Search results

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.

Policy brief on how to mitigate the negative impacts of Universal Credit on financial insecurity and crime based on the paper d’Este, R. and Harvey, A. (2022), “The unintended consequences of welfare reforms: Universal Credit, financial insecurity, and crime”, The Journal of Law, Economics, and Organization.

The purpose of this paper is to use an evaluation of a micro-place-based hot-spot policing implementation to highlight the potential issues raised by data quality standards in the recording and measurement of crime data and police officer movements.

The study focusses on an area of London (UK) which used a predictive algorithm to designate micro-place patrol zones for each police shift over a two-month period. Police officer movements are measured using GPS data from officer-worn radios. Descriptive statistics regarding the crime data commonly used to evaluate this type of implementation are presented, and simple analyses are presented to examine the effects of officer patrol duration (dosage) on crime in micro-place hot-spots.

The results suggest that patrols of 10-20 minutes in a given police shift have a significant impact on reducing crime; however, patrols of less than about 10 minutes and more than about 20 minutes are ineffective at deterring crime.

Due to the sparseness of officer GPS data, their paths have to be interpolated which could introduce error to the estimated patrol dosages. Similarly, errors and uncertainty in recorded crime data could have substantial impact on the designation of micro-place interventions and evaluations of their effectiveness.

This study is one of the first to use officer GPS data to estimate patrol dosage and places particular emphasis on the issue of data quality when evaluating micro-place interventions.