Arbeitspapier

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

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.

Language
Englisch

Bibliographic citation
Series: GLO Discussion Paper ; No. 787

Classification
Wirtschaft
Returns to Education
Wages, Compensation, and Labor Costs: General
Subject
returns to education
endogeneity
continuous treatment
sample selection
GPSM
Lewbel
China

Event
Geistige Schöpfung
(who)
Chen, Jie
Pastore, Francesco
Event
Veröffentlichung
(who)
Global Labor Organization (GLO)
(where)
Essen
(when)
2021

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Chen, Jie
  • Pastore, Francesco
  • Global Labor Organization (GLO)

Time of origin

  • 2021

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