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The Economic Determinants of Crime: an Approach through Responsiveness Scores

Author

Listed:
  • Giovanni Cerulli

    () (CNR-IRCrES)

  • Maria Ventura

    () (STICERD, London School of Economics)

  • Christopher F Baum

    () (Boston College
    DIW Berlin)

Abstract

Criminality has always been part of human social interactions, shaping the way peoples have constructed states and legislation. As social order became a greater concern for the public authorities, interest in investigating incentives pushing individuals towards engaging in illegal activities has become a central issue of the political agenda. Building on the existing literature, this paper proposes to focus on a few primary determinants of crime, whose effect is in- vestigated using a Responsiveness Scores (RS) approach performed over 50 US states during the period 2000-2012. The RS approach allows us to account for unit heterogeneous response to each single determinant, thus paving the way to a more in-depth analysis of the relation between crime and its drivers. We attempt to overcome the limitations posed by standard regression methods, which assume a single coefficient for all determinants, thus contributing to the literature in the field with stronger evidence on determinants' e ects and the geographical patterns of responsiveness scores.

Suggested Citation

  • Giovanni Cerulli & Maria Ventura & Christopher F Baum, 2018. "The Economic Determinants of Crime: an Approach through Responsiveness Scores," Boston College Working Papers in Economics 948, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:948
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    References listed on IDEAS

    as
    1. Cerulli, Giovanni, 2014. "The Impact of Technological Capabilities on Invention: An Investigation Based on Country Responsiveness Scores," World Development, Elsevier, vol. 59(C), pages 147-165.
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    4. Oreopoulos, Philip, 2007. "Do dropouts drop out too soon? Wealth, health and happiness from compulsory schooling," Journal of Public Economics, Elsevier, vol. 91(11-12), pages 2213-2229, December.
    5. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, September.
    6. Abdul Abdullah & Hristos Doucouliagos & Elizabeth Manning, 2015. "Does Education Reduce Income Inequality? A Meta-Regression Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 29(2), pages 301-316, April.
    7. Gumus, Erdal, 2003. "Crime in Urban Areas: An Empirical Investigation," MPRA Paper 42106, University Library of Munich, Germany.
    8. Eric D. Gould & Bruce A. Weinberg & David B. Mustard, 2002. "Crime Rates And Local Labor Market Opportunities In The United States: 1979-1997," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 45-61, February.
    9. Giovanni Cerulli, 2017. "Estimating responsiveness scores using rscore," Stata Journal, StataCorp LP, vol. 17(2), pages 422-441, June.
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    More about this item

    Keywords

    Crime; Incentives; Responsiveness Scores;
    All these keywords.

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • P46 - Economic Systems - - Other Economic Systems - - - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty

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