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Minimum wage and employment in the U.S.: an application of Bayesian quantile kink regression

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  • Marc K. Chan
  • Akbar Zamanzadeh

Abstract

We examine whether the employment effects of minimum wage depend on unknown tipping points in the labor market. We apply a continuous threshold regression model—regression kink with unknown thresholds—to U.S. state-level panel data in 1993–2016 to estimate the tipping point and quantile employment effects. Overall, we find that the marginal effect is near-zero or mildly negative below the tipping point, and it is considerably more negative above it. The tipping occurs at 50–55% of the state’s median wage among women and 40–45% among men. Simulations of minimum wage reforms reveal nonlinear and asymmetric employment effects.

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  • Marc K. Chan & Akbar Zamanzadeh, 2025. "Minimum wage and employment in the U.S.: an application of Bayesian quantile kink regression," Econometric Reviews, Taylor & Francis Journals, vol. 44(6), pages 673-695, July.
    • Handle: RePEc:taf:emetrv:v:44:y:2025:i:6:p:673-695
    DOI: 10.1080/07474938.2025.2451339
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