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

Habibullah, M.S. and Baharom, A.H. (2008): Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Bounds Testing; Malaysia; Crime
• Subjects: E - Macroeconomics and Monetary Economics > E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy > E24 - Employment ; Unemployment ; Wages ; Intergenerational Income Distribution ; Aggregate Human Capital ; Aggregate Labor Productivity; E - Macroeconomics and Monetary Economics > E0 - General > E00 - General

References

REFERENCES Becker, G.S. (1968). Crime and Punishment: An Economic Approach. Journal of Political Economy 76: 1169-1217.

Deadman, D.F. and Pyle, D.J. (1997). Forecasting Recorded Property Crime using a Time-Series Econometric Model. British Journal of Criminology 37(3): 437-445.

Dickey, D.A. and Fuller, W.A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica 49: 1057-1077.

Ehrlich, I. (1973). Participation in Illegitimate Activities: A Theoretical and Empirical Investigation. Journal of Political Economy 38(3): 521-565.

Fajnzylber, P., Lederman, D. and Loayza, N. (2002). What Causes Violent Crime? European Economic Review 46: 1323-1357.

Freeman, R.B. (1996). Why Do So Many Young American Men Commit Crimes and What Might We Do About It. Journal of Economic Perspectives 10(1): 25-42.

Hale, C. (1998). Crime and the Business Cycle in Post-War Britain Revisited. British Journal of Criminology 38(4): 61-698.

Masin, A.M.M. and Msih, R. (1996). Temporal Causality and the Dynamics of Different Categories of Crime and Their Socioeconomic Determinants: Evidence from Australia. Applied Economics 28: 1093-1104.

Narayanan, P.K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37, 1979-1990.

Pesaran, M.H., Shin, Y., and Smith, R.J. (2001). Bounds testing approaches t the analysis of level relationships. Journal of Applied Econometrics, 16, 289-326.

Pyle, D.J. and Deadman, D.F. (1994). Crime and the Business Cycle in Post-War Britain. British Journal of Criminology 34(3): 339-357.

Scorcu, A.E. and Cellini, R. (1998). Economic Activity and Crime in the Long-run: An Empirical Investigation on Aggregate Data from Italy, 1951-1994. International Review of Law and Economics 18: 279-292.

Stock, J.H. and Watson, M. (1993). A simple estimator of cointegrating vestors in higher order integrated systems. Econometrica 61: 783-820.