Parameters affecting crime in Iran with non-parametric Bayesian network approach and spatial causality

Document Type : Research Paper

Authors

1 PhD in Economics, Department of Economics, University of Isfahan, Isfahan, Iran.

2 Corresponding Author, Assistant Professor, Department of Economics, University of Zanjan, Zanjan

3 PhD Student in Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran

4 Associate Professor of Economics, Department of Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran

5 Professor of Economics, Faculty of Economics and Management, University of Tabriz, Tabriz, Iran

6 PhD in Electrical Engineering, Department of Electrical Engineering, University of Tabriz, Tabriz, Iran

Abstract

One of the challenges of the last century, especially in developing countries, is the excessive increase in crime rates. Iran, as one of the developing countries, is not exempt from this rule. In this regard, in this research, socio-economic parameters affecting theft in 429 cities of Iran in 2015 have been investigated. For this purpose, five socio-economic indicators including unemployment rate, industrialization rate, economic participation rate, divorce rate and urbanization rate have been used. In this study, two non-parametric Bayesian network models and spatial causality have been used. The results of Bayesian non-parametric network analysis show that except for the rate of economic participation, other variables have a direct effect on theft. On the other hand, the most important variables affecting theft are urbanization rate and unemployment rate. The results obtained from the spatial causality method also confirm the results of the Bayesian non-parametric network method, taking into account the spatial effects and the neighborhood between the cities

Keywords

Main Subjects

References

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Quarterly Journal of Applied Theories of Economics
Volume 12, Issue 44
June 2025
Pages 185-212

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