Quantifying the economic effects of narcotics trafficking in Mexico using remote-sensed measures of illicit crop production

Regions involved in the production and shipment of illicit drugs often exhibit high levels of violence, weak institutions, elevated risks of extortion for firms, and poor development. Despite this, the economic consequences of the drug trade re main unclear , particularly in legal sectors of the economy. To study the effects of drug production, we examine the context of Mexico, where rural farmers face the tradeoff between the production of legal crops and drugs ( particularly marijuana and opium poppy) . Simultaneously , drug trafficking organizations (DTOs) choose to locate in areas best suited to facilitate the transport of drugs from areas of production to markets , and choose to extort legitimate firms where they operate . Therefore, to understand the downstream effects of such organizations, it is crucial to have a sense of where illicit drug production occurs in the absence of reliable information about DTO activities . Previous work ha s examined indirect measures of drug production such as military eradication efforts, for which spatial and temporal coverage may be incomplete. H owever, recent work in the field of remote sensing allow s for a new alternative in the detection of illegal drug production. B uild ing on the work of Liu et al. (2018), w e employ a deep learning based approach based upon geolocated eradication data to classify poppy production areas using a combination of high resolution multispectral and medium-quality hyperspectral satellite imagery. To quantify the economic effects of DTOs , we combine these remote-sensed measures of opium production with a general equilibrium trade model in the spirit of Sotelo (2019) that allows for tradeoffs between legal crop and illegal drug production ; this interaction can potentially impact other regions and sectors of the economy through spillover effects and by the reorganization of drug trafficking organizations .