Legal Change: Integrating Selective Litigation, Judicial Preferences, and Precedent

The claim that the common law displays an economic logic is a centerpiece of the positive economic theory of law. A key question in this literature is whether this outcome is due to the conscious efforts of judges, or the result of invisible hand processes. This paper develops a model in which to two effects combine to determine the direction of legal change. The main conclusions are, first, that judicial bias can prevent the law from evolving toward efficiency if the fraction of judges biased against the efficient rule is large enough; and second, that precedent affects the rate of legal change but not its direction.

Sentencing Guidelines, Judicial Discretion, And Social Values

This paper studies the institutional structure of criminal sentencing, focusing on the interaction between legislatures, which set sentencing ranges ex ante, and judges, who choose actual sentences from within those ranges ex post. The key question concerns the optimal degree of judicial discretion, given the sequential nature of the process and the possibly divergent interests of legislatures and judges regarding the social function of criminal punishment. The enactment of sentencing reform in the 1970s and 80s provides both a context for the model and an opportunity to evaluate its conclusions.

Optimal Test for Parameter Instability When the Unstable Process and the Error Distribution are Unknown

This paper proposes asymptotically optimal tests for unstable parameter process under the feasible circumstance that the researcher has little information about the unstable parameter process and the error distribution, and suggests conditions under which the knowledge of those processes does not provide asymptotic power gains. I first derive a test under known error distribution, which is asymptotically equivalent to LR tests for correctly identified unstable parameter processes under suitable conditions. The conditions are weak enough to cover a wide range of unstable processes such as various types of structural breaks and time varying parameter processes. The test is then extended to semiparametric models in which the underlying distribution in unknown but treated as unknown infinite dimensional nuisance parameter. The semiparametric test is adaptive in the sense that its asymptotic power function is equivalent to the power envelope under known error distribution.