日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

Effects of Sibship Size and Gender on Educational Attainment in Japan:
Analyses of JGSS-2006
Keiko HIRAO
Faculty of Humanities
Sophia University
女子の高等教育進学選好に対する少子化の影響−JGSS-2006 のコホート分析−
平尾 桂子
上智大学文学部
This paper explored the effect of sibship size on the educational attainment of men andwomen born in Japan between 1916 and 1986.

The data used in this study come from

JGSS-2006, which is a part of the East Asian Social Surveys Project. Using multinomial logistic
regression, the odds of attending 4-year university and junior college vs. high school or lower,
were estimated. I found that the negative effect of sibship size was stronger for women’s
probability for attending 4-year university, but not for their attending junior college.

The

gender-specific negative effect was significant for the youngest cohort born after 1970 on women’s
probability of attending 4-year university. These results suggest changing patterns of educational
investment for daughters in Japan, in which gender per se is beginning to have weaker effect, but
the constraints on the part of parents’ resources that interact with gender is determining parents’
willingness to invest in their daughters’ education.
Key Words: JGSS, educational attainment, sibling structure
教育達成に対するきょうだい数の影響、特に性別による相違について JGSS-2006 を用いて検証した。使用したサンプルは、1916 年から 1986 年生まれの男女 4254 名である。
進学先を１）大学以上、２）短大・高専、３）高校以下のカテゴリー変数とする多項ロジス
ティック回帰分析を用いて推定した結果、教育達成に対するきょうだい数の負の影響は特に女子の 4 年制大学への進学確率に対して強くはたらくこと、さらに、この交互作用は特に 1970 年以降生まれの若いコホートで有意に達していることが明らかになった。その一方で、短大への進学確率に対しては、きょうだい数と性別の交互作用はどのコホートでも有意に達していない。これらの結果から、女子の４年制大学への進学決定に対して、主に性別による選択的教育投資から予算制約による選択的投資に移行していることが示唆される。
キーワード：JGSS，教育達成，きょうだい構成

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日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

1. Introduction
When infant mortality declines along with economic development, the parents’ demand for“quality” of their children surpasses the demand for their “quantity” (Becker 1981; Becker and Lewis
1973). Past research in the field of stratification and sociology of education supports this statementwith the robust findings on the negative relationship between sibship size and educational attainmentof children (e.g. Blake 1989; Steelman et. al, 2002; Blau and Duncan 1967). The resource dilution
hypothesis has been one of the strongest explanations on this negative association (Blake 1989). It
maintains that parents’ resources (both monetary and non-monetary) are “diluted” when shared among
multiple children; thus each child receives a smaller amount of the resources as the number of theirsiblings increases. The causal mechanisms, however, are still subject to further scrutiny, because
studies on the effects of birth order, spacing of birth timing, and gender composition have yielded
mixed results (Steelman et al, 2002). A major body of the past literature is based on the datacollected in the U.S., and thus little is still known about the patterns of parental investment in different
cultural contexts, particularly where there is asymmetric preference on the sex of the children.
In the East Asian context, where there is strong preference for sons, the fertility decline has
resulted in different fates for girls and for boys. As can be seen from the cases in China and Korea,
for example, the demographic change has interacted with the existing patriarchal cultural values andresulted in intensified gender inequality. The gender-asymmetric effect of fertility decline includes
an imbalance in the sex ratio among registered children, higher mortality rates among female infants,(Hull 1990; Park 1983; Ren 1995; Zeng et al. 1993), “feminization” of orphans (Johansson andNygren 1991), and suspected selective abortion (Park and Cho 1995). Regarding the effect of sibling
configuration on educational outcome, Greenhalgh (1985) demonstrated and Chu, Xie and Yu (2007)
confirmed that parents in Taiwan sacrifice the educational opportunities of older daughters and use
their earnings to subsidize the education of their younger brothers and sisters.
If Greenhalgh’s (and Chu, Xie and Yu’s) argument holds true across different stages ofindustrialization, we should expect “the historical residue of patriarchal institutions” (Greenhalgh
1985: 265) to remain in a highly industrialized society with a patriarchal background, such as Japan.
If, on the other hand, what Greenhalgh observed in the parental behavior in Taiwan was theirtransitional reaction to the rapid growth of market economy, we would expect to see, in anindustrialized East Asian country, a different system through which parents allocate their resources totheir sons and their daughters.
This paper explores the effect of sibship size on the educational attainment of men and womenborn in Japan between 1916 and 1986. Of particular interest is whether there has been a change inintra-family transfer of resources for boys and for girls. The last two decades in Japan have marked arapid change in gender attitude, women’s status, and intergenerational relations. For one thing, theenrollment patterns for higher education have shown dramatic changes especially for women; more
women are aspiring to 4-year university rather than junior colleges, which used to be a predominantly“female track” for higher education. For the other, the sex preference has turned to favor daughters.
The shift of sex preference took place in the mid-1980s, which coincides with the time when women’senrollment patterns for higher education began to change. In this respect, Japan presents a very
interesting case for examining how demographic shift and changes in traditional values interact witheach other and mediate the impact of gender on the intergenerational allocation of resources.
The project presented in this paper is a part of the East Asian Social Surveys Project (EASS
2006), which investigates family structure and relations in Japan, Korea, Taiwan and China. The
strength of EASS Project is that it uses comparable questionnaires (wording and scales, etc). The

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日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

findings presented in this paper are the first step toward comparable research in the East Asian context.
First, I will discuss the contextual background on how Japanese educational system is structured
vis-à-vis intra-family transfer of resources on men and on women. Second, I will describe the data
and method used in this research, followed by the results and conclusion.

2. The Japanese Context
2.1 Gender Track in Higher Education
Many scholars have pointed out the gendered nature of higher education in Japan. The
enrollment rates to “higher education,” when 4-year university and junior college are combined, thegender gap has now disappeared or even reversed. When we look at the enrollment rates by school
types, however, there is a sharp distinction: a very small number of men would go to junior college,
while junior college was an option that a majority of women were tracked into.
Shinotsuka (1995), for example, points out that the increase in the female enrollment in “higher
education,” especially until the early 1970s, occurred mainly in the women’s colleges and juniorcolleges that burgeoned in this period. The average annual growth rate in the women-only 4-yearcolleges was 4.5% between 1951 and 1971, while the overall number of 4-year universities increased
at 2.8% during the same period. Expansion of junior colleges was even more dramatic; the averageannual growth rate in the number of junior colleges, most of which accept only women, was more than
5.0% during the same period. Even though the post-World War II higher-educational system adopted
coeducation as a principle, in reality the gendered track in higher education continued at least until the
1980s. The steady increase in the number of women-only universities and junior colleges during thisperiod reflects the demand for sex-segregated education and the expectation that these institutions
would provide different kinds of schooling for women.
Similarly, Japanese parents are known to hold different educational aspirations for boys and forgirls. For example, even in 2002, when the Cabinet Office conducted the Second Basic Survey on
Youth, 65% of parents of school-age boys answered that they want their child to proceed to 4-year
university, while only 41% of fathers and 47% of mothers of girls hold the same aspiration (Cabinet
Office 2002). In spite of such gender-differentiated aspirations for the educational attainment of theiroffspring, in the recent years there has been a significant change in the enrollment patterns for higher
education.
Figure 1 shows the trends of enrollment rates for men and women by types of school. Solidlines represent male and broken lines represent female; solid dots are for 4-year university and white
dots are for junior college respectively. (The “cohort” represents the breakdown of the birth cohort,which will be described in detail in the method section.) As in the case of other industrializedcountries, there has been a gradual improvement in educational opportunity, but the distinct gendersegregation in higher education is apparent. It was only in 1996 that the women’s enrollment rate for
4-year university surpassed that for junior college.
This structural change is more apparent in figure 2 where the actual number of students admitted
every year to each type of school is plotted along with the changes in the cohort size of 18 year-olds(solid black line). It shows that the male enrollment number for 4-year university stays around
370,000 in the 1990; the increase in the enrollment rate for male was mainly due to the decline of thedenominator, the cohort size. On the other hands, the number of women enrolled in 4-year university
increased from 104,000 in 1985 to 250,000 in 2002, while the number of women enrolled in juniorcollege dropped from 236,000 in 1993 to 93,000 in 2004. In other words, the gender track of higher
education is changing both in enrollment ratio and in actual number of student admissions.

35日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

60.0
Cohort <=1945

Cohort 1946-1955

Cohort 1956-1970

Cohort 1970+

50.0

40.0

% 30.0

20.0

10.0

19
54
19
56
19
58
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04

0.0

Year
Male University

Female University

Male JC

Female JC

Source: Basic School Survey and Census, various years
Figure 1 Trends in Enrollment Rates by School Type and Sex

400,000
350,000
300,000

First Baby-boomer
Second Baby-boomer

250,000
200,000
150,000
100,000
50,000

19
55
19
57
19
59
19
61
19
63
19
65
19
67
19
69
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03

0

Year
Male 4-year Univ

Female 4-year Univ

Female JC

Cohort Size of 18 Year-olds by 100)（

Source: Basic School Survey and Census, various years
Figure 2 Trends in the Actual Number of Students Admitted to Different Types of Higher Education by Sex and the Cohort Size of 18 Yearolds

Has the declining fertility, which translates into declining number of children per family, affected
the parents’ investment patterns for children’s education? Does the negative effect of sibship size
affect boys and girls in the same way? These questions constitute the core issue of this study.
2.2 Sex Preference
Another interesting feature of the Japanese fertility trend, when compared with other East Asiansocieties, is the weakening of son preference. As mentioned above, decline of fertility has somewhat
intensified the son preference in China and Korea, but this was not the case in Japan.
According to the Twelfth National Fertility survey conducted in 2002, among the married women36日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

who answered the ideal number of children to be “one”, 73% preferred the only child to be a girl.
Among those who answered the ideal number of children to be “two,” 12% chose “all females,” while
only 1.9% chose “all males.” The pattern that favors female offspring has been observed since theNinth Fertility Survey administered in 1987 and the tendency to prefer girls has gradually intensified(National Institute of Population and Social Security Research 2003). While the most popularanswer has continued to be “two children, one of each sex,” parents now seem to prefer daughterswhen they are asked to choose between the two sexes.
We can also see the trend toward female preference in the expected fertility; for all categories ofexisting number of children, planned fertility was consistently higher for those who do not have any
daughters. That is, those who do not yet have daughters are more willing to add children (Ministry of
Health and Welfare 1993).
There has not been much research done to investigate the underlining structure of this shift in sex
preference. Sakai (1992) reports regional differences as well as occupational differences: those living
in Chugoku, Shikoku and Kyushu areas show relatively high proportions of son preference; those whoare self-employed tend to prefer sons as well. He also reports some effects of attitudes on the valueof children, suggesting a relative increase in the value of daughters as providers of elderly care.
Kojima (2003) reports that men are more likely to prefer sons, while women are more likely to favordaughters. Despite these intra-society differences, the overall weakening of son preference in Japan
is apparent compared with the cases in Taiwan and Korea, where there still remains strong preferences
for sons (Kojima 2006).
Whether distinctiveness of the Japanese case is a historical phenomenon or due to some structuraldifference is subject to further investigation. Some researchers, however, speculate that increased
demands for emotional support and for actual care in parents’ older ages (e.g. listening to problems
and keeping the social networks) account for the trend to favor girls over boys (Ministry of Health andWelfare 1993; Sakai 1996).
How do these changing attitudes on children’s value regarding their sex translate into the patterns
in which parents allocate their resources for the education of their sons and their daughters? It is a
key question to understand the implication of demographic change on gender structure. It is because
education functions as an important indicator of the social status and economic well being of anindividual through its ties with employment opportunities. In this sense, it is not too much to say thatgender equality (or inequality) lies in the patterns of intra-family resource transfer.

3. Data and Method
The data used for this study come from the Japanese General Social Surveys (JGSS), a national
representative survey project started in the year 2000. For the analyses of the study presented in thispaper, I used the JGSS-2006, conducted in October - December 2006 among men and women between
the ages of 20 and 89. The samples were drawn using a stratified two-stage random sampling
procedure, stratified by regional block and by population size. The survey was administered via
face-to-face interview for the core question items, along with self-administered modules, part of whichwere developed in accordance with the East Asian Social Surveys (EASS). The sample size is 4,254
with the response rate of 59.8%.
3.1 Dependent Variable
Past research has conventionally used years of schooling as an indicator of educational attainment.
This method assumes that the educational outcome can be measured in interval scale; the difference37日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

between 14 and 15 years of schooling is the same as the difference between 12 and 13. However, I
use categorical measurement in this study for two reasons. First, parents’ decision for educational
investment for children is not continuous; rather it is a discrete decision of 1) whether they want theirchild(ren) to proceed beyond high school;(1) 2) if so, which “type” of school do they want theirchild(ren) to attend. Second, the cost of education is not continuous; it costs extra money for theparents in the first year that their children proceed to the upper school. The extra costs include
application and admission fees, registration fees, etc.; such one-time costs impose a heavier financial
burden on the parents. Third, as shown in figures 1 and 2, years of schooling do not depict thegender-specific tracks in the higher education in Japan. As described above, a majority of men, when
they are to attain tertiary education beyond high school, would go to 4-year university, while until
recently a majority of women were tracked into junior college. It is only in the past ten years that
this pattern has begun to change.
3.2 Explanatory Variables
Sibship size is defined as the number of children in the respondents’ family of origin, which iscomputed as a sum of elder/younger brothers and sisters (including the deceased) plus one(respondent). Therefore, if a respondent does not have any brothers or sisters, this would take a valueof one (only child). Unfortunately, the JGSS does not ask the birth year of each sibling; therefore, weknow the birth order and gender composition of the respondents’ siblings but not the spacing of birthtiming. Also unavailable is their siblings’ educational outcomes, which prevents us from controlling
unobserved heterogeneity of their family background. A dummy variable of female is coded as one
if the respondent is female and otherwise as zero.
3.3 Controlling Variables
Controlling variables include birth cohort, fathers’ education, city size of residence and living
standard at the age of 15. The birth cohort is coded as 1) 1916 -1945, 2) 1946-1954, 3) 1955-1970,
and 4) 1970-1986. These categories roughly correspond with the 1) pre-World War II, 2) post-war
baby boomers, 3) cohort born during the high economic growth, and 4) cohort born during the slow
economic growth. The “birth cohort” in figure 1 shows the historical time when each cohort reached
the age 18. The oldest cohort is used as a reference category. City size of residence at the age 15 iscategorized into: 1) large city, 2) small-/mid-sized city, 3) township, and 4) village (reference
category). Likewise, the living standard at the age 15 is categorized into: 1) far above average, 2)
above average, 3) average, 4) below average, and 5) far below average (reference category). Father’s
education is determined as “the last school attended” and is categorized as 1) 4-year university or
higher, 2) junior college, 3) unknown,(2) 4) high school or lower (reference category).
3.4 Methods
I employ multinomial logistic regression with “high school or lower” as the reference category.
In the first stage, the main effect of sibship size and sex is estimated (MODEL I), and in the second
stage, the interaction term of sibship size and sex in added in the model to test if there is a different
effect of sibship size for men and for women (MODEL II). This procedure is adopted for the total
sample, and then for each cohort to investigate if there has been a change in the effect of the
explanatory variables.

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日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

4. Descriptive Statistics
Table 1 shows the descriptive statistics of the variables used in the analyses. The educational
attainment reflects the general improvement of educational opportunities. The city size of residence
at the age of 15 shows general trend of urbanization, but not necessarily to large cities. The living
standard at the age of 15, though statistically significant, shows little difference among cohorts, withapproximately half of the respondents answering that their living standard in the past was “average.”
Fathers’ education shows increasing proportion of university attainment while more than half in every
cohort have education of high school or lower. The average number of siblings shows a significant
decline from 4.8 for the oldest cohort to 2.5 for the youngest cohort. Moreover, the variance issmaller among younger cohort, indicating the strengthening of “two children” as the norm.
Table 1 Descriptive Statistics of Variables Used in the Analyses
Total

By Cohort1946 - 1954 1955 - 1969
995
803

Sample Size
Education

4,225<= 1945900

University or Higher
Junior College
High School or Lower
City Size of Residence at the Age of 15
Large City
Small-/Mid-sized City
TownshipVillage
Living Standard at the Age of 15
Far Above Average
Above Average
Average
Below Average
Far Below Average
Fathers' Education
University or HigherJC
Unknown/Deceased
High School or Lower
Female1=female

20.0%
12%
68%

9.9%
5%
85%

17.4%
12%
71%

14%
40%
32%
14%

14%
32%
31%
24%

14%
36%
36%
14%

15%
45%
33%
6%

14%
52%
30%
4%

2%
15%
46%
27%
11%

3%
11%
42%
29%
15%

2%
13%
43%
31%
11%

2%
17%
45%
28%
8%

2%
20%
55%
18%
6%

10%
4%
24%
62%
53%

5%
4%
28%
63%
52%

4%
5%
28%
63%
52%

12%
5%
22%
62%
56%

21%
4%
17%
59%
53%

3.6

4.8

3.5

2.6

2.5 ***

(1.9)

(2.2)

(1.6)

(1.0)

(.9)

Sibship Size

1970+
1,556

p.
***

Mean

(S.D.)* p<.05 ** p<.01 *** p<.001

25.3% 33.7%
19%
19%
56%
47%
***

***

***

5. Results
Table 2 shows the result of multinomial logistic regression on the total sample. In general, theyounger cohorts have a higher chance of attending higher education. Living in the urban area, higher
living standard, and having a father with higher education increase the odds of attending a 4-year
university, but does not show any effect on the odds of attending a junior college. Being female
substantially decreases the odds of attending a 4-year university but increases the chance of going to ajunior college. Compared with men, women have about 25% probability of attending 4-year
university, while there is about twice the chance of being tracked to junior college. The number ofsiblings decrease the probability of proceeding beyond high school; about 20% decrease in the chancewith every sibling added to the family.
This negative effect of sibship size is stronger for women attending 4-year university (MODEL
II). With every sibling added to the family, men experience about 10% (1-.89) decrease in their

39日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

chance of attending 4-year university while women’s chance for attending 4-year university decreases
by 70% (1- .689 x .513). On the other hand, the sibship size does not have any effect for womenattending junior college, or rather, being female and having more siblings seems to slightly increase
the chance of being tracked to junior college, as the main effect of being female increases from 2.1 to
2.8 when the interaction is taken into account. In separate analyses, I tested the effect of gender
Table 2 Coefficients from the Multinomial Logistic Regression; Overall Samples
MODEL I
4-year University/High School or lower
B
S.E
Exp (B)
Constant-2.3460.287＊
Cohort
1970+
1.142
0.145
3.134 ***
1956 - 1970
0.910
0.144
2.485 ***
1946 - 1955
0.605
0.148
1.830 ***<= 19450.000 .
.
City Size of Residence at the Age of 15
Large City
1.179
0.213
3.251 ***
Small-/Mid-sized City
0.790
0.196
2.204 ***
Township
0.380
0.202
1.462
Village
0.000 .
.
Living Standard at the Age of 15
Far Above Average
0.978
0.343
2.659 **
Above Average
1.409
0.211
4.090 ***
Average
0.697
0.192
2.007 ***
Below Average
0.482
0.202
1.619 ＊
Far Below Average
0.000 .
.
Fathers' Education
University or Higher
1.692
0.144
5.433 ***
JC
1.632
0.207
5.114 ***
Unknown/Deceased-0.6180.131
0.539 ***High School or Lower
0.000 .
.
Female-1.3590.099
0.257 ***
Number of Siblings-0.201
0.036
0.818 ***
Female X Number of Siblings
MODEL I
JC/High School or Lower
Constant
Cohort1970+
1956 - 1970
1946 - 1955<= 1945
City Size of Residence at the Age of 15
Large City
Small-/Mid-sized City
TownshipVillage
Living Standard at the Age of 15
Far Above Average
Above Average
Average
Below Average
Far Below Average
Fathers' Education
University or HigherJC
Unknown/Deceased
High School or Lower
FemaleNumber of Siblings
Female X Number of Siblings-2 Log Likelihood
Chi Square (df)Model Change (=2LL)* p<.05 ** p<.01 *** p<.001-3.832

0.338

***

1.443
1.421
0.872
0.000 .

0.175
0.168
0.176

4.234 ***
4.140 ***
2.392 ***

0.359
0.186
0.040
0.000 .

0.218
0.190
0.194

1.280
1.503
0.974
0.641
0.000 .

0.388
0.261
0.242
0.255

0.774
1.335
-0.2330.000 .
0.738
-0.153

0.175
0.233
0.130

4611.481405.334

.
1.432
1.204
1.041
.
3.595 **
4.497 ***
2.649 ***
1.899 ＊.
2.168 ***
3.800 ***
0.792
.
0.114
0.041

2.091 ***
0.858 ***

B
-2.558MODEL II
S.E
0.291

1.150
0.927
0.624
0.000 .

0.146
0.144
0.148

1.152
0.780
0.386
0.000 .

0.213
0.197
0.203

0.987
1.415
0.704
0.486
0.000 .

0.344
0.211
0.192
0.202

Exp (B)***
3.157 ***
2.527 ***
1.866 ***.
3.164 ***
2.180 ***
1.472.
2.682 **
4.118 ***
2.022 ***
1.626 *
.

1.702
0.145
1.641
0.209
-0.6100.131
0.000 .
.
-0.6670.170-0.1090.039-0.373
0.080
MODEL II
0.354

***

1.435
1.414
0.862
0.000 .

0.174
0.168
0.175

4.201 ***
4.112 ***
2.368 ***

0.349
0.178
0.037
0.000 .

0.218
0.191
0.195

1.277
1.512
0.976
0.642
0.000 .

0.389
0.261
0.242
0.255

0.794
1.352
-0.2330.000 .
1.045
-0.075-0.137

0.176
0.233
0.131

.
1.417
1.194
1.038
.
3.585 **
4.536 ***
2.654 ***
1.901 *.
2.213 ***
3.865 ***
0.792
.
0.191
0.064
0.076

2.844 ***
0.928
0.872

***
25.45540

0.513 ***
0.897 **
0.689 ***

-4.0003180.691(30)

5.487 ***
5.161 ***
0.543 ***

(2)

***

日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

composition of the sibling, particularly of the existence of brothers; however, neither elder nor
younger brother showed any significant effect. (Results not shown.)
Table 3 presents the estimates from multinomial logistic regression applied for each cohort. The
model that includes the interaction effect of sibship size and sex is presented only when the model fit
is improved. In general, the negative effect of being female on the probability of attending 4-year
Table 3 Coefficients from the Multinomial Logistic Regression by Cohort-1945
MODEL I

1946-54
MODEL I

1955-69
MODEL I

1970+
MODEL I
MODEL II

University/High School or Lower
Exp (B)
Exp (B)
Exp (B)
Exp (B)
Exp (B)
City Size of Residence at the Age of 15
Large City
7.61 ***
2.46 *
2.74 *
1.06
1.02
Small-/Mid-sized City
2.51 **
1.82
2.56 *
1.07
1.02
Township
1.68
1.22
1.32
0.96
0.93
Village.
.
.
.
.
Living Standard at the Age of 15
Far Above Average
0.87
16.93 ***
1.78
4.04
4.52
Above Average
5.68 ***
8.34 ***
2.46 *
3.20 **
3.45 **
Average
2.35 *
2.04
1.63
2.03
2.21
Below Average
1.57
2.15
1.46
1.47
1.55
Far Below Average
.
.
.
.
.
Fathers' Education
University or Higher
8.65 ***
10.78 ***
4.69 ***
4.65 ***
4.67 ***
JC
6.10 ***
6.53 ***
6.27 ***
3.24 *
3.40 *
Unknown/Deceased
0.64
0.38 **
0.49 **
0.70
0.70High School or Lower .
.
.
.
.
Female0.09 ***
0.19 ***
0.27 ***
0.53 ***
1.27
Number of Siblings
0.94
0.72 ***
0.67 ***
0.63 ***
0.82
Female X Number of Siblings
0.54 **-1945
MODEL I

1946-54
MODEL I

JC/High School or Lower
Exp (B)
Exp (B)
City Size of Residence at the Age of 15
Large City
1.91
3.13 *
Small-/Mid-sized City
1.14
2.37
Township
1.19
1.89
Village.
.
Living Standard at the Age of 15
Far Above Average
2.17
8.76
Above Average
5.64 ***
10.80 **
Average
1.55
6.14 *
Below Average
1.13
3.30
Far Below Average.
.
Fathers' Education
University or Higher
4.17 ***
3.18
JC
4.32 **
4.40 **
Unknown/Deceased
0.71
0.93
High School or Lower .
.
Female1.25
1.83 *
Number of Siblings
0.95
0.81 *
Female X Number of Siblings-2 Log Likelihood
Chi SquaredfModel Change (=2LL)* p<.05 ** p<.01 *** p<.001

849.7
321.5 ***
24622.3
245.6 ***
24

41

1955-69
MODEL I

1970+
MODEL I
MODEL II

Exp (B)

Exp (B)

Exp (B)

0.71
0.83
0.63

0.61
0.65
0.65

0.60
0.63
0.64

.

.
3.67
4.61 **
3.12 *
2.01

.

.
4.60
2.56
2.13
2.28

.
2.20 *
3.31 *
0.76

.

4.77
2.66 *
2.21
2.35
.

1.72
3.71 **
0.80
.

1.72
3.86 **
0.80.

2.93 ***
0.82 *

2.63 ***
0.59 ***

3.93 **
0.68
0.77

824.9
301.9 ***
24766.1
197.7 ***
24758.1
205.7 *
26
8.005

日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

university shows a gradual decline; however, even for the youngest cohort born after 1970, women
have only half the chance of attending 4-year university as men have. The interaction term of sibshipsize and sex is significant only for the youngest cohort for attending 4-year university, and when thisterm is added the main effect of sex is no longer significant. While the odds of women attending
junior college show stable effect, the effect of sibship size is decreased for the youngest cohort. The
effect of sibship size does not have any significant effect for women attending junior college, andadding this interaction term slightly increases the main effect of females attending junior college.
Having a father with higher educational background increases the chance of men and women
going to 4-year university, but this effect is somewhat weaker for the probability of going to juniorcollege. The declining effect of city size for 4-year college and no effect for junior college suggest
increasing educational opportunities in the rural areas.

6. Discussion and Conclusion
This study explored the effect of sibship size on educational outcome of men and women born
between 1916 and 1986 in Japan. The negative effect of sibship size is replicated in this study and I
found that, when tested with the total sample, it is stronger for women attending 4-year college, but
not for them attending junior college. Women are more likely to be tracked into junior college when
parents decide to provide them with education beyond high school. The probability of women goingto a junior college compared with that of men is approximately twice as much, regardless of thenumber of siblings.
The cohort analyses revealed that there is a gradual increase in the probability of womenattending 4-year university and the negative interaction with the sibship size is found significant only
for the youngest cohort born after 1970. In other words, for the cohorts born before 1969, the genderof the child was the most important factor, if not the only factor, when parents decided how much andto whom they would transfer their resources for the education of their offspring. This result is inaccordance with the findings of Yano (1982), who found that the private return for women’s educationin the 1970s was higher for junior college than for 4-year university. In light of his findings, it was arational choice for parents to send their daughters to junior college, which provides higher return on
educational investment with maximized chance in the marriage market. Yano (1996) also found thatthe private return for junior college declined in the 1980s, suggesting the declining market value of
women with diplomas from a junior college.
It seems that the patterns of parents’ educational investment for their daughters is responding tothis change and that they began to send their daughters to 4-year colleges. The effect of sibship sizethat disfavors women among the younger cohort, in a sense can be seen as a sign that the constraints
on parents’ resources count more rather than the sex of the child per se. In other words, when adaughter does not have “competitors” for her parents’ resources, gender alone began to have arelatively smaller effect on her parents’ decisions about whether they are willing to provide 4-year
university education.
Needless to say, there are more factors to be investigated on the direction and the degree ofchanging patterns of educational investment for women in Japan. The results presented in this paper
will take on deeper meanings when I can extend the analyses in comparative terms. I hope to revisit
the findings of this study when the EASS data for other East Asian countries become available.

42日本版 General Social Surveys 研究論文集[7] JGSS で見た日本人の意識と行動 JGSS Research Series No.4

[Acknowledgement]
The Japanese General Social Surveys (JGSS) are designed and carried out at the Institute ofRegional Studies at Osaka University of Commerce in collaboration with the Institute of Social
Science at the University of Tokyo under the direction of Ichiro TANIOKA, Michio NITTA, Noriko
IWAI and Tokio YASUDA. The project has been financially assisted by Gakujutsu Frontier Grants
from the Japanese Ministry of Education, Culture, Sports, Science and Technology for the 1999-2008
academic years.
[Footnotes](1) The enrollment rate in high school is above 97%.
(2) The “unknown” category was created in order to maintain the sample size.

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