Morality and Markets: A Comment on Predicting Crime

(Excerpt) In their article, Predicting Crime, Professors Henderson, Wolfers, and Zitzewitz propose an intriguing and futuristic series of market-based models surrounding the broad topic of crime prevention. Harnessing widely dispersed knowledge among groups of people, including cops on the beat, criminologists, residents of neighborhoods, elected officials, snitches, and possibly even the criminals themselves, the authors posit that prediction markets will help to estimate crime statistics more accurately and therefore result in more efficient deployment of policing resources. Further, they hypothesize that posing particular policy alternatives—for example, the option of eliminating the death penalty—to a widely dispersed market will result in a more transparent and open decision-making process. In addition to making important contributions to questions of prediction market design, their article explores and amplifies a discussion already underway that seeks to identify productive and socially beneficial uses for prediction markets. Crime prevention would surely rank highly along any measure of important governmental functions, and the topic the authors have selected is therefore of particular significance. Over the past decade, prediction markets have become both a more familiar and a more acceptable way to forecast a wide variety of future events. Prediction markets have recently proliferated because, among other reasons, technological barriers to entry are lower than they once were and numerous prediction market providers have entered the field. As a greater number of people learn about these markets and their potential for gathering and consolidating information, new uses and possibilities continue to be explored. Also, as a greater number of people learn that prediction markets can also be fun—certainly, winning provides a hedonic benefit—the lure to potential participants increases. Politically minded students have told me that they tracked prediction markets in the last election the same way that those in my age group check polls. The main difference is that while checking polls is largely a passive exercise, prediction markets, on the other hand, give their participants a stake in the outcome by allowing them to contribute information; thus, participants in prediction markets feel more engaged and involved as market participants