Cengiz, D;
Arindrajit, D;
Lindner, A;
Zentler-Munro, D;
(2022)
Seeing Beyond the Trees: Using Machine Learning to Estimate the Impact of Minimum Wages on Labor Market Outcomes.
Journal of Labor Economics
, 40
(S1)
S203-S247.
10.1086/718497.
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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.
| Type: | Article |
|---|---|
| Title: | Seeing Beyond the Trees: Using Machine Learning to Estimate the Impact of Minimum Wages on Labor Market Outcomes |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1086/718497 |
| Publisher version: | https://doi.org/10.1086/718497 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Economics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10140298 |
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