A Distributional Analysis of the Public-Private Wage Differential in India

23 Pages Posted: 24 Aug 2010 Last revised: 16 Apr 2023

See all articles by Mehtabul Azam

Mehtabul Azam

Oklahoma State University - Stillwater; IZA Institute of Labor Economics

Nishith Prakash

University of Connecticut; Institute for the Study of Labor

Abstract

We investigate the public-private wage differential in India using nationally representative micro data. While the existing literature focuses on average wage differential, we study the differences in the wage distributions. The raw wage differential between public and private sector is positive across the entire distribution for both genders irrespective of area of residence. A quantile regression based decomposition analysis reveals that the differences in observed characteristics (covariate effect) account for only a small part of the wage differential at lower quantiles, but a larger part at higher quantiles. At the very top of the distribution, covariate effect account for a majority of the observed wage differential.

Keywords: quantile regression, public-private wage differential, India

JEL Classification: J3, J45

Suggested Citation

Azam, Mehtabul and Prakash, Nishith, A Distributional Analysis of the Public-Private Wage Differential in India. IZA Discussion Paper No. 5132, Available at SSRN: https://ssrn.com/abstract=1663172 or http://dx.doi.org/10.2139/ssrn.1663172

Mehtabul Azam (Contact Author)

Oklahoma State University - Stillwater ( email )

Stillwater, OK 74078-0555
United States

IZA Institute of Labor Economics ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Nishith Prakash

University of Connecticut ( email )

365 Fairfield Way, U-1063
Storrs, CT 06269-1063
United States

HOME PAGE: http://https://sites.google.com/site/nishithprakash1978/

Institute for the Study of Labor ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
92
Abstract Views
768
Rank
513,302
PlumX Metrics