Determining the odds of employment in Pakistan

Abstract

Purpose

The paper aims to identify the determinants of employment in Pakistan. In light of the jobless growth Pakistan has experienced starting from 2000, this is a valid concern. The paper discusses the structural relationship between employment and growth in Pakistan and analyzes it empirically within an economic geography framework.

Design/methodology/approach

The paper applies a Logit regression analysis to data from Pakistan Social and Living Standard Measurement Survey for the years 2010, 2012 and 2014. While this survey is published annually, the paper uses data at the district level, which is available only every alternate year. Data are collected at the individual level and can be mapped back to the household level. Each wave of data covers at least 70,000 households. The survey provides data on employment status, health, education, sanitation, economic situation and asset ownership. The analysis is conducted using Stata. The paper uses computer vision to present and trace changing employment patterns in Pakistan over time. To do so, the paper uses MATLAB. The data are transformed to KMV format and the plotting is done using Google Earth.

Findings

The paper shows how household characteristics affect the odds of employment in Pakistan, finding evidence of provincial disparities. Moreover, the paper shows that non-wage income from assets reduces the odds of being employed. The paper identifies the various income thresholds for the five income sources examined to have an impact on the odds of employment.

Originality/value

The novelty of this research is the identification of the determinants of employment in Pakistan and their analysis from the perspective of economic geography. This paper should be useful for policymakers and international financial organizations concerned with structural change in Pakistan.

Citation

Aftab, I. and Mazher, U. (2019), "Determining the odds of employment in Pakistan", Indian Growth and Development Review, Vol. 12 No. 2, pp. 229-241. https://doi.org/10.1108/IGDR-06-2019-0056