Beliefs, Precedent, and the Dynamics of Access to Justice: A Bayesian Microfounded Model

Abstract

This study adds to the literature on how both plaintiffs' beliefs and legal precedent affect access to justice. It also studies how actual accesses to the judiciary result, in turn, in the establishment of further precedent that is able to affect the behavior of new prospective plaintiffs. The analysis is based on a micro-founded Bayesian learning model. The dynamic model shows that precedent, indeed, can rectify biased beliefs. However, the rectification power significantly depends upon both the merit of the case and the stickiness of subjective beliefs. The results highlight that although plaintiffs learn from precedent, under some circumstances meritorious causes of action hardly proceed through the court, or can even disappear from the court after an initial positive trend; on the other hand, frivolous claims can continue to flourish.