TECHNOLOGICAL LEARNING AND LABOR MARKET DYNAMICS

B-Tier
Journal: International Economic Review
Year: 2015
Volume: 56
Issue: 1
Pages: 27-53

Authors (4)

Martin Gervais (University of Georgia) Nir Jaimovich (not in RePEc) Henry E. Siu (University of British Columbia) Yaniv Yedid‐Levi (not in RePEc)

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The search‐and‐matching model of the labor market fails to match two important business cycle facts: (i) a high volatility of unemployment relative to labor productivity, and (ii) a mild correlation between these two variables. We address these shortcomings by focusing on technological learning‐by‐doing: the notion that it takes workers' time using a technology before reaching their full productive potential with it. We consider a novel source of business cycles, namely, fluctuations in the speed of technological learning, and show that a search‐and‐matching model featuring such shocks can account for both facts. Moreover, our model provides a new interpretation of recently discussed “news shocks.”

Technical Details

RePEc Handle
repec:wly:iecrev:v:56:y:2015:i:1:p:27-53
Journal Field
General
Author Count
4
Added to Database
2026-01-25