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Violent Crime in Latin American Cities

Carlos J. Vilalta Jos? G. Castillo Juan A. Torres

Institutions for Development Sector

Institutional Capacity of the State Division

DISCUSSION PAPER N?

IDB-DP-474

August 2016

Violent Crime in Latin American Cities

Carlos J. Vilalta Jos? G. Castillo Juan A. Torres

August 2016

 Copyright ? 2016 Inter-American Development Bank. This work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license ( licenses/by-nc-nd/3.0/igo/legalcode) and may be reproduced with attribution to the IDB and for any noncommercial purpose. No derivative work is allowed. Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC-IGO license. Note that link provided above includes additional terms and conditions of the license. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent.

Contact: Jos? Antonio Mejia-Guerra, Joseam@.

Abstract* In the last two decades, Latin America has been describes as an unsafe and violent region. Nonetheless, such picture is mostly based on homicide rates. Even though homicide is considered the best recorded crime, it does not provide full account of other forms of violent crime. Moreover, a great deal of research on crime throughout the region tends to be descriptive and anecdotal. Misunderstanding the causes of crime and disregarding evidence might induce policy makers to implement ineffective strategies, particularly at the local level. Therefore, based on Social Disorganization Theory, this study explains violent crime across and within selected cities of Latin America. JEL code: K420 Keywords: crime, crime levels, crime hot spots, crime trends, law enforcement, murder, policing, study of crime

* Special thanks to UNODC, in particular to the Center of Excellence in Statistical Information on Government, Crime, Victimization and Justice, and the Statistics & Surveys Sections for their technical assistance.

Index Prologue ............................................................................................................................................. 6 Introduction......................................................................................................................................... 7 1. Violent Crime in Latin America: context, trends and dynamics ................................................... 9

1.1. Homicide trends at regional, sub-regional and country levels ............................................. 9 1.2. Homicide and other violent crimes in Latin American countries ........................................ 14 1.3. Homicide in Latin American cities: exemplifying the variation ........................................... 16 1.4. Violent crimes in Latin American cities .............................................................................. 19 1.5. Characteristics of violent crimes ........................................................................................ 22

1.5.1. Homicide ..................................................................................................................... 22 1.5.2. Other violent crimes .................................................................................................... 26 2. Explaining violent crime in Latin America.................................................................................. 27 2.1. Traditional perspectives ..................................................................................................... 27 2.1.1. Economic perspective ................................................................................................. 27 2.1.2. The socio-structural perspective ................................................................................. 28 2.1.3. The political perspective.............................................................................................. 29 2.1.4. Limitations of existing research................................................................................... 29 2.2. Social disorganization theory ............................................................................................. 30 3. Data analysis and interpretation ............................................................................................... 36 3.1. Inter-urban analysis ........................................................................................................... 38 3.1.1. Data analysis............................................................................................................... 39 3.2. Intra-urban analysis ........................................................................................................... 43 3.3. Zapopan (Mexico) .............................................................................................................. 44 3.3.1. Zapopan: Country and city context ............................................................................. 44 3.3.2. Descriptive statistics and mapping.............................................................................. 46 3.3.3. Poisson regression analysis........................................................................................ 52 3.3.4. Geographically Weighted Regression analysis........................................................... 53 3.4. The Great Metropolitan Area of Costa Rica (GMA) ........................................................... 58 3.4.1. GMA: Country and city context ................................................................................... 58 3.4.2. Descriptive statistics and mapping.............................................................................. 59 3.4.3. Poisson Regression analysis ...................................................................................... 63 3.4.4. Geographically Weighted Regression analysis........................................................... 64 3.5. Santiago de Chile (Chile) ................................................................................................... 67 3.5.1. Santiago: Country and city context ............................................................................. 67 3.5.2. Descriptive statistics and mapping.............................................................................. 69 3.5.3. Poisson Regression analysis ...................................................................................... 75 3.5.4. Geographically Weighted Poisson Regression analysis ............................................. 76 4. Discussion................................................................................................................................. 81 4.1. Summary of findings .......................................................................................................... 81

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