经济
失业
2019年冠状病毒病(COVID-19)
货币政策
货币经济学
膨胀(宇宙学)
大流行
经济衰退
2019-20冠状病毒爆发
人口经济学
休克(循环)
大萧条
摘要
This paper shows that daily Google trends can be used as an alternative to conventional U.S. data (with alternative frequencies) on unemployment, interest rates, inflation and coronavirus disease 2019 (COVID-19). This information is used to investigate the effects of COVID-19 and the corresponding monetary policy on the U.S. unemployment, both nationally and across U.S. states, by using a structural vector autoregression model. Historical decomposition analyses show that the U.S. unemployment is mostly explained by COVID-19, whereas the contribution of monetary policy is almost none. An investigation based on the U.S. states further suggests that COVID-19 and the corresponding monetary policy conducted based on nationwide economic developments have resulted in unequal changes in state-level unemployment rates, suggesting evidence for distributive effects of national monetary policy.
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