Quantile Regression Analysis of Monthly Earnings in Pakistan

I. A. ARSHAD, U. YOUNAS, A. W. SHAIKH, M. S. CHANDIO

Abstract


In this study, we empirically analyze the monthly earning distribution of Pakistan. The log of monthly earning is taken as a response variable, while education, experience, age, sex, marital status, nature of work, region, and the provinces are used as explanatory variables. Ordinary least square regression and quantile regression techniques are used to estimate the relationship among these variables. Quantile regression, instead of the point estimate of the conditional mean, can be used to estimate the whole distribution, especially the upper tail and lower tail which we are interested in. The comparison of OLS, and quantile regression shows that quantile regression can provide more informative estimation results. We also use quantile regression’s equivariant property to transform our response variable from log to level.

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