The changing pattern of wage returns to education in post-reform China
M Asadullah () and
Structural Change and Economic Dynamics, 2020, vol. 53, issue C, 137-148
This paper examines the labor market returns to schooling in China during 2010–2015 by using two rounds of the China General Social Survey data. While our OLS estimates based on Mincerian earnings function confirm the importance of human capital in China's post-reform economy, they highlight a number of important changes in the labor market performance of educated workers. The average returns to schooling have declined during the study period, albeit modestly. The fall in returns is much larger in urban locations, coastal regions and among women (from 10.4%, 9.9% and 7.8% in 2010 to 8.3%, 7.8% and 6.3% in 2015 respectively). Workers with university diplomas and good English language skills continue to enjoy a high wage return. These findings are unchanged regardless of model specifications and corrections for endogeneity bias using conventional as well as Lewbel instrumental variable approaches. We discuss the potential explanations for the observed changes and their policy implications.
Keywords: Gender gap; Schooling; English-language premium; Selection bias; Post-reform China (search for similar items in EconPapers)
JEL-codes: I26 J30 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:streco:v:53:y:2020:i:c:p:137-148
Access Statistics for this article
Structural Change and Economic Dynamics is currently edited by F. Duchin, H. Hagemann, M. Landesmann, R. Scazzieri, A. Steenge and B. Verspagen
More articles in Structural Change and Economic Dynamics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().