Essays on economics of education and inequality

El documento resume los resultados de los tres ensayos sobre economía de la educación y de igualdad de oportunidades que se realizaron para el caso de Colombia.

Economic shocks and crime: evidence from the crash of ponzi schemes

In November 2008, Colombian authorities dismantled a network of Ponzi schemes, making hundreds of thousands of investors lose tens of millions of dollars throughout the country. Using original data on the geographical incidence of the Ponzi schemes, this paper estimates the impact of their break down on crime. We find that the crash of Ponzi schemes differentially exacerbated crime in affected districts. Confirming the intuition of the standard economic model of crime, this effect is only present in places with relatively weak judicial and law enforcement institutions, and with little access to consumption smoothing mechanisms such as microcredit. In addition, we show that, with the exception of economically-motivated felonies such as robbery, violent crime is not affected by the negative shock.

Neighborhood characteristics and the spatial concentration of crime: Evidence for Bogotá

Using a unique neighborhood crime dataset for Bogotá in 2011, this study uses a spatial econometric approach and examines the role of socioeconomic and agglomeration variables in explaining the variance of crime. It uses two different types of crime, violent crime represented in homicides and property crime represented in residential burglaries. These two types of crime are then measured in non-standard crime statistics that are created as the area incidence for each crime in the neighborhood. The existence of crime hotspots in Bogotá has been shown in most of the literature, and using these non-standard crime statistics at this neighborhood level some hotspots arise again, thus validating the use of a spatial approach for these new crime statistics. The final specification includes socioeconomic, agglomeration, land-use and visual aspect variables that are then included in a SARAR model an estimated by the procedure devised by Kelejian and Prucha (2009). The resulting coefficients and marginal effects show the relevance of these crime hotspots which is similar with most previous studies. However, socioeconomic variables are significant and show the importance of age, and education. Agglomeration variables are significant and thus more densely populated areas are correlated with more crime. Interestingly, both types of crimes do not have the same significant covariates. Education and young male population have a different sign for homicide and residential burglaries. Inequality matters for homicides while higher real estate valuation matters for residential burglaries. Finally, density impacts positively both crimes.