G2TT
来源类型Discussion paper
规范类型论文
来源IDDP14362
DP14362 The Macroeconomics of Automation: Data, Theory, and Policy Analysis
Nir Jaimovich; Itay Saporta Eksten; Yaniv Yedid-Levi; Henry Siu
发表日期2020-01-28
出版年2020
语种英语
摘要During the last four decades, the U.S. has experienced a fall in the employment in middle-wage, "routine-task-intensive," occupations. We analyze the characteristics of those who used to be employed in such occupations and show that this type of individual is nowadays more likely to be out of the labor force or working in low-paying occupations. Based on these findings, we develop a quantitative, general equilibrium model, with heterogeneous agents, labor force participation, occupational choice, and investment in physical and automation capital. We first use the model to evaluate the distributional consequences of automation. We find heterogeneity in its impact across different occupations, leading to a significant polarization in welfare. We then use this framework as a laboratory to evaluate various public policies such as retraining, and explicitly redistributive policies that transfer resources from those who benefit from automation to those who bear the brunt of its costs. We assess the tradeoffs between the aggregate impact and welfare distributional consequences of such policies.
主题Macroeconomics and Growth ; Monetary Economics and Fluctuations
关键词Polarization Automation Routine employment Labor force participation Universal basic income Unemployment insurance Retraining
URLhttps://cepr.org/publications/dp14362-0
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/543256
推荐引用方式
GB/T 7714
Nir Jaimovich,Itay Saporta Eksten,Yaniv Yedid-Levi,et al. DP14362 The Macroeconomics of Automation: Data, Theory, and Policy Analysis. 2020.
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