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The purpose of this study is to investigate the socioeconomic determinants of property crimes on convicted offenders in the Chilga district correctional institution (CDCI).

This study conducted a socioeconomic determinant of property crimes on convicted offenders using quantitative research. Respondents consisted of a random sample of 170 convicted offenders in CDCI. This study used descriptive statistics, logistic regression and Pearson correlations for analyzing the quantitative data in CDCI.

The results of the study showed that the age at first engagement, educational status, offender’s immediate economic situation and previous experience of the offender were the perceived reasons in one’s major property crime offending. However, average monthly income, peer effect and family structure (grown up with) were found to be non-perceived reasons. Youths who are unmarried, illiterate and unemployed offenders had over three times more probabilities of committing theft than robbery and burglary in the winter season, especially in February, because of the determinants of illiteracy and unemployment such as negligence for the future life. Furthermore, the convicted offenders who were illiterate, unemployed and raised by single parents have engaged in theft for the first time, but burglary and robbery by employed and literate offenders in more probable.

This paper takes a fresh perspective on knowledge about property crime and economic as well as criminological theories using various bodies of academic research. This paper’s insight will be helpful to fill the literature gaps; there are lot research studies with little investigations addressing to the issue of the determinants of property crime. It will also be useful for policymakers to mitigate the determinant of property crime.

The main purpose of this paper is to analyze the determinants of money laundering in Italy. Given the high heterogeneity in terms of economic, social and institutional characteristics, Italy is a compelling case study.

By using annual data over the period 2008 to 2013, the authors estimate a balanced panel data linear model using feasible generalized least squares. Following the main literature on the economics of crime, the authors regress the crime rate in each region-year against a set of determinants that include socio-economic, enforcement and crime-specific factors.

The authors’ findings reveal that, in most Italian regions, enforcement activities do exert significant deterrence on criminal behaviors: and a negative relationship between enforcement and money laundering can be identified only when there are high levels of enforcement efforts. Moreover, the authors find that the major determinants influencing the rate of money laundering differ between northern, central and southern regions, confirming the existence of regional dualism. In particular, the crime rate in the northern and central area is positively related to the level of corruption and the incidence of mafia-type crimes and negatively related to educational attainment, whereas in the southern regions, money laundering is positively related to the size of the gaming and gambling sector.

The present paper contributes to the extant literature on the economics of crime in several ways. First, it explicitly analyzes a specific type of financial crime, which presents the higher degree of sanctioning regime in the Italian legislation. Second, Italy offers an important country study because of the forceful presence of mafia clans and organized crime systems operating in the illegal market.

The purpose of this paper is to evaluate the impact of social exposure activities, risk awareness measures, individual and family characteristics and the socioeconomic environment where the individual resides on the probability of property crime victimization.

A state preference model of crime is employed using victimization surveys data for several years complemented with municipality level data from population census. Logit regressions for the probability of victimization are run for males and females separately and using different specifications.

Regression estimates show that self-protection measures do not offset significantly the probability of victimization and that the likelihood of repeat victimization is highly significant. The most likely victims of property crime in Mexico do not live in highly marginalized communities. Finally, the covariates related to income are stronger predictors of victimization than the level of social exposure.

Further research is needed that considers other types of crime and complements the victimization data with police resources data.

This paper helps to obtain a better understanding of property crime in Mexico and its victims. The main results can help policy makers to allocate scarce resources more efficiently and design more efficient measures to fight property crime in Mexico.

The data set used combines individual and family data from several victimization surveys and complements it with municipality level characteristics from population census. The analysis of victimization is made for the entire country and not for large cities only.

The primary purpose of this paper is to empirically investigate the impact of educational attainment on crime rates across 33 Indian states over the period 2001 to 2013. This paper also examines the role of various macroeconomic, socio-economic and demographic factors in determining the variation of crimes in India.

First, this paper provides a representative theoretical model and discusses the possible relationship between crime and education. Second, the paper applies a dynamic panel data (DPD) model to extract more precise, unbiased and reliable estimates of the effect of education in abating different crime rates. The main advantage of using the dynamic panel model is to address the problem of endogeneity in some regressors and capture the time persistent effect of education on crime.

Empirical findings reveal that a 1% increase in gross enrolment ratio leads to the reduction of total crime by 8%. However, a unique finding identifies a positive association between tertiary education and economic crime. This finding further goes against the general belief that criminals tend to be less educated than non-criminals.

This paper recommends that instead of punishment and mandatory law enforcement for offenders, increase in government expenditure and different educational attainment ratios can go a long way to combat crime in India, which has posed a serious threat to the stability of society. Furthermore, utilizing the information on offenders' educational attainment in examining the crime rates can be a future research agenda for policymakers.

This study contributes to the empirical debate of ‘crime-education nexus’ by examining the role of education on crime in India. This study is the first of its kind that focuses on the aspects of crime and education more recently and investigates the relationship between crime and education due to the recent changes in educational attainment ratios and crime rate.

Economic hardship and crime is always a debatable issue in the political economy literature. Some authors define poverty leads to crime some are completely opposite. The purpose of this paper is to find out the impact of poverty on crime in the USA.

Using time series data of USA over the period from 1965 to 2016, this study applies autoregressive distributed lag approach to identify the effect of poverty on crime.

The outcomes confirm a positive co-integrating relationship between poverty and property crime. It can be argued that poverty ultimately leads property crime in long run in the USA. However, unemployment and GDP exhibit neither long-run nor short-run relationship with property crime and they are not cointegrated for the calculated period.

The subject of this paper helps to explain and analyze the nexus between poverty and crime in the USA.

Government and policymakers should focus more on poverty rather than unemployment alone to control property crime.

This study attempts to identify the consequences of economic hardship and poverty on the crime in the advanced economy like USA.

The main purpose of this study is to examine the dynamic relationship between tourist arrivals, inflation, unemployment and crime rates in Malaysia. This study covered the annual data from 1970 to 2008.

The multivariate Johansen‐Juselius cointegration test is employed to examine the potential long‐run equilibrium relationship. While the Granger causality test within the vector error‐correction modelling (VECM) framework is applied to determine the causal relationship between crime rate and its determinants.

The Johansen‐Juselius cointegration test result reveals that the variables are cointegrated and the dynamic ordinary least squares estimator suggest that unemployment, inflation and tourist arrivals are positively related to crime rates in Malaysia. For Granger causality, in the long‐run tourist arrivals, inflation and unemployment rates Granger cause crime rate in Malaysia. However, in the short run we find bilateral causality between unemployment, crime and tourist arrivals. Finally, the variance decompositions and impulse response functions analyses implied that unemployment, inflation and tourist arrivals are important in explaining the variation in crime for Malaysia.

The estimated crime rate function for Malaysia demonstrated that promoting supply‐side economy and also increases the numbers of police and patrolling duties in the potential crime areas will reduce the crime rate in Malaysia and in the same time attract more tourist arrivals to Malaysia.