Estimating Mincerian Earning Function for Engineering Trainings in Pakistan

Abstract

Mincerian Earning Function (MEF), with its standard assumptions, is a dominant model to estimate earning returns to education through its earning-schooling relationship in labor markets. This study explores empirical evidence to estimate the MEF for different years of engineering training in Pakistan. The theoretical model of MEF is used to specify the main determinants of general education, experience, engineering training, and other variables to show a snapshot of technical training and earning relationships in Pakistan. The instrumental variable two stages least square (IV2SLS) technique gives estimates of MEF for the selected sample size of 371 qualified respondents in the fields of engineering education and training in this study. The two-stage random sampling technique is used to collect cross-sectional data, and the results are statistically significant for general education and engineering training in the case of Pakistan. General education, experience, engineering training, and the provinces associations for the respondents likely influence the log earnings of the respondents. The results put forth insightful policy implications for national and provincial public policy processes for human capital formation in the fields of science and technology.