in both
status attainment process model and mobility-table analysis. Where income issues havefallen under the jurisdiction of economists, social stratification theory has never focusedon them, with a very few exceptions such as Kanomata (2001). Researchers studying
social stratification have seldom participated in arguments about the increasing Gini
coefficient. In other words, social stratification theory has not responded properly to thefirst challenge by disparity society theory. What about the second challenge by disparity
society theory? Social stratification theory and social mobility analysis have focused
mainly on social stratum and social class. They have used social stratum or social classas an analytical concept when discussing stratum structure or class structure or whenanalyzing intergenerational or intra-generational mobility. These analyses have implicitly
assumed that all workers are in regular employment. The National Survey of Social
Stratification and Social Mobility (henceforth, SSM Survey) has been conducted every
ten years since 1955. In it, the above assumption was not misguided until 1975, as thesurvey subjects were men only. However, after the survey subjects were expanded toinclude women beginning 1985, it became necessary to take workers in non-regular48

employment into consideration. Even so, researchers only took up issues related tofemale workers in non-regular employment and paid scant attention to the existence ofmale workers in non-regular employment. From young part-timers to middle-aged malepart-timers, issues related to male workers in non-regular employment should no longer
be ignored. As shown in Figure 1, the proportion of casual/daily employment has
increased in both men and women since around 1995.

25

Women

20

15
%

Total

10
Men

5

0
1985

1990
Figure 1

1995
2000
Proportion of Casual/Daily Workers

2005

Source: Labor Force Survey

The conventional stratum/class schema fails to address the disparities between
regular and non-regular employment properly because social stratification studies often
conduct analyses using occupational strata. For instance, using the above-described eightoccupational strata (which are known as the SSM Classification), these studies analyze
the distribution of people across, or the intergenerational or intra-generational mobility
across, these strata. Such analyses are based on an assumption that people in the same
occupational stratum have similar life chances, similar values, and similar consciousness.
They also assume that different strata are associated with different ranks of prestige andincome. On the other hand, class studies, as mentioned above, use the two major classes(capitalists and workers) which are distinguished by the ownership of the means of49

production (as is the case with the classical Marxist view) or, alternatively, classes thatcategorize people based on control and autonomy at the site of production (Wright, 1978).
In these studies, class is defined based on the relations between social groups in one way
or another. These stratum/class schemas are not capable of properly detecting differences
between workers in regular employment and those in non-regular employment. For
instance, part-time university teachers and full-time lawyers, both of whom are in thesame professional stratum, would have significantly different life chances due to thesignificant difference in income. Similarly, in the unskilled stratum, unskilled workers
getting jobs through contractors and those in regular employment would be in a sort of‘class conflict’ situation because the former workers’ low wages secure the latter’s highwages.
Thus, it would be necessary to treat the employment status of regular or
non-regular employment in the same manner as stratum/class is treated as a factor
generating inequality (in income, etc.). From the eyes of social stratification theorists,
this is what is argued by disparity society theory in its challenge to social stratification
theory. Certainly, it is logically possible to incorporate employment status into thestratum schema as an additional dimension in the strata, by considering it as a factor
generating differences in income or prestige. However, conventional social stratification
theory has not practically done so, because it has implicitly assumed that all workers are
in regular employment. Therefore, apart from whether the stratum schema should be
expanded to include employment status, we must attach employment status the same
importance as we have done to occupation.
This paper conducts two analyses of income in response to the two challenges by
disparity society theory described above. The first analysis compares the degrees towhich stratum and employment status defines income when both are included in themodel simultaneously. The second analysis investigates whether or not the disparities inincome so defined are widening, based on the argument presented by disparity society
theory that the disparities are widening.

4

Data

The data used are from the SSM Surveys conducted in 1995 and 20051. The subjects ofthese surveys were men and women, aged between 20 and 69 and living in all parts of1

Use of the data has been approved by the 2005 SSM Research Committee.
50Japan. These surveys inquired in detail about the subjects’ occupation and occupational
history. The 1995 survey used two types of questionnaire, A and B. For bothquestionnaires, the planned sample size was 2016 persons for each sex. Data werecollected from 1248 men and 1405 women for Questionnaire A and from 1242 men and1462 women for Questionnaire B. The response rates were 61.9%, 69.7%, 61.9% and72.5%, respectively, after invalid cases were excluded. In the 2005 survey, the planned
sample size was 14140 and 5746 cases were collected. The response rate calculated after
excluding invalid cases was 44.1% 2.
The aforementioned SSM Classification was applied to the categorization ofoccupations. In the actual survey, respondents were requested to answer open questions
about their occupations. After the answers were collected, occupational codes (a slightly
less than 200 codes) were assigned to the unrestricted answers. The SSM Classifications
were created by compiling these codes from the professional to the farming categories, as
described above.
In the SSM Surveys, annual income was inquired into not in actual amount but
in brackets (for example, ‘between 4 million or more and under 4.5 million yen’). In thispaper, the middle value of each bracket (in the above example, 4.25 million yen) is used
as a proxy for actual amount. For comparison purposes between 1995 and 2005, income
was adjusted for consumer price level changes, with 1995 treated as the reference year.

5

Does Class Count?

Erik Olin Wright, a leading authority on class analysis, published a book titled ClassCounts (1997). This book suggests that class is a very powerful variable to exp lainvarious social phenomena. A similar argument has been presented in Japan by Kenji
Hashimoto (2001). Most researchers specialising in stratification/class studies, including
Wright and Hashimoto, assume that stratification/class is an important explanatory factor.
These researchers use stratum/class to explain stratum/class identification and party
support or use parental stratum/class to explain children’s educational attainment.
How well can stratification/class explain income? An analysis of income using
data from the 2005 SSM Survey will address this question. As a preliminary analysis,
income levels are stratified into quartiles, and the proportions of subjects in the highest
quartile (the highest income group) between the professional and the skilled strata under2

The data from the 2005 SSM Survey are based on the third version (distributed on July 12, 2007).
51

the SSM Classification are compared on the bases of regular employment andnon-regular employment (Figure 2). As shown in Figure 2, the proportion of subjects in
the highest quartile is higher in the professional than the skilled stratum for both regularand non-regular employment. However, the difference in the proportion of these subjects
is much larger between regular and non-regular employment in the same occupational
stratum than between the professional and the skilled strata. This figure demonstrates
that income is more strongly determined by employment status than stratification/class 3.

70
60
50
40
%
30
20
10
0
Professional
Figure 2

Non-regular employment
Regular employment
Skilled

Proportion of Persons in the Highest Quartile
by Occupation and by Employment Status

Source: The 2005 SSM Survey in Japan Data

In order to make a more precise analysis of this phenomenon, a multiple
regression analysis was conducted, where the dependent variable was income(logarithmic income) and the independent variables were current occupation in terms ofoccupational stratification (with sales serving as the reference category under the SSM
Classification), employment status (with non-regular employment serving as thereference category), sex, and age. The regression formula was:ln(y) = b0 + b1 female + b2 age + b3 employer + b4 regular employment+ b5 self-employed + b6 professional + b7 managerial + b8 clerical + b9 skilled
3

It would be a more precise analysis to use wage rather than income in order to study t hediscrepancies between regular and non-regular employment. However, wage per hour, week, ormonth is difficult to measure in the SSM project. Thus we use income instead of wage.
52

+ b10 semi-skilled + b11 unskilled + b12 farming + e(1)where y is income and ln(y) is its natural logarithm. Terms b0 through b12 are partial
regression coefficients (PRCs) and e is an error term. Female is a dummy variable (male= 0, female = 1). If b1 is a positive number, women’s income would be exp(b1 ) times asmuch as men’s 4 (exp represents the base of natural logarithm). If b1 is a negative number,men’s income would be 1/exp(b1 ) times as much as women’s. Age is actual age in years.
Therefore, if b2 is a positive number, older people would have higher income.
Employment status is a dummy variable with non-employment serving as the reference
category. Therefore, if b4 is a positive number, regular employees’ income would be
exp(b4) times as much as non-regular employees’. Occupation is a dummy variable withsales serving as the reference category. If, for instance, b6 is a positive number,professional workers’ income would be exp(b6) times as much as sales workers’. If b6 is anegative number, sales workers’ income would be 1/exp(b6 ) times as much asprofessional workers’.
Results of the analysis are summarized in Table 1. If we look at the results for
employment status, we see that the PRC for regular employees is 0.755. This isstatistically significant at 1% level 5. This means that, when the other variables arecontrolled for, regular employees’ income would be 2.13 (= exp(0.755)) times as much as
non-regular employees’.

4

Suppose y 1 and y 2 represent women’s and men’s income, respectively. If the values of all othervariables are equal, the following calculation holds:ln(y 1) – ln(y 2) = b1
ln (y 1/ y 2) = b1
y 1/ y 2 = exp(b1)y 1 = exp (b1) y 2
If b1 is a positive number, exp(b1) would be larger than unity. In this case, women’s income
would be exp(b1) times as much as men’s, as shown in the above formula. If b1 is a negative number,exp(b1) would be smaller than unity. The above formula can be converted into y 2 = y 1/exp(b1). Thismeans that men’s income would be 1/exp(b1) times as much as women’s (where 1/exp(b1) is larger
than unity).
5
In all social surveys, including the SSM Surveys, data are of sampled subjects and not of all
members of the society. It is thus necessary to verify whether an analysis based on sampled dataapplies to the society at large. This verification is known as statistical testing. In the present testing, it
is tested that the PRC is not zero for the general population (Japanese society at large) either. Being‘statistically significant at 1% level’ means that the hypothesis that ‘the PRC for the population iszero’ is rejected with a probability of 99%. Therefore, an independent variable with the statisticallysignificant PRC would affect income in the general population as well.
53

Table 1 Results of a Multiple Regression Analysis with Logarithmic Income
as the Dependent Variable(Source: The 2005 SSM Survey in Japan Data)
Age
0.007 **
Female-0.776 **Employment status (reference: non-regular employment)
Employer
0.830 **
Regular employment
0.755 **
Self-employed
0.310 **
Occupational strata (reference: sales)
Professional
0.417 **
Managerial
0.452 **
Clerical
0.198 **
Skilled-0.046
Semi-skilled-0.114 **Unskilled-0.155 **Farming-0.058Constant
5.028 **
2
0.520
Adjusted RN3417

As for the effects of current occupation when sales serves as the reference
category, the PRCs for professional, managerial, and clerical are positive and are
significant at 1% level. On the other hand, the PRCs for skilled, semi-skilled, unskilled,
and farming are negative, with those for semi-skilled and unskilled being significant at
1% level. These results indicate that income disparities exist between white-collar
occupations (professional, managerial, and clerical) and blue-collar occupations and that,in terms of income level, sales is similar to skilled and farming.
Let us go back to the first opening question and examine whether income is morestrongly affected by stratum (in terms of SSM Classification for the purpose of ouranalysis here) or employment status (non-regular employment vs. regular employment).
The PRCs for different occupational strata vary from -0.155 (unskilled) to 0.452(managerial), with difference lying between the minimum and maximum values at 0.607.
On the other hand, the difference between the PRCs for non-regular employment andregular employment statuses is 0.755, as shown above. These results show that income
level is affected more by employment status than by current occupation. From theseresults, it would be fair to say that disparity society theory is correct in its assertion that a
disparity exists between regular employment and non-regular employment. Conventionalsocial stratification theory and social mobility analysis use occupation-based concepts ofstratum or class. As a determinant of income, however, employment status is more54

powerful than these concepts. Researchers specializing in these conventional theories
should be willing to reflect on their failure to recognize the significance of employment
status.
Disparity society theory has made another point that disparities have widened inrecent years. Typical researchers making this point include Tachibanaki (1998), whodemonstrated an increase in the Gini coefficient, and Sato (2000), who showed anincrease in the closure of the upper white-collar stratum. The next section examines theempirical validity of the argument that disparities are widening.

6

Have Disparities Widened?

To begin from the conclusion, we cannot say that the disparities have widened as long as
based on the 1995 and 2005 SSM Survey data. A provisional calculation by Hiroshi
Ishida and Satoshi Miwa, members of the SSM research project, demonstrated there wasno change from 1995 to 2005 in intergenerational mobility between parent and childgenerations in terms of relative mobility or pure mobility (i.e. intergenerational mobility
after controlling for industrial and occupational structures). The decade in question saw
various social changes, including the collapse of lifetime employment, the introductionof merit systems, and an increase of non-regular employment. However, the relative
mobility pattern shows no change in the association between parents’ and children’s
occupations. According to the same provisional calculation, the odds ratio for the upper
white-collar employees discussed by Sato (2000) in his book Fubyōdō shakai Nippon(Unequal society Japan) decreased from 1995 to 2005, although the decrease was notstatistically significant 6.
The odds ratio for a certain stratum is an indicator showing how more likely
people from that stratum will enter the same stratum than will those from other strata.
The higher the value, the less likely those from other strata will enter that particular
stratum. Suppose, for example, a given society consists of two strata: the upper
white-collar employee (UWCE) stratum and the stratum of all others. Let us also supposethat a table of intergenerational mobility, as shown in Table 2, was obtained from asurvey. In the society represented by the table, the forty persons from the UWCE stratum
all enter the same stratum, whereas none of the eighty persons from the other stratum can
6

The wording ‘not statistically significant’ as used in this context means that the hypothesis that ‘theodds ratio for 1995 and that for 2005 are not the same’ is rejected.
55

enter the UWCE stratum. This is a hypothetical status society. The possibility of persons
from the UWCE stratum entering the same stratum is expressed by odds of (the numberof persons from the UWCE stratum who enter the same stratum) / (the number of persons
from the UWCE stratum who enter the other stratum). In this case, the odds are 40/0, or
infinity. On the other hand, the possibility of those from the other stratum entering the
UWCE stratum is expressed by odds of (the number of persons from the other stratum
who enter the UWCE stratum) / (the number of persons from the other stratum who enter
the same stratum). In Table 2, the odds are 0/80, or zero. The odds ratio for the UWCE
stratum is the ratio of these two odds, which is ∞/0, or infinity.
Table 2

Hypothetical Status SocietyChildren’s strata
Upper white-collar

Stratum of all others

employee stratum
Upper white-collar
Parents’ strata

40

0

0

80

employee stratum
Stratum of all others

Let us then consider a hypothetical society where anyone may be able to enterthe UWCE stratum regardless of the stratum of his/her origin (Table 3). In this case, theprobability of a person (whether he/she is from the UWCE stratum or from the other)entering the UWCE stratum would be 0.25 (10/40 for those from the UWCE stratum and20/80 for those from the other stratum). In this society, the odds ratio for the UWCE
stratum would be (10/30)/(20/60), i.e. 1.
Table 3

Hypothetical Equal Opportunity SocietyChildren’s strata
Upper white-collar

Stratum of all others

employee stratum
Upper white-collar
Parents’ strata

10

30

20

60

employee stratum
Stratum of all others

56Thus, the odds ratio varies from one (complete equality of opportunity) toinfinity (complete inequality of opportunity). Needless to say, in the real world the levelof equality of opportunity is somewhere between complete equality and complete
inequality and thus the odds ratio would be somewhere between one and infinity.
Using data from the SSM Surveys conducted between 1955 and 1995, Sato
(2000) formulated tables of intergenerational mobility between fathers’ occupations andchildren’s occupations at the age of forty by year of birth. Year of birth was stratified into
five periods: 1896-1915 (i.e. aged 40-59 years at the 1955 survey), 1906-1925 (i.e. aged
40-59 years at the 1965 survey), 1916-1935 (i.e. aged 40-59 years at the 1975 survey),
1926-1945 (i.e. aged 40-59 years at the 1985 survey), and 1936-1955 (i.e. aged 40-59
years at the 1995 survey). In the manner described above, the odds ratio for the UWCE
stratum was calculated for each birth cohort based on the intergenerational mobility table.
The results showed that the odds ratio decreased between the generations born in the
periods 1896-1915 and 1926-1945, whereas it increased between the generations born inthe periods 1926-1945 and 1936-1955. This implies an increased exclusivity of the
UWCE stratum, or that it became harder for those from the other strata to enter the
UWCE stratum. However, according to a provisional calculation by Ishida and Miwa,
who made the same analysis as Sato after adding the 2005 SSM Survey data (thegeneration born in 1946-1965), there has been no change in the level of exclusivity of the
UWCE stratum. Why there has been no change is a question for future study, but at leastin terms of intergenerational mobility, the inequality of opportunity has not become
greater.
Next, let us look at the change in the distribution of income. Table 4 shows acomparison of the quintiles of income between 1995 and 2005. The quotient obtained by
dividing the fourth quintile by the first quintile is 14.3 and 13.3 for 1995 and 2005,
respectively, showing a reduction during this decade. The Gini coefficient is 0.448 and
0.437 for 1995 and 2005, respectively, also showing a reduction during the decade(although this change is not statistically significant) 7.

7

The wording ‘not statistically significant’ as used in this context means that the hypothesis that ‘theGini coefficient for 1995 and that for 2005 are not the same’ is rejected.
57

Table 4 Quintiles of Income(Source: The 1995 and 2005 SSM Survey data)
1995
2005
1st quintile
100
111.7
2nd quintile
300
223.4
3rd quintile
400
372.3
4th quintile
600
595.7

Moderately reduced income disparities have also been shown by anotheranalysis, which is a modified version of the multiple regression analysis used in thepreceding section. If, as argued by disparity society theory, the disparities have been
widening, the income disparities between different employment statuses and among
different occupational strata would have increased during the period between 1995 and2005. In a multiple regression analysis, this can be expressed as follows. In theemployment status, the PRC for regular employment would be greater. As shown in
Formula 1, the PRC for regular employment, b4 , indicates that regular employees’
income would be exp(b4) times as much as non-regular employees’. Therefore, the larger
this PRC, the greater the difference in income between non-regular and regular
employment. Similarly, as for the occupational strata, the PRCs for professional,
managerial and clerical strata would be greater. On the other hand, the PRCs for skilled,semi-skilled, unskilled and farming strata were negative in 1995. If the income
disparities among occupational strata have widened, the negative values would be greater(in terms of absolute value), because a greater negative PRC would mean lower income
compared to the sales stratum.
In order to verify these predictions, a multiple regression analysis was conductedin the same manner as described above, using the 1995 SSM Survey data. When
comparing the results of this analysis with those of the analysis of the 2005 SSM Survey
data, the 1995 results show the same pattern as the 2005 survey. Income was higher for
regular than non-regular employment and higher for professional, managerial, andclerical and lower for semi-skilled, unskilled, and farming, than sales.

58

Table 5 Results of a Multiple Regression Analysis with Logarithmic Income
as the Dependent Variable(Source: The 1995 and 2005 SSM Survey data)
1995
2005
**
Age
0.008
0.007 ****
Female-0.894-0.776 **Employment status (reference: non-regular employment)
Employer
1.048 **
0.830 **
Regular employment
0.840 **
0.755 **
Self-employed0.614 **
0.310 **
Occupational strata (reference: sales)
Professional
0.344 **
0.417 ****
Managerial
0.492
0.452 **
Clerical
0.193 **
0.198 **
Skilled-0.046-0.046**
Semi-skilled-0.110-0.114 **Unskilled-0.283 **-0.155 ****Farming-0.423-0.058**Constant
4.935
5.028 **
2
0.556
0.520
Adjusted R
N
3507
3417

However, an interesting trend is found when we compare the results for 1995
with those for 2005. For all employment statuses—employer, regular employment, andself-employed—the PRCs decreased from 1995 to 2005. This indicates a reduction in the
disparities between these employment statuses and non-regular employment. Particularlyinteresting is the reduction in the disparity between regular and non-regular employment.
As for the occupational strata, the PRC for professional workers increased, while thosefor unskilled and farming, which are negative, decreased in terms of absolute value. Thismeans that while the income disparity between sales and professional widened, thatbetween sales, on one hand, and unskilled and farming, on the other, reduced.
These findings indicate that income disparities decreased on the whole from1995 to 2005. In order to analyze these findings more precisely, a multiple regression
analysis was conducted in which the PRCs for 1995 (as shown in Table 5) are fixed andwhich included terms representing the interaction between each explanatory variable andyear of survey (1995 = 0, 2005 = 1). The sign of the PRC of an interaction term would
indicate whether the disparity widened or reduced. For instance, if the PRC of the term
representing the interaction between regular employment and year of survey is 0.1 andsignificant, this indicates that the income disparity between non-regular and regular
employment increased by 0.1 from 1995 to 2005. Conversely, if the coefficient is -0.1
59

and significant, this means that the income disparity reduced by 0.1 8.
Therefore, if the disparities have truly widened, the PRCs for the terms
representing the interaction between the employment statuses of employer, regular
employment, and self-employed, on one hand, and year of survey, on the other, should bepositive and significant. As for the occupational strata, the PRCs for the terms
representing the interaction between professional, managerial, and clerical, on one hand,
and year of survey, on the other, should be positive and significant, whereas those for theterms representing the interaction between skilled, semi-skilled, unskilled, and farming,on one hand, and year of survey, on the other, should be negative and significant. Resultsof this regression analysis are shown in Table 6. They are considerably different from thepredictions described above. With respect to employment status, the PRCs for the terms
representing the interaction between employer, regular employment, and self-employed,on one hand, and year of survey, on the other, are all negative and significant. This
indicates a reduction in the disparities between the statuses of employer, regular
employment, and self-employed, on one hand, and that of non-regular employment, on
the other. As for the occupational strata, the PRC for the term representing the interaction
between professional and year of survey is positive and significant, which is consistent
with the above prediction. However, the PRCs for the terms representing the interaction
between unskilled and farming, on one hand, and year of survey, on the other are also
positive and significant. This indicates a reduction in the disparities between theseoccupations and sales. The PRCs for the terms representing the interaction between theoccupations other than professional, unskilled, and farming, on one hand, and year of
survey, on the other, are not significant. The PRC for the term representing theinteraction between female dummy and year of survey is positive and significant, whichindicates a reduction in the disparity between men and women.

8

To put it more precisely, a significant PRC of 0.1 for the term representing the interaction between
regular employment and year of survey would mean the following: since the PRC for regular
employment in 1995 is 0.840, which means that regular employees’ income was exp(0.840) times (i.e.
2.32 times) as much as non-regular employees’ in 1995, the level of disparity for 2005 would be
exp(0.840 + 0.1), or 2.56 times in favor of regular employees. A PRC of -0.1 for the same term as
above would mean that the disparity reduced to exp(0.840-0.1), or 2.10 times in favor of regular
employees.
60Table 6 Results of a Multiple Regression Analysis with the Partial Regression
Coefficients Fixed for 1995 and Logarithmic Income as the Dependent Variable(Source: The 1995 and 2005 SSM Survey data)
Age
0.008 **
Female-0.894 **Employment status (reference: non-regular employment)
Employer
1.048 **
Regular employment
0.840 **
Self-employed0.614 **
Occupational strata (reference: sales)
Professional
0.344 **
Managerial
0.492 **
Clerical
0.193 **
Skilled-0.046
Semi-skilled-0.110 **Unskilled-0.283 **Farming-0.423 **Age x year of survey-0.001
Female x year of survey
0.132 **
Employer x year of survey-0.203 **Regular employment x year of survey-0.063 *Self-employed x year of survey-0.289 **Professional x year of survey
0.094 *
Managerial x year of survey-0.026
Clerical x year of survey
0.027
Skilled x year of survey
0.023
Semi-skilled x year of survey
0.018
Unskilled x year of survey
0.148 **
Farming x year of survey
0.377 **
Constant
4.938 **
N
6924

Figure 3 presents these results in a more readily understandable manner. The
vertical axis represents PRC values. The results have been adjusted so that the results forthe reference categories used in the multiple regression analysis (male, non-regular
employment, and sales) are shown at level zero. The horizontal axis represents years
1995 and 2005. For coefficients larger than zero (the reference level), a sloped line
falling from left to right and that rising from left to right indicate a reduction andwidening, respectively, of the disparity. For coefficients smaller than zero, a sloped line
rising from left to right and that falling from left to right indicate a reduction andwidening, respectively, of the disparity. It is obvious that the income disparities
decreased for all categories except professional. Thus, we can conclude that the income
disparities have not necessarily widened; in fact, they have reduced on the whole.
61

1.5
Employer

1
Regular employment

0.5

Self-employed
Professional

0Male, non-regular employment, and sales
Unskilled
Farming-0.5

Female-1
Figure 3 Changes in Partial Regression Coefficients between the Two Survey Years
Source: The 1995 and 2005 SSM Survey data

7

Toward More Fruitful Dialogue

Disparity society theory raised some important issues that had been overlooked by social
stratification theory. In particular, the income disparity between non-regular and regular
employment was a blind spot that had been generally overlooked by conventional social
stratification theory. In an attempt to reflect on this failure, this paper reconfirmed thisargument presented by disparity society theory using the SSM Survey data. However, theother argument that the disparities have been widening was not supported. Certainly, one
may speculate that this conclusion is attributable in part to the particular feature of the
SSM Survey whose data on the wealthy and poor people are relatively limited. However,this characteristic is present in both 1995 and 2005 SSM Survey data, and it does notnecessarily seem to be the cause for the failure to support the alleged widening ofdisparities. Another point to note is that the analysis conducted in this paper covers theworking population only and excludes the unemployed. While the present analysis has
focused on the income disparity between regular and non-regular employment, it must beconceded that this paper has failed to examine the disparity between the employed andthe unemployed.
Needless to say, I have no intention to claim that the SSM Survey data covers all
social phenomena concerning social stratification and inequalities in contemporary Japan.
62

Still, I believe that the results of the analysis conducted here will corroborate the stated
reduction in the income disparities. Researchers supporting disparity society theory may
argue against this conclusion, but I am sure that continuous dialogue on this and anumber of other topics will open doors for new studies.

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