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Structural Intervention Time Series Analysis of Crime Rates: The Impact of Sentence Reform in Virginia

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Author Info

  • Suncica Vujic

    (University of Bath, Bath, UK)

  • Jacques Commandeur

    (VU University Amsterdam)

  • Siem Jan Koopman

    (VU University Amsterdam)

Abstract

We adopt a structural time series analysis to investigate the impact of parole abolition and sentence reform in Virginia on reported crime rates. The Commonwealth of Virginia abolished parole and reformed sentencing for all felony offences committed on or after January 1, 1995. To examine the impact of Virginia's change in legislation on reported crime rates from 1995 onwards, we perform an intervention time series analysis based on structural time series models. We empirically find that the change in legislation has significantly reduced the burglary rates and to a lesser extent the murder rates in Virginia. For other violent crimes such as rape and aggravated assault the evidence of a significant reduction in crime rates is less evident or is not found. This empirical study for Virginia also provides an illustration of how an effective intervention time series analysis can be carried out in crime studies.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 12-007/4.

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Date of creation: 30 Jan 2012
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Handle: RePEc:dgr:uvatin:20120007

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Web page: http://www.tinbergen.nl

Related research

Keywords: Intervention time series analysis; Crime rates; Structural time series models; Unobserved components time series models;

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References

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  1. Daniel Kessler & Steven D. Levitt, 1998. "Using Sentence Enhancements to Distinguish between Deterrence and Incapacitation," NBER Working Papers 6484, National Bureau of Economic Research, Inc.
  2. 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.
  3. Atkinson, A. C. & Koopman, S. J. & Shephard, N., 1997. "Detecting shocks: Outliers and breaks in time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 387-422, October.
  4. Siem Jan Koopman & Marius Ooms & André Lucas & Kees van Montfort & Victor van der Geest, 2008. "Estimating systematic continuous-time trends in recidivism using a non-Gaussian panel data model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(1), pages 104-130.
  5. Ehrlich, Isaac, 1973. "Participation in Illegitimate Activities: A Theoretical and Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 521-65, May-June.
  6. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 407-17, October.
  7. Grogger, Jeffrey, 1991. "Certainty vs. Severity of Punishment," Economic Inquiry, Western Economic Association International, vol. 29(2), pages 297-309, April.
  8. Harvey, Andrew C & Fernandes, C, 1989. "Time Series Models for Count or Qualitative Observations: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 422, October.
  9. Commandeur, Jacques J.F. & Koopman, Siem Jan, 2007. "An Introduction to State Space Time Series Analysis," OUP Catalogue, Oxford University Press, number 9780199228874.
  10. Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543.
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Cited by:
  1. Suncica Vujic & Siem Jan Koopman & Jacques J. F. Commandeur, 2012. "Economic Trends and Cycles in Crime: A Study for England and Wales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 232(6), pages 652-677, November.

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