This paper considers racial profiling in traffic stops as a public policy problem. Efficiency and equity considerations are characterized. I argue that while there is a strong argument that racial profiling produces a violation of fairness, specifically in the treatment of innocent black motorists, the efficiency effects of profiling are not known. One cannot assign probabilities to the possible magnitudes of either deterrent effects or the harms of profiling to individuals. This makes the assessment of profiling an example of decisionmaking under ambiguity. I defend a notion of a “Fairness Presumption” that requires a policymaker to be able to make an affirmative case if a policy is to be implemented that induces unfairness. On this basis, I reject racial profiling as a policy. Steven N. Durlauf Department of Economics University of Wisconsin 1180 Observatory Drive Madison, WI 53706-1393 [email protected]

This paper provides a model of individual decisionmaking in the presence of neighborhood effects. By neighborhood effects, we refer to interdependencies between individual decisions and the decisions and characteristics of others within a common neighborhood. As such, neighborhood effects are forms of social interactions; in fact the terms would seem to be interchangeable in many contexts. Within economics, there has developed an increasing recognition that neighborhood effects play a possibly major role in explaining a range of individual behaviors; rich empirical and theoretical literatures have developed. A failing of much of this work is the absence of strong connections between theory and empirics. This paper addresses this limitation by providing a model of multinomial choice with neighborhood effects. The model represents a generalization of the binary choice model of William Brock and Steven Durlauf (2001a,b). The model is econometrically implementable and so has the potential of allowing for structural estimation of neighborhood effects. Section I outlines a basic choice model with neighborhood effects. Section II specializes the structure using a multinomial logit framework. Section III considers econometric implementation. Section IV discusses some limitations of the framework and proposes some research directions. Proofs of all theorems may be found in Brock and Durlauf (2001c).

In this paper, we describe a set of trade-offs that policymakers face with respect to fluctua? tions at different frequencies. A complete treat? ment is given in Brock, Durlauf, and Rondina (2008). The presence of frequency-specific effects of policy choices has generally not been a focus of macroeconomic policy analysis, important exceptions include Alexei Onatski and Noah M. Williams (2003). Our analysis dif? fers from previous studies in that our objective is to understand to what extent a policymaker is forced, when choosing a feedback rule to sta? bilize the economy, to exacerbate volatility at some frequencies in order to reduce them at oth? ers, or whether it is possible to reduce volatil? ity at all frequencies. These trade-offs, known as design limits in the control theory literature, are important in understanding what stabiliza? tion policies do, and also possess implications for policy design in the presence of policymaker ignorance.

This paper examines how estimates of the deterrent effect of capital punishment depend on alternate choices of assumptions concerning the homicide process. Specific models of the homicide process represent bundles of these assumptions, which involve the unobserved heterogeneity, the relevant penalty probabilities for homicide choices, possible cross-polity parameter variation, and exchangeability between polity-time pairs that do and do not experience positive numbers of murders. We demonstrate how various assumptions have driven the conflicting findings from studies on capital punishment, and isolate a particular set of assumptions that are required to find a positive deterrent effect.