Analysing Econometric Bias and Non-linearity in Returns to Education of Pakistan

This study estimates the returns to education while controlling endogeneity and sample selection biases in Pakistan, over a time period using Ordinary Least Square (OLS), simultaneous approach using both Heckman Sample Selection and Instrumental Variable, and Fixed Effect techniques. Household Integrated Economic Survey (HIES) data for 2004-05 and 2011-12 time periods have been used in this study. The returns to education have been found downward biased in OLS estimates for both time periods. The unbiased real returns to education have increased on average for wage workers over time period. Landholding and Non-earned income have been used as exclusion restrictions to control for sample selection bias in the Heckman Sample Selection technique. The endogeneity bias has been controlled for with the help of parental education as instrument in Instrumental Variable technique. Both techniques have also been used collectively or simultaneously to get more efficient estimate in simultaneous approach. Household Fixed Effect technique has also been used with the assumption that ability and family characteristics largely remain same within family or household. The increase in the unbiased and real returns to education shows that profitability still exists in investing in education whereas experience via skill enhancement reinforces this rise in wage. Sadly, the historic gender and regional discriminations persist or aggravate in wage market. Married persons are getting more in returns relative to the unmarried individuals. Having negative implications for income inequality, Convexity in education-earning relationship in Pakistan has been confirmed by Indicator Function technique for both time periods. Low education prompt low-earning workers who would be unable to bear the schooling cost of their children. This seriously inhibits earning potential making income inequality worse. JEL Classification: I26, I24, J24 Keywords: Returns to Education, Human Capital