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The policy is always greener: impact heterogeneity of Covid-19 vaccination lotteries in the US

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  • Giulio Grossi

    (University of Florence)

Abstract

Covid-19 vaccination has posed crucial challenges to policymakers and health administrations worldwide. Besides the pressure posed by the pandemic, government administrations have to strive against vaccine hesitancy, which seems to be higher with respect to previous vaccination rollouts. To increase the vaccinated population, Ohio announced a monetary incentive as a lottery for those who were vaccinated. 18 other states followed this first example, with varying results. In this paper, we want to evaluate the effect of such policies within the potential outcome framework using the penalized synthetic control method. In the context of staggered treatment adoption, we estimate the effects at a disaggregated level using a panel dataset. We focused on policy outcomes at the county, state, and supra-state levels, highlighting differences between counties with different social characteristics and time frames for policy introduction. We also studied the treatment effect to see whether the impact of these monetary incentives was permanent or only temporary, accelerating the vaccination of citizens who would have been vaccinated in any case.

Suggested Citation

  • Giulio Grossi, 2023. "The policy is always greener: impact heterogeneity of Covid-19 vaccination lotteries in the US," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(4), pages 1351-1375, October.
    • Handle: RePEc:spr:stmapp:v:32:y:2023:i:4:d:10.1007_s10260-023-00709-x
    DOI: 10.1007/s10260-023-00709-x
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    References listed on IDEAS

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