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"Study hard and make progress every day": Updates on returns to education in China

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  • Chen, Jie
  • Pastore, Francesco

Abstract

In this paper, we apply Generalized Propensity Score matching (GPSM) method, which deals with a continuous treatment variable, to estimate the returns to education in China from 2010 to 2017. Results are compared with OLS estimates from the classical Mincerian equation, as well as estimates from two instrumental variable methods (i.e., 2SLS and Lewbel). We use the Chinese General Social Survey data, including a subset newly released in 2020. We find that returns to education in China experienced a slight decrease in 2010-2015, but reverted back in 2017. With the more exible GPSM method, we also find that returns to university education remain higher than returns to secondary or compulsory education. The GPSM estimates are also closer to OLS estimates, compared to both instrumental variable methods.

Suggested Citation

  • Chen, Jie & Pastore, Francesco, 2021. ""Study hard and make progress every day": Updates on returns to education in China," GLO Discussion Paper Series 787, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:787
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    Cited by:

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    3. Jie Chen & Francesco Pastore, 2024. "Dynamics of returns to vocational education in China: 2010–2017," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.

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    More about this item

    Keywords

    returns to education; endogeneity; continuous treatment; sample selection; GPSM; IV; Lewbel; China;
    All these keywords.

    JEL classification:

    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General

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