American Economic Review Vol. 95 No. 2 2005
Optimal Search Profiling with Linear Deterrence
Abstract
I examine here an aspect of law enforcement that has recently been the subject of debate. This is the choice of a profiling policy wherein decisions to search for evidence of crime may vary with observable covariates of the persons at risk of being searched. Policies that make search rates vary with personal attributes are variously defended as essential to effective law enforcement and denounced as unfair to classes of persons subjected to relatively high search rates. Variation of search rates by race has been particularly controversial; see, for example, Knowles, Persico, and Todd (2001), Persico (2002), and Dominitz (2003). Whereas recent research on profiling has sought to define and detect racial discrimination, my concern is to understand how a social planner might choose a profiling policy. This paper studies optimal profiling in a simple, illustrative setting. In related work (Manski, 2004), I consider how a planner might reasonably behave when he does not possess all of the information needed to determine an optimal policy. Section I poses a utilitarian planning problem whose objective is to minimize the social cost of crime and search. Search is costly per se, and search that reveals a crime entails costs for punishment of offenders. Search is beneficial to the extent that it deters or prevents crime.
- DOI
- 10.1257/000282805774669817
- Volume
- 95
- Issue
- 2
- Pages
- 122-126
- Language
- en
- Sources
- bibtex:phds-export.bib openalex crossref