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Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach

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  • Habibullah, M.S.
  • Baharom, A.H.

Abstract

Economists recognized that economic conditions have an impact on crime activities. In this study we employed the Autoregressive Distributed Lag (ARDL) bounds testing procedure to analyze the impact of economic conditions on various categories of criminal activities in Malaysia for the period 1973-2003. Real gross national product was used as proxy for economic conditions in Malaysia. Our results indicate that murder, armed robbery, rape, assault, daylight burglary and motorcycle theft exhibit long-run relationships with economic conditions, and the causal effect in all cases runs from economic conditions to crime rates and not vice versa. In the long-run, strong economic performances have a positive impact on murder, rape, assault, daylight burglary and motorcycle theft, while on the other hand, economic conditions have negative impact on armed robbery.

Suggested Citation

  • Habibullah, M.S. & Baharom, A.H., 2008. "Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach," MPRA Paper 11910, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:11910
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    References listed on IDEAS

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    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. Stock, James H & Watson, Mark W, 1993. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, Econometric Society, vol. 61(4), pages 783-820, July.
    3. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    4. Richard B. Freeman, 1996. "Why Do So Many Young American Men Commit Crimes and What Might We Do about It?," Journal of Economic Perspectives, American Economic Association, vol. 10(1), pages 25-42, Winter.
    5. 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.
    6. Fajnzylber, Pablo & Lederman, Daniel & Loayza, Norman, 2002. "What causes violent crime?," European Economic Review, Elsevier, vol. 46(7), pages 1323-1357, July.
    7. Ehrlich, Isaac, 1973. "Participation in Illegitimate Activities: A Theoretical and Empirical Investigation," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 521-565, May-June.
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    Cited by:

    1. Muhammad Ahad, 2016. "Nexus between Income Inequality, Crime, Inflation and Poverty: NewEvidence fromStructural Breaksfor Pakistan," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 4(3), pages 133-145, March.
    2. Mahmoud MOURAD, 2022. "Impact of Welfare and Unemployment on the Crimes in the United States: Co-integration Analysis," Journal of Public Administration and Governance, Macrothink Institute, vol. 12(2), pages 120-120, December.
    3. Abdul Hamid, Baharom & Habibullah, Muzafar & Mohd Noor, Zaleha, 2013. "Crime and Its Socio-Macroeconomics Determinants: A Panel-Error-Correction Cointegration Analysis," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 47(2), pages 13-24.

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    More about this item

    Keywords

    Bounds Testing; Malaysia; Crime;
    All these keywords.

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E00 - Macroeconomics and Monetary Economics - - General - - - General

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