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Does more crime mean fewer jobs? An ARDL model

Author

Listed:
  • C. Detotto
  • M. Pulina

Abstract

This paper analyses how a set of economic variables and a deterrence variable affect criminal activity. Furthermore, it highlights the extent to which crime is detrimental for the economic activity. The case study is Italy for the time span 1970 up to 2004. An Autoregressive Distributed Lags approach is employed to assess the cointegration status of the variables under investigation. A Granger causality test is also implemented to establish temporal interrelationships. The main finding is that all crime typologies, but homicides and fraud, have a crowding-out effect on legal economic activity, reducing the employment rate.

Suggested Citation

  • C. Detotto & M. Pulina, 2009. "Does more crime mean fewer jobs? An ARDL model," Working Paper CRENoS 200905, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    • Handle: RePEc:cns:cnscwp:200905
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    File URL: https://crenos.unica.it/crenos/node/1696
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    Citations

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    Cited by:

    1. Ms. Concha Verdugo Yepes & Mr. Peter L. Pedroni & Xingwei Hu, 2015. "Crime and the Economy in Mexican States: Heterogeneous Panel Estimates (1993-2012)," IMF Working Papers 2015/121, International Monetary Fund.
    2. André Filipe Guedes Almeida & Gabriel Caldas Montes, 2020. "Effects of crime and violence on business confidence: evidence from Rio de Janeiro," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1669-1688, May.
    3. Oliviero A. Carboni & Claudio Detotto, 2016. "The economic consequences of crime in Italy," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 43(1), pages 122-140, January.
    4. Eleftherios Goulas & Athina Zervoyianni, 2013. "Economic growth and crime: does uncertainty matter?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(5), pages 420-427, March.
    5. Bianca Biagi & Claudio Detotto, 2020. "Crime as Tourism Externality," Regional Studies, Taylor & Francis Journals, vol. 48(4), pages 693-709, July.
    6. Cerro, Ana María & Rodríguez Andrés, Antonio, 2010. "The Effect of Crime on the Job Market: An ARDL approach to Argentina," MPRA Paper 44457, University Library of Munich, Germany.
    7. Halicioglu, Ferda & Andrés, Antonio R. & Yamamura, Eiji, 2012. "Modeling crime in Japan," Economic Modelling, Elsevier, vol. 29(5), pages 1640-1645.
    8. Ferda Halicioglu, 2012. "Temporal causality and the dynamics of crime in Turkey," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 39(9), pages 704-720, July.
    9. Kumar, Surender, 2013. "Crime and Economic Growth: Evidence from India," MPRA Paper 48794, University Library of Munich, Germany.

    More about this item

    Keywords

    crime; deterrence; economic variables; crowding-out effect;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • K14 - Law and Economics - - Basic Areas of Law - - - Criminal Law
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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