Poster Paper: Drug-Related Violence and Labor Productivity: Evidence Using a Spatial Panel Data Model

Thursday, July 19, 2018
Buidling 5, Libreria Foyer (Bookstore Foyer) (ITAM)

*Names in bold indicate Presenter

David Saucedo De La Fuente, University of Texas, Dallas

The purpose of the research project is to investigate the effect of drug-related violence on Mexico’s economy during the period 2006-2017 at the state level. First, in estimating the effects of drug-related crimes on labor productivity, the research project contributes to the growing literature on Mexico’s Drugs War by using an exploratory spatial data analysis with the aim to provide evidence of global and local spatial autocorrelation as well as spatial heterogeneity in the distribution of drug-related violence. The detection of spatial clusters of drug-related crimes allows to identify the persistence of spatial disparities across Mexican regions (e.g., border states vs. non-border states). Second, a spatial econometric approach examines the impact of drug-related violence on labor productivity by controlling for economic and socioeconomic variables as well as government security policies. Briefly, a spatial panel data model not only controls for spatial autocorrelation and individual heterogeneity across regions, but also allows to identify spillover effects which is relevant for regional policy implications. That is, a spatial econometric approach can identify the effect(s) of rising drug-related violence of neighborhood states on a state’s labor productivity. In doing so, the spatial econometric analysis takes into account both manufacturing and non-manufacturing activities. Last but not least, the results expect to contribute not only to the literature by adding a spatial dimension to the analysis of crime on economic variables, but also to a public policy agenda that could reduce drug-related violence in targeted areas and promote regional productivity spillovers.