38 6 2014 11 Vol. 38 No. 6 November 2014 76 Population Research * 100872 Trends of Education Inequality in China A Cohort Perspective Wu Xiwei Abstract Using the data from the third wave survey of the Social Status of Women in China this study investigates the inequality of both educational outcome and educational opportunity and how they vary with cohorts. There are two main findings. First regardless of gender the degree of inequality of educational outcome increases with cohorts but the acceleration rate tends to decrease. This trend mainly results from the increase in both of the inequality of opportunity and the weight of importance which is due to the expansion of population at risk and the raised expected gain at the junior-to-senior high school transition. Second among all cohorts inequality of educational outcome for men is lower than for women because women experience higher inequality of opportunity at all transitions but the gender gap at every transition tends to vanish with cohort. The paper concludes with discussion of the methodological and substantive significance of this research. Keywords Inequality of Educational Opportunity Inequality of Educational Outcome Birth Cohort Author Wu Xiwei is Associate Professor Center for Population and Development Studies Renmin University of China Beijing. Email wuxiwei@ ruc. edu. cn * 10@ ZH020
6 77 2006 2007 1 1995 9 1 5 ~ 6 9 9 2008 1
78 38 Figure 1 1 Diagram of Sequential Decision on Education Transition Mare 1981 Mare 1981 Raftery & Hout 1993 Lucas 2001 2003 2006 2006 2006 Buis 2010 Robert Mare 1981 distribution of education Mare Robert Mare weighted sum Maarten L. Buis 2010 Buis Ryder 1965
6 79 2 logit Mare 1980 1981 logit Maarten L. Buis 2010 logit sequential logit model logit 1 Buis 1 logit i 1 k i 2 exp α k + λ k SES i p ki = 1 1 + exp α k + λ k SES i λ k k α k k 1 SES λ k Mincer 1974 Xie & Hannum 1996 scaling logit E L logit 3 E L = 1 - p 1i l 0 + p 1i 1 - p 2i l 1 + p 1i p 2i 1 - p 3i l 2 + p 1i p 2i p 3i l 3 2 SES logit SES logit SES 2 SES 1 2 3 k - 1 k 1 6 l 1 = 6 9 l 2 = 9 12 l 3 = 12 16 l 4 = 16
80 38 E L SES = { 1 p 1 1 - p 1 1 - p 2 l 1 + p 2 1 - p 3 l 2 + p 2 p 3 l 3 - l } 0 λ 1 + { p 1 p 2 1 - p 2 1 - p 3 l 2 + p 3 l 3 - l } 1 λ 2 + { p 1 p 2 p 3 1 - p 3 l 3 - l } 2 λ 3 3 3 1 1 p 1 p 1 p 2 2 p k 1 - p k 0. 5 3 1 - p 2 l 1 + p 2 1 - p 3 l 2 + p 2 p 3 l 3 l 0 IEOut k IEOpps proportion at risk variance expected gain IEOut = K k = 1 weight k IEOpps k weight k = at risk k variance k gain k 4 IEOpps k weight k proportion of people at risk universality Maarten L. Buis 2010 logit 4 3
6 81 18 ~ 64 29698 1943 1992 logit / 6 9 12 16 1 / 1949 1985 19339 1 n = 19339 Table 1 Descriptive Statistics of Selected Variables % % % 49. 62 50. 38 1949 ~ 1953 9. 90 11. 26 8. 51 1954 ~ 1958 13. 04 14. 60 11. 45 1959 ~ 1963 14. 20 14. 48 13. 91 1964 ~ 1968 17. 93 17. 30 18. 57 1969 ~ 1973 18. 46 17. 48 19. 46 1974 ~ 1978 12. 95 12. 01 13. 91 1979 ~ 1983 10. 12 9. 37 10. 88 1984 ~ 1985 3. 40 3. 50 3. 30 22. 59 20. 41 24. 80 41. 99 42. 44 41. 54 18. 64 19. 27 18. 01 16. 77 17. 88 15. 65 a 0 27. 53 29. 99 25. 00 6 40. 44 40. 00 40. 53 9 19. 34 17. 81 20. 89 12 9. 41 8. 79 10. 04 15 1. 86 1. 74 1. 98 16 1. 37 1. 28 1. 45 18 0. 06 0. 04 0. 08 a. 0 6 = 5 / 12 15 16 18
82 38 1 50. 38% 49. 62% 1949 ~ 1953 1979 35% 6 2 Table 2 2 Trends on Mean Number of Years of Schooling by Gender and Its Difference 1990-2010 1990 7. 54 3. 86 5. 91 4. 25-1. 63 2000 8. 23 3. 34 6. 98 3. 84-1. 26 2010 8. 86 3. 49 7. 96 4. 09-0. 90 1990 2000 2010 4 3 logit 4 IEOpps weights IEOut weights 0. 5 3 50 20 2 3 1 1960 10% 30% 4 1
6 83 Figure 2 2 1949 ~ 1992 Distribution of Highest Achieved Level of Education for Men over Birth Cohorts Figure 3 3 1949 ~ 1992 Distribution of Highest Achieved Level of Education for Women over Birth Cohorts
84 38 Figure 4 4 Mean Number of Years of Schooling for Men and Women over Birth Cohorts 2010 18 ~ 64 logit 3 1949 1949 10 1949 IEOpps 1 10 0. 013 < 0. 051 < 0. 056 0. 020 < 0. 062 > 0. 033 3 logit 5 1
6 85 12 1 2 3 logit Table 3 Parameter Estimates from Sequential Logit Model n = 9743 0. 216 *** 0. 042-0. 444 *** 0. 052 0. 119 0. 087 0. 151 *** 0. 014 0. 067 *** 0. 013 0. 008 0. 020 * 0. 013 + 0. 007 0. 051 *** 0. 007 0. 056 *** 0. 010 0. 217 *** 0. 067-0. 390 *** 0. 087-1. 197 *** 0. 152 n = 9596 0. 201 *** 0. 044-0. 480 *** 0. 062 0. 406 *** 0. 118 0. 142 *** 0. 014 0. 055 *** 0. 015 0. 091 *** 0. 026 * 0. 020 *** 0. 007 0. 062 *** 0. 008 0. 033 *** 0. 013-0. 185 ** 0. 076-0. 555 *** 0. 111-2. 318 *** 0. 232 1 Log likelihood = - 11324. 686 Log likelihood = - 10546. 766 2 ** p < 0. 01 * p < 0. 05 + p < 0. 10 Figure 5 5 logit Estimated Inequality of Educational Outcome according to the Sequential Logit Model
86 38 4 5 weight 1950 1955 1960 1965 1970 1975 1980 1985 8 6 7 3 6 7 5 5 6 Figure 6 Decomposition of IEOut into IEOpps and Weights for Men
6 87 7 Figure 7 Decomposition of IEOut into IEOpps and Weights for Women 8 9 4 3 50% 50% 1965 1 2 1 2 4
88 38 8 Figure 8 Decomposition of Weights into at Risk Variance and Expected Gain for Men 9 Figure 9 Decomposition of Weights into at Risk Variance and Expected Gain for Women
6 89 5 2001 2007 Maarten L. Buis 2010 1949 ~ 1985 1 2 Hannum & Xie 1994 Lu & Treiman 2008 2011 2010 1 2
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