TECHNOLOGICAL LEARNING AND LABOR MARKET DYNAMICS

• 成果类型: Article
• 署名作者: Gervais, Martin; Jaimovich, Nir; Siu, Henry E.; Yedid-Levi, Yaniv
• 署名单位: University of Iowa; Duke University; National Bureau of Economic Research; University of British Columbia
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/iere.12093
• 发表日期: 2015
• 页码: 27-53
• 关键词: business-cycle; equilibrium unemployment; European unemployment; cyclical behavior; Wage stickiness; Matching models; fluctuations; search; VACANCIES; job

摘要

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.