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Tun-Jen Chiang, The Information-Forcing Dilemma in Damages Law (Wash. U. in St. Louis Legal Stud. Research Paper No. 16-08-03, 2016), available at SSRN.

There is a rule in the world of remedies that has always struck me as unfair. The rule, generally speaking, is that damages are not available unless they can be proven with certainty. For example, suppose that I own a pub and hire a karaoke DJ for Friday night. Karaoke is popular in my town and I advertise the event widely. On Friday afternoon, however, the DJ breaches and I’m left without entertainment. During the night, patrons show up and ask about the DJ. Many of them express disappointment; some decide to remain and have a couple drinks but some leave right away. I bring suit for $1,000 in damages. Even though liability is clear in this case, I am not likely to recover a dime in damages because my estimate of damages is, in the eyes of the law, little more than conjecture. If this seems unfair to you, you’re in good company. In fact, some courts see it the same way and have tried to soften the “certainty” requirement by awarding damages that seem like a “good guess.” But the “good guess” approach has its own downside. Guesses are sometimes wrong—especially when the guesser stands to benefit from guessing too high. So what is a court to do?

Scholars and jurists have wrestled with this problem for some time but nobody, to my knowledge, has done so as successfully as Tun-Jen Chiang in his new article, The Information-Forcing Dilemma in Damages Law. Unlike prior scholars, Chiang does not attempt to find the sweet spot between the “certainty” and “good guess” approaches. Instead, he takes a step back and tries to understand the problem. The problem is not simply that we have yet to find the sweet spot; it’s that information deficits force courts to fall back on a general sense of fairness. This sense of fairness will, of course, skew different ways in different cases. Chiang helpfully illustrates how courts oscillate between “certainty” and “good guess” approaches as they attempt to implement vague notions of fairness. In one case (or perhaps one period of time), courts move from “certainty” to “good guess” to ameliorate the unfairness to plaintiffs, but then move from “good guess” back to “unfairness” to ameliorate unfairness to defendants. And then the process starts all over again.

The same information deficit foils other attempts to solve the problem. Instead of choosing between a “certainty” or “good guess” approach, legislatures and courts have also experimented with solutions such damages caps or shifting the burden of proof. But these solutions, Chiang shows, are simply further attempts to pinpoint the appropriate level of fairness in a world of inadequate information. But that approach, like others, is prone to oscillation because fairness concerns will always re-assert themselves.

Once Chiang illustrates the real problem—inadequate information—he proposes a solution. Specifically, he argues that

Courts should require a party to produce damages information . . . if and only if two conditions are met. First, the social benefit of having additional information on some issue must outweigh the social cost of collecting the information and presenting it in court . . . . Second, courts should impose the burden of proof on the party that can more cheaply produce the information required. (P. 46.)

At first glance, the first of these two prongs seems unsatisfying. How in the world will a court determine the “social benefit” of presenting evidence of the business my pub lost when the DJ breached, the “social cost” of adducing this evidence? (Note that these costs and benefits are social, not private; if my private benefit exceeds my private cost, I would collect and produce the information without further incentive.) Chiang recognizes the problem, however. He acknowledges that courts will not be able to precisely calculate these costs and benefits. Yet he defends the criterion, persuasively in my view, as a tool for forcing courts to recognize the trade-offs that are inherent in the choice. When these trade-offs are submerged within the doctrine (as they are now), the doctrine oscillates over time because a given result, when stated in stark, black-and-white terms, appears to ignore costs. When a choice is explicitly acknowledged to be balance of costs and benefits, oscillation should be less common because costs are better (and more openly) accounted for.

The second prong of Chiang’s proposed solution does more than simply remind courts what should matter. It specifically instructs courts to consider who can more cheaply produce evidence of loss and penalize that party for failing to do so. But without knowing the nature of the evidence, how can a court know who can more cheaply produce it? Chiang’s solution is to impose a burden of producing evidence of both parties and then allow the court to penalize the party who could have produced more but didn’t. This would set off, as Chiang puts it, a

virtuous cycle where the threat of a penalty on one side (say the plaintiff) indices the plaintiff to produce more and better evidence, which in turn induces the defendant to produce more and better evidence, and so on—the cycle stops only at the point where both parties have produced all cost-effective evidence and therefore do not expect to be found negligent [in the production of evidence] at all. (P. 54.)

Chiang’s solution strikes me as worth a try. If there a cost-effective way for me to find out how many customers I lost at my pub, I should do so. If I don’t do, but instead throw a big damages number at the court, I should not get the benefit of a “good guess” rule. In contrast, if the DJ can cost-effectively determine how much business I lost but did not do so, he should not get the benefit of the certainty rule. What happens if both of us do our best? This is one place where Chiang comes up a bit short, at least on my reading. He does not appear to address that possibility. To his credit, the problem of damages should be less acute in this context because both parties have adduced as much evidence as feasible, thus making the court’s job easier. But there will still be situations when the amount of damages is uncertain even after both parties have done their best. If the court applies a pro-defendant certainty rule at that point, that would seem to diminish the plaintiff’s incentive to produce evidence up front. That is, the plaintiff can only obtain a pro-plaintiff “good guess” rule if (1) the plaintiff is non-negligent and (2) the defendant is negligent. Perhaps the plaintiff’s incentive to adduce as much cost-effective evidence as possible will still be strong enough given that she cannot capitalize on a defendant’s negligence unless she herself is non-negligent. If that is so, Chiang’s solution is a good one, though it would help to more fully explain that point (which is possible because the article still appears to be in draft form).

In sum, scholars, jurists or practitioners who have found themselves perplexed by the prospect of proving damages should read Chiang’s fine article. He helpfully explains why doctrine in this field has oscillated over time and offers an innovative and efficient way to solve the problem. I enjoyed reading it, lots.

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Cite as: Jack Preis, Calculating Damages in an Uncertain World, JOTWELL (April 7, 2017) (reviewing Tun-Jen Chiang, The Information-Forcing Dilemma in Damages Law (Wash. U. in St. Louis Legal Stud. Research Paper No. 16-08-03, 2016), available at SSRN),