While most economic studies of crime have examined the determinants of criminal activity, this paper asks the reverse question: how does crime affect economic behavior? We study the relationship between crime and savings in the cities of São Paulo, a wealthy but crime-ridden state in Brazil....

Most models of optimal income tax enforcement assume that income is either random or solely remunerates labor, neglecting that auditing strategies may depend on observable inputs. This paper outlines a model to optimally monitor self-employed entrepreneurs when, in addition to reported profits,...

This paper introduces cash transfers targeting the poor in an incomplete markets model with heterogeneous agents facing idiosyncratic risk. These transfers change the degree of insurance in the economy and aect precautionary motives asymmetrically, leading the poorest households to decrease...

This paper augments a relatively standard dynamic general equilibrium model with financial frictions in order to quantify the macroeconomic effects of the credit deepening process observed in many Latin American (LA) countries in the last decade, most notably in Brazil. In the model, a stylized...

A public job can be seen as a source of insurance against income risk. Indeed, many public employees have job stability, which is compounded with a less volatile and more compressed wage distribution. Hence, by increasing its number of public employees, the government enhances the overall degree...

We use data from a unique survey of members of drug-trafficking gangs in favelas (slums) of Rio de Janeiro, Brazil, to characterize drug-trafficking jobs and study the selection into gangs, analyzing what distinguishes gang-members from other youth living in favelas. We also estimate wage...

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially orgeometrically). In other...

In this paper we show the validity of the adaptive LASSO procedure in estimating stationary ARDL(p,q) models with GARCH innovations. We show that, given a set of initial weights, the adaptive Lasso selects the relevant variables with probability converging to one. Afterwards, we show that the...