Corruption and Growth Under Weak Identification

The goal of this paper is to revisit the influential work of Mauro [1995] focusing on the strength of his results under weak identification. He finds a negative impact of corruption on investment and economic growth that appears to be robust to endogeneity when using two-stage least squares (2SLS). Since the inception of Mauro [1995], much literature has focused on 2SLS methods revealing the dangers of estimation and thus inference under weak identification. We reproduce the original results of Mauro [1995] with a high level of confidence and show that the instrument used in the original work is in fact 'weak' as defined by Staiger and Stock [1997]. Thus we update the analysis using a test statistic robust to weak instruments. Our results suggest that under Mauro's original model there is a high probability that the parameters of interest are locally almost unidentified in multivariate specifications. To address this problem, we also investigate other instruments commonly used in the corruption literature and obtain similar results.

Evaluation of Police Patrol Patterns

This paper describes an ArcView extension that allows police planners to design patrol districts and to evaluate them by displaying various performance measures. It uses a spatially distributed queuing system (the Larson Hypercube) to calculate expected travel times, workloads, preventive patrol frequencies, and other variables; and it allows planners to see the unavoidable tradeoffs among their objectives. Using this tool, planners can experiment with various patrol patterns to find those that best meet their Department.s goals. For example, those patrol patterns which are best in terms of average response time don.t do as well as others in terms of workload balance, or those that are best in terms of achieving a uniform response time across different parts of the city don't do as well as others in terms of minimizing inter-district dispatches. There is, of course, no perfect solution for this problem: the facts of the situation force us to balance competing goals. Described here is a way of explicitly weighting the alternative objectives.

Search, Seizure and (False?) Arrest: An Analysis of Fourth Amendment Remedies when Police can Plant Evidence

The Fourth Amendment prohibits unreasonable searches and seizures in criminal investigations. The Supreme Court has interpreted this to require that police obtain a warrant prior to search and that illegally seized evidence be excluded from trial. A consensus has developed in the law and economics literature that tort liability for police officers is a superior means of deterring unreasonable searches. We argue that this conclusion depends on the assumption of truth-seeking police, and develop a game-theoretic model to compare the two remedies when some police officers (the bad type) are willing to plant evidence in order to obtain convictions, even though other police (the good type) are not (where this type is private information). We characterize the perfect Bayesian equilibria of the asymmetric-information game between the police and a court that seeks to minimize error costs in deciding whether to convict or acquit suspects. In this framework, we show that the exclusionary rule with a warrant requirement leads to superior outcomes (relative to tort liability) in terms of truth-finding function of courts, because the warrant requirement can reduce the scope for bad types of police to plant evidence