Cassan Guilhem, Van Steenvoort Milan
University of Namur, CEPR, DEFIPP, CRED and CEPREMAP, Rue de Bruxelles 61, 5000, Namur, Belgium.
Maastricht University Tongersestraat 53, 6211LM, Maastricht, Netherlands.
SSM Popul Health. 2021 Dec;16:100912. doi: 10.1016/j.ssmph.2021.100912. Epub 2021 Sep 14.
The difference in COVID 19 death rates across political regimes has caught a lot of attention. The "" view suggests that autocracies may be more efficient at putting in place policies that contain COVID 19 spread. On the other hand, the "" view underlines that autocracies may be under reporting their COVID 19 data. We use fixed effect panel regression methods to discriminate between the two sides of the debate. Our results present a more nuanced picture: once pre-determined characteristics of countries are accounted for, COVID 19 death rates equalize across political regimes during the first months of the pandemic, but remain largely different a year into the pandemic. This emphasizes that early differences across political regimes were mainly due to omitted variable bias, whereas later differences are likely due to data manipulation by autocracies. A year into the pandemic, we estimate that this data manipulation may have hidden approximately 400,000 deaths worldwide.
不同政治体制下新冠疫情死亡率的差异引起了广泛关注。一种观点认为，专制政权在实施控制新冠疫情传播的政策方面可能更有效率。另一方面，另一种观点强调，专制政权可能少报了其新冠疫情数据。我们使用固定效应面板回归方法来区分这场辩论的双方观点。我们的结果呈现出一幅更为细致入微的图景：一旦考虑到各国预先确定的特征，在疫情的头几个月里，不同政治体制下的新冠疫情死亡率趋于相等，但在疫情爆发一年后仍存在很大差异。这表明，不同政治体制早期的差异主要是由于遗漏变量偏差，而后期的差异可能是由于专制政权的数据操纵。在疫情爆发一年后，我们估计这种数据操纵可能在全球范围内掩盖了约40万例死亡。
