IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/27439.html
   My bibliography  Save this paper

Scarring Body and Mind: The Long-Term Belief-Scarring Effects of COVID-19

Author

Listed:
  • Julian Kozlowski
  • Laura Veldkamp
  • Venky Venkateswaran

Abstract

The largest economic cost of the COVID-19 pandemic could arise from changes in behavior long after the immediate health crisis is resolved. A potential source of such a long-lived change is scarring of beliefs, a persistent change in the perceived probability of an extreme, negative shock in the future. We show how to quantify the extent of such belief changes and determine their impact on future economic outcomes. We find that the long-run costs for the U.S. economy from this channel is many times higher than the estimates of the short-run losses in output. This suggests that, even if a vaccine cures everyone in a year, the COVID-19 crisis will leave its mark on the US economy for many years to come.

Suggested Citation

  • Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2020. "Scarring Body and Mind: The Long-Term Belief-Scarring Effects of COVID-19," NBER Working Papers 27439, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:27439
    Note: AP EFG
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w27439.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lars Peter Hansen & Thomas J Sargent, 2014. "Beliefs, Doubts and Learning: Valuing Macroeconomic Risk," World Scientific Book Chapters, in: UNCERTAINTY WITHIN ECONOMIC MODELS, chapter 10, pages 331-377, World Scientific Publishing Co. Pte. Ltd..
    2. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    3. James H. Stock, 2020. "Data Gaps and the Policy Response to the Novel Coronavirus," NBER Working Papers 26902, National Bureau of Economic Research, Inc.
    4. Veldkamp, Laura & Wolfers, Justin, 2007. "Aggregate shocks or aggregate information? Costly information and business cycle comovement," Journal of Monetary Economics, Elsevier, vol. 54(Supplemen), pages 37-55, September.
    5. Vadim Elenev & Tim Landvoigt & Stijn Van Nieuwerburgh, 2022. "Can the covid bailouts save the economy?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 37(110), pages 277-330.
    6. Kristoffer P. Nimark, 2014. "Man-Bites-Dog Business Cycles," American Economic Review, American Economic Association, vol. 104(8), pages 2320-2367, August.
    7. Pablo D. Fajgelbaum & Edouard Schaal & Mathieu Taschereau-Dumouchel, 2017. "Uncertainty Traps," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1641-1692.
    8. Fernando E. Alvarez & David Argente & Francesco Lippi, 2020. "A Simple Planning Problem for COVID-19 Lockdown," NBER Working Papers 26981, National Bureau of Economic Research, Inc.
    9. François Gourio, 2013. "Credit Risk and Disaster Risk," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(3), pages 1-34, July.
    10. Nir Jaimovich & Sergio Rebelo, 2009. "Can News about the Future Drive the Business Cycle?," American Economic Review, American Economic Association, vol. 99(4), pages 1097-1118, September.
    11. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2020. "The Tail That Wags the Economy: Beliefs and Persistent Stagnation," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2839-2879.
    12. Timothy Cogley & Thomas J. Sargent, 2005. "The conquest of US inflation: Learning and robustness to model uncertainty," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 528-563, April.
    13. Velde, François R., 2022. "What Happened to the U.S. Economy during the 1918 Influenza Pandemic? A View Through High-Frequency Data," The Journal of Economic History, Cambridge University Press, vol. 82(1), pages 284-326, March.
    14. Beaudry, Paul & Portier, Franck, 2004. "An exploration into Pigou's theory of cycles," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1183-1216, September.
    15. Carvalho, V & Garcia, Juan R. & Hansen, S. & Ortiz, A. & Rodrigo, T. & More, J. V. R., 2020. "Tracking the COVID-19 Crisis with High-Resolution Transaction Data," Cambridge Working Papers in Economics 2030, Faculty of Economics, University of Cambridge.
    16. Miklós Koren & Rita Pető, 2020. "Business disruptions from social distancing," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-14, September.
    17. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    18. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    19. Oscar Jorda & Sanjay R. Singh & Alan M. Taylor, 2022. "Longer-Run Economic Consequences of Pandemics," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 166-175, March.
    20. Julia K. Thomas & Aubhik Khan, 2011. "Default Risk and Aggregate Fluctuations in an Economy with Production Heterogeneity," 2011 Meeting Papers 1333, Society for Economic Dynamics.
    21. Lars Peter Hansen, 2007. "Beliefs, Doubts and Learning: Valuing Economic Risk," NBER Working Papers 12948, National Bureau of Economic Research, Inc.
    22. Andrew Atkeson, 2020. "What Will be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," Staff Report 595, Federal Reserve Bank of Minneapolis.
    23. Van Nieuwerburgh, Stijn & Veldkamp, Laura, 2006. "Learning asymmetries in real business cycles," Journal of Monetary Economics, Elsevier, vol. 53(4), pages 753-772, May.
    24. Jonathan Eaton & Mark Gersovitz, 1981. "Debt with Potential Repudiation: Theoretical and Empirical Analysis," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 48(2), pages 289-309.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2019. "The Tail That Keeps the Riskless Rate Low," NBER Macroeconomics Annual, University of Chicago Press, vol. 33(1), pages 253-283.
    2. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2020. "The Tail That Wags the Economy: Beliefs and Persistent Stagnation," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2839-2879.
    3. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2015. "The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation," Working Papers 15-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    4. Anna Orlik & Laura Veldkamp, 2014. "Understanding Uncertainty Shocks and the Role of Black Swans," NBER Working Papers 20445, National Bureau of Economic Research, Inc.
    5. Tian, Can, 2022. "Learning and firm dynamics in a stochastic equilibrium," Journal of Economic Theory, Elsevier, vol. 203(C).
    6. Laura Veldkamp & Anna Orlik, 2016. "Understanding Uncertainty Shocks and the Role of the Black Swan," Working Papers 16-04, New York University, Leonard N. Stern School of Business, Department of Economics.
    7. Laura Veldkamp, 2022. "Understanding Uncertainty Shocks and the Role of Black Swans," Finance and Economics Discussion Series 2022-083, Board of Governors of the Federal Reserve System (U.S.).
    8. Hinterlang, Natascha & Moyen, Stephane & Röhe, Oke & Stähler, Nikolai, 2023. "Gauging the effects of the German COVID-19 fiscal stimulus package," European Economic Review, Elsevier, vol. 154(C).
    9. Hikaru Saijo & Cosmin Ilut, 2015. "Learning, Confidence, and Business Cycles," 2015 Meeting Papers 917, Society for Economic Dynamics.
    10. Schaal, Edouard & Taschereau-Dumouchel, Mathieu, 2023. "Herding through booms and busts," Journal of Economic Theory, Elsevier, vol. 210(C).
    11. Garriga, Carlos & Manuelli, Rody & Sanghi, Siddhartha, 2022. "Optimal management of an epidemic: Lockdown, vaccine and value of life," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    12. Çakmaklı, Cem & Demiralp, Selva & Özcan, Şebnem Kalemli & Yeşiltaş, Sevcan & Yıldırım, Muhammed A., 2023. "COVID-19 and emerging markets: A SIR model, demand shocks and capital flows," Journal of International Economics, Elsevier, vol. 145(C).
    13. Masciandaro, Donato & Goodhart, Charles & Ugolini, Stefano, 2021. "Pandemic recession and helicopter money: Venice, 1629–1631," Financial History Review, Cambridge University Press, vol. 28(3), pages 300-318, December.
    14. Łukasz Rachel, 2020. "An Analytical Model of Covid-19 Lockdowns," Discussion Papers 2029, Centre for Macroeconomics (CFM).
    15. Laura Veldkamp & Anna Orlik, 2014. "Uncertainty Shocks and the Role of the Black Swan," 2014 Meeting Papers 275, Society for Economic Dynamics.
    16. Hikaru Saijo, 2014. "The Uncertainty Multiplier and Business Cycles," Working Papers e067, Tokyo Center for Economic Research.
    17. Tortorice, Daniel L, 2018. "The business cycle implications of fluctuating long run expectations," Journal of Macroeconomics, Elsevier, vol. 58(C), pages 266-291.
    18. Greg Kaplan & Benjamin Moll & Giovanni L. Violante, 2020. "The Great Lockdown and the Big Stimulus: Tracing the Pandemic Possibility Frontier for the U.S," NBER Working Papers 27794, National Bureau of Economic Research, Inc.
    19. Edouard Schaal & Mathieu Taschereau-Dumouchel, 2020. "Herding cycles," Economics Working Papers 1714, Department of Economics and Business, Universitat Pompeu Fabra, revised May 2023.
    20. Funke, Michael & Tsang, Andrew, 2020. "The People’s bank of China’s response to the coronavirus pandemic: A quantitative assessment," Economic Modelling, Elsevier, vol. 93(C), pages 465-473.

    More about this item

    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:27439. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.