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Income inequality and violent crime : evidence from Mexico's drug war (Английский)

The relationship between income inequality and crime has attracted the interest of many researchers, but little convincing evidence exists on the causal effect of inequality on crime in developing countries. This paper estimates this effect in a unique context: Mexico's Drug War. The analysis takes advantage of a unique data set containing inequality and crime statistics for more than 2,000 Mexican municipalities covering a period of 20 years. Using an instrumental variable for inequality that tackles problems of reverse causality and omitted variable bias, this paper finds that an increment of one point in the Gini coefficient translates into an increase of more than 10 drug-related homicides per 100,000 inhabitants between 2006 and 2010. There are no significant effects before 2005. The fact that the effect was found during Mexico's Drug War and not before is likely because the cost of crime decreased with the proliferation of gangs (facilitating access to knowledge and logistics, lowering the marginal cost of criminal behavior), which, combined with rising inequality, increased the expected net benefit from criminal acts after 2005.

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  • Автор

    Enamorado Enamorado,Ted, Lopez-Calva,Luis-Felipe, Rodriguez Castelan,Carlos, Winkler-Seales,Hernan Jorge

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  • Тип документа

    Рабочий документ в рамках исследования вопросов политики

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    Латинская Америка и страны Карибского бассейна,

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  • Название документа

    Income inequality and violent crime : evidence from Mexico's drug war

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    income inequality;real per capita income;federal law enforcement agency;Municipalities;effect inequality;Poverty & Inequality;increase in inequality;increasing income inequality;cost of crime;access to knowledge;lack of resource;homicide rate;criminal activity;monetary poverty measures;police and security;degree of poverty;violent crime rate;national population council;impact of inequality;food poverty line;basic food basket;distribution of household;effects of income;determinants of crime;scale of inequality;general population;national income distribution;labor market institution;average household income;local public expenditure;household survey data;expenditure per capita;high crime rate;rising income inequality;linear regression model;global financial crisis;education and health;instrumental variable;empirical evidence;criminal behavior;local inequality;municipality level;organized crime;local income;causal effect;measurement error;criminal organization;welfare indicator;unit increase;urban municipality;increasing inequality;Political Economy;census data;robustness check;population size;summary statistic;monetary measure;real income;crime statistic;cross-country study;legal activity;social tension;Drug use;drug traffic;empirical literature;estimation methodology;youth gang;inequality measure;literature review;police force;human capital;social capital;higher inequality;Real estate;universal coverage;anecdotal evidence;municipal police;income growth;local spending;transportation expense;civil disturbance;military intervention;citizen security;traffic infraction;federal police;urban sector;negative correlation;descriptive statistic;federal spending;development study;state authority;standard error;explanatory variable;peace research;immigration flows;Urban Violence;Public Spending;research assistance;annual sale;border cities;social structure;poverty matters;random sample;private security;security service;drug trafficker;judiciary system;binding constraint;weighted average;crime level;empirical work;municipal government;criminal group;present evidence;negative effect;inequality datum;economics literature;expected utility;Economic Inequality;poverty increase;social exclusion;poverty status;property crime;police activity;illegal activities;positive impact;empirical investigation;Violent Conflict;sole responsibility;judicial inefficiency;economics research;illegitimate activity;public figures;median income;cross-sectional data;school district;time-series analysis;social cost;estimation strategy;econometric model;delinquent behavior;urban study;collaborative effort;open access;alternative measure;mapping poverty;rising inequality;declining inequality;enterprise survey;Social Welfare;income poverty;socioeconomic variables;drug gangs;welfare variable;statistical significance;literate population;incentive mechanism;crime cost;causal relationship;geographic pattern;asset poverty;development policy;family structure;rural level;vehicle theft;income regressions;regional migration;negative relationship;basic diet;inequality level;population mean;sample mean;local factors;

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