{"title":"大流行期间非药物干预措施对失业的影响","authors":"Edward Kong, Dániel Prinz","doi":"10.2139/ssrn.3581254","DOIUrl":null,"url":null,"abstract":"We use high-frequency Google search data, combined with data on the announcement dates of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic in U.S. states, to isolate the direct impact of state-level NPIs on own-state unemployment in an event study framework. Exploiting the differential timing of the introduction of restaurant and bar limitations, non-essential business closures, stay-at-home orders, large-gatherings bans, school closures, and emergency declarations, we analyze how Google searches for claiming unemployment insurance varied from day to day and across states. We describe a set of assumptions under which proxy outcomes can be used to estimate a causal parameter of interest when data on the outcome of interest are limited. Using this method, we quantify the share of overall growth in unemployment during the COVID-19 pandemic that was directly due to each of these state-level NPIs. We find that between March 14 and 28, restaurant and bar limitations and non-essential business closures can explain 6.0% and 6.4% of UI claims respectively, while the other NPIs did not directly increase own-state UI claims.","PeriodicalId":439996,"journal":{"name":"Health & the Economy eJournal","volume":"308 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"The Impact of Non-Pharmaceutical Interventions on Unemployment During a Pandemic\",\"authors\":\"Edward Kong, Dániel Prinz\",\"doi\":\"10.2139/ssrn.3581254\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We use high-frequency Google search data, combined with data on the announcement dates of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic in U.S. states, to isolate the direct impact of state-level NPIs on own-state unemployment in an event study framework. Exploiting the differential timing of the introduction of restaurant and bar limitations, non-essential business closures, stay-at-home orders, large-gatherings bans, school closures, and emergency declarations, we analyze how Google searches for claiming unemployment insurance varied from day to day and across states. We describe a set of assumptions under which proxy outcomes can be used to estimate a causal parameter of interest when data on the outcome of interest are limited. Using this method, we quantify the share of overall growth in unemployment during the COVID-19 pandemic that was directly due to each of these state-level NPIs. We find that between March 14 and 28, restaurant and bar limitations and non-essential business closures can explain 6.0% and 6.4% of UI claims respectively, while the other NPIs did not directly increase own-state UI claims.\",\"PeriodicalId\":439996,\"journal\":{\"name\":\"Health & the Economy eJournal\",\"volume\":\"308 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health & the Economy eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3581254\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health & the Economy eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3581254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Impact of Non-Pharmaceutical Interventions on Unemployment During a Pandemic
We use high-frequency Google search data, combined with data on the announcement dates of non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic in U.S. states, to isolate the direct impact of state-level NPIs on own-state unemployment in an event study framework. Exploiting the differential timing of the introduction of restaurant and bar limitations, non-essential business closures, stay-at-home orders, large-gatherings bans, school closures, and emergency declarations, we analyze how Google searches for claiming unemployment insurance varied from day to day and across states. We describe a set of assumptions under which proxy outcomes can be used to estimate a causal parameter of interest when data on the outcome of interest are limited. Using this method, we quantify the share of overall growth in unemployment during the COVID-19 pandemic that was directly due to each of these state-level NPIs. We find that between March 14 and 28, restaurant and bar limitations and non-essential business closures can explain 6.0% and 6.4% of UI claims respectively, while the other NPIs did not directly increase own-state UI claims.