IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v186y2020ics0165176519303921.html
   My bibliography  Save this article

Near-losses in insurance markets: An experiment

Author

Listed:
  • Heinrich, Timo
  • Seifert, Matthias
  • Then, Franziska

Abstract

Several studies report changes in risk taking subsequent to experiencing near-loss events. We disentangle strategic and non-strategic reactions to such near-losses experimentally. We observe that near-losses affect the supply and demand for insurance under strategic uncertainty but not individual evaluations.

Suggested Citation

  • Heinrich, Timo & Seifert, Matthias & Then, Franziska, 2020. "Near-losses in insurance markets: An experiment," Economics Letters, Elsevier, vol. 186(C).
    • Handle: RePEc:eee:ecolet:v:186:y:2020:i:c:s0165176519303921
    DOI: 10.1016/j.econlet.2019.108781
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176519303921
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2019.108781?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. Vincent P. Crawford & Nagore Iriberri, 2007. "Level-k Auctions: Can a Nonequilibrium Model of Strategic Thinking Explain the Winner's Curse and Overbidding in Private-Value Auctions?," Econometrica, Econometric Society, vol. 75(6), pages 1721-1770, November.
    2. Eizo Akiyama & Nobuyuki Hanaki & Ryuichiro Ishikawa, 2017. "It is Not Just Confusion! Strategic Uncertainty in An Experimental Asset Market," Economic Journal, Royal Economic Society, vol. 127(605), pages 563-580, October.
    3. Eizo Akiyama & Nobuyuki Hanaki & Ryuichiro Ishikawa, 2017. "It is Not Just Confusion! Strategic Uncertainty in An Experimental Asset Market," Economic Journal, Royal Economic Society, vol. 127(605), pages 563-580, October.
    4. Jack L. Knetsch & J. A. Sinden, 1984. "Willingness to Pay and Compensation Demanded: Experimental Evidence of an Unexpected Disparity in Measures of Value," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 99(3), pages 507-521.
    5. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    6. Björn Bartling & Florian Engl & Roberto A. Weber, 2015. "Game form misconceptions are not necessary for a willingness-to-pay vs. willingness-to-accept gap," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 72-85, July.
    7. Johannes G. Jaspersen, 2016. "Hypothetical Surveys And Experimental Studies Of Insurance Demand: A Review," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 217-255, January.
    8. Heather Rosoff & Jinshu Cui & Richard S. John, 2013. "Heuristics and biases in cyber security dilemmas," Environment Systems and Decisions, Springer, vol. 33(4), pages 517-529, December.
    9. Robin L. Dillon & Catherine H. Tinsley & Matthew Cronin, 2011. "Why Near‐Miss Events Can Decrease an Individual's Protective Response to Hurricanes," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 440-449, March.
    10. Cheung, Stephen L. & Hedegaard, Morten & Palan, Stefan, 2014. "To see is to believe: Common expectations in experimental asset markets," European Economic Review, Elsevier, vol. 66(C), pages 84-96.
    11. Catherine H. Tinsley & Robin L. Dillon & Matthew A. Cronin, 2012. "How Near-Miss Events Amplify or Attenuate Risky Decision Making," Management Science, INFORMS, vol. 58(9), pages 1596-1613, September.
    12. Robin L. Dillon & Catherine H. Tinsley, 2008. "How Near-Misses Influence Decision Making Under Risk: A Missed Opportunity for Learning," Management Science, INFORMS, vol. 54(8), pages 1425-1440, August.
    13. Arifovic, Jasmina & Ledyard, John, 2007. "Call market book information and efficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1971-2000, June.
    14. Camerer, Colin & Kunreuther, Howard, 1989. "Experimental Markets for Insurance," Journal of Risk and Uncertainty, Springer, vol. 2(3), pages 265-299, September.
    15. Ulrich Schmidt & Stefan Traub, 2009. "An Experimental Investigation of the Disparity Between WTA and WTP for Lotteries," Theory and Decision, Springer, vol. 66(3), pages 229-262, March.
    16. Eisenberger, Roselies & Weber, Martin, 1995. "Willingness-to-Pay and Willingness-to-Accept for Risky and Ambiguous Lotteries," Journal of Risk and Uncertainty, Springer, vol. 10(3), pages 223-233, May.
    17. Gary Charness & Dan Levin, 2009. "The Origin of the Winner's Curse: A Laboratory Study," American Economic Journal: Microeconomics, American Economic Association, vol. 1(1), pages 207-236, February.
    18. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    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. Corgnet, Brice & Hernán-González, Roberto & Kujal, Praveen, 2020. "On booms that never bust: Ambiguity in experimental asset markets with bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    2. Breitmoser, Yves & Schweighofer-Kodritsch, Sebastian, 2019. "Obviousness around the clock," Discussion Papers, Research Unit: Market Behavior SP II 2019-203, WZB Berlin Social Science Center.
    3. Utz Weitzel & Christoph Huber & Jürgen Huber & Michael Kirchler & Florian Lindner & Julia Rose & Lauren Cohen, 2020. "Bubbles and Financial Professionals," The Review of Financial Studies, Society for Financial Studies, vol. 33(6), pages 2659-2696.
    4. Hirota, Shinichi & Huber, Juergen & Stöckl, Thomas & Sunder, Shyam, 2022. "Speculation, money supply and price indeterminacy in financial markets: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 1275-1296.
    5. Penalver, Adrian & Hanaki, Nobuyuki & Akiyama, Eizo & Funaki, Yukihiko & Ishikawa, Ryuichiro, 2020. "A quantitative easing experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    6. Baghestanian, S. & Lugovskyy, V. & Puzzello, D., 2015. "Traders’ heterogeneity and bubble-crash patterns in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 82-101.
    7. Yves Breitmoser & Sebastian Schweighofer-Kodritsch, 2022. "Obviousness around the clock," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 483-513, April.
    8. Hanaki, Nobuyuki & Akiyama, Eizo & Ishikawa, Ryuichiro, 2018. "Behavioral uncertainty and the dynamics of traders’ confidence in their price forecasts," Journal of Economic Dynamics and Control, Elsevier, vol. 88(C), pages 121-136.
    9. Anna Conte & Werner Güth & Paul Pezanis-Christou, 2023. "Strategic ambiguity and risk in alternating pie-sharing experiments," Journal of Risk and Uncertainty, Springer, vol. 66(3), pages 233-260, June.
    10. Shinichi Hirota & Juergen Huber & Thomas Stock & Shyam Sunder, 2018. "Speculation and Price Indeterminacy in Financial Markets: An Experimental Study," Cowles Foundation Discussion Papers 2134, Cowles Foundation for Research in Economics, Yale University.
    11. Kiss, Hubert J. & Kóczy, László Á. & Pintér, Ágnes & Sziklai, Balázs R., 2022. "Does risk sorting explain overpricing in experimental asset markets?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 99(C).
    12. Giamattei, Marcus & Huber, Jürgen & Lambsdorff, Johann Graf & Nicklisch, Andreas & Palan, Stefan, 2020. "Who inflates the bubble? Forecasters and traders in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    13. Ciril Bosch-Rosa & Thomas Meissner & Antoni Bosch-Domènech, 2018. "Cognitive bubbles," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 132-153, March.
    14. Helland, Leif & Iachan, Felipe S. & Juelsrud, Ragnar E. & Nenov, Plamen T., 2021. "Information quality and regime change: Evidence from the lab," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 538-554.
    15. Sylvain Chassang & Christian Zehnder, 2019. "Secure Survey Design in Organizations: Theory and Experiments," Working Papers 2019-22, Princeton University. Economics Department..
    16. Moser, Johannes, 2018. "Hypothetical thinking and the winner's curse: An experimental investigation," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181506, Verein für Socialpolitik / German Economic Association.
    17. Timothy N. Cason & Anya Samek, 2015. "Learning through passive participation in asset market bubbles," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(2), pages 170-181, December.
    18. Nobuyuki Hanaki & Eizo Akiyama & Yukihiko Funaki & Ryuichiro Ishikawa, 2017. "Diversity in Cognitive Ability Enlarges Mispricing in Experimental Asset Markets," GREDEG Working Papers 2017-08, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    19. Llorente-Saguer, Aniol & Sheremeta, Roman M. & Szech, Nora, 2023. "Designing contests between heterogeneous contestants: An experimental study of tie-breaks and bid-caps in all-pay auctions," European Economic Review, Elsevier, vol. 154(C).
    20. Duchêne, Sébastien & Guerci, Eric & Hanaki, Nobuyuki & Noussair, Charles N., 2019. "The effect of short selling and borrowing on market prices and traders’ behavior," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

    More about this item

    Keywords

    Insurance; Markets; Near-losses; Near-miss events; Strategic uncertainty;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    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:186:y:2020:i:c:s0165176519303921. 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.