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Optimal liability for optimistic tortfeasors

European Journal of Law and Economics volume 41, pages 559–574 (2016)Cite this article

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.

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Notes

  1. Sunstein (2000) considers optimism and the role of law in debiasing this judgment error, considering the special challenges posed by the fact that the vast majority of people believe that they are less likely than other people to be subject to automobile accidents, infection from AIDS, heart attacks, asthma, and many other health risks, even though they do not lack statistical information about these risks in general. See Luppi et al. (2014) for debiasing versus insulating strategies in tort law.

  2. A growing body of law and economics literature, including Sunstein (1997) and Jolls et al. (1998), points out the need of a more accurate understanding of behavior and individual choice in legal context, in order to take into account the shortcomings in human behavior when structuring the law. See Parisi and Smith (2005), Teichman and Zamir (2014) and Zeiler and Teitelbaum (2015) for a complete literature review of behavioral law and economics.

  3. Jolls and Sunstein (2006) discuss the idea of “debiasing through law”, instead of “debiasing law”, i.e. to insulate legal outcomes from the effects of boundedly rational behavior. Debiasing through law is instead aimed at developing legal strategies attempting to reduce or eliminate boundedly rational behavior. Jolls and Sunstein provide a general description of debiasing through law with application to many areas, as consumer safety law, corporate law and property law.

  4. There are two forms of judgment bias that follow from unrealistic optimism: overconfidence bias which implies an overestimation of one’s own ability, and self-serving bias which is a tendency to evaluate evidence or make judgments in a way that benefits oneself (Muren 2004).

  5. Weinstein (1980) asked students to estimate the likelihoods of various events happening to them and showed that they rated their chances of experiencing positive (negative) events significantly above (below) the average for their peers.

  6. See, among others, Forsythe et al. (1999) for overestimation of desirable events and Babcock et al. (1995) for a self-serving bias in an experiment on legal disputes.

  7. According to the better-than-average effect, individuals regard themselves as being above average for positive traits and below average for negative ones. There are five explanations for what causes the better-than-average effect: selective recruitment, egocentrism, focalism, self-versus-aggregate comparison and better-than-average heuristic. See Alicke and Govorun (2005) for a complete review of the better-than-average effect.

  8. Legal scholars introduced the concept of debiasing through law both with reference to procedural rules governing adjudication (Babcock et al. 1995; Babcock et al. 1997) and substantive law (Jolls and Sunstein 2006).

  9. See, among others, Fischhoff 1982; Sanna et al. 2002; Weinstein and Klein 2002. Debiasing may be used instrumentally in conjunction with other cognitive biases. Sherman et al. (2002) note that making an occurrence “available” increases individuals’ estimates of the likelihood of the occurrence, thereby using the availability bias to correct for the optimism bias. An opposite pessimism bias is instead exhibited with respect to the risk of accidents that are either salient, catastrophic or technological in nature (see Sunstein 1997; Jolls 1998; Jolls et al. 1998; see also Slovic et al. 1982; Viscusi and Magat 1987).

  10. Pronin et al. (2002) were the first to identify the blind spot bias, finding that most test subjects were unable to apply general information about biases to their own judgment-making processes. Upon explaining the better-than-average effect to test subjects, Pronin, Lin and Ross discovered that most subjects evaluated themselves as less biased than average. In the analysis that follows, we shall occasionally utilize this terminology, referring to individuals affected by the above-average effect and illusory superiority bias as “optimistic” or affected by “optimism bias.”.

  11. In order to avoid opportunistic reliance on legal forgiveness, forgiveness strategies only adjust the standard of due care to account for some representative level of bias (e.g., the level of optimism of the “average person”), without attempting a factual inquiry as to how affected a particular individual was. Subjective test of the better-than-average effect, if at all desirable should be limited to the proof of absence of bias, to avoid that unbiased parties could opportunistically rely on forgiveness and undertake a lower level of due care. See, e.g., Vaughan v. Menlove (1837) 132 ER 490 (CP) (articulating why courts should be reluctant to tailor the due care level). Tailoring the due care standard to individuals’ eccentricities would, in fact, create a moral hazard problem and/or exacerbate natural optimism of individuals.

  12. See also Luppi et al. 2014 and Luppi and Parisi 2015.

  13. With no loss of generality, the victim and the tortfeasor are treated as representative agents. The model can be easily extended to account for the distribution of optimism bias in the population. In this case, the distortion in beliefs would be exhibited on average in the population.

  14. In general, threats of liability or forgiveness can be combined with debiasing solutions. In the following analysis we assume debiasing efforts by the government have been carried out to the limit of their cost-effectiveness, leaving a residual level of bias, such that \(p^{o} < p\). When debiasing through information is perfectly effective, then \(p^{o} = p\), and parties will make privately optimal choices with respect to care and activity. Conversely, when debiasing through information is only partially effective, then \(p^{o} < p\).

  15. The model could be extended to consider the choice of optimal activity level. Legal forgiveness may mitigate the activity level distortions for optimistic individuals when a defense of comparative negligence is allowed (in both negligence and strict liability regimes). Forgiveness strategies restores the second-best efficient activity level that is typically chosen by the bearer of residual liability. The main idea behind this effect is that forgiveness strategies shift the cost of optimism from one party to the other, increasing the cost of the activity for the residual bearer, notwithstanding his optimistically biased perceptions. In cases of unilateral optimism, activity levels are not corrected when the optimistic party is held residually liable.

  16. It can be seen from inspection of FOCs (3) and (4) in the alternative case of \(p_{xy} < 0\) and \(p_{xy} > 0\).

  17. U.S. v. Carroll Towing Co., 159 F.2d 169 (2d. Cir. 1947). The first articulation of the “Hand Formula” was given in T.J. Hooper, 60 F.2d 737 (2d Cir.), Cert. Denied U.S. 662 (1932).

  18. Vaughan v. Menlove (1837) 132 ER 490 (CP).

  19. Holm v. Sponco Mfg., 324 N.W.2d 207 (1982).

  20. Stetz v. Skaggs Drug Centers, 114 N.M. 465 (1992).

  21. Emery v. Federated Foods, 262 Mont. 83 (1993).

  22. Emery v. Federated Foods, 262 Mont. 91 (1993).

  23. The parody of the “reasonable person” found in Herbert (1935, p. 3) is significant on this point.

References

  • Alicke, M. D., & Govorun, O. (2005). The better-than-average effect. In M. D. Alicke, D. A. Dunning, & J. I. Krueger (Eds.), The self in social judgment. New York: Psychology Press.

    Google Scholar 

  • Babcock, L., Loewenstein, G., & Issacharoff, S. (1997). Creating convergence: Debiasing biased litigants. Law and Social Inquiry, 22, 913–925.

    Article  Google Scholar 

  • Babcock, L., Loewenstein, G., Issacharoff, S., & Camerer, C. (1995). Biased judgments of fairness in bargaining. American Economic Review, 85, 1337–1343.

    Google Scholar 

  • Bigus, J. (2006). Tort liability and probability weighting function according to prospect theory. In Paper presented at the sixteenth annual meeting of the American Law and Economics Association, Berkeley, Calif.

  • Cantril, H. (1938). The prediction of social events. Journal of Abnormal and Social Psychology, 33, 364–389.

    Article  Google Scholar 

  • Choquet, G. (1954). Theory of capacities. Annales de l’institute Fourier, 5, 131–295.

    Article  Google Scholar 

  • Colman, A. M. (2001). The dictionary of psychology. Applied Cognitive Psychology, 15, 349–351.

    Article  Google Scholar 

  • Dari-Mattiacci, G., & Hendriks, E.-S. (2013). Relative fault and efficient negligence: Comparative negligence explained. Review of Law and Economics, 9(1), 1–40.

    Article  Google Scholar 

  • DeJoy, D. M. (1989). The optimism bias and traffic accident risk perception. Accident Analysis and Prevention, 21, 333–340.

    Article  Google Scholar 

  • Eide, E. (2007). Accident liability with rank dependence. Kritische Vierteljahresschrift fu¨r Gesetzgebung und Rechtswissenschaft 1/2:160–71

  • Finn, P., & Bragg, B. W. E. (1986). Perception of the risk of an accident by younger and older drivers. Accident Analysis and Prevention, 18, 289–298.

    Article  Google Scholar 

  • Fischhoff, B. (1982). Debiasing. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases. New York: Cambridge University Press.

    Google Scholar 

  • Forsythe, R., Rietz, T. A., & Ross, T. W. (1999). Wishes, expectations and actions: A survey on price formation in election stock markets. Journal of Economic Behavior & Organization, 39, 83–110.

    Article  Google Scholar 

  • Ganuza, J. J., & Gomez, F. (2008). Realistic standards: Optimal negligence with limited liability. Journal of Legal Studies, 37, 577–594.

    Article  Google Scholar 

  • Ganuza, J. J., & Gomez, F. (2011). Soft negligence standards and the strategic choice of firm size. Journal of Legal Studies, 40, 439–466.

    Article  Google Scholar 

  • Guppy, A. (1992). Subjective probability of accident and apprehension in relation to self-other bias, age, and reported behavior. Accident Analysis and Prevention, 25, 375–382.

    Article  Google Scholar 

  • Herbert, A. P. (1935). Misleading cases (10th ed.). London: Eyre Methuen.

    Google Scholar 

  • Jolls, C. (1998). Behavioral economic analysis of redistributive legal rules. Vanderbilt Law Review, 51, 1653–1677.

    Google Scholar 

  • Jolls, C., & Sunstein, C. R. (2006). Debiasing through law. Journal of Legal Studies, 35, 199–241.

    Article  Google Scholar 

  • Jolls, C., Sunstein, C. R., & Thaler, R. (1998). A behavioral approach to law and economics. Stanford Law Review, 50, 1471–1550.

    Article  Google Scholar 

  • Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.

    Article  Google Scholar 

  • Lichtenstein, S., Slovic, P., Frischhoff, B., Layman, M., & Combs, B. (1978). Judged frequency of lethal events. Journal of Experimental Psychology: Human Learning and Memory, 4, 551–578.

    Google Scholar 

  • Lund, F. H. (1925). The psychology of belief. Journal of Abnormal and Social Psychology, 20, 174–196.

    Article  Google Scholar 

  • Luppi, B., & Francesco, P. (2015, forthcoming). Behavioral approach to Tort law. In J. Teitelbaum & K. Zeiler (Eds.), Handbook of behavioral law and economics. Elgar.

  • Luppi, B., Parisi, F., & Pi, D. (2014). Debiasing vs. insulating strategies in Tort law. In D. Teichman & E. Zamir (Eds.), Oxford handbook of behavioral economics and the law (pp. 143–163). Oxford: Oxford University Press.

    Google Scholar 

  • Matthews, M. L., & Moran, A. R. (1986). Age differences in male drivers’ perception of accident risk: The role of perceived driving ability. Accident Analysis and Prevention, 18, 299–313.

    Article  Google Scholar 

  • McKenna, F. P., Stainer, R. A., & Lewis, C. (1991). Factors underlying illusory self-assessment of driving skill in males and females. Accident Analysis and Prevention, 23, 45–52.

    Article  Google Scholar 

  • Muren, A. (2004). Unrealistic optimism about exogenous events: An experimental test. Research Papers in Economics (Vol. 1), Stockholm University, Department of Economics

  • Parisi, F. (1992). Liability for negligence and judicial discretion. Berkeley, CA: California University Press.

    Google Scholar 

  • Parisi, F., & Smith, V. L. (Eds.). (2005). The law and economics of irrational behavior. Palo Alto, CA: Stanford University Press.

    Google Scholar 

  • Posner, E. A. (2003). Probability errors: Some positive and normative implications for tort and contract law. Supreme Court Economic Review, 11, 125–141.

    Article  Google Scholar 

  • Pronin, E., & Kugler, M. B. (2007). Valuing thoughts, ignoring behavior: The introspection illusion as a source of the bias blind spot. Journal of Experimental Social Psychology, 43(4), 565–578.

    Article  Google Scholar 

  • Pronin, E., Lin, D. Y., & Ross, L. (2002). The bias blind spot: Perceptions of bias in self versus others. Personality and Social Psychology Bulletin, 28, 369–381.

    Article  Google Scholar 

  • Quiggin, J. (1982). A theory of anticipated utility. Journal of Economic Behavior & Organization, 3, 323–343.

    Article  Google Scholar 

  • Quiggin, J. (1993). Generalized expected utility theory: The rank dependent model. Boston: Kluwer Academic Publishers.

    Book  Google Scholar 

  • Sanna, L., Schwarz, N., & Stocker, S. L. (2002). When debiasing backfires: accessible content and accessibility experiences in debiasing hindsight. Journal of Experimental Psychology. Learning, Memory, and Cognition, 28, 497–502.

    Article  Google Scholar 

  • Shavell, S. (1987). Economic analysis of accident law. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Sherman, S. J., Cialdini, R. B., Schwartzman, D. F., & Reynolds, K. D. (2002). Imagining can heighten or lower the perceived likelihood of contracting a disease: The mediating effect of ease of imagery. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment. New York: Cambridge University Press.

    Google Scholar 

  • Slovic, P., Frischhoff, B., & Lichtenstein, S. (1982). Facts versus fears: Understanding perceived risk. In D. Kahnemann, P. Slovic, & A. Tversky (Eds.), Judgement under uncertainty: Heuristics and biases (pp. 462–492). Cambridge: Cambridge University Press.

    Google Scholar 

  • Stiglitz, J. E. (1986). Economics of the public sector. New York: W.W. Norton.

    Google Scholar 

  • Sunstein, C. R. (1997). Behavioral analysis of law. University of Chicago Law Review, 64, 1175–1195.

    Article  Google Scholar 

  • Sunstein, C. R. (2000). Behavioral law and economics. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Svenson, O. (1981). Are we all less risky and more skillful than our fellow drivers? Acta Psychologica, 47, 143–148.

    Article  Google Scholar 

  • Svenson, O., Frischhoff, B., & MacGregor, D. (1985). Perceived driving safety and seatbelt usage. Accident Analysis and Prevention, 17, 119–133.

    Article  Google Scholar 

  • Teichman, D., & Zamir, E. (Eds.). (2014). Oxford handbook of behavioral economics and the law. Oxford: Oxford University Press.

    Google Scholar 

  • Teitelbaum, J. C. (2007). A unilateral accident model under ambiguity. Journal of Legal Studies, 36, 431–477.

    Article  Google Scholar 

  • Viscusi, W. Kip. (2002). Smoke-filled rooms. Chicago: University of Chicago Press.

    Book  Google Scholar 

  • Viscusi, W. K., & Magat, W. A. (1987). Learning about risk: Consumer and worker responses to hazard warnings. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39, 806–820.

    Article  Google Scholar 

  • Weinstein, N. D., & Klein, W. M. (2002). Resistance of Personal Risk Perceptions to Debiasing Interventions. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment. New York: Cambridge University Press.

    Google Scholar 

  • Wenglert, L., & Rosén, A.-S. (2000). Measuring optimism-pessimism from beliefs about future events. Personality and Individual Differences, 28, 717–728.

    Article  Google Scholar 

  • Zeiler, K., & Teitelbaum, J. (2015). Research handbook on behavioral law and economics. Research handbooks in law and economics series. Edward Elgar Publishing Limited.

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Acknowledgments

We are grateful to Theresa Stadheim for her generous research assistance.

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Authors and Affiliations

  1. Department of Economics, University of Modena and Reggio Emilia, Modena, Italy

    Barbara Luppi

  2. Law School, University of Minnesota, Minneapolis, MN, USA

    Francesco Parisi

  3. Department of Economics, University of Bologna, Bologna, Italy

    Francesco Parisi

Authors
  1. Barbara Luppi
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  2. Francesco Parisi
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Correspondence to Francesco Parisi.

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Luppi, B., Parisi, F. Optimal liability for optimistic tortfeasors. Eur J Law Econ 41, 559–574 (2016). https://doi.org/10.1007/s10657-016-9523-6

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  • DOI: https://doi.org/10.1007/s10657-016-9523-6

Keywords

  • Optimism bias
  • Better-than-average effect
  • Blind-spot bias
  • Forgiveness

JEL Classification

  • K13
  • K43
  • D03
  • D81