Research

Rusli Latimaha · Zakaria Bahari · Nor Asmat Ismail ·Jurnal Ekonomi Malaysia ·2018

This paper investigated the main factors influencing the basic needs budget in three major cities with a high cost of living in Malaysia. The analysis of variance tests result indicated that the Federal Territory of Kuala Lumpur, the state of Penang and Johor are places with high cost of living. The result also revealed that the middle income group are those who earn an income between RM2,992.50 to RM8,999 a month and the salaries of teachers were used as a proxy for the middle income groups. The Ordinary Least Squares (OLS) regression analysis indicated that there is a difference between the basic needs budget for single-adults and one-working parent families and furthermore, the basic needs budget in the cities of Kuala Lumpur, Johor Baharu and George Town is slightly different in each town. By and large, there is a difference in the basic needs budget between single-adults in Kuala Lumpur and Johor Bahru, and between two-working parent families among the three major cities. It is however interesting to note that there is no difference in the basic needs budgets among one-working parent families in these cities. The results also revealed that the total household income, family size, age of head of household, sex ratio, number of rooms, electrical appliances usage cost, broadband subscribers and number of privately owned cars all significantly influenced the basic needs budget regardless of which cities the respondents live.

Rusli Latimaha · Zakaria Bahari · Nor Asmat Ismail ·Jurnal Ekonomi Malaysia ·2019

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 specifcally, 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 affrm the most preferred model to explain criminal behaviour is by using Fixed Effects Model almost for all types of street crime. The fndings of the estimated coeffcients reveal that the cost of living is negatively related to all street crime types and not signifcant 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 signifcant 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 defnition of crime into percentage and the results show that the cost of living is signifcant 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 infuencer on all types of street crime rates and has a negative relationship. Finally, the unemployment rate is only signifcant 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.