Multidimensional skill mismatch

Fatih Guvenen, Burhan Kuruscu, Satoshi Tanaka, David Wiczer

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

What determines the earnings of a worker relative to his peers in the same occupation? What makes a worker fail in one occupation but succeed in another? More broadly, what are the factors that determine the productivity of a worker-occupation match? To help answer questions like these, we propose an empirical measure of multidimensional skill mismatch that is based on the discrepancy between the portfolio of skills required by an occupation and the portfolio of abilities possessed by a worker for learning those skills. This measure arises naturally in a dynamic model of occupational choice and human capital accumulation with multidimensional skills and Bayesian learning about one's ability to learn skills. Not only does mismatch depress wage growth in the current occupation, it also leaves a scarring effect-by stunting skill acquisition-that reduces wages in future occupations. Mismatch also predicts different aspects of occupational switching behavior. We construct the empirical analog of our skill mismatch measure from readily available US panel data on individuals and occupations and find empirical support for these implications. The magnitudes of these effects are large: moving from the worst-to best-matched decile can improve wages by 11 percent per year for the rest of one's career.

Original languageEnglish (US)
Pages (from-to)210-244
Number of pages35
JournalAmerican Economic Journal: Macroeconomics
Volume12
Issue number1
DOIs
StatePublished - Jan 1 2020

Fingerprint Dive into the research topics of 'Multidimensional skill mismatch'. Together they form a unique fingerprint.

Cite this