Determinants and convergence incidence of crime

This study aims of investigating the economics of crime in selected 21 countries in the world which include Australia, Austria, Canada, Cyprus, Denmark, Estonia, Finland, France, Greece, Hungary, Ireland, Italy, Japan, Netherland, New Zealand, Norway, Poland, Spain, Sweden, United Kingdom and United States of America. The specific objectives are, firstly, to investigate determinants of crime, especially the impact of socio-economic variables on crime incidence and occurrence. Secondly, to investigate the impact of crime on nation’s economic growth and finally the convergence of crime incidence. As for the first objective of investigating the relationship between socioeconomic variables and crime, independent variables we’re chosen carefully by studying theories of crime causation as well as past literatures and we decided to employ income level, unemployment rate, and inflation rate. On top of that, we also included political violence, both domestic and regional in order to enrich the study. As for the theoretical background of the study we started by adapting the model and framework that was introduced by Viren (2001) based on Becker (1968), Block and Heineke (1975). We made slight modification by rephrasing the model in order to not only capture the long run relationship but also the short run dynamics. As for the investigation of the impact of crime on nations economy we begun with the classic framework of Solow-Swan growth model, we progressed with the recommendation by Cellini (1997) and took into account of Islam (1995). Panel-error-correction based cointegration (Persyn and Westerlund (2008)) was employed to investigate the linkages between socio-economic variables and crime as per our main aim, as well as for the second aim of understanding the impact of crime on nation’s economic growth. As for the final aim of investigating the convergence of crime incidence, we formulated the benchmark, which is the average crimes rate as per the group of countries namely, all countries, transition and developed economies and we proceed to measure the difference of crime rates of the respective economies and the benchmark, and finally, the difference or the gap that was obtained, were tested for their statistical properties. For this analysis, we employed a panel unit root test that caters for cross sectional dependence (Pesaran CADF test). The scope of the study covers 21 countries with data spanning for 41 years (1960 to 2001) We could conclude a number of observations from our study. Firstly, the results revealed a negative long run relationship between income level and crime, incidence, which translates literally to a notion that a higher income would enable the people to enjoy a better life, and vice versa worsening income could induce strain and create pressure on society. The result also indicated a positive long run relationship between inflation and crime, the logical explanation is almost the same, whereby while higher prices would enable firm and business to receive much higher return and profit. However, majority of people, who are actually fix income earners, would definitely feel the pinch due to high prices which translate to worsening purchasing power, which will induce strain; Similar positive results were also obtained for the relationship between unemployment and, crime as well as lending rate and crime. Losing source of income would means that one has to fend elsewhere in order to survive, some might take the shortcut, namely committing a crime. A steep lending rate is a nuisance for people since the cost of repayment is burdensome. As for the political violence variable, domestic political violence seems to be negatively related; on the contrary regional political violence is positively related. We believe this might be attributed to the spillover effect. All these signs are as anticipated and justified in this study and are concurrent with most of the past literatures. Secondly, it is found that as anticipated, crime indeed has a negative impact on economic growth as showed by the results of the estimation. As for the convergence of crime, the results clearly shows that for all three cases, there are no convergence (all, transition and developed economies). It proves the point that crime occurrences are country or economy specific, the incidence of crime is indeed correlated with number of factors. Different economic background, differing punishments, various regulations, diverse culture plays a part in occurrence of crime. Some policy implications of this study are that the policy makers needs to cautiously and carefully plane crime policies, rather than focusing on punishments, they should look at avenues of prevention, and this study had shown that if the socio-economic conditions are improved it would lead to reduction of crime rates