The Nexus Between Child Abuse and Economic Conditions: Empirical Evidence from Malaysia (original) (raw)
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Female Labour Force and Child Abuse in Malaysia Using ARDL Approach
Jurnal Ekonomi Malaysia, 2019
Economic growth plays an important role in determining the number of female labour force. As economic growth intensifies, the number of female labour force increases simultaneously. However, the rise in the number of female labour force can lead to an increase in the number of child abuse cases. Therefore, this study is essential to explore the relationship between female labour force and child abuse cases in Malaysia. This study employs the ARDL bound testing approach and the results show that a higher number of female labour force can contribute to a higher child abuse case in Malaysia. Therefore, policies on female labour force should be formulated to cushion its effects on child abuse cases.
Unemployment, Immigrants, Price Level, Population and Crime: Cointegration Analysis of Malaysia
International Journal of Academic Research in Economics and Management Science, 2020
The crime index in Malaysia shown two distinctive overall trend patterns; increasing trend from 1982 to 2009 and decreasing from 2009 to 2016. On the other hand, the country's real GDP growth fluctuated substantially over the 34 years of period. Nevertheless, Malaysia has achieved its highest growth rate at 6.2% in the third quarter of 2017. Being a developing country with an open economy policy and industrialized market, it is, therefore, becoming important to study whether the economic condition does affect the crime rate in Malaysia. Hence, the purpose of this study is to investigate the relationship between economic variables (unemployment rate, price level, total immigrants, and population) and the crime index. Utilizing time-series data from the year 1982 to 2016 the study began with the analysing unit root test. The data must be proven stationary in order to proceed with other analyses. The cointegration analysis was done to capture the long-run equilibrium between variables. Findings showed that the economic variables investigated are crucial determinants and do impact the crime rate in Malaysia.
Factors Affecting Crime Rate in Malaysia Using Autoregressive Distributed Lag Modeling Approach
Pertanika journal of social science and humanities, 2022
An unlawful act that harms other people, societies, or countries is described as a crime, which the authorities or governments can punish. However, since each country has its own set of rules, the definition of crime varies from one region to another. According to the Department of Statistics Malaysia ABSTRACT An increase in the crime rate may jeopardize a country's development and economic growth. Thus, understanding the relationship between crime and a few determinants is crucial in sustaining the economic growth in Malaysia. The four determinants used in this research are economic growth, population, education level, and inflation rate. The data covers the period from 1984 to 2019, and Autoregressive Distributed Lag (ARDL) modeling approaches were used in this research. The findings showed that only the population has a significant positive impact on crime rates for long-term and short-term relationships. Meanwhile, economic growth and education level have a significant long-term positive effect on the crime rate. On the other hand, the inflation rate did not significantly impact the crime rate in long-term and short-term relationships. Interestingly, it was found in the findings that the crime rate and population showed a bidirectional causal relationship indicating that the past population values are useful for a better prediction of the current crime rate and vice versa. Thus, the Malaysian government should encourage people to cooperate with the enforcement authorities to deter crime for future environmental safety effectively.
Crime and Unemployment in Malaysia: ARDL Evidence
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Exploring the Relationship between Tertiary Education and Child Maltreatment: An ARDL Analysis
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This study aims to investigate the correlation between child abuse and tertiary education as a potential determining factor, in addition to established variables such as unemployment, inflation, and economic growth. The data spanning from 1989 to 2020 is analyzed using the Autoregressive Distributed Lag (ARDL) technique. Our findings reveal that inflation can have both short-term and long-term effects on child abuse, while unemployment primarily has a long-term impact on child abuse. However, an interesting discovery emerges as tertiary education demonstrates a protective effect, effectively reducing child abuse in the long run. These findings emphasize the significance of formulating strategies to mitigate the child abuse rate. Policymakers should consider allocating increased resources to enhance tertiary education, recognizing its potential role in preventing child abuse. By focusing on education and addressing the other identified determinants, the government can develop a compr...
Crime and economic conditions in Malaysia: An ARDL Bounds Testing Approach
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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.
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Violent Crime and Unemployment in Nigeria: An ARDL Bound Test Cointegration
Journal of Economic Info, 2019
This study attempts to examine whether there is a long-run relationship existing between crime rates and unemployment in Nigeria for the period 2004 to 2016. The autoregressive distributed lag (ARDL) bounds testing approach was used to determine the cointegration between unemployment and crime rates. The results show that unemployment and crime (murder, armed robbery, robbery, assaults, sexual offense, and cultism) are cointegrated. The empirical findings show that the unemployment rate and violent crime, such as; armed robbery, robbery-murder, assaults, sex violence, and cultism are all cointegrated. The long-run coefficients results indicated that the unemployment rate has a positive and significant effect on murder, sex violence, assaults, and cultism.
Unemployment, poverty, inflation and crime nexus: Cointegration and causality analysis of Pakistan
Pakistan Economic and Social …, 2009
This study is designed to investigate the relationship between crime and various economic indicators such as unemployment, poverty and inflation in Pakistan. The study covers the period for 1975-2007. The stationary properties of the time series data are examined by using Augmented Dickey-Fuller (ADF) test. Johansen Maximum Likelihood Cointegration and Granger Causality tests are applied to find out long-run relationship along with causality among the variables. The findings of the tests provide evidence of the existence of long-run cointegration relationship among crime, unemployment, poverty and inflation. The Granger causality has been tested through Toda-Yamamoto procedure. The causality results show that crime is Granger caused by unemployment, poverty and inflation in Pakistan.
Crime and Income Inequality: The Case of Malaysia
Journal of Politics and Law, 2009
This paper examines the causality between income inequality and crime in Malaysia for the period 1973-2003. Autoregressive Distributed Lag (ARDL) bounds testing procedure is employed to (1) analyze the impact of income inequality on various categories of criminal activities as well as to (2) analyze the impact of various categories of criminal activities on income inequality. Interestingly our results indicate that income inequality has no meaningful relationship with any of the various categories of crime selected, such as total crime, violent crime, property crime, theft and burglary. Crime exhibits neither long-run nor short run relationships with income inequality and they are not cointegrated. It cannot be denied that there is ambiguity in the empirical studies of crime economics regarding various income variables leading to often mixed and contradicting results, which might be a good explanation of this finding.