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Determinants of violent and property crimes in England and Wales: a panel data analysis

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  • Lu Han
  • Siddhartha Bandyopadhyay
  • Samrat Bhattacharya

Abstract

We examine various determinants of property and violent crimes by using police force area level (PFA) data on England and Wales over the period of 1992--2008. Our list of potential determinants includes two law enforcement variables namely crime-specific detection rate and prison population, and various socio-economic variables such as unemployment rate, real earnings, proportion of young people and the Gini Coefficient. By adopting a fixed effect dynamic GMM estimation methodology we attempt to address the potential bias that arises from the presence of time-invariant unobserved characteristics of a PFA and the endogeneity of several regressors. There is a significant positive effect of own-lagged crime rate. The own-lagged effect is stronger for property crime, on an average, than violent crime. We find that, on an average, higher detection rate and prison population leads to lower property and violent crimes. This is robust to various specifications. However, socio-economic variables with the exception of real earnings play a limited role in explaining different crime types.

Suggested Citation

  • Lu Han & Siddhartha Bandyopadhyay & Samrat Bhattacharya, 2013. "Determinants of violent and property crimes in England and Wales: a panel data analysis," Applied Economics, Taylor & Francis Journals, vol. 45(34), pages 4820-4830, December.
  • Handle: RePEc:taf:applec:v:45:y:2013:i:34:p:4820-4830
    DOI: 10.1080/00036846.2013.806782
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    Cited by:

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    3. Li, Jing & Wan, Guanghua & Wang, Chen & Zhang, Xueliang, 2019. "Which indicator of income distribution explains crime better? Evidence from China," China Economic Review, Elsevier, vol. 54(C), pages 51-72.
    4. Siddhartha Bandyopadhyay & Samrat Bhattacharya & Rudra Sensarma, 2015. "An analysis of the factors determining crime in England and Wales: A quantile regression approach," Economics Bulletin, AccessEcon, vol. 35(1), pages 665-679.
    5. Brosnan, Stephen, 2017. "The Impact of Sports Participation on Crime in England between 2012 and 2015," MPRA Paper 78596, University Library of Munich, Germany.
    6. Stephen Brosnan, 2018. "The Socioeconomic Determinants of Crime in Ireland from 2003-2012," The Economic and Social Review, Economic and Social Studies, vol. 49(2), pages 127-143.
    7. Pina-Sánchez, Jose & Buil-Gil, David & brunton-smith, ian & Cernat, Alexandru, 2021. "The impact of measurement error in models using police recorded crime rates," SocArXiv ydf4b, Center for Open Science.
    8. Saqib Amin & Nawaz Ahmad, 2018. "Ethnic Diversity, Social Exclusion and Economic Determinants of Crimes: A Case Study of Pakistan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(1), pages 267-286, November.
    9. Bagchi Aniruddha & Bandyopadhyay Siddhartha, 2016. "Workplace Deviance and Recession," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 16(1), pages 47-81, January.
    10. Ozkan, Turgut, 2016. "Reoffending among serious juvenile offenders: A developmental perspective," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 18-31.
    11. Jonathan Torres‐Tellez & Alberto Montero Soler, 2023. "After the economic crisis of 2008: Economic conditions and crime in the last decade for the case of Spain," American Journal of Economics and Sociology, Wiley Blackwell, vol. 82(3), pages 223-239, May.
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    13. Dmitry Burakov, 2019. "Oil Hikes, Drugs and Bribes: Do Oil Prices Matter for Crime Rate in Russia?," International Journal of Energy Economics and Policy, Econjournals, vol. 9(1), pages 84-94.

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