Working Paper: NBER ID: w27122
Authors: Nir Jaimovich; Itay Saporta-Eksten; Henry E. Siu; Yaniv Yedid-Levi
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: Automation; Labor Market; Public Policy; Welfare; General Equilibrium Model
JEL Codes: E24; E25; E61
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| automation (L23) | decline in likelihood of individuals with routine occupational characteristics working in routine jobs (J29) |
| routine occupational characteristics (J28) | transition to nonparticipation in labor force (J26) |
| routine occupational characteristics (J28) | employment in nonroutine manual occupations (J69) |
| transition from routine jobs (J63) | decline in wages and welfare (I38) |
| nonroutine cognitive workers (J24) | substantial gains in wages (J31) |
| automation (L23) | occupational transitions (J62) |
| automation (L23) | welfare outcomes (I38) |