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A Quantitative Theory of Information, Worker Flows, and Wage Dispersion

Amanda Michaud

American Economic Journal: Macroeconomics, 2018, vol. 10, issue 2, 154-83

Abstract: Employer learning provides a link between wage and employment dynamics. Workers who are selectively terminated when their low productivity is revealed subsequently earn lower wages. If learning is asymmetric across employers, randomly separated high-productivity workers are treated similarly when hired from unemployment, but recover as their next employer learns their type. I provide empirical evidence supporting this link, then study whether employer learning is an empirically important factor in wage and employment dynamics. In a calibrated structural model, learning accounts for 78 percent of wage losses after unemployment, 24 percent of life-cycle wage growth, and 13 percent of cross-sectional dispersion observed in data.

JEL-codes: D83 E24 J23 J24 J31 J62 (search for similar items in EconPapers)
Date: 2018
Note: DOI: 10.1257/mac.20160136
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Citations: View citations in EconPapers (6)

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