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Meta Analysis of Empirical Deterrence Studies: an explorative contest

Rupp, Thomas (2006):
Meta Analysis of Empirical Deterrence Studies: an explorative contest.
Darmstadt, In: Darmstadt Discussion Papers in Economics, [Online-Edition: http://tuprints.ulb.tu-darmstadt.de/4753],
[Report]

Abstract

A sample of 200 studies empirically analyzing deterrence in some way is evaluated. Various methods of data mining (stepwise regressions, Extreme Bounds Analysis, Bayesian Model Averaging, manual and naive selections) are used to explore different influences of various variables on the results of each study. The preliminary results of these methods are tested against each other in a competition of methodology to evaluate their performance in forecasting and fitting the data and to conclude which methods should be favored in an upcoming extensive meta-analysis. It seems to be the case that restrictive methods (which select fewer variables) are to be preferred when predicting data ex ante, and less parsimonious methods (which select more variables) when data has to be fitted (ex post). In the former case forward stepwise regression or Bayesian Model Selection perform very well, whereas backward stepwise regression and Extreme Bounds Analysis are to be preferred in the latter case.

Item Type: Report
Erschienen: 2006
Creators: Rupp, Thomas
Title: Meta Analysis of Empirical Deterrence Studies: an explorative contest
Language: English
Abstract:

A sample of 200 studies empirically analyzing deterrence in some way is evaluated. Various methods of data mining (stepwise regressions, Extreme Bounds Analysis, Bayesian Model Averaging, manual and naive selections) are used to explore different influences of various variables on the results of each study. The preliminary results of these methods are tested against each other in a competition of methodology to evaluate their performance in forecasting and fitting the data and to conclude which methods should be favored in an upcoming extensive meta-analysis. It seems to be the case that restrictive methods (which select fewer variables) are to be preferred when predicting data ex ante, and less parsimonious methods (which select more variables) when data has to be fitted (ex post). In the former case forward stepwise regression or Bayesian Model Selection perform very well, whereas backward stepwise regression and Extreme Bounds Analysis are to be preferred in the latter case.

Series Name: Darmstadt Discussion Papers in Economics
Volume: 174
Place of Publication: Darmstadt
Uncontrolled Keywords: meta analysis, data mining, deterrence, criminometrics
Divisions: 01 Department of Law and Economics
01 Department of Law and Economics > Volkswirtschaftliche Fachgebiete
Date Deposited: 31 Jan 2016 20:57
Official URL: http://tuprints.ulb.tu-darmstadt.de/4753
URN: urn:nbn:de:tuda-tuprints-47538
Additional Information:

JEL classification: C81, K14, K42

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