The Role of Public University in Japan Reexamined: Have Public Universities Expanded Disadvantaged People’s Opportunity for University Education? ISA RC28 Spring Meeting May 27, 2016 National University of Singapore Wataru NAKAZAWA Graduate School of Human Sciences Osaka University

Contents Motivation Research backgrounds and the current situation of higher education in Japan Hypotheses Method Data Results Conclusion and Discussion

Motivation (1) Inequality in university education Cultural or social capitals (Bourdieu and Passeron 1970) School structures such as tracking (Oakes 1985; Gamoran 1986; Pallas et al. 1992) Relative risk aversion (Breen and Goldthorpe 1997) Reduction of Educational Inequality (Breen et al. 2009; Breen et al. 2010) Tuition fees tend to increase because of the financial deficit in some industrial countries.

Motivation (2) Free tuition or decrease in tuition fees. Scholarships or grants Other financial supports Removal of economic barrier 　　　・・・・・・ 　⇒seem to secure equal educational opportunity. We need to examine whether or not these policies progress to universities.

Motivation(3) On the other hand, Positive correlation between SES and academic grades. University applicants may concentrate on those universities that are relatively low costs because they want to avoid paying high costs. ⇒Those who have high academic grades may be advantageous to enroll in universities. Thus, even if the private economic burden has been reduced, we cannot expect that a lower SES would progress to university. Rather, after all, a higher SES dominates among university applicants.

Figure 1. Share of Private Expenditure on Education 2012 (Source: OECD 2015 ChartB3.1) Japan

Figure 2. Financial Support for socially Disadvantaged Students 2011 (Source: OECD 2015 ChartB5.3.) Japan

Universities in Japan (as of 2015) Source: Basic Survey of Schools by MEXT

Figure 5. Changes of University Tuition Fees Sources: Annual Report of the Retail Price Survey (Major Items for Ku-area of Tokyo), and Annual Report on the Family Income and Expenditure Survey The tuition fees of private universities always exceeded those of national (public) universities. ※　Bunkei （文系） includes humanity and social sciences. Rikei （理系） includes natural sciences, engineering, agriculture, medicine, and pharmacy.

Figure 6. Changes of Household Burden on University Tuition Fees Sources: Annual Report of the Retail Price Survey (Major Items for Ku-area of Tokyo), and Annual Report on the Family Income and Expenditure Survey This number implies the proportion of tuition fees relative to the average annual income of employees’ households. The burden of tuition fees Rikei private> Bunkei private> National The burden has increased since the latter half of 1970s.

National Universities in Japan Each prefecture has national universities. Except for some famous universities which collect students from nationwide, national universities tend to collect local students. Learning conditions (for example, low student-faculty ratio) are better than those in private universities. Entrance examination: private universities demand 1～3subject(s) national universities demand over 5 subjects ⇒Higher academic grades are required. Higher prestige and trust among Japanese people.

Hypotheses Those who had lower socioeconomic backgrounds were more likely to choose national universities. National universities did not provide greater opportunities for university education for people with lower socioeconomic backgrounds in spite of lower tuition fees.

Method y selection = x1 + ν1 + ε1 Bivariate probit selection models Selection equation (dependent variable: 1=university attendee, 0 = not university attendees) Outcome equation (dependent variable: 1=national university, 0 = private university) y selection = x1 + ν1 + ε1 y outcome = x2 + ν2 + ε2 , if y selection=1 x = independent variables, ν = unobserved heterogeneity, ε = random error cor (ν1+ε1, ν2+ε2) = ρ

Data Social Stratification and Social Mobility (SSM)Survey SSM1985 Men = 509 SSM1995 Men = 706, Women = 838 SSM2005 Men = 1,924, Women = 2,187 Japanese Life Course Panel Survey (JLPS) Men = 1,576, Women = 1,715 Merged these four (three) datasets. N(men)=4,715 N(women)=4,740 　 Born between 1935-85. N(men, university attendees)=1,855 N(women, university attendees)=855

Independent Variables(1) Socioeconomic backgrounds Men (N=4715) Women (N=4740) Father's Occupation Whole samples Univ. attendee EGP I + II (Service Class) .228 .378 .214 .420 EGP IIIa (Routine non-manual) .134 .184 .144 .208 EGP IVa+b (petty bourgeoisie) .141 .113 .106 EGP V+VI (Skilled worker) .093 .068 .066 EGP IIIb + VIIa (Non- , Semi –Skilled) .203 .171 .211 .157 EGP IVc + VIIb (Agriculture) .200 .086 .198 .043 Father's Education Primary or Secondary .791 .612 .782 .477 Tertiary .209 .388 .219 .523

Independent Variables(2) Residential areas Men (N=4715) Women (N=4740) Whole samples Univ. attendee Hokkaido and Tohoku .152 .115 .153 .094 Kanto (including Tokyo) .255 .303 .254 .338 Chubu .093 .081 .062 Tokai (including Nagoya) .125 .120 .124 Kinki (including Osaka, Kyoto) .140 .163 .136 .174 Chugoku and Shikoku .104 .101 .110 .106 Kyushu .131 .116 .130 .111

Independent Variables(3) Control variables Men (N=4715) Women (N=4740) Survey Whole samples Univ. attendee SSM85 .108 .106 - SSM95 .150 .121 .177 .102 SSM05 .408 .347 .461 .305 JLPS .334 .427 .362 .593 Birth cohort 1936-45 .180 .104 .153 .020 1946-55 .192 .152 .175 .073 1956-65 .148 .162 .135 .119 1966-75 .281 .320 .308 .329 1976-85 .199 .263 .230 .460

Independent Variables(4) Instrumental variables Specific variables of selection and outcome equations should be considered (Holm and Jæger 2011). Men (N=4715) Women (N=4740) Whole samples Univ. attendee Range of Academic Grade Middle and Low .626 .377 .633 .276 High .374 .623 .367 .724 High School Course Vocational .357 .167 .282 .157 Academic (General) .556 .833 .629 .843 Did not go to high school .088 - .089

Results (1) Men Only probit coefficients of socioeconomic backgrounds Coefficients of cohort, residential areas, survey, grades, and high school courses are omitted + p<.10, * p<.05, ** p<.01, *** p<.001 ρ = -.808 Simple Probit Bivariate (Outcome) Coef. S.E. Father's Occupation (vs. EGP I + II) IIIa .005 .097 .066 .085 IVa + b -.089 .122 .238 .102 * V + VI -.165 .153 .222 .127 + IIIb + VIIa .128 .103 .394 .088 *** IVc + VIIb .004 .133 .492 .110 Father's Education (vs. Primary or Secondary) Tertiary Education .136 .077 -.196 .069 **

Results (2) Women Only probit coefficients of socioeconomic backgrounds Coefficients of cohort, residential areas, survey, grades, and high school courses are omitted + p<.10, * p<.05, ** p<.01, *** p<.001 ρ = -.655 Simple Probit Bivariate (Outcome) Coef. S.E. Father's Occupation (vs. EGP I + II) IIIa -.056 .139 .093 .124 IVa + b .089 .175 .300 .156 + V + VI -.660 .272 * -.271 .242 IIIb + VIIa -.063 .159 .187 .143 IVc + VIIb -.208 .266 .239 .236 Father's Education (vs. Primary or Secondary) Tertiary Education -.027 .113 -.293 .105 **

Conclusion The first hypothesis, those who had lower socioeconomic backgrounds were more likely to choose national universities, was supported. Recent changes may destroy the national university’s traditional role which provided more equal opportunity for tertiary education.

Discussion Choice of instrumental variables in the bivariate probit selection models. In the future, specialty(bunkei/rikei) should be considered.

Acknowledgement I would like to thank the Research Committee of the SSM 2015 and JLPS for permitting me to obtain and use these data. This research was supported by Grants-in-Aid for Scientific Research (reference 15K04359) from the Japan Society for the Promotion of Science (JSPS).