Predicting crime /

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Bibliographic Details
Author / Creator:Henderson, M. Todd, author.
Imprint:[Chicago, Illinois] : Law School, University of Chicago, 2008.
Description:1 online resource (64 pages).
Language:English
Series:John M. Olin Law & Economics Working Paper ; no. 402 (2d ser.)
John M. Olin Program in Law & Economics working paper ; 2nd ser., no. 402.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/8919613
Hidden Bibliographic Details
Other authors / contributors:Wolfers, Justin, author.
Zitzewitz, Eric, author.
Notes:"April 2008."
Title from online title page (viewed October 11, 2012).
Includes bibliographical references.
Summary:"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 paper proposes and examinesthe use of prediction markets to forecast crime rates and the impact on crime from changes to crime policy, such as resource allocation, policing strategies, sentencing, postconviction treatment, and so on. We make several contributions to the prediction markets and crime forecasting literature. 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 policy-making applications, such as crime rate forecasting. Specifically, we develop the idea of prediction market event studies that can be used to test the influence of policy changes, both real and hypothetical, on crime rates. Given the high costs of changing policies, say issuing a moratorium on the death penalty or lowering mandatory minimum sentences for certain crimes, these markets provide a useful tool for policy makers operating under uncertainty. These event studies and the other policy markets we propose face a big hurdle, however, because predictions about the future imbed assumptions about the very policy choices they are designed to measure. We offer a method by which policy makers 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."

MARC

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100 1 |a Henderson, M. Todd,  |e author.  |1 http://isni.org/isni/0000000464700903  |0 http://id.loc.gov/authorities/names/no2012120323  |1 http://viaf.org/viaf/262637598 
245 1 0 |a Predicting crime /  |c M. Todd Henderson, Justin Wolfers, and Eric Zitzewitz. 
264 1 |a [Chicago, Illinois] :  |b Law School, University of Chicago,  |c 2008. 
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490 1 |a John M. Olin Law & Economics Working Paper ;  |v no. 402 (2d ser.) 
500 |a "April 2008." 
504 |a Includes bibliographical references. 
520 |a "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 paper proposes and examinesthe use of prediction markets to forecast crime rates and the impact on crime from changes to crime policy, such as resource allocation, policing strategies, sentencing, postconviction treatment, and so on. We make several contributions to the prediction markets and crime forecasting literature. 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 policy-making applications, such as crime rate forecasting. Specifically, we develop the idea of prediction market event studies that can be used to test the influence of policy changes, both real and hypothetical, on crime rates. Given the high costs of changing policies, say issuing a moratorium on the death penalty or lowering mandatory minimum sentences for certain crimes, these markets provide a useful tool for policy makers operating under uncertainty. These event studies and the other policy markets we propose face a big hurdle, however, because predictions about the future imbed assumptions about the very policy choices they are designed to measure. We offer a method by which policy makers 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." 
500 |a Title from online title page (viewed October 11, 2012). 
650 0 |a Crime forecasting  |x Methodology. 
650 0 |a Criminal behavior, Prediction of.  |0 http://id.loc.gov/authorities/subjects/sh85034039 
650 7 |a Crime forecasting  |x Methodology.  |2 fast  |0 (OCoLC)fst00883036 
650 7 |a Criminal behavior, Prediction of.  |2 fast  |0 (OCoLC)fst00883179 
700 1 |a Wolfers, Justin,  |e author.  |0 http://id.loc.gov/authorities/names/no99075158  |1 http://viaf.org/viaf/42892681 
700 1 |a Zitzewitz, Eric,  |e author.  |0 http://id.loc.gov/authorities/names/no00084366  |1 http://viaf.org/viaf/6006531 
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