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

Abstract

We assess the effect of the minimum wage on labor market outcomes such as employment, unemployment, and labor force participation for most workers affected by the policy. We apply modern machine learning tools to construct demographically-based treatment groups capturing around 75% of all minimum wage workers-a major improvement over the literature which has focused on fairly narrow subgroups where the policy has a large bite (e.g., teens). By exploiting 172 prominent minimum wages between 1979 and 2019 we find that there is a very clear increase in average wages of workers in these groups following a minimum wage increase, while there is little evidence of employment loss. Furthermore, we find no indication that minimum wage has a negative effect on the unemployment rate, on the labor force participation, or on the labor market transitions. Furthermore, we detect no employment or participation responses even for sub-groups that are likely to have a high extensive margin labor supply elasticity-such as teens, older workers, or single mothers. Overall, these findings provide little evidence for changing search effort in response to a minimum wage increase.

Minimum Wages and Optimal Redistribution in the Presence of Taxes and Transfers

“…The results on workers' welfare are consistent with Cengiz et al (2019Cengiz et al ( , 2021 the United Kingdom and find that profit margins fell by almost 30%. Harasztosi and Lindner (2019) find that profits fell around 1% after a large minimum wage increase in Hungary.…”

“…Conversely, the effect on high-skill workers' wages is essentially zero. Both results are consistent with Cengiz et al (2019Cengiz et al ( , 2021's findings on wage, employment, and participation effects. On the other hand, profits per establishment fell, on average, 2.5% after the state-level minimum wage increases.…”

“…As discussed above, the model can accommodate positive wage effects with limited employment effects (Manning, 2021). This can be rationalized without strong participation effects, which Cengiz et al (2021) suggest are negligible. Also, the model can generate wage spillovers between (e.g., Derenoncourt et al, 2021) and within (e.g., Giupponi and Machin, 2018) firms.…”

“…Note, however, that the behavioral response depends on f l (U l ), which may be small. This may result in an equilibrium effect with positive wage effects, limited employment effects, and quantitatively negligible effects on participation, which Cengiz et al (2021) suggest constitutes a puzzle for the random-search literature. 8…”

“…Cengiz et al (2021) argues that the random-search literature needs large participation effects to rationalize positive wage effects with no disemployment effects. Directed search alleviates this force by reallocating applications within the labor market.…”