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Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?

Author

Listed:
  • Qi Li

    (Capital University of Economics and Business
    Texas A&M University)

  • Wei Long

    (Tulane University)

Abstract

This paper examines the treatment effect of the justice reform enacted on January 1, 1995, in Virginia. Using FBI’s Uniform Crime Report data about crime rates per 100,000 population from 1960 to 2010, we find that after the reform the reported aggregated violent crime rate declined significantly and is mainly driven down by the decrease in robbery. We also consider property crime and find that the reported property crime rate does not decline until 4 years later, indicating that the justice reform in Virginia also has lagged treatment effect on property crime.

Suggested Citation

  • Qi Li & Wei Long, 2018. "Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?," Empirical Economics, Springer, vol. 55(4), pages 2027-2045, December.
    • Handle: RePEc:spr:empeco:v:55:y:2018:i:4:d:10.1007_s00181-017-1332-4
    DOI: 10.1007/s00181-017-1332-4
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    References listed on IDEAS

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    1. Alberto Abadie, 2005. "Semiparametric Difference-in-Differences Estimators," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(1), pages 1-19.
    2. Steven D. Levitt, 1996. "The Effect of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(2), pages 319-351.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    4. Myers, Samuel L, Jr, 1980. "The Rehabilitation Effect of Punishment," Economic Inquiry, Western Economic Association International, vol. 18(3), pages 353-366, July.
    5. Li, Kathleen T. & Bell, David R., 2017. "Estimation of average treatment effects with panel data: Asymptotic theory and implementation," Journal of Econometrics, Elsevier, vol. 197(1), pages 65-75.
    6. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    7. McPheters, Lee R & Mann, Robert & Schlagenhauf, Don, 1984. "Economic Response to a Crime Deterrence Program: Mandatory Sentencing for Robbery with a Firearm," Economic Inquiry, Western Economic Association International, vol. 22(4), pages 550-570, October.
    8. Cheng Hsiao & H. Steve Ching & Shui Ki Wan, 2012. "A Panel Data Approach For Program Evaluation: Measuring The Benefits Of Political And Economic Integration Of Hong Kong With Mainland China," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 705-740, August.
    9. Levitt, Steven D, 1998. "Why Do Increased Arrest Rates Appear to Reduce Crime: Deterrence, Incapacitation, or Measurement Error?," Economic Inquiry, Western Economic Association International, vol. 36(3), pages 353-372, July.
    10. Shepherd, Joanna M, 2002. "Police, Prosecutors, Criminals, and Determinate Sentencing: The Truth about Truth-in-Sentencing Laws," Journal of Law and Economics, University of Chicago Press, vol. 45(2), pages 509-534, October.
    11. Sanjeev Sridharan & Suncica Vujic & Siem Jan Koopman, 2003. "Intervention Time Series Analysis of Crime Rates," Tinbergen Institute Discussion Papers 03-040/4, Tinbergen Institute.
    12. Bai, ChongEn & Li, Qi & Ouyang, Min, 2014. "Property taxes and home prices: A tale of two cities," Journal of Econometrics, Elsevier, vol. 180(1), pages 1-15.
    13. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    14. Ilyana Kuziemko, 2013. "How should inmates be released from prison? An assessment of parole versus fixed-sentence regimes," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 128(1), pages 371-424.
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    Cited by:

    1. Hongjun Li & Zheng Li & Cheng Hsiao, 2023. "Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices," Empirical Economics, Springer, vol. 64(6), pages 2661-2682, June.

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    More about this item

    Keywords

    Average treatment effect; Counterfactual analysis; Parole abolition; Truth-in-Sentencing;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law

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