Seeing beyond the Trees: Using Machine Learning to Estimate the Impact of Minimum Wages on Labor Market Outcomes

A-Tier
Journal: Journal of Labor Economics
Year: 2022
Volume: 40
Issue: S1
Pages: S203 - S247

Authors (4)

Doruk Cengiz (not in RePEc) Arindrajit Dube (University of Massachusetts-Am...) Attila Lindner (not in RePEc) David Zentler-Munro (not in RePEc)

Score contribution per author:

1.009 = (α=2.02 / 4 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We assess the effect of the minimum wage on labor market outcomes. First, we apply modern machine learning tools to predict who is affected by the policy. Second, we implement an event study using 172 prominent minimum wage increases between 1979 and 2019. We find a clear increase in wages of affected workers and no change in employment. Furthermore, minimum wage increases have no effect on the unemployment rate, labor force participation, or labor market transitions. Overall, these findings provide little evidence of changing search effort in response to a minimum wage increase.

Technical Details

RePEc Handle
repec:ucp:jlabec:doi:10.1086/718497
Journal Field
Labor
Author Count
4
Added to Database
2026-01-25