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Identifying Efficient Crime-Combating Policies by VAR Models: The Example of Switzerland


  • Patricia Funk
  • Peter Kugler


Current research suggests that the crime-combating instrument sentence probability is more effective than sentence severity. However, the focus of the simultaneous (or very short-run) impact of the law enforcement policy on crime impedes a comparison of these two instruments with respect to their long-term effectiveness. With Swiss data, this article investigates the dynamic interrelationships between enforcement policy and crime and finds that overall, sentence severity is about the same effective as sentence probability. Furthermore, the authors show how the VAR-modeling technique can be exploited to conveniently distinguish between deterrence and incapacitation effects. More concrete recommendations toward a cost-effective crime-reduction policy can be derived. (JEL "C32", "K42") Copyright 2003 Western Economic Association International.

Suggested Citation

  • Patricia Funk & Peter Kugler, 2003. "Identifying Efficient Crime-Combating Policies by VAR Models: The Example of Switzerland," Contemporary Economic Policy, Western Economic Association International, vol. 21(4), pages 525-538, October.
  • Handle: RePEc:bla:coecpo:v:21:y:2003:i:4:p:525-538

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    References listed on IDEAS

    1. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters,in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
    2. Steven D. Levitt, 1998. "Juvenile Crime and Punishment," Journal of Political Economy, University of Chicago Press, vol. 106(6), pages 1156-1185, December.
    3. H. Naci Mocan & Hope Corman, 2000. "A Time-Series Analysis of Crime, Deterrence, and Drug Abuse in New York City," American Economic Review, American Economic Association, vol. 90(3), pages 584-604, June.
    4. Samuel L. Myers, 1983. "Estimating the Economic Model of Crime: Employment Versus Punishment Effects," The Quarterly Journal of Economics, Oxford University Press, vol. 98(1), pages 157-166.
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    6. Ann Dryden Witte, 1980. "Estimating the Economic Model of Crime With Individual Data," The Quarterly Journal of Economics, Oxford University Press, vol. 94(1), pages 57-84.
    7. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    8. Cornwell, Christopher & Trumbull, William N, 1994. "Estimating the Economic Model of Crime with Panel Data," The Review of Economics and Statistics, MIT Press, vol. 76(2), pages 360-366, May.
    9. Corman, Hope & Joyce, Theodore & Lovitch, Norman, 1987. "Crime, Deterrence and the Business Cycle in New York City: A VAR Approach," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 695-700, November.
    10. Helen Tauchen & Ann Dryden Witte & Harriet Griesinger, 1993. "Criminal Deterrence: Revisiting the Issue with a Birth Cohort," NBER Working Papers 4277, National Bureau of Economic Research, Inc.
    11. Viren, Matti, 1994. "A test of an economics of crime model," International Review of Law and Economics, Elsevier, vol. 14(3), pages 363-370, September.
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    Cited by:

    1. Justina A.V. Fischer, 2005. "The Impact of Direct Democracy on Crime: Is the Median Voter Boundedly Rational?," University of St. Gallen Department of Economics working paper series 2005 2005-14, Department of Economics, University of St. Gallen.
    2. Vujić Sunčica & Koopman Siem Jan & Commandeur J.F., 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(6), pages 652-677, December.
    3. Nikolaos Dritsakis & Alexandros Gkanas, 2009. "The effect of socio-economic determinants on crime rates: An empirical research in the case of Greece with cointegration analysis," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Eastern Macedonia and Thrace Institute of Technology (EMATTECH), Kavala, Greece, vol. 2(2), pages 51-64, December.
    4. Yu Liu & Thomas M. Fullerton Jr. & Nathan J. Ashby, 2013. "Assessing The Impacts Of Labor Market And Deterrence Variables On Crime Rates In Mexico," Contemporary Economic Policy, Western Economic Association International, vol. 31(4), pages 669-690, October.
    5. Vujić, Sunčica & Commandeur, Jacques J.F. & Koopman, Siem Jan, 2016. "Intervention time series analysis of crime rates: The case of sentence reform in Virginia," Economic Modelling, Elsevier, vol. 57(C), pages 311-323.
    6. Ferda Halicioglu, 2012. "Temporal causality and the dynamics of crime in Turkey," International Journal of Social Economics, Emerald Group Publishing, vol. 39(9), pages 704-720, July.

    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law


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