Updates on Returns to Education in India: Analysis using PLFS 2018-19 Data

Arbeitspapier

In this paper, we report returns to education in India using unit level data from the nationwide Periodic Labour Force Survey for 2018-19. OLS estimates from the classical Mincerian equation are presented. Various econometric techniques (e.g., conventional IV and heteroskedasticity-based IV models) are used to address endogeneity and sample selection issue. For regular workers, compared to those with no formal education, an additional year of literacy education increases yearly return by 2.3%, primary education by 3.4%, middle school education by 3.7%, secondary school education by 4.5%, higher secondary education by 5.8%, graduate and diploma by 9.8%, and postgraduate and above level of education by 8.2%. We also find a widening of the wage distribution, with striking differences across social groups, sectors, locations. First, returns to middle-school and above level of education are higher for women than for men; second, returns to graduate and above level of education are higher for urban than for rural workers; third, returns to workers in the public sector are higher than returns in the private or third sectors; fourth, returns to the scheduled tribe are the highest across all the castes. Over the last decade, returns to education have reduced. We provide evidence showing that this may be because more people hold higher levels of education qualifications, while the demand for skills remains quite stable. Overall, our policy suggestion is that in India, as in other lowmiddle- income countries, especially in rural areas, it is important to increase primary and secondary level of education in rural areas, and the tertiary level in urban areas and to equalize the life chances of some social groups.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: GLO Discussion Paper ; No. 1016

Classification and Topics

• Classification: Wirtschaft ; Returns to Education ; Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination ; Economics of Gender; Non-labor Discrimination ; Wages, Compensation, and Labor Costs: General ; Single Equation Models; Single Variables: General
• Subject: returns to education ; endogeneity ; sample selection ; India

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Chen, Jie ; Kanjilal-Bhaduri, Sanghamitra ; Pastore, Francesco
• Event: Veröffentlichung
• (who): Global Labor Organization (GLO)
• (where): Essen
• (when): 2022

Further information

• Handle: http://hdl.handle.net/10419/248703
• Last update: 10.03.2025, 11:44 AM CET