% % % %

* 2010 2008 2003 1995-2002 37% - 38% * 71073004 10YJC880002 CAA11007 24

1988 84. 4% 1995 82. 5% 1999 77. 9% 2004 77. 2% 1999 2006 2008 9 2010 20 90 25

2012. 5 Gustafsson & Li 2000 1988 1995 Zhang et al. 2008 Psacharopoulos & Patrinos 2004 2004 2006 Jamison & Gaag 1987 2003 2004 1998 Zhang et al. 2005 2008 2008 1. 26

2010 2005 Brown 93. 1% 6. 9% 6. 95% 93. 05% 2007 1988-2001 Appleton 1992 20% 2011 2006 Brown 86. 3% 13. 7% 25. 7% 74. 3% 2. Liu et al. 2000 Hughes & Maurer-Fazio 2002 1992 Oaxaca 2008 Appleton 3. 27

2012. 5 2006 1999 Brown 67. 9% 32. 1% 20. 5% 79. 5% 2008 2002 Brown 80. 4% 19. 6% 72% 28% Oaxaca Brown Appleton Oaxaca Oaxaca 1973 Brown Brown et al. 1980 Brown Appleton Appleton et al. 1999 2011 28

Chinese Family Panel Studies CFPS CFPS 2010 2007 2008 2009 2010 25 CFPS / / 21822 16-60 8270 29

2012. 5 22 19 16 15 12 9 6 / 0 2003 7 = 1 = 0 = 1 = 0 = 1 = 0 = 1 = 0 = 1 = 0 2003 2006 5 / / 57% 43% 4 3 / 1 2 3 1 % 35. 7 49. 2 5. 85 3. 97 29. 8 30. 2 6940 4286 28. 9 16. 8 8. 60 8. 33 22. 6 20. 2 26754 19152 35. 4 34. 0 9. 66 10. 12 22. 1 18. 8 31799 22500 100 100 7. 99 6. 79 25. 0 24. 6 21467 12974 30

2 % 10. 4 9. 6 11. 20 11. 85 23. 2 18. 0 29276 25521 10. 3 6. 4 9. 96 10. 67 23. 4 19. 5 26532 21389 27. 0 22. 0 8. 71 9. 08 21. 5 18. 3 29648 20942 1. 8 1. 4 9. 26 8. 73 26. 1 22. 3 20849 13473 50. 5 60. 6 6. 50 4. 70 27. 5 28. 6 14483 7191 3 % 7. 0 3. 0 10. 81 10. 48 23. 2 18. 2 44891 33370 6. 9 9. 5 11. 92 12. 60 19. 7 15. 6 34892 26510 6. 6 6. 0 10. 61 11. 99 23. 2 15. 4 27073 26892 11. 7 18. 0 8. 93 8. 64 21. 8 20. 3 25012 17262 31. 6 13. 9 8. 27 7. 68 22. 5 21. 7 25756 17653 36. 1 49. 6 5. 83 3. 95 29. 8 30. 2 6991 4283 OLS - 0. 610 lnw = β 0 + β 1 Female + e i OLS 31

OLS 2012. 5 4 4 % 18 38 33 33 51 51 29 22 34 27 28 31 43 43 44 40 40 42 41 32 38 37 48 43 Hierarchical Linear Models HLM Raudenbush & Bryk 2002 2010 HLM Cross-Classified Multilevel Model e ijk b 00j c 00k 32

e ijk b 00j c 00k HLM b 10j c 10k Y ijk = π 0jk + π 1jk Female ijk + π 2jk Edu ijk + π 3jk Exp ijk + π 4jk Exp 2 ijk + π 5jk P ijk + π 6jk O ijk + π 7jk O Female ijk + e ijk Y ijk j k i π 0 jk j k π 1 jk j k π p jk j k P O O F e ijk i jk 0 σ 2 π 0jk = θ 0 + b 00j + c 00k + γ 0p Unit j + β 0p Industry k π 1jk = θ 1 + b 10j + c 10k + γ 1p Unit j + β 1p Industry k π p jk = θ p 33

2012. 5 θ 0 θ 1 γ 0p γ 1p β 0p β 1p b 00j c 00k 0 τ b00 τ c00 τ b00 = 0. 06347 *** τ c00 = 0. 12812 *** 6. 4% 0. 06347 / 0. 79969 + 0. 06347 + 0. 12812 12. 9% 80. 7% 5 Y ijk = π 0 jk + e ijk π 0jk = θ 0 + b 00j + c 00k 1 OLS - 0. 610-0. 311 τ b10 = 0. 00305 * 95% - 0. 419-0. 2027-0. 311 ± 槡 0. 00305 τ c10 = 0. 00131 5 Y ijk = π 0 jk + π 1 jk Female ijk + e ijk π 0jk = θ 0 + b 00j + c 00k π 1 jk = θ 1 + b 10j + c 10k 2 4. 5% OLS 11. 7% 34

1998 2003 5 Y ijk = π 0 jk + π 1 jk Edu ijk + π 2jk Exp ijk + π 3jk Exp 2 ijk + e ijk π 0jk = θ 0 + b 00j + c 00k 3 2-0. 311 4-0. 324 Y ijk = π 0 jk + π 1 jk Female ijk + π 2jk Edu ijk + π 3jk Exp ijk + π 4jk Exp 2 ijk + e ijk π 0jk = θ 0 + b 00j + c 00k π 1 jk = θ 1 + b 10j + c 10k 4 π 5 jk = 0. 005 π 6 jk = - 0. 009 5 Y ijk = π 0 jk + π 1 jk Female ijk + π 2jk Edu ijk + π 3jk Exp ijk + π 4jk Exp 2 ijk + π 5 jk F Edu ijk + π 6jk F Exp ijk + π 7jk F Exp 2 ijk + e ijk π 0jk = θ 0 + b 00j + c 00k π 1jk = θ 1 + b 10j + c 10k 3 5 γ 01 = 0. 267 γ 02 = 0. 102 γ 03 = 0. 284 35

2012. 5 β 01 = 1. 132 β 02 = 1. 155 γ 11 = 0. 206 γ 12 = 0. 124 γ 13 = 0. 036 β 11 = 0. 005 β 12 = 0. 008 5 Y ijk = π 0 jk + π 1 jk Female ijk + π 2jk Edu ijk + π 3jk Exp ijk + π 4jk Exp 2 ijk + e ijk π 0jk = θ 0 + b 00j + c 00k + γ 0p Unit j + β 0p Industry k π 1 jk = θ 1 + b 10j + c 10k + γ 1p Unit j + β 1p Industry k P O 6 5-0. 328-0. 302 5 Y ijk = π 0 jk + π 1 jk Female ijk + π 2jk Edu ijk + π 3jk Exp ijk + π 4jk Exp 2 ijk + π 5jk P ijk + π 6jk O ijk + e ijk π 0jk = θ 0 + b 00j + c 00k + γ 0p Unit j + β 0p Industry k π 1 jk = θ 1 + b 10j + c 10k + γ 1p Unit j + β 1p Industry k O Female ijk 6 π 21jk π 25jk 5 6 7 36

Becker 1971 30% OLS - 0. 610 1. 84-0. 311 1. 36 1 2 49. 2% 3. 97 60. 6% 4. 7 2 6-0. 302 2006 Gustafsson & Li 2000 37

38 2012. 5

39

40 2012. 5

41

2012. 5 2 24. 3% 9. 6 / 39. 4 21% 10. 4 /49. 5 1 16. 8% 34% 1 2. 02 1 1. 22 5 3-0. 324-0. 328 2007 2008 Liu et al. 2000 Hauser & Xie 2005 2008 2006 Zhou 2000 42

3 7% 3% 0. 95 6. 95 8. 05 1. 1 6. 79 7. 99 1. 2 1 OLS 11. 7% vs. 9. 3% π 5jk = 0. 005 4 Xie & Hannum 1996 1988 2. 2% 4. 5% 43

2012. 5 1 3. 85 4. 58 4. 47 5. 24 2 Becker 1971 2008 44

2004 3 2003 9 2007 4 2011 2 2006 2003 2 2004 12 1998 5 2008 2 2003 6 1999 2006 5 2008 2 2006 6 2011 4 2005 2 2010 5 2008 1995-2003 2 2008 2002 2 2008 8 2006 3 2006 5 Appleton S. J. Hoddinott & P. Krishnan 1999 The Gender Wage Gap in Three African Countries. Economic Development and Cultural Change 47 2. Becker G. S. 1971 The Economics of Discrimination. IL University of Chicago Press. Brown R. S. M. Moon & B. Zoloth 1980 Incorporating Occupational Attainment in Studies of Male-Female Earnings Differentials. The Journal of Human Resources 15 1. Gustafsson B. & S. Li 2000 Economic Transformation and the Gender Earnings Gap in Urban 45

2012. 5 China. Journal of Population Economics 13 2. Hauser S. & Y. Xie 2005 Temporal and Regional Variation in Earnings Inequality Urban China in Transition between 1988 and 1995. Social Science Research 34. Hughes J. & M. Maurer-Fazio 2002 Effects of Marriage Education and Occupation on the Female /Male Wage Gap in China. Pacific Economic Review 7 1. Jamison D. & J. V. Gaag 1987 Education and Earnings in the People's Republic of China. Economics of Education Review 6 2. Liu P. X. Meng & J. Zhang 2000 Sectoral Gender Wage Differentials and Discrimination in the Transitional Chinese Economy. Journal of Population Economics 13. Oaxaca R. 1973 Male-Female Wage Differentials in Urban Labor Markets. International Economic Review 14 3. Psacharopoulos G. & H. A. Patrinos 2004 Returns to Investment in Education A Further Update. Education Economics 12 2. Raudenbush S. W. & A. S. Bryk 2002 Hierarchical Linear Model Applications and Data Analysis Methods. CA Sage Publications. Xie Y. & E. Hannum 1996 Regional Variation in Earnings Inequality in Reform-era Urban China. American Journal of Sociology 101 4. Zhang J. Y. Zhao A. Park & X. Song 2005 Economic Returns to Schooling in Urban China 1988-2001. Journal of Comparative Economics 33 4. Zhang J. J. Han J. Liu & J. Zhao 2008 Trends in the Gender Earnings Differential in Urban China 1988-2004. Industrial and Labor Relations Review 61 2. Zhou X. G. 2000 Economic Transformation and Income Inequalityin Urban China Evidence from Panel Data. American Journal of Sociology 105 4. 46

SOCIOLOGICAL STUDIES Bimonthly Vol. 27 2012 5 September 2012 PAPER Social Capital and Marketization in the Labor Market Zhang Wenhong & Zhang Li 1 Abstract As a useful force for market is social capital embedded into marketization or not This is the core of the debate between social capital and marketization. According to the existing literature both social capital and marketization are variables which cannot be operated easily. And that's the reason of the appearance of different empirical results on the relationship between them. In this paper the results of data analysis from Jsnet 2009 in 8 Chinese cities show that different measurements of marketization have significant effects on the determination of the relationship between social capital and marketization. But we still find a consistent result among the three measurements of time unit and city marketization enhances the recognition of social capital while reduces the value of this capital at the same time. Human Capital Labor Market Segmentation and Gender Income Gap Deng Feng & Ding Xiaohao 24 Abstract By making use of a nationally representative dataset collected by China Family Panel Studies in 2010 this study applied cross-classified multilevel model to examine how human capital and segmented labor market with three tiers affected gender income gaps. The results indicated that the differences in gender distribution a- mong industries and sectors caused by the allocative effect of education constituted the major part of gender income gaps. There were no significant income differences between men and women when they did the same jobs. The major reason for women's higher rate of return to education was that the less-educated women were more likely to suffer from salary inequality and discrimination. Social Capital in Educational Attainment The perspectives of network resource and social closure Zhao Yandong & Hong Yanbi 47 242