IDEAS home Printed from https://ideas.repec.org/a/bla/obuest/v75y2013i3p435-454.html
   My bibliography  Save this article

How Does Education Affect the Earnings Distribution in Urban China?

Author

Listed:
  • Le Wang

Abstract

China's phenomenal growth is accompanied by both relatively low level of standards of living and high inequality. It is widely believe that investing in education could be an effective strategy to promote higher standards of living as well as to reduce inequality. However, little is known about whether this belief is empirically supported. To this end, we employ a recently developed distributional approach to estimate returns to education across the whole earnings distribution in urban China during economic transition. We find that returns to education are generally more pronounced for individuals in the lower tail of the earnings distribution than for those in the upper tail, in stark contrast to the results found in developed countries. Our result implies that education indeed reduces earnings inequality while increasing individuals' earnings. We also find that the returns to education are uniformly larger for women than for men across the distribution. The results suggest the presence of added effects of education on earnings, as opposed to productivity-enhancing effects, for disadvantaged groups. Finally, we find that rates of educational return increased over time for all parts of the earnings distribution.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Le Wang, 2013. "How Does Education Affect the Earnings Distribution in Urban China?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(3), pages 435-454, June.
  • Handle: RePEc:bla:obuest:v:75:y:2013:i:3:p:435-454
    DOI: 10.1111/obes.2013.75.issue-3
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/10.1111/obes.2013.75.issue-3
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1111/obes.2013.75.issue-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Knight, John & Yueh, Linda, 2004. "Job mobility of residents and migrants in urban China," Journal of Comparative Economics, Elsevier, vol. 32(4), pages 637-660, December.
    2. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
    3. John Gibson & Bonggeun Kim, 2007. "Measurement Error in Long-term Retrospective Recall Surveys Of Earnings," Working Papers in Economics 07/03, University of Waikato.
    4. Dennis Tao Yang & Vivian Weijia Chen & Ryan Monarch, 2010. "Rising Wages: Has China Lost Its Global Labor Advantage?," Pacific Economic Review, Wiley Blackwell, vol. 15(4), pages 482-504, October.
    5. Harmon, Colm & Hogan, Vincent & Walker, Ian, 2003. "Dispersion in the economic return to schooling," Labour Economics, Elsevier, vol. 10(2), pages 205-214, April.
    6. George Psacharopoulos & Harry Anthony Patrinos, 2004. "Returns to investment in education: a further update," Education Economics, Taylor & Francis Journals, vol. 12(2), pages 111-134.
    7. Martins, Pedro S. & Pereira, Pedro T., 2004. "Does education reduce wage inequality? Quantile regression evidence from 16 countries," Labour Economics, Elsevier, vol. 11(3), pages 355-371, June.
    8. Fan, Shenggen & Kanbur, Ravi & Zhang, Xiaobo, 2008. "Regional Inequality In China: An Overview," Working Papers 51157, Cornell University, Department of Applied Economics and Management.
    9. John Giles & Albert Park & Meiyan Wang, 2019. "The Great Proletarian Cultural Revolution, Disruptions to Education, and the Returns to Schooling in Urban China," Economic Development and Cultural Change, University of Chicago Press, vol. 68(1), pages 131-164.
    10. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    11. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    12. Patrinos, Harry Anthony & Ridao-Cano, Cris & Sakellariou, Chris, 2006. "Estimating the returns to education : accounting for heterogeneity in ability," Policy Research Working Paper Series 4040, The World Bank.
    13. Henderson, Daniel J. & Polachek, Solomon W. & Wang, Le, 2011. "Heterogeneity in schooling rates of return," Economics of Education Review, Elsevier, vol. 30(6), pages 1202-1214.
    14. Wang, Xiaojun & Fleisher, Belton M. & Li, Haizheng & Li, Shi, 2007. "Access to Higher Education and Inequality: The Chinese Experiment," IZA Discussion Papers 2823, Institute of Labor Economics (IZA).
    15. Schennach, Susanne M., 2008. "Quantile Regression With Mismeasured Covariates," Econometric Theory, Cambridge University Press, vol. 24(4), pages 1010-1043, August.
    16. Fleisher, Belton M. & Sabirianova, Klara & Wang, Xiaojun, 2005. "Returns to skills and the speed of reforms: Evidence from Central and Eastern Europe, China, and Russia," Journal of Comparative Economics, Elsevier, vol. 33(2), pages 351-370, June.
    17. Chernozhukov, Victor & Hansen, Christian, 2008. "Instrumental variable quantile regression: A robust inference approach," Journal of Econometrics, Elsevier, vol. 142(1), pages 379-398, January.
    18. Zhong Zhao, 2005. "Migration, Labor Market Flexibility, and Wage Determination in China: A Review," Labor and Demography 0507009, University Library of Munich, Germany.
    19. Fleisher, Belton M. & Hu, Yifan & Li, Haizheng & Kim, Seonghoon, 2011. "Economic transition, higher education and worker productivity in China," Journal of Development Economics, Elsevier, vol. 94(1), pages 86-94, January.
    20. Chernozhukov, Victor & Hansen, Christian & Jansson, Michael, 2007. "Inference approaches for instrumental variable quantile regression," Economics Letters, Elsevier, vol. 95(2), pages 272-277, May.
    21. Zhang, Junsen & Zhao, Yaohui & Park, Albert & Song, Xiaoqing, 2005. "Economic returns to schooling in urban China, 1988 to 2001," Journal of Comparative Economics, Elsevier, vol. 33(4), pages 730-752, December.
    22. Millimet Daniel L & Wang Le, 2006. "A Distributional Analysis of the Gender Earnings Gap in Urban China," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-50, February.
    23. Fleisher, Belton M. & Wang, Xiaojun, 2004. "Skill differentials, return to schooling, and market segmentation in a transition economy: the case of Mainland China," Journal of Development Economics, Elsevier, vol. 73(1), pages 315-328, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Le, 2012. "Economic transition and college premium in urban China," China Economic Review, Elsevier, vol. 23(2), pages 238-252.
    2. Cui, Yuling & Nahm, Daehoon & Tani, Massimiliano, 2013. "Earnings Differentials and Returns to Education in China, 1995-2008," IZA Discussion Papers 7349, Institute of Labor Economics (IZA).
    3. Lili Kang & Fei Peng, 2012. "A selection analysis of returns to education in China," Post-Communist Economies, Taylor & Francis Journals, vol. 24(4), pages 535-554, March.
    4. Andini, Corrado, 2017. "Tertiary Education for All and Wage Inequality: Policy Insights from Quantile Regression," IZA Policy Papers 132, Institute of Labor Economics (IZA).
    5. Balestra, Simone & Backes-Gellner, Uschi, 2017. "Heterogeneous returns to education over the wage distribution: Who profits the most?," Labour Economics, Elsevier, vol. 44(C), pages 89-105.
    6. Santiago Budria, 2010. "Schooling and the distribution of wages in the European private and public sectors," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 1045-1054.
    7. Wang, Xiaojun & Fleisher, Belton M. & Li, Haizheng & Li, Shi, 2007. "Access to Higher Education and Inequality: The Chinese Experiment," IZA Discussion Papers 2823, Institute of Labor Economics (IZA).
    8. Anil K. Bera & Antonio F. Galvao Jr. & Gabriel V. Montes-Rojas & Sung Y. Park, 2014. "Which Quantile is the Most Informative? Maximum Likelihood, Maximum Entropy and Quantile Regression," World Scientific Book Chapters, in: Kaddour Hadri & William Mikhail (ed.), Econometric Methods and Their Applications in Finance, Macro and Related Fields, chapter 7, pages 167-199, World Scientific Publishing Co. Pte. Ltd..
    9. Hai Fang & Karen N. Eggleston & John A. Rizzo & Scott Rozelle & Richard J. Zeckhauser, 2012. "The Returns to Education in China: Evidence from the 1986 Compulsory Education Law," NBER Working Papers 18189, National Bureau of Economic Research, Inc.
    10. Chen, Yi & Jiang, Sheng & Zhou, Li-An, 2020. "Estimating returns to education in urban China: Evidence from a natural experiment in schooling reform," Journal of Comparative Economics, Elsevier, vol. 48(1), pages 218-233.
    11. Andini, Corrado & Andini, Monica, 2015. "A Note on Unemployment Persistence and Quantile Parameter Heterogeneity," IZA Discussion Papers 8819, Institute of Labor Economics (IZA).
    12. Bang, James T. & Mitra, Aniruddha & Wunnava, Phanindra V., 2016. "Do remittances improve income inequality? An instrumental variable quantile analysis of the Kenyan case," Economic Modelling, Elsevier, vol. 58(C), pages 394-402.
    13. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    14. Chesher, Andrew, 2017. "Understanding the effect of measurement error on quantile regressions," Journal of Econometrics, Elsevier, vol. 200(2), pages 223-237.
    15. Yuanyuan Chen & Shuaizhang Feng, 2011. "Parental Education and Wages: Evidence from China," Frontiers of Economics in China, Higher Education Press, vol. 6(4), pages 568-591, December.
    16. Gu, Tao, 2019. "Wage determination and fixed capital investment in an imperfect financial market: the case of China," MPRA Paper 95986, University Library of Munich, Germany.
    17. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    18. Belloni, Alexandre & Chernozhukov, Victor & Chetverikov, Denis & Fernández-Val, Iván, 2019. "Conditional quantile processes based on series or many regressors," Journal of Econometrics, Elsevier, vol. 213(1), pages 4-29.
    19. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    20. Tommaso Gabrieli & Antonio F. Galvao, Jr. & Antonio F. Galvao, Jr., 2010. "Who Benefits from Reducing the Cost of Formality? Quantile Regression Discontinuity Analysis," Real Estate & Planning Working Papers rep-wp2010-11, Henley Business School, University of Reading.

    More about this item

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J7 - Labor and Demographic Economics - - Labor Discrimination
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:obuest:v:75:y:2013:i:3:p:435-454. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/sfeixuk.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/sfeixuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.