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Title: Returns to schooling in Palestine: a Bayesian approach

Authors: Mohsen Ayyash; Tareq Sadeq; Siok Kun Sek

Addresses: School of Mathematical Sciences, University Sains Malaysia, 11800 USM, Penang, Malaysia ' Department of Economics, Faculty of Business and Economics, Birzeit University, Birzeit, West Bank 627, Palestine ' School of Mathematical Sciences, University Sains Malaysia, 11800 USM, Penang, Malaysia

Abstract: This paper presents an empirical method to find more efficient estimates of returns to schooling using Bayesian linear regression instead of OLS method. The private returns to schooling in Palestine using the Palestinian labour force survey (PLFS) for the year 2017 have been estimated, where on average, males earn 40.7% more than females. Separate regressions have been performed for males and females, in which the returns to schooling for females are found higher than their males' counterparts. Bayesian inference has also been applied into Heckman two-step procedure with logit and probit models to correct self-selection bias for females' sample. It is found that logit Heckman correction yields positive and higher coefficient of years of schooling than probit and OLS. The wage disparities in Palestine have been found influenced by various factors like age, sex, and occupational groups. These findings are useful for policymakers to plan for future investment in higher education.

Keywords: Bayesian linear regression; wages; returns to schooling.

DOI: 10.1504/IJEED.2020.104285

International Journal of Education Economics and Development, 2020 Vol.11 No.1, pp.37 - 57

Received: 06 Nov 2018
Accepted: 08 Apr 2019

Published online: 26 Dec 2019 *

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