DP14362 The Macroeconomics of Automation: Data, Theory, and Policy Analysis
|Author(s):||Nir Jaimovich, Itay Saporta-Eksten, Henry Siu, Yaniv Yedid-Levi|
|Publication Date:||January 2020|
|Date Revised:||April 2020|
|Keyword(s):||automation, labor force participation, Polarization, Retraining, Routine Employment, Unemployment insurance, universal basic income|
|Programme Areas:||Monetary Economics and Fluctuations, Macroeconomics and Growth|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=14362|
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.