In this post, we build on the work of Dixit & McAdams (see our previous two posts) in order to create a general bargaining model of civil litigation. Let’s consider a civil case for our model. Specifically, let’s assume the case has survived the pre-trial stage (i.e. the judge has denied any motions to dismiss or motions for summary judgment); thus the case is scheduled to go to trial. Further assume that the losing side will appeal. There are two possible outcomes for each side:
|1. Win at trial and win on appeal.||Or lose at trial but win on appeal.|
|2. Win at trial but lose on appeal.||Or lose at trial and lose on appeal.|
Next, how do we assign probabilities to these possible outcomes? Should these probabilities be equally weighted, or does the fact that the case has survived the pre-trial stage affect these probabilities in some way? In many respects, this same problem occurs in the political impasse over the Supreme Court that Dixit & McAdams describe in their short HBR paper. In sum, there is a possibility that the parties to a conflict will weigh these probabilities differently. Moreover, all other things being equal, the more optimistic both sides are about winning, the less likely they will settle the case out of court. So the key question in litigation is, what legal or extra-legal factors will most likely lead the parties to be optimistic when they are assessing the relevant probabilities?