Cartelnomics

Cartelnomics. Felipe Juncal. 2024.

Abstract.

Impact of Drug Traffic Organizations (DTOs) on the economy of mexican municipalities.

DTOs presence is associated with a decrease in:

1. formal employment
2. the number of establishments,
3. average wages, and
4. total wage mass.

through mechanisms such as:

1. extortion, and
2. creation of uncertainty.

Sectorial differences highlighted: 

1. Sectors with high fixed costs and significan upfront capital investments are the most affected: Manufacturing, commerce and construction.
2. Sector with greater mobility and lower entry barriers are less affected: Services.

Intro.

DTOs are complex organizations with highly defined command and control structures that produce, transport, and/or distribute large quantities of illicit drugs.

Beyond criminal violence, the mere presence of DTOs can put economic activity at risk and modify the decisions of multiple agents, such as business people and entrepeneurs, due to the extraction of rents and the creation of uncertainty.

Use of differences-in-differences.

Correction biases through treatment effects: 

1. Borusyak, 2021,
2. Callaway, 2020
3. Chaisemartin, 2020

Data from:

1. Sobrino, 2020.
2. Encuesta Nacional de Victimización de Empresas.
3. Atlas de Complejidad Económica. 

Review.

1. Balleta and Lavezzi (2023). DTOs create additional fied costs that distort investment decisions in firms. Credit rationing: higher interest rates.
2. Robles et al (2015). Violence reduces electricity consumption.
3. Utar (2022). Violence reduces plant output, product distribution, and employment.
4. Sotlkin Moss (2023). DTOs presence increases price dispersion by 3 MXN in CPI basket.
5. Wysocki (2015). Displacement of students to areas withlower levels of violence.
6. Gómez (2021). Decreased nominal wages.
7. Dettoto and Otranto (2010). Misallocation of resources: extortion and increased marginal costs.
8. Mascarúa (2022). Lower use of inputs, contraction of wages and distortion of occupational choice.
9. Ornelas (2018). Non-productive investment such as protection.
10. Hoelscher (2021). Micro, small and medium navigate through legality, illegality and violence.
11. Jaspers (2019). Integration of DTOs into legal networks and legitimate businesses.
12. Estancona and Tiscornia (2022). DTOs expanding to control the avocado sector.
13. Farfán Méndez (2019). DTOs long term investments, risk averse ML.
14. Vázquez Valencia (2019). Network analysis to uncover criminal reltionships between political, criminal and financial entities.
15. Rodríguez Hurtado (2023). DTOs select more prosperous and developed areas in Mexico.

Context.

Competitive elections, political changes. New authorities not aligned with cartels. Competition of new cartels escalated into violence. Trejo and Ley (2022). Electoral competition and partisan conflict contributes to the rise in the number of DTOs. From 15 in 2000 to 75 in 2020.

Alcocer (2022). Diversification of activities beyond drug trafficking: extortion, kidnapping, rent-seeking, and extraction of natural resources.

Model.

Ym,s,t = α + β1DTO m,t + ɣm + δt + vs + εi

1. Difference in differences per Borusyac (2021)
2. Two Way Fixed Effects (TWFE)
3. Parallel trends
4. Robustness check:
1. Callaway (2020)
2. Chaisemartin (2020)

Results.

Table. Reduction due to the presence of DTOs (%) 

	FIRMS	JOBS	WAGES	BILL
TOTAL	2.4	4.3	4.8	8.1
INDUSTRY	4.1	8.1	2.9*
SALES	4.9	8.0	6.2*
SERVICES	3.2	2.6*	2.5*

Cartel influence is more pronounced when a single cartel arrives to a place than when we see an increase in the number of DTOs.

Conclusions.

• Underscores the adverse economic impacts of organized crime.
• There is a distinctions between mere presence and open violence.
• Economic repercussions of DTOs presence are not uniform across industries.
• The arrival of additional DTOs does not significantly exacerbate the adverse impacts.
• Policies must address the particular vulnerabilities of the different sectors.