Is the fight against Mexican drug cartels beneficial to public
security?
Nils-Hendrik KLANN
University of Göttingen & University of Heidelberg
New Directions in Welfare 2011 Congress
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Motivation
“We have 18 months and if we do not produce a tangible success
that is recognizable to the Mexican people, it will be difficult to
sustain this confrontation into the next administration.”
Gerónimo Gutiérrez, Deputy Secretary for Domestic Security
(Diplomatic cable from 2009; Wikileaks)
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Motivation
The ‘War on Drugs’ has become a global phenomenon as
governments in many countries seek to fight the activities of
international drug cartels.
The growing sophistication of drug gangs as well as their everincreasing affinity to violence against opponents pose a direct
challenge to the authority of governments.
In many countries, society is caught in the middle between
opposing forces in an increasingly brutal conflict between gangs
and security forces.
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Motivation
Acting both as a producer and transport hub for drugs, Mexico has
become the center stage for an extremely violent conflict between
gangs competing to deliver drugs to the US market.
Since 2006, the Mexican government has significantly stepped up
its initiative against drug cartels, relying on police as well as 35,000
soldiers to fight Mexico’s drug cartels.
With regards to tackling the activities of Mexico’s drug cartels, the
government’s anti-drug initiative is often called into question.
New Directions in Welfare 2011 Congress
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Motivation
On the other hand, no empirical analysis exists to date focusing on
the broader implications of Mexico’s drug war for society.
Objective of this paper
Investigate the effect of Mexico’s anti-drug initiative on the
prevalence of non-drug offences such as property crime, assault,
rape and murder at the district level.
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Outline
1.
2.
3.
4.
5.
Introduction
Literature Overview
Research Outline
Empirical Results
Conclusion
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1. Introduction
With the ‘War on Drugs’ going on for several years and its effect on
cartel activities dubious at best, which effects will this initiative have
on the Mexican society?
This paper focuses on the prevalence of non-drug related offences
in the approximately 2500 municipal districts in the time period from
1998 until 2008 to assess whether or not the intensity of anti-drug
efforts impacts on the prevalence of non-drug crime (NDC).
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2. Literature Overview
Prior research on the effect of drug enforcement on other forms of
crime focus provide contrasting predictions:
Theory 1 Intensified drug enforcement increases non-drug crime
Welfare of society is reduced as the anti-drug initiative implies
negative externalities in the form of rising crime rates.
Relies on seminal contribution by Becker (1986) and Ehrlich (1973)
predicting the likelihood of criminal activity in the light of expected
gains and costs:
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2. Literature Overview
Several sources such as Sollars, Benson et al. (1994)
Benson, Kim et al. (1994), Benson, Rasmussen et al. (1998)
Benson, Leburn et al. (2001) analyze the implications of a marked
concentration of police forces to battle drug offenders in 67 Florida
counties around the 80s and 90s on non-drug crime.
Also, Resignato (2000) and Shepard and Blackley (2005) conduct
a similar investigation focusing on New York State.
Key finding
the concentration of finite law enforcement
resources on one predominant type of crime
increases all other types of crime (crowding out effect)
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2. Literature Overview
An alternative explanation of this positive relationship is discussed
in Miron (1999) and with an empirical analysis in Miron (2001).
Here, violence is a systemic feature of black markets, in which
participants are unable to resort to legal institutions such as
the police or courts to resolve disputes or enforce their property
rights. This process is exacerbated as enforcement intensifies.
Key finding
Intensifying enforcement efforts increases
the potential for violent turf wars.
Classic example: gang crime in the ambit of alcohol prohibition in
the United States. (e.g., Asbridge and Weerasinghe (2009))
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2. Literature Overview
Theory 2 Intensified drug enforcement reduces non-drug crime
Contrasting opinion see the potential for complementarity between
the objectives to fight DC and NDC offenders.
In an ideal case, stepping up drug enforcement not only reduces
drug offences but beyond that yields additional gains as the
measure leads to a simultaneous reduction of non-drug offences
e.g., robbery, assault and kidnapping.
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2. Literature Overview
Analyzing US crime and incarceration data for the time period of
1983 until 1996 Kuziemko and Levitt (2004) find evidence that
stricter punishment of drug offences yields a twofold effect:
1.
2.
longer incarceration of drug offenders impacts negatively
on the duration served by NDC felons BUT counter to the
predictions of the aforementioned Becker framework has
no proliferating effect on NDC crime:
significant negative relationship between the incarceration
of drug offenders and non-drug crime:
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2. Literature Overview
Key finding
Incarcerating drug offenders indirectly
helps to reduce non-drug crime as
drug offenders dedicate a significant share
of their activities towards offences such as
assault and murder.
In line with this, Levitt and Venkatesh (2000) which investigate the
daily routine and financials of a Chicago drug gang finds that about
one fourth of a gang member’s time is dedicated to violent crime:
Shipley (1989) finds similar trends analyzing offences committed by
incarcerated drug offenders:
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2. Literature Overview
Summary of the two strands of literature
Limited Police
resources
Crowding out
effects
NDC
increase
Incarcerating
drug traffickers
positive
secondary
effects
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NDC
decrease
July 1, 2016
3. Research Outline and Methodology
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3. Research Outline and Methodology
Analysis of district-level data from approx. 2500 municipal districts,
spread out over 32 federal states over the time period of
1998-2008; running the following empirical model:
Dependent variable
NDC log of non-drug crime incidents in a district (5 indicators)
Source: Statistical Yearbooks from 32 federal states; National Statistics Institute
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3. Research Outline and Methodology
Independent Variables
DE share of drug arrests over all
arrests in a district
DENS district population per km2
Source: Statistical Yearbooks from 32 states;
Mexican National Statistics Institute (INEGI)
the Mexican Geographic Service
POP log district population
URATE district unemployment rate
Source: Natl. Institute for Federalism and Municipal Development
Source: Secretary for Employment and Social Security (STPS)
HIGHW Highway Dummy
CDET deterrence arrests/offences
Source: Author’s calculation
Source: Authors calculation based on Statistical Yearbooks from
32 federal states; National Statistics Institute
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Source: Authors calculation based on surface data from
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3. Research Outline and Methodology
Offences implemented as depended variable include
- Robbery
- Assault
- Rape
- Murder
- Gang murder*
*Data on gang murder is provided by the Mexican Interior Ministry from the year
2006 onwards. Victims were categorized as gang victims based on the
circumstances of their death, e.g., the use of large caliber weapons, signs of torture
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4 Empirical Results
Regression Framework
Ordinary Least Squares (baseline)
FE (district fixed effects)
Negative Binomial (count data)
GMM (endogeneity)
Robustness checks carried out in the course of regressions:
Exclusion of each federal state and year
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[Pooled OLS] Total offences in log
Robbery
drug enforcement
Assault
Murder
Rape
4. Empirical
Results
-0.615*** -1.465***
0.022
-0.304**
log of population
log of density
unemployment rate
highway in district
robbery | arrests/offences
(-7.60)
1.234***
(95.57)
-0.032***
(-3.88)
10.548***
(22.53)
0.357***
(11.55)
-2.021***
(-29.28)
assault | arrests/offences
(-19.13)
1.064***
(89.96)
-0.006
(-0.86)
5.168***
(12.30)
0.246***
(8.60)
(0.29)
0.881***
(69.45)
-0.089***
(-11.70)
-3.830***
(-8.83)
-0.023
(-0.77)
-1.802***
(-33.30)
rape | arrests/offences
-8.672***
(-66.82)
R2
0.834
N
5097
* p<0.10, ** p<0.05, *** p<0.01
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0.996**
(2.43)
0.704***
(11.46)
-0.238***
(-6.75)
5.048***
(2.59)
-0.174
(-1.35)
-1.866***
(-32.67)
murder | arrests/offences
constant
(-2.45)
0.888***
(51.06)
-0.035***
(-3.56)
-0.900*
(-1.77)
0.005
(0.13)
Gang Killings
-6.846***
(-55.76)
0.844
4976
-5.584***
(-46.47)
0.722
3876
-0.290
(-1.07)
-2.020***
(-28.78)
-6.238***
(-34.30)
0.778
2330
-5.719***
(-9.80)
0.291
545
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[Fixed Effects] Total offences in log
Robbery
drug enforcement
Assault
Murder
4. Empirical
Results
-0.474*** -0.544***
-0.324***
log of population
unemployment rate
robbery | arrests/offences
(-7.16)
0.088**
(2.06)
0.291
(0.47)
-1.744***
(-24.52)
assault | arrests/offences
(-8.04)
0.173***
(3.82)
-2.481***
(-3.45)
(-4.42)
0.032
(0.81)
-2.234***
(-3.03)
-0.396**
(-2.37)
0.135***
(2.99)
-0.759
(-0.72)
Gang Killings
0.632
(1.13)
0.125
(0.97)
28.767***
(5.38)
-1.326***
(-19.24)
murder | arrests/offences
-1.428***
(-21.22)
rape | arrests/offences
constant
Rape
-8.672***
(-66.82)
0.346
4878
-6.846***
(-55.76)
0.220
4714
-5.584***
(-46.47)
0.308
3663
-0.566
(-1.48)
-1.420***
(-17.29)
-6.238***
(-34.30)
0.384
2091
-5.719***
(-9.80)
0.533
353
R2
N
* p<0.10, ** p<0.05, *** p<0.01
All regressions with time and district fixed effects; robust t-values in brackets
Standard errors in OLS Fixed Effects regressions adjusted for clustering across districts
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[Negative Binomial] Total offences
Assault
Murder
4.Robbery
Empirical
Results
drug enforcement
log of population
unemployment rate
highway in district
robbery | arrests/offences
-0.481***
(-8.91)
0.184***
(9.47)
0.058
(0.14)
-0.168**
(-2.23)
-1.850***
(-33.73)
assault | arrests/offences
-0.613***
(-10.45)
0.141***
(7.59)
-3.097***
(-6.64)
-0.461***
(-5.59)
-0.268***
(-3.80)
0.005
(0.21)
-2.946***
(-4.66)
-0.279**
(-2.27)
-1.452***
(-29.46)
rape | arrests/offences
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-0.787***
(-5.18)
0.012
(0.44)
0.660
(0.85)
-0.046
(-0.30)
Gang Killings
1.624***
(5.36)
0.600***
(11.99)
2.879
(1.22)
-0.119
(-0.71)
-1.362***
(-28.24)
murder | arrests/offences
N
4878.000
* p<0.10, ** p<0.05, *** p<0.01
Rape
4714.000
3663.000
-0.272
(-1.01)
-1.520***
(-20.56)
2091.000
1160.000
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[GMM] Total offences
Robbery
lagged dependent
drug enforcement
log of population
0.327***
(5.43)
-0.306***
(-3.36)
0.796***
(10.20)
4.856***
(5.86)
0.257***
(4.18)
-1.568***
(-14.89)
Assault
Murder
Rape
(6.45)
-0.848***
(-9.69)
0.742***
(13.88)
2.194***
(3.43)
0.166***
(3.05)
0.208***
(4.60)
0.025
(0.31)
0.590***
(15.20)
-3.166***
(-4.14)
0.021
(0.35)
0.216***
(3.53)
-0.222
(-1.50)
0.638***
(10.60)
-1.270*
(-1.80)
0.017
(0.28)
. 0.291***
4. Empirical Results
unemployment rate
highway in district
robbery | arrests/offences
assault | arrests/offences
-1.244***
(-17.12)
rape | arrests/offences
-5.224***
(-8.88)
-4.519***
(-11.28)
-3.600***
(-11.57)
-0.770
(-1.19)
-1.725***
(-16.45)
-4.208***
(-8.23)
R2
N
3380
3236
2670
1622
Hansen J
13.882
17.279
11.085
13.337
(p-value)
0.178
0.068
0.351
0.148
Arellano-Bond test for AR1 in 1st differences -6.351
-7.494
-7.957
-4.212
(p-value)
0.000
0.000
0.000
0.000
Arellano-Bond test for AR2 in 1st differences -1.047
-0.574
-0.868
-0.32
(p-value)
0.295
0.566
0.385
0.749
Number of districts
670
685
572
471
Number of instruments
27
27
27
26
* p<0.10, ** p<0.05, *** p<0.01
Two-step System GMM with time fixed effects and Windmeijer finite sample correction
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0.837***
(3.67)
0.805
(1.19)
0.202*
(1.80)
2.361
(0.84)
-0.159
(-0.64)
-1.503***
(-16.92)
murder | arrests/offences
constant
Gang Killings
-1.914
(-1.35)
195
0.278
0.598
176
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5. Conclusion
Regarding the effect of drug enforcement in general:
A greater share of arrests among all arrests seems to reduce the
Prevalence of most NDC offences at the district level.
Some indication exists regarding the expected positive relationship
between drug enforcement and gang murder – results should be
Interpreted with caution however, given the short time span of the
Data.
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5. Conclusion
Regarding the control variables:
In line with expectations, population yields a positive effect on the
number of offences.
Unemployment has a significant effect on crime - however no
singular relationship can be derived from the results.
Deterrence measures show the expected negative effect on all
types of crime except gang murder.
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5. Conclusion
Thank you
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