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<p>Despite nearly 70 percent of the American public supporting legalization of recreational marijuana, opponents argue that increased marijuana use may diminish motivation, impede cognitive function, and harm health, each of which could adversely affect adults’ economic well-being. This study is the first to explore the impacts of recreational marijuana laws (RMLs) on employment and wages. Difference-in-differences estimates show little evidence that RMLs adversely affect labor market outcomes among most working-age individuals. Rather, our estimates show that RML adoption is associated with an increase in agricultural employment, consistent with the opening of a new licit market. A causal interpretation of our findings is supported by event-study analyses using dynamic difference-in-differences estimates designed to expunge bias due to heterogeneous and dynamic treatment effects, and alternative policy estimates generated using a synthetic control design.</p>

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The effects of recreational marijuana legalization on employment and earnings

  • 期刊论文

  • 发表日期：

    2025年5月10日

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  • Dhaval M. Dave,
  • Yang Liang,
  • Caterina Muratori,
  • Joseph J. Sabia

摘要

Despite nearly 70 percent of the American public supporting legalization of recreational marijuana, opponents argue that increased marijuana use may diminish motivation, impede cognitive function, and harm health, each of which could adversely affect adults’ economic well-being. This study is the first to explore the impacts of recreational marijuana laws (RMLs) on employment and wages. Difference-in-differences estimates show little evidence that RMLs adversely affect labor market outcomes among most working-age individuals. Rather, our estimates show that RML adoption is associated with an increase in agricultural employment, consistent with the opening of a new licit market. A causal interpretation of our findings is supported by event-study analyses using dynamic difference-in-differences estimates designed to expunge bias due to heterogeneous and dynamic treatment effects, and alternative policy estimates generated using a synthetic control design.