Working Paper: CEPR ID: DP14362
Authors: Nir Jaimovich; Itay Saporta-Eksten; Yaniv Yedid-Levi; Henry Siu
Abstract: 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.
Keywords: polarization; automation; routine employment; labor force participation; universal basic income; unemployment insurance; retraining
JEL Codes: No JEL codes provided
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| automation (L23) | labor market outcomes (J48) |
| routine occupations (J29) | non-participation (J22) |
| routine occupations (J29) | nonroutine manual occupations (J28) |
| automation (L23) | wages of routine occupations (J31) |
| automation (L23) | welfare of nonroutine cognitive workers (J28) |
| retraining (M53) | welfare for some workers (I38) |
| retraining (M53) | wages of existing workers (J31) |