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The Effect of Adult Criminals’ Spillovers On the Likelihood of Youths Becoming Criminals

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  • Carlos Medina
  • Jorge Andrés Tamayo
  • Christian Posso

Abstract

We use a unique data set at the individual level to estimate an empirical model explaining the probability of young individuals to become criminals as a function of the presence of adult criminals in their neighborhoods, an a complete set of control variables, including census sector fixed effects. We use the census of criminals captured in Medellín between 2000 and 2010 to construct our peer’s variables, and find a strong and robust positive effect of the presence of adult criminal neighbors on the probability of becoming criminal. The result is robust across different specifications of the presence of criminals, and with respect to the probability of committing different types of crimes, even controlling for contextual and group effects. Both modeling peer effects as the sum of friends’ efforts and modeling them as deviations from the means, affect the likelihood to become criminal, although with differential importance by type of crime.

Suggested Citation

  • Carlos Medina & Jorge Andrés Tamayo & Christian Posso, 2013. "The Effect of Adult Criminals’ Spillovers On the Likelihood of Youths Becoming Criminals," Borradores de Economia 755, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:755
    DOI: 10.32468/be.755
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    References listed on IDEAS

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    1. Criminal path-dependence (Medellin)
      by UDADISI in UDADISI on 2013-03-06 09:00:00

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    Cited by:

    1. Leonardo Fabio Morales & Lina Cardona-Sosa, 2014. "The Influence of Neighborhood Characteristics on Wages and Labor Supply in an Urban Context: The Case of a Latin-American City," Borradores de Economia 844, Banco de la Republica de Colombia.
    2. Leonardo Fabio Morales & Lina Cardona-Sosa, 2015. "Calidad de los vecindarios y oferta laboral femenina en un contexto urbano: un caso aplicado a la ciudad de Medellín," Borradores de Economia 12588, Banco de la Republica.

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    More about this item

    Keywords

    Crime; Social Interactions.;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • K40 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - General
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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