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.

Covid-19 疫苗接种给全世界的政策制定者和卫生管理部门带来了严峻的挑战。除了大流行带来的压力外，政府当局还必须努力消除对疫苗的犹豫，与之前的疫苗接种相比，这种犹豫似乎更高。为了增加疫苗接种人口，俄亥俄州宣布对接种疫苗的人进行货币奖励，即抽奖。其他 18 个州也效仿了第一个例子，但结果各不相同。在本文中，我们希望使用惩罚综合控制方法在潜在结果框架内评估此类政策的效果。在采用交错治疗的背景下，我们使用面板数据集在分类水平上估计效果。我们关注县、州和超州各级的政策成果，突出不同社会特征县之间的差异以及政策出台的时间框架。我们还研究了治疗效果，看看这些货币激励措施的影响是永久性的还是暂时的，从而加速了无论如何都会接种疫苗的公民的疫苗接种。