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Does the Link between Unemployment and Crime Depend on the Crime Level? A Quantile Regression Approach

Author

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  • Entorf, Horst

    (Goethe University Frankfurt)

  • Sieger, Philip

    (Goethe University Frankfurt)

Abstract

Two alternative hypotheses – referred to as opportunity- and stigma-based behavior – suggest that the relationship between unemployment and crime also depends on preexisting local crime levels. In order to analyze conjectured nonlinearities between both variables, we are using quantile regressions applied to German county panel data. While both conventional OLS and quantile regressions confirm the positive link between unemployment and crime for property crimes, results for assault differ with respect to the method of estimation. Whereas conventional mean regressions do not show any significant effect (which would confirm the usual result found for violent crimes in the literature), quantile regression uncovers that size and importance of the relationship are conditional on the crime rate: The partial effect is significantly positive for moderately low and median quantiles of local assault rates.

Suggested Citation

  • Entorf, Horst & Sieger, Philip, 2014. "Does the Link between Unemployment and Crime Depend on the Crime Level? A Quantile Regression Approach," IZA Discussion Papers 8334, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp8334
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    References listed on IDEAS

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    Cited by:

    1. Brosnan, Stephen, 2016. "The Socioeconomic Determinants of Crime in Ireland from 2003-2012," MPRA Paper 74118, University Library of Munich, Germany.
    2. Lastauskas, Povilas & Tatsi, Eirini, 2017. "Spatial Nexus in Crime and Unemployment in Times of Crisis," Working Paper Series 2/2017, Stockholm University, Swedish Institute for Social Research.
    3. Katarzyna Wawrzyniak & Iwona Bak & Katarzyna Cheba & Maciej Oesterreich, 2020. "The Similarity of European Union Countries in Terms of the Structure of the Unemployed," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 416-429.
    4. 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.
    5. Mohamad Kassem & Amjad Ali & Marc Audi, 2019. "Unemployment Rate, Population Density and Crime Rate in Punjab (Pakistan): An Empirical Analysis," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 8(2), pages 92-104, June.
    6. Süß Philipp, 2020. "Regional Market Income Inequality and its Impact on Crime in Germany: A Spatial Panel Data Approach with Local Spillovers," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 240(4), pages 387-415, August.
    7. 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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    More about this item

    Keywords

    quantile regression; crime; unemployment; market of offences;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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