IDEAS home Printed from https://ideas.repec.org/a/kap/ejlwec/v41y2016i3d10.1007_s10657-016-9523-6.html
   My bibliography  Save this article

Optimal liability for optimistic tortfeasors

Author

Listed:
  • Barbara Luppi

    (University of Modena and Reggio Emilia)

  • Francesco Parisi

    (University of Minnesota
    University of Bologna)

Abstract

As Alicke and Govorun (The self in social judgment, Psychology Press, New York, 2005, p. 85) observed, “most people are average, but few people believe it.” Optimism and other forms of inflated perception of the self lead parties to exercise suboptimal precautions when undertaking risky activities and often undermine the incentive effects of tort rules. In this paper, we show that the presence of optimism undermines several critical assumptions, upon which law and economics scholars have relied when modeling the incentive effects of tort law. We construct a model representing the incentives of “optimistic” tortfeasors and victims, and consider mechanisms for mitigating the effects of biased decision-making. We show that in the presence of optimism, comparative negligence rules are preferable to contributory negligence rules (i.e., the traditional equivalence between contributory and comparative negligence does not hold). Further, we discover the surprising conclusion that the most effective way to correct optimism may often simply be to “forgive” it, shielding optimistic individuals from liability, rather than holding them liable for the harms they cause.

Suggested Citation

  • Barbara Luppi & Francesco Parisi, 2016. "Optimal liability for optimistic tortfeasors," European Journal of Law and Economics, Springer, vol. 41(3), pages 559-574, June.
    • Handle: RePEc:kap:ejlwec:v:41:y:2016:i:3:d:10.1007_s10657-016-9523-6
    DOI: 10.1007/s10657-016-9523-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10657-016-9523-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10657-016-9523-6?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. Christine Jolls & Cass R. Sunstein, 2006. "Debiasing through Law," The Journal of Legal Studies, University of Chicago Press, vol. 35(1), pages 199-242, January.
    2. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    3. Babcock, Linda, et al, 1995. "Biased Judgments of Fairness in Bargaining," American Economic Review, American Economic Association, vol. 85(5), pages 1337-1343, December.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Joshua C. Teitelbaum, 2007. "A Unilateral Accident Model under Ambiguity," The Journal of Legal Studies, University of Chicago Press, vol. 36(2), pages 431-477, June.
    6. Dari-Mattiacci Giuseppe & Hendriks Eva S., 2013. "Relative Fault and Efficient Negligence: Comparative Negligence Explained," Review of Law & Economics, De Gruyter, vol. 9(1), pages 1-40, June.
    7. Viscusi, W. Kip, 2002. "Smoke-Filled Rooms," University of Chicago Press Economics Books, University of Chicago Press, edition 1, number 9780226857473, January.
    8. Juan José Ganuza & Fernando Gomez, 2011. "Soft Negligence Standards and the Strategic Choice of Firm Size," The Journal of Legal Studies, University of Chicago Press, vol. 40(2), pages 439-466.
    9. Juan José Ganuza & Fernando Gómez, 2008. "Realistic Standards: Optimal Negligence with Limited Liability," The Journal of Legal Studies, University of Chicago Press, vol. 37(2), pages 577-594, June.
    10. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 83-110, May.
    11. Muren, Astri, 2004. "Unrealistic Optimism about Exogenous Events: An Experimental Test," Research Papers in Economics 2004:1, Stockholm University, Department of Economics.
    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. Andrea Castellano & Fernando Tohmé & Omar O. Chisari, 2020. "Product liability under ambiguity," European Journal of Law and Economics, Springer, vol. 49(3), pages 473-487, June.
    2. Chopard, Bertrand & Obidzinski, Marie, 2021. "Public law enforcement under ambiguity," International Review of Law and Economics, Elsevier, vol. 66(C).
    3. Marie Obidzinski & Yves Oytana, 2022. "Advisory algorithms and liability rules," Working Papers hal-04222291, HAL.
    4. Marie Obidzinski & Yves Oytana, 2022. "Prediction, human decision and liability rules, CRED Working paper No 2022-06," Working Papers hal-04034871, HAL.

    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. Nathalie Chappe & Raphaël Giraud, 2013. "Confidence, Optimism and Litigation: A Litigation Model under Ambiguity," Working Papers hal-04287896, HAL.
    2. Christine Jolls, 2007. "Behavioral Law and Economics," NBER Working Papers 12879, National Bureau of Economic Research, Inc.
    3. Chopard, Bertrand & Obidzinski, Marie, 2021. "Public law enforcement under ambiguity," International Review of Law and Economics, Elsevier, vol. 66(C).
    4. Kaluszka, Marek & Krzeszowiec, Michał, 2012. "Pricing insurance contracts under Cumulative Prospect Theory," Insurance: Mathematics and Economics, Elsevier, vol. 50(1), pages 159-166.
    5. Serrao, Amilcar & Coelho, Luis, 2004. "Cumulative Prospect Theory: A Study Of The Farmers' Decision Behavior In The Alentejo Dryland Region Of Portugal," 2004 Annual meeting, August 1-4, Denver, CO 20245, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Massimiliano Amarante & Mario Ghossoub & Edmund Phelps, 2012. "Contracting for Innovation under Knightian Uncertainty," Cahiers de recherche 18-2012, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    7. Mohammed Abdellaoui & Olivier L’Haridon & Horst Zank, 2010. "Separating curvature and elevation: A parametric probability weighting function," Journal of Risk and Uncertainty, Springer, vol. 41(1), pages 39-65, August.
    8. Xue Dong He & Sang Hu & Jan Obłój & Xun Yu Zhou, 2017. "Technical Note—Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model," Operations Research, INFORMS, vol. 65(1), pages 97-103, February.
    9. Yaron Azrieli & Christopher P. Chambers & Paul J. Healy, 2020. "Incentives in experiments with objective lotteries," Experimental Economics, Springer;Economic Science Association, vol. 23(1), pages 1-29, March.
    10. Ariane Charpin, 2018. "Tests des modèles de décision en situation de risque. Le cas des parieurs hippiques en France," Revue économique, Presses de Sciences-Po, vol. 69(5), pages 779-803.
    11. Moshe Levy & Haim Levy, 2013. "Prospect Theory: Much Ado About Nothing?," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 7, pages 129-144, World Scientific Publishing Co. Pte. Ltd..
    12. Bocqueho, Geraldine & Jacquet, Florence & Reynaud, Arnaud, 2011. "Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114257, European Association of Agricultural Economists.
    13. Markus Dertwinkel-Kalt & Jonas Frey, 2020. "Optimal Stopping in a Dynamic Salience Model," CESifo Working Paper Series 8496, CESifo.
    14. Zimper, Alexander, 2012. "Asset pricing in a Lucas fruit-tree economy with the best and worst in mind," Journal of Economic Dynamics and Control, Elsevier, vol. 36(4), pages 610-628.
    15. Luís Santos-Pinto & Adrian Bruhin & José Mata & Thomas Åstebro, 2015. "Detecting heterogeneous risk attitudes with mixed gambles," Theory and Decision, Springer, vol. 79(4), pages 573-600, December.
    16. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet E., 2014. "Dual criteria decisions," Journal of Economic Psychology, Elsevier, vol. 41(C), pages 101-113.
      • Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet, 2009. "Dual Criteria Decisions," Working Papers 02-2009, Copenhagen Business School, Department of Economics.
    17. Chiu, W. Henry, 2019. "Comparative statics in an ordinal theory of choice under risk," Mathematical Social Sciences, Elsevier, vol. 101(C), pages 113-123.
    18. Yokoo, Hide-Fumi & Arimura, Toshi H. & Chattopadhyay, Mriduchhanda & Katayama, Hajime, 2023. "Subjective risk belief function in the field: Evidence from cooking fuel choices and health in India," Journal of Development Economics, Elsevier, vol. 161(C).
    19. Segal, Uzi, 1987. "The Ellsberg Paradox and Risk Aversion: An Anticipated Utility Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(1), pages 175-202, February.
    20. Riddel, Mary C. & Shaw, W. Douglass, 2006. "A Theoretically-Consistent Empirical Non-Expected Utility Model of Ambiguity: Nuclear Waste Mortality Risk and Yucca Mountain," Pre-Prints 23964, Texas A&M University, Department of Agricultural Economics.

    More about this item

    Keywords

    Optimism bias; Better-than-average effect; Blind-spot bias; Forgiveness;
    All these keywords.

    JEL classification:

    • K13 - Law and Economics - - Basic Areas of Law - - - Tort Law and Product Liability; Forensic Economics
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:kap:ejlwec:v:41:y:2016:i:3:d:10.1007_s10657-016-9523-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.