(untitled) (The Pakistan Development Review, 2008)
Ever since the pioneering work on human capital modeling by Becker (1964) and Mincer (1974), estimation of earning potential and wage differentials in terms of differences in human capital endowments has been a favourite topic of research throughout the world. The empirical evidence has established, may be beyond doubt, that low returns are usually associated with low-level of human capital possessed by economic agents. Using appropriate controls for innate abilities, education, experience and training as primary determinants of human capital, the residual differential in wages among differentiated groups (on the basis of gender, race, and region) has often been characterised as discrimination [Blinder (1973) and Oaxaca (1973)]. The empirical estimation made further advances when the issue of sample selection bias was also settled by Heckman (1980). More recently the focus of research has shifted from differentials measured at the conditional mean (average) value to measurement at different points of wage distribution to test the ‘glass ceiling and sticky floor’ hypothesis.1 Some of the studies where quantile regression approach of Koenker and Bassett (1978) and Buchinsky (1998) has been adopted include Bjorklund and Vroman (2001), Dolado and Llorens (2004), and Albrecht, Vuuren, and Vroman (2004). On the basis of this research, the glass ceiling hypothesis has received fair amount of empirical support in much of the developed world. On the other hand, the sticky floor hypothesis has only been observed in some of the countries located in the southern Europe. The focus of present study is on Pakistan with three main objectives. First, to investigate if analysis at the conditional mean is sufficient to explain wage differential or an extensive work covering different points of wage distribution is required to have proper insight to the issue. This would, in turn, enable us to determine which of the two hypotheses, i.e., the glass ceiling or the sticky floor, is prevalent in the country? For this purpose, gender wage differentials at different quantiles, i.e., 10th, 25th, median,