[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/wly/canjec/v57y2024i3p989-1027.html
   My bibliography  Save this article

Observational learning and firm dynamics

Author

Listed:
  • Zachary Mahone
  • Filippo Rebessi
Abstract
This article investigates the implications of observational learning for firm dynamics. Because consumers learn through past purchase decisions, monopolistic firms can induce information cascades through prices. We characterize when cascades arise and argue that the fragile nature of cascades is reflected in firm‐level data. We measure fragility using reversals: periods when a firm with historically stable revenues experiences a large, sudden change in earnings. We document a robust pattern that the frequency of reversals among stable firms declines with age, and show a calibration exercise delivers an untargeted age profile in line with the data. Finally, efficiency is discussed. Apprentissage par observation et dynamique des entreprises. Cet article étudie l'incidence de l'apprentissage par observation sur la dynamique des entreprises. Puisque les consommateurs apprennent de leurs décisions d'achat antérieures, les entreprises monopolistiques peuvent induire des cascades d'information par les prix. Nous caractérisons le moment où les cascades arrivent et soutenons que leur nature fragile se reflète dans les données d'entreprise. Nous mesurons la fragilité à l'aide de renversements : des périodes où une entreprise aux recettes historiquement stables vit un grand changement soudain dans ses gains. Nous documentons un modèle robuste où la fréquence des renversements au sein des entreprises stables décline avec l'âge, et montrons un exercice de calibration qui produit un profil d'âge non ciblé conforme aux données. Enfin, nous abordons l'efficience.

Suggested Citation

  • Zachary Mahone & Filippo Rebessi, 2024. "Observational learning and firm dynamics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(3), pages 989-1027, August.
    • Handle: RePEc:wly:canjec:v:57:y:2024:i:3:p:989-1027
    DOI: 10.1111/caje.12729
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/caje.12729
    Download Restriction: no
    File URL: https://libkey.io/10.1111/caje.12729?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
    ---><---

    References listed on IDEAS

    as
    1. Luigi Paciello & Andrea Pozzi & Nicholas Trachter, 2019. "Price Dynamics With Customer Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(1), pages 413-446, February.
    2. Subir Bose & Gerhard Orosel & Marco Ottaviani & Lise Vesterlund, 2006. "Dynamic monopoly pricing and herding," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 910-928, December.
    3. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    4. Hongbin Cai & Yuyu Chen & Hanming Fang, 2009. "Observational Learning: Evidence from a Randomized Natural Field Experiment," American Economic Review, American Economic Association, vol. 99(3), pages 864-882, June.
    5. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    6. Emin M. Dinlersoz & Mehmet Yorukoglu, 2012. "Information and Industry Dynamics," American Economic Review, American Economic Association, vol. 102(2), pages 884-913, April.
    7. Kenneth Hendricks & Alan Sorensen & Thomas Wiseman, 2012. "Observational Learning and Demand for Search Goods," American Economic Journal: Microeconomics, American Economic Association, vol. 4(1), pages 1-31, February.
    8. Subir Bose & Gerhard Orosel & Marco Ottaviani & Lise Vesterlund, 2006. "Dynamic monopoly pricing and herding," RAND Journal of Economics, The RAND Corporation, vol. 37(4), pages 910-928, December.
    9. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    10. Kevin Lane Keller & Donald R. Lehmann, 2006. "Brands and Branding: Research Findings and Future Priorities," Marketing Science, INFORMS, vol. 25(6), pages 740-759, 11-12.
    11. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    12. Emin M. Dinlersoz & Mehmet Yorukoglu, 2012. "Information and Industry Dynamics," American Economic Review, American Economic Association, vol. 102(2), pages 884-913, April.
    13. John Haltiwanger & Ron S. Jarmin & Javier Miranda, 2013. "Who Creates Jobs? Small versus Large versus Young," The Review of Economics and Statistics, MIT Press, vol. 95(2), pages 347-361, May.
    14. Juanjuan Zhang, 2010. "The Sound of Silence: Observational Learning in the U.S. Kidney Market," Marketing Science, INFORMS, vol. 29(2), pages 315-335, 03-04.
    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. Zachary Mahone & Filippo Rebessi, 2019. "Consumer Learning and Firm Dynamics," Department of Economics Working Papers 2019-08, McMaster University.
    2. Liangfei Qiu & Arunima Chhikara & Asoo Vakharia, 2021. "Multidimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Information Systems Research, INFORMS, vol. 32(3), pages 876-894, September.
    3. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    4. Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2018_1716, CEMFI.
    5. Jin Huang, 2017. "To Glance or to Peruse: Observational and Active Learning from Peer Consumers," Working Papers wp2017_1716, CEMFI.
    6. Daniel Garcia & Sandro Shelegia, 2018. "Consumer search with observational learning," RAND Journal of Economics, RAND Corporation, vol. 49(1), pages 224-253, March.
    7. Liangfei Qiu & Asoo Vakharia & Arunima Chhikara, 2019. "Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence," Working Papers 19-01, NET Institute.
    8. Fernandes, Ana P. & Tang, Heiwai, 2014. "Learning to export from neighbors," Journal of International Economics, Elsevier, vol. 94(1), pages 67-84.
    9. Tristan Gagnon-Bartsch & Antonio Rosato, 2024. "Quality Is in the Eye of the Beholder: Taste Projection in Markets with Observational Learning," American Economic Review, American Economic Association, vol. 114(11), pages 3746-3787, November.
    10. Parakhonyak, Alexei & Vikander, Nick, 2023. "Information design through scarcity and social learning," Journal of Economic Theory, Elsevier, vol. 207(C).
    11. Jin-Hyuk Kim & Peter Newberry & Calvin Qiu, 2015. "An Empirical Analysis of a Crowdfunding Platform," Working Papers 15-12, NET Institute.
    12. Davide Crapis & Bar Ifrach & Costis Maglaras & Marco Scarsini, 2017. "Monopoly Pricing in the Presence of Social Learning," Management Science, INFORMS, vol. 63(11), pages 3586-3608, November.
    13. Laurent Cavenaile & Pau Roldan-Blanco, 2021. "Advertising, Innovation, and Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 251-303, July.
    14. Anna K. Edenbrandt & Christian Gamborg & Bo Jellesmark Thorsen, 2020. "Observational learning in food choices: The effect of product familiarity and closeness of peers," Agribusiness, John Wiley & Sons, Ltd., vol. 36(3), pages 482-498, June.
    15. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    16. Jurui Zhang & Yong Liu & Yubo Chen, 2015. "Social Learning in Networks of Friends versus Strangers," Marketing Science, INFORMS, vol. 34(4), pages 573-589, July.
    17. Shijie Lu & Dai Yao & Xingyu Chen & Rajdeep Grewal, 2021. "Do Larger Audiences Generate Greater Revenues Under Pay What You Want? Evidence from a Live Streaming Platform," Marketing Science, INFORMS, vol. 40(5), pages 964-984, September.
    18. Philipp Kircher & Andrew Postlewaite, 2008. "Strategic Firms and Endogenous Consumer Emulation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(2), pages 621-661.
    19. Arieli, Itai & Koren, Moran & Smorodinsky, Rann, 2022. "The implications of pricing on social learning," Theoretical Economics, Econometric Society, vol. 17(4), November.
    20. Catherine Tucker & Juanjuan Zhang & Ting Zhu, 2013. "Days on market and home sales," RAND Journal of Economics, RAND Corporation, vol. 44(2), pages 337-360, June.

    More about this item

    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:wly:canjec:v:57:y:2024:i:3:p:989-1027. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1540-5982 .

    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.