Measuring impact of health crises on economies: A staggered synthetic control approach with bias-correction

Abstract

The latest global pandemic demonstrated that the effects of the health crises can be quite considerable for the economies. Despite the negative effects, the understanding of the economic impacts of health crises is constrained due to the limited research in this area. Analyzing the dataset of past health crises and utilizing advanced causal inference method, bias-corrected synthetic control with staggered adoption, we find that health crises cause significant losses for the GDP of the affected countries, and the effects continue for the following years.