Reducing Cartel Violence: The Mexican Dilemma Between Social and Security Spending

TL;DR

This paper uses optimal control theory to analyze resource allocation strategies between social programs and security measures in Mexico, revealing that current efforts are nearly optimal but insufficient to significantly reduce cartel violence, which requires much larger investments over time.

Contribution

It introduces a novel optimal control framework to model cartel dynamics and evaluate policy effectiveness, providing insights into resource allocation for violence reduction.

Findings

Cartel's economic burden exceeds US$19 billion annually.

Current budget allocations are nearly optimal but insufficient for significant violence reduction.

Substantial increased funding and time are necessary for meaningful impact.

Abstract

Organised crime in Mexico threatens societal stability and public safety, driving pervasive violence and economic disruption. Despite security investments and social programs designed in part to reduce involvement in crime, cartel power and violence continue to persist. This study evaluates existing policies and introduces a novel framework using optimal control theory to analyse cartel dynamics. Specifically, by modelling resource allocation between security measures and social programs, we identify optimal strategies to mitigate the impacts of cartels. Findings reveal that Mexico's largest cartel imposes an annual economic burden exceeding \text{US\$ } 19 billion, 2.5 times the government's investment in science and technology. We further demonstrate that current budget allocations between social and security programs are nearly optimal yet insufficient to reduce cartel violence significantly. In light of these findings, we demonstrate that achieving meaningful harm reduction would require a significantly larger budget and would take over a decade, even with increased funding.