I point out that the Coase theorem suggests there should not be wasteful discovery, in the sense that the value to the requester is less than the cost to the responder. I use a toy model to show that a sufficiently informed court could design a mechanism under which the Coasean prediction is...

Event studies, a half-century-old approach to measuring the effect of events on stock prices, are now ubiquitous in securities fraud litigation. In determining whether the event study demonstrates a price effect, expert witnesses typically base their conclusion on whether the results are...

In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust...

The relationship between legal standards of proof and thresholds of statistical significance is a well-known and studied phenomena in the academic literature. Moreover, the distinction between the two has been recognized in law. For example, in Matrix v. Siracusano, the Court unanimously...

When are litigants' statistical estimates legally sufficient, given that courts use the preponderance of the evidence standard? We answer this question using Bayesian hypothesis testing and principles of federal procedural law, focusing on the common case of statistical estimation evidence from...

Many observers believe the Supreme Court's Twombly and Iqbal opinions have curtailed access to civil justice. But previous empirical studies looking only at Rule 12(b)(6) grant rates have failed to capture the full effect of these cases because they have not accounted for party selection —...

In this paper I derive several straightforward restrictions imposed by the Becker model of discrimination in the highway search and pre-trial release contexts. I explain how these restrictions may be tested using real-world data at the decision level (e.g., whether to search or whether to...

Researchers have increasingly realized the need to account for within-group dependence in estimating standard errors of regression parameter estimates. The usual solution is to calculate cluster-robust standard errors that permit heteroskedasticity and within-cluster error correlation, but...