The Price of Punishment
The prospect of punitive damages poses a particularly difficult challenge for parties in litigation. In the first place, there is generally so much uncertainty about their award and scale that parties have great difficulty in estimating them. For corporate defendants there are important questions about materiality and appropriate accounting disclosure. For general counsel and financial managers, the possibility of a large punitive damage award represents a unique valuation and risk management challenge. In extreme cases, punitive damage risk may become a corporate governance issue involving questions of financial distress, solvency and stock valuation impact. And through all of these issues, there is the question of how the prospect of punitive damages should influence the settlement bargaining process. In short, given so much uncertainty, how are we to put a price on punishment?
While few cases involving punitive damage risk ever proceed to court, research has suggested a “shadow effect” of punitive damages in settlement negotiations. In this essay, we examine some of the difficulties associated with pricing punitive damages and provide an overview of our own quantitative approach.
Courts and scholars have long recognized difficulties with the application of punitive damages: how they should be determined and whether or not they achieve their purpose. At issue is whether the inherent uncertainty surrounding punitive damages undermines their purpose. In Exxon Shipping Co. v Baker , the Supreme Court of the United States refers to the “stark unpredictability of punitive awards” as “the real problem”. However, this problem is not just a matter of legal policy, but a very real economic concern for parties seeking to settle disputes involving the potential for punitive damage awards.
If punitive damages are so completely uncertain, how do litigants currently reach a settlement over their potential award? And more importantly, how should they? To understand this issue we must first examine the nature of punitive damages and the uncertainty attending them.
There are two dimensions to the unpredictability referred to by the Supreme Court. The first is the question of whether or not punitive damages will be awarded. The second is the quantum of damages if they are. Neither of which offers any measure of certainty for litigants. The overall infrequency with which punitive damages are awarded might provide initial comfort for fearful defendants, but then the potential for their surprise application can be equally vexing. The uncertainty in the finding of a punitive award is then only compounded by a very wide and uncertain range in the quantum of damages themselves. While the average ratio of punitive damages to compensatory damages is usually close to unity, outlier judgments can provide for enormous variance. Hersch and Viscusi (2010) observe that in a sample of “blockbuster” punitive damage cases (those over $100 million) the median ratio of punitive damages to compensatory damages was a staggering 8.85.
THE SHADOW EFFECT
The potential for punitive damage awards at trial and the tremendous uncertainty attending their application and scale inevitably impacts settlement negotiations. Sometimes referred to as the “shadow effect”, this is the tendency of settlement agreements to reflect or “discount” the risk of a potential punitive award.
We might reasonably ask whether this shadow effect can be at all significant given the relatively rare incidence of both trials and punitive damage awards themselves. However, in their 1998 paper, “Punitive Damages: An Economic Analysis”, Polinsky (1997), caution that “It would be a mistake to conclude that because punitive damages are not a significant factor in cases that go to trial, they also are not a significant factor in the settlement process.” That punitive damage cases are rarely pursued to adjudication does not mean that such damages are not frequently present in settlement negotiations.
Surprisingly, very little empirical research has been done to quantify the scale of the punitive shadow. In his study of insurance adjustor data, Koenig (1998) refers to the “largely unexplored shadow” effect of punitive damages. Nevertheless, Koenig was able to show that 10.6% of settled insurance claims were affected by the threat of punitive damages.
Doherty and Eckles (2003) note that, “”Threats” of punitive damages loom over the bargaining process, and both parties to litigation do, in fact, bargain in the “shadow” of punitive damages.” Taking a financial economic approach to punitive damages research, Rhee (2012) describes how the potentially catastrophic corporate liability associated with punitive damage risk provides the plaintiff with an arbitrage opportunity in settlement negotiations. In effect, the plaintiff can bargain strategically to capture some consideration of an anticipated punitive damages award in the settlement agreement.
Priest (1996) observes that, “It is obvious and indisputable that a punitive damages claim increases the magnitude of the ultimate settlement and, indeed, affects the entire settlement process, increasing the likelihood of litigation.”
While most of this research relates to punitive damages in particular, much of it could equally apply to the shadow effect of outlier judgment awards in general – punitive or compensatory. In the remainder of this essay we will refer to punitive and outlier awards interchangeably.
At issue more generally, are the normative and descriptive theories as to the shadow effect of what Rhee refers to as “low frequency, high severity awards”. In our view, the characterization of the award is incidental. From a financial economics point of view, we might better think of the problem as one of discounting the statistical “fat tail” that the prospect of outlier punitive or compensatory damages creates in an otherwise normal distribution of expected judgement awards.
It is interesting to speculate how litigants actually price outlier award expectations in practice and what thought processes govern the size and shape of the shadow in their settlement bargaining. For example, how would a litigant price his expectation of a 10% chance of a $100 million punitive damage award? Clearly there is a punitive damage expected value of $10 million at issue. But what thought processes take the litigant from his belief about the expected value at trial to his consideration of this amount in the settlement price? There is no doubt that litigants navigate this path from expected value to settlement, but because of the largely private nature of settlement agreements, the size and shape of the punitive shadow may never be fully understood empirically.
The more important question from our perspective is the normative one: how should particular opposing litigants price the potential for a punitive damage award in their individual settlement negotiations? To explore this question, we will first review some research on normative theories and later discuss our own approach.
Research is scant on normative approaches to settlement bargaining over punitive damage awards. However there is some evidence of what we might call a “full accounting” expected value approach in which the probability weighted amount of the expected punitive damages award is simply added to the settlement price.
In their model of punitive damages in insurance claims settlement, Doherty and Eckles find that where punitive damage awards are available asymmetrically, the insured will “only be indifferent between going to court and settling if he can obtain the expected value of that [punitive damage] lottery in the settlement offer.” Other research sketches a similar “full accounting” expected value approach to punitive damages pricing.
This research syncs with a simple heuristic solution to the settlement pricing problem in which litigants price punitive damages in settlement at their full undiscounted expected value. In this framework it would be argued that a 10% probability of a $100 million punitive damage award would contribute $10 million to the settlement price. Such an approach is certainly tractable and has intuitive appeal. The only problem is that it very likely overstates the normative value of punitive damage risk. [More]
- Exxon Shipping Company, et al., Petitioners v. Grant Baker et al. No. 07-219, Supreme Court of the United States (2008 U.S. LEXIS 5263).
- A fat tailed probability distribution has an unusually high probability of an extreme observation when compared to a normal distribution.
Hersch, Joni, and W. Kip Viscusi. 2010. “Punitive Damages by Numbers: Exxon Shipping Co. v. Baker.” Supreme Court Economic Review, 18: 259-280.
Polinsky, A. Mitchel, 1997. “Are Punitive Damages Really Insignificant, Predictable, and Rational? A Comment on Eisenberg et al. , 26 J. LEGAL STUD. 663, 667 (1997).
Koenig, T., 1998. “The Shadow Effect of Punitive Damages on Settlements.” Wisconsin Law Review, 1, 169-209.
Doherty, Neil and Eckles, David, 2003. “Punitive Damage Effects on Post-Loss Bargaining and Settlement.” Insurance and Risk Management, University of Pennsylvania.
Rhee, Robert J., 2012. “A Financial Economic Theory of Punitive Damages”, Michigan Law Review, Vol. 111, 2012, pp. 1-56.
Priest, George L., 1996. “Punitive Damages Reform: The Case of Alabama”, 56 Louisiana Law Review.