Anmerkungen:
In: Economic Modelling, Vol. 83, 2019
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 27, 2022 erstellt
Beschreibung:
Work experience is a key variable in earnings function estimates and wage gap decompositions. Because data on actual work experience are rare, studies commonly use proxies, such as potential experience. But potential experience is identical for all individuals of the same age and level of education, so it ignores labor market intermittency because of childbirth and child-rearing—a critical omission when analyzing gender differences in earnings. This paper constructs a better proxy: expected work experience—the sum of the annual probabilities that an individual worked in the past. This measure can be generated using commonly available data on labor force participation rates by age and gender to gauge the probability of past work. Applying the measure to labor force survey data from the Philippines shows that conventional proxies underestimate the contribution of gender differences in work experience in explaining the gender wage gap