Ability Matching and Occupational Choice

Abstract

This paper develops and estimates an individual model of occupational choice and learning that allows for correlated learning across occupation-specific abilities. As an individual learns about their occupation-specific ability in one occupation, this experience will be broadly informative about their abilities in all occupations. Workers continually process their entire history of information, which they use to determine when to change careers, as well as which new career to go to. Endogenizing information in this manner has been computationally prohibitive in the past. I estimate the model in an innovative way using the Expectation and Maximization (EM) algorithm. The model is estimated on the National Longitudinal Survey of Youth 1997. The estimates suggest that both direct and indirect learning play an important role in early career wage growth, with those with the lowest levels of education achieving the largest increases.

Keywords: occupational choice, correlated learning, dynamic discrete choice, expectation and maximization algorithm

JEL Classification: J24, J31, J62