Public versus Private Sector Wage Gap in Egypt: Evidence from Quantile Regression on Panel Data

Arbeitspapier

This paper considers the public and private sector wage earners in Egypt and examines their wage distribution during 1998-2012 using Egyptian Labor Market Panel Survey. We estimate the public-private sector wage gap with Mincer wage equations both at the mean and at different quantiles of the wage distribution. In this process we take into account observable and unobservable characteristics of the individuals using the panel feature of the data with a fixed effects model. We address sector of employment selection issue for both males and females. We find that there is very little evidence of sample selection in our data. Therefore, we present both the selection corrected results and the results with no selection correction. We find a persistent public sector wage penalty for males and public sector wage premium for females in the face of extensive sensitivity checks. They are larger when unobserved heterogeneity is taken into account for males but insignificant for females. They are similar across the quantiles for males but, smaller at the top than at the bottom of the conditional wage distribution for females. We further examine the public sector wage gap over time and in different sub-groups according to age and education. The public sector wage penalty for males has decreased recently over time and is larger for the better educated and younger. We also find substantial regional differences in public sector wage gap for males. ****** Please cite the published version: Aysit Tansel, Halil I. Keskin and Zeynel Abidin Ozdemir (2020), "Public-Private Sector Wage Gap by Gender in Egypt: Evidence from Quantile Regression on Panel Data, 1998-2018", World Development, vol. 135: November 2020. https://doi.org/10.1016/j.worlddev.2020.105060 ******

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: GLO Discussion Paper ; No. 260

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Economics of Gender; Non-labor Discrimination ; Wage Level and Structure; Wage Differentials ; Public Sector Labor Markets
• Thema: Public Sector ; Private Sector ; Wage Gap ; Gender ; Sample Selection ; Quantile Regression ; Panel Data ; Egypt

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Tansel, Aysit ; Keskin, Halil Ibrahim ; Ozdemir, Zeynel Abidin
• Ereignis: Veröffentlichung
• (wer): Global Labor Organization (GLO)
• (wo): Maastricht
• (wann): 2018

Weitere Informationen

• DOI: doi:10.1016/j.worlddev.2020.105060
• Handle: http://hdl.handle.net/10419/183175
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ