IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v200y2021ics0165176521000161.html
   My bibliography  Save this article

Expectation formation following pandemic events

Author

Listed:
  • An, Zidong
  • Liu, Dingqian
  • Wu, Yuzheng

Abstract

Previous studies find that the degree of information rigidity is negatively associated with natural disaster shocks, recessions, and high economic uncertainty, suggesting that the expectation formation process is state dependent. Matching a large panel data of macroeconomic forecasts to the pandemic data, this letter shows that the degree of information rigidity declines significantly following pandemic events, confirming that the expectation formation process is also driven by unexpected health shocks.

Suggested Citation

  • An, Zidong & Liu, Dingqian & Wu, Yuzheng, 2021. "Expectation formation following pandemic events," Economics Letters, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:ecolet:v:200:y:2021:i:c:s0165176521000161
    DOI: 10.1016/j.econlet.2021.109739
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176521000161
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2021.109739?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Carola Binder, 2020. "Coronavirus Fears and Macroeconomic Expectations," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 721-730, October.
    2. Chang Ma & John Rogers & Sili Zhou, 2023. "Modern Pandemics: Recession and Recovery," Journal of the European Economic Association, European Economic Association, vol. 21(5), pages 2098-2130.
    3. Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
    4. Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
    5. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    6. Kajal Lahiri & Yongchen Zhao, 2016. "Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(2), pages 187-215, December.
    7. repec:zbw:bofitp:2020_016 is not listed on IDEAS
    8. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
    9. Zidong An & João Tovar Jalles & Prakash Loungani, 2018. "How well do economists forecast recessions?," International Finance, Wiley Blackwell, vol. 21(2), pages 100-121, June.
    10. Nordhaus, William D, 1987. "Forecasting Efficiency: Concepts and Applications," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 667-674, November.
    11. Scott R. Baker & Tucker S. McElroy & Xuguang S. Sheng, 2020. "Expectation Formation Following Large, Unexpected Shocks," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 287-303, May.
    12. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    13. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    14. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    15. Binder, Carola, 2017. "Consumer forecast revisions: Is information really so sticky?," Economics Letters, Elsevier, vol. 161(C), pages 112-115.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Xin & Xu, Xiaoguang, 2023. "Monetary policy transmission modeling and policy responses," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

    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. Conrad, Christian & Lahiri, Kajal, 2023. "Heterogeneous expectations among professional forecasters," ZEW Discussion Papers 23-062, ZEW - Leibniz Centre for European Economic Research.
    2. Zidong An & Salem Abo‐Zaid & Xuguang Simon Sheng, 2023. "Inattention and the impact of monetary policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 623-643, June.
    3. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    4. Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    5. Born, Benjamin & Enders, Zeno & Müller, Gernot J., 2023. "On FIRE, news, and expectations," Working Papers 42, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    6. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).
    7. Han, Zhao, 2024. "Asymmetric information and misaligned inflation expectations," Journal of Monetary Economics, Elsevier, vol. 143(C).
    8. Constantin Bürgi & Julio L. Ortiz, 2022. "Overreaction through Anchoring," CESifo Working Paper Series 10193, CESifo.
    9. Constantin Bürgi, 2020. "Expectation Formation and the Persistence of Shocks," Working Papers 2020-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting, revised Sep 2020.
    10. Andrade, Philippe & Gautier, Erwan & Mengus, Eric, 2023. "What matters in households’ inflation expectations?," Journal of Monetary Economics, Elsevier, vol. 138(C), pages 50-68.
    11. Tsiaplias, Sarantis, 2020. "Time-Varying Consumer Disagreement and Future Inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    12. Fiechter, Chad M. & Kuethe, Todd H. & Zhang, Wendong, 2022. "Information Rigidities in Farmland Value Expectations," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322070, Agricultural and Applied Economics Association.
    13. Fiechter, Chad & Kuethe, Todd & Zhang, Wendong, 2023. "Information Rigidities and Farmland Value Expectations," ISU General Staff Papers 202306131414240000, Iowa State University, Department of Economics.
    14. Vereda, Luciano & Savignon, João & Gouveia da Silva, Tarciso, 2021. "A new method to assess the degree of information rigidity using fixed-event forecasts," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1576-1589.
    15. Zaremba, Adam & Cakici, Nusret & Bianchi, Robert J. & Long, Huaigang, 2023. "Interest rate changes and the cross-section of global equity returns," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    16. George-Marios Angeletos & Chen Lian, 2018. "Forward Guidance without Common Knowledge," American Economic Review, American Economic Association, vol. 108(9), pages 2477-2512, September.
    17. Atahan Afsar; José Elías Gallegos; Richard Jaimes; Edgar Silgado Gómez & José Elías Gallegos & Richard Jaimes & Edgar Silgado Gómez, 2020. "Reconciling Empirics and Theory: The Behavioral Hybrid New Keynesian Model," Vniversitas Económica 18560, Universidad Javeriana - Bogotá.
    18. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    19. Zhao Han & Xiaohan Ma & Ruoyun Mao, 2023. "The Role of Dispersed Information in Inflation and Inflation Expectations," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 48, pages 72-106, April.
    20. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.

    More about this item

    Keywords

    Expectation formation; Information rigidity; Forecast smoothing; Pandemic;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

    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:eee:ecolet:v:200:y:2021:i:c:s0165176521000161. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.