IDEAS home Printed from https://ideas.repec.org/p/wiw/wiwrsa/ersa15p757.html
   My bibliography  Save this paper

Commuting Time and Urban Violence in Brazil

Author

Listed:
  • Raul Silveira Neto

    ()

  • Klebson Moura

Abstract

Empirical evidence about the influence of exposure to public spaces on victimization strongly support the routine activities theory but, maybe reflecting the difficult of available data, specific evidence about the influence of the commuting on probability of victimization is not abundant. As registered by United Nation Office on Drugs and Crimes (UNODOC, 2012), Brazil is one of the most violent country of the world, with homicide rates around 27.1 (homicides per one hundred thousand people) in 2011, the third highest rate among Latin America countries (behind of only Colombia and Venezuela). This situation, in fact, reflect a general situation of high violence related to other kinds of crime in the country; as related to the violence associated to robbery, for example, the numbers of UNDOC (2012) for 2010 put Brazil, with rates (occurrences per one hundred thousand) of robbery and of theft among the three most violent Latin American Countries. But the problem of urban violence is neither the only substantive urban problem of Brazilian big urban centers, nor it is dissociated to other urban problems in these centers. Besides the risk of being victim of urban violence, visitors or inhabitants of Brazilian metropolitan regions must face with the problem of low mobility in these cities. The very bad quality of public transport together with public indirect subsidies for using individual transport make short distance locomotion a very high time demand action (IPEA, 2013). According to the more recent information of PNAD (PNAD 2012), the average commuting time for the inhabitant of Brazilian metropolitan regions was around 40.8 minutes in 2012, a very high number if compared to metropolitan regions around the world (Pereira and Schwanen, 2013; Silveira Neto et al. 2014). In this paper, we analyze this relationship using a large nationally representative cross-section sample of Brazilian individuals for 2009 using more traditional multivariate regressions and propensity score matching techniques to create counterfactuals. We also perform robustness checks, by applying different estimators (Abadie and Imbens, 2002), and implement a simulation-based sensitivity analysis that supports a causal interpretation of the results (Ichino wt al. 2008). We find that individuals with more than one hour of commuting have an overall 2.1% increase in the probability of being victim of robbery, with no robust impact on theft. Also, following the exposure literature we find larger effect on the probability of robbery victimization on women when compared with men, 2.5% and 2.2% respectively.

Suggested Citation

  • Raul Silveira Neto & Klebson Moura, 2015. "Commuting Time and Urban Violence in Brazil," ERSA conference papers ersa15p757, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa15p757
    as

    Download full text from publisher

    File URL: http://www-sre.wu.ac.at/ersa/ersaconfs/ersa15/e150825aFinal00757.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    2. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    3. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    4. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters,in: Essays in the Economics of Crime and Punishment, pages 1-54 National Bureau of Economic Research, Inc.
    5. Gaviria, Alejandro & Pages, Carmen, 2002. "Patterns of crime victimization in Latin American cities," Journal of Development Economics, Elsevier, vol. 67(1), pages 181-203, February.
    6. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    7. Alberto Abadie & David Drukker & Jane Leber Herr & Guido W. Imbens, 2004. "Implementing matching estimators for average treatment effects in Stata," Stata Journal, StataCorp LP, vol. 4(3), pages 290-311, September.
    8. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
    9. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
    10. Rafael Henrique Moraes Pereira & Tim Schwanen, 2013. "Tempo de Deslocamento Casa - Trabalho no Brasil (1992-2009): Diferenças Entre Regiões Metropolitanas, Níveis de Renda e Sexo," Discussion Papers 1813, Instituto de Pesquisa Econômica Aplicada - IPEA.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    commuting; urban violence; treatment effect;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • K49 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Other

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wiw:wiwrsa:ersa15p757. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Gunther Maier). General contact details of provider: http://www.ersa.org .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.