52 Ariz. L. Rev. [i] (2010)

handle is hein.journals/arz52 and id is 1 raw text is: AR I ZONA
LXV
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VOLUME 52                        2010                      NUMBER 1
CONTENTS
PAGE
THE J. BYRON MCCORMICK LECTURE
LESSONS FROM THE FINANCIAL CRISIS                     Joe Nocera     1
FEATURE ARTICLE
PREDICTING CRIME                              M  Todd Henderson
Justin Wolfers & Eric Zitzewitz  15
Prediction markets have been proposed for a variety of public policy
purposes, but no one has considered their application in perhaps the most obvious
policy area: crime. This Article proposes and examines the use of prediction
markets to forecast crime rates and the potential impact on crime policy, such as
changes in resource allocation, policing strategies, sentencing, post-conviction
treatment, and so on.
First, we argue that prediction markets are especially useful in crime rate
forecasting and criminal policy analysis because information relevant to
decisionmakers is voluminous, dispersed, and difficult to process efficiently. After
surveying the current forecasting practices and techniques, we examine the use of
standard prediction markets-such as those being used to predict everything from
the weather to political elections to flu outbreaks-as a method of forecasting
crime rates of various kinds.
Second, we introduce some theoretical improvements to existing prediction
markets that are designed to address specific issues that arise in crime rate
forecasting. Specifically, we develop the idea of prediction market event studies
that could test the influence of real and hypothetical policy changes on crime rates.
Given the high costs of changing policies, such as issuing a moratorium on the
death penalty or lowering mandatory minimum sentences for certain crimes, these
markets provide a useful tool for policymakers operating under uncertainty.
But, the event studies and the other policy markets we propose face a big
hurdle because predictions about the future imbed assumptions about the very
policy choices they are designed to measure. We offer a method by which
policymnakers can interpret market forecasts in a way that isolates or unpacks
underlying crime factors from expected policy responses, even when the responses
are dependent on the crime factors.
Finally, we discuss some practical issues about designing these markets, such
as how to ensure liquidity, how to structure contracts, and the optimal market
scope. We conclude with a modest proposal for experimenting with markets in this
policy area.

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