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

TL;DR

This study evaluates the impact of Covid-19 vaccination lotteries in the US, revealing heterogeneous effects across regions and social groups, and analyzing whether incentives had lasting or temporary influences on vaccination rates.

Contribution

It introduces a causal analysis using the penalized synthetic control method to assess staggered vaccination lottery policies at multiple levels.

Findings

Heterogeneous effects across counties and states.

Incentives accelerated vaccination among hesitant populations.

Impact duration varied, with some effects being temporary.

Abstract

Covid-19 vaccination has posed crucial challenges to policymakers and health administrations worldwide. In addition to the pressure posed by the pandemic, government administration has to strive against vaccine hesitancy, which seems to be considerably higher concerning previous vaccination rollouts. To increase the vaccination protection of the population, Ohio announced a monetary incentive as a lottery for those who decided to vaccinate. This first example was followed by 18 other states, 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. We treat with a panel dataset and estimate causal effects at a disaggregated level in the context of staggered treatment adoption. 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 nature of 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.