Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020.
Identifieur interne : 000006 ( Main/Exploration ); précédent : 000005; suivant : 000007Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020.
Auteurs : Austan Goolsbee [États-Unis] ; Chad Syverson [États-Unis]Source :
- Journal of public economics [ 0047-2727 ] ; 2021.
Abstract
The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from "nonessential" to "essential" businesses and from restaurants and bars toward groceries and other food sellers.
DOI: 10.1016/j.jpubeco.2020.104311
PubMed: 33262548
PubMed Central: PMC7687454
Affiliations:
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An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from "nonessential" to "essential" businesses and from restaurants and bars toward groceries and other food sellers.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">33262548</PMID><DateRevised><Year>2020</Year><Month>12</Month><Day>12</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0047-2727</ISSN><JournalIssue CitedMedium="Print"><Volume>193</Volume><PubDate><Year>2021</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Journal of public economics</Title><ISOAbbreviation>J Public Econ</ISOAbbreviation></Journal><ArticleTitle>Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020.</ArticleTitle><Pagination><MedlinePgn>104311</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.jpubeco.2020.104311</ELocationID><Abstract><AbstractText>The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from "nonessential" to "essential" businesses and from restaurants and bars toward groceries and other food sellers.</AbstractText><CopyrightInformation>© 2020 Published by Elsevier B.V.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Goolsbee</LastName><ForeName>Austan</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>University of Chicago Booth School of Business, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NBER, United States.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Syverson</LastName><ForeName>Chad</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>University of Chicago Booth School of Business, United States.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NBER, United States.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>11</Month><Day>25</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>J Public Econ</MedlineTA><NlmUniqueID>101084660</NlmUniqueID><ISSNLinking>0047-2727</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Borders</Keyword><Keyword MajorTopicYN="N">COVID</Keyword><Keyword MajorTopicYN="N">Consumer activity</Keyword><Keyword MajorTopicYN="N">Economic activity</Keyword><Keyword MajorTopicYN="N">Essential business</Keyword><Keyword MajorTopicYN="N">Lockdown</Keyword><Keyword MajorTopicYN="N">Pandemic</Keyword><Keyword MajorTopicYN="N">Shelter in place</Keyword><Keyword MajorTopicYN="N">Sheltering orders</Keyword><Keyword MajorTopicYN="N">Shutdown</Keyword><Keyword MajorTopicYN="N">States</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>06</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>09</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>10</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>12</Month><Day>2</Day><Hour>5</Hour><Minute>31</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>12</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>12</Month><Day>3</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33262548</ArticleId><ArticleId IdType="doi">10.1016/j.jpubeco.2020.104311</ArticleId><ArticleId IdType="pii">S0047-2727(20)30175-4</ArticleId><ArticleId IdType="pmc">PMC7687454</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
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