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Social distancing and local bias

dc.contributor.authorLiu, Yi
dc.contributor.authorJin, Justin
dc.contributor.authorMichael Lee-Chin & Family Institute for Strategic Business Studies
dc.date.accessioned2023-01-17T21:25:55Z
dc.date.available2023-01-17T21:25:55Z
dc.date.issued2022-12
dc.description23 p. ; Includes bibliographical references (p. 16); Acknowledgements: Yi Liu acknowledges the financial support from Trent Durham Dean’s Research Awards to fund this project.en_US
dc.description.abstractThis study investigates the effect of social distancing on the local bias of institutional investors. Using SafeGraph’s Social Distancing Metrics data and SEC’s EDGAR 13F filings, we find that stay-at-home duration ratio decreases institutional investors’ local holdings and firms’ institutional ownership in the U.S. We also exploit the lockdown orders across various states during the COVID- 19 pandemic as exogenous shocks to conduct the stacked regression estimation, which yields a similar result. Our channel analysis using abnormal return indicates that social distancing mitigates local bias by constraining the information advantage of local investors rather than alleviating their cognitive bias. Valuation Insight Investors are known to hold relatively larger shares of the securities of firms located nearby. The study finds that this preference is reduced for investors who work from the home more often. The reason uncovered is that the time at home reduces the informational advantage of local investors. Thus, orders to institutional investment firms become less localized. It follows that, all else equal, working from home may reduce the value of investment portfolios.en_US
dc.identifier.urihttp://hdl.handle.net/11375/28227
dc.relation.ispartofseriesMichael Lee-Chin & Family Institute for Strategic Business Studies Working Paper;2022-06
dc.subjectSocial distancingen_US
dc.subjectCOVID-19en_US
dc.subjectLocal biasen_US
dc.subjectInstitutional ownershipen_US
dc.titleSocial distancing and local biasen_US
dc.typeWorking Paperen_US

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