Examining the linkages between street crime and selected state economic variables in Malaysia: a panel data analysis

• Main Authors: Rusli Latimaha,, Zakaria Bahari,, Nor Asmat Ismail,
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2019
• Online Access: http://journalarticle.ukm.my/14068/1/jeko_53%281%29-6.pdf; http://journalarticle.ukm.my/14068/; http://www.ukm.my/fep/jem/content/2019.html

In this paper, the authors use dynamic panel data in order to assess the linkages between the cost of living, income inequality, gross domestic product (GDP) per capita, population and unemployment rate with respect to the street crime rate in Malaysia. More specifically, the investigation considers whether the following could be capable of generating any difference in the crime rate observed across many types of street crime. The F-test, Breusch-Pagan Lagrange Multiplier test and Hausman tests affirm the most preferred model to explain criminal behaviour is by using Fixed Effects Model almost for all types of street crime. The findings of the estimated coefficients reveal that the cost of living is negatively related to all street crime types and not significant as well as unemployment rate. There is a motivation towards street crime not to earn a living or jobless, but other motivating push factors that relate to the personalities of the offenders such as drug addiction. Moreover, income inequality is only significant in terms of total street crime and unarmed robbery gang estimation models as well as GDP per capita and population in snatch and theft estimation models. Interestingly, we extend the by changing the definition of crime into percentage and the results show that the cost of living is significant with the correct sign and has a positive relationship with all types of street crime rates except for snatch and theft estimation models. The GDP per capita is also a main influencer on all types of street crime rates and has a negative relationship. Finally, the unemployment rate is only significant in the unarmed robbery estimation models and has a positive relationships as well as income inequality variable in total street crime and unarmed robbery gang estimation models. This street crime has been shown to be sensitive to the change in unemployment rate and income inequality and also have positive linkages.