TECHNOLOGICAL LEARNING AND LABOR MARKET DYNAMICS |
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Authors: | Martin Gervais Nir Jaimovich Henry E Siu Yaniv Yedid‐Levi |
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Affiliation: | 1. University of Iowa, USA;2. Duke University, U.S.A. and NBER, U.S.A;3. University of British Columbia, Canada, and NBER, U.S.A. |
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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.” |
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