Judicial Decision Making: A Dynamic Reputation Approach

Abstract

We seek to contribute to an understanding of how judicial elections affect the incentives and decisions of judges. We develop a theoretical model suggesting that judges who are concerned about their reputation would tend to "decide against their prior" as they approach elections. That is, judges who imposed a large number of severe sentences in the past, and are thus perceived to be strict, would tend to impose less severe sentences prior to elections, and judges who imposed a large number of light sentences in the past, and are perceived to be lenient, would tend to impose more severe sentences prior to elections. Using data from the Pennsylvania Commission on Sentencing (PCS), we test, and find evidence consistent with, the predictions of our model.

JEL Classification: D82, K40, K41