Bushes and Bullets: Illegal Cocaine Markets and Violence in Colombia

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NOVIEMBRE DE 2013

Documentos CEDE

C E D E

Centro de Estudios sobre Desarrollo Económico

ISSN 1657-7191 Edición electrónica.

Daniel Mejía

Pascual Restrepo

Bushes and Bullets:

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Serie Documentos Cede, 2013-53

ISSN 1657-7191 Edición electrónica.

Noviembre de 2013

Bogotá, D. C., Colombia

Teléfonos: 3394949- 3394999, extensiones 2400, 2049, 3233

[email protected] http://economia.uniandes.edu.co

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C E D E

Centro de Estudios sobre Desarrollo Económico

Bushes and Bullets:

Illegal Cocaine Markets and Violence in

Colombia.

Daniel Mej´ıa and Pascual Restrepo

∗

October 23, 2013

Abstract

This paper proposes a new identification strategy to estimate the causal impact of illicit drug markets on violence using a panel of Colombian municipalities covering the period 1994-2008. Using a UNODC survey of Colombian rural households involved in coca cultivation, we estimate the determinants of land suitability for coca cultivation. With these results we create a suitability index that depends on the altitude, erosion, soil aptitude, and precipita-tion of a municipality. Our exogenous suitability index predicts the presence of coca crops cross sectionally and its expansion between 1994-2000. We show that following an increase in the demand for Colombian cocaine, coca cultivation increases disproportionately in munici-palities with a high suitability index. This provides an exogenous source of variation in the extent of coca cultivation within municipalities that we use as an instrument to uncover the causal effect of illegal cocaine markets on violence. We find that a 10% increase in the value of coca cultivation in a municipality increases homicides by about 1.25%, forced displace-ment by about 3%, attacks by insurgent groups by about 2%, and incidents involving the explosion of land mines by about 1%. Our evidence is consistent with the view suggesting that prohibition creates rents for suppliers in illegal markets, and these rents cause violence as different armed groups fight each other, the government and the civil population for their control and extraction.

Keywords: Violence, Illegal Markets, Cocaine, Colombia. JEL Classification Numbers: D74, K42.

∗_{Mej´ıa: Universidad de los Andes, e-mail: [email protected]. Restrepo: Corresponding author,}

Mas-sachusetts Institute of Technology, e-mail: [email protected]. The authors wish to thank Daron Acemoglu, Josh Angrist, Adriana Camacho and Camilo Garc´ıa for their helpful comments. Ana Mar´ıa Ibáñez, Margarita Gáfaro and Fabio Sánchez kindly provided most of the data used in this study. Mar´ıa José Uribe, Nicolás Idrobo and Catalina Ulloa provided excellent research assistance. All errors are ours.

Bushes and Bullets:

Illegal Cocaine Markets and Violence in

Colombia.

Daniel Mej´ıa and Pascual Restrepo

∗

October 23, 2013

Abstract

Bushes and Bullets:

Illegal Cocaine Markets and Violence in

Colombia.

Daniel Mej´ıa and Pascual Restrepo

∗

October 23, 2013

Abstract

Bushes and Bullets:

Illegal Cocaine Markets and Violence in

Colombia.

Daniel Mej´ıa and Pascual Restrepo

∗

October 23, 2013

Abstract

Bushes and Bullets:

Illegal Cocaine Markets and Violence in

Colombia.

Daniel Mej´ıa and Pascual Restrepo

∗

October 23, 2013

Abstract

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Arbustos y balas:

Mercados ilegales de coca´ına y violencia en Colombia

Daniel Mej´ıa y Pascual Restrepo

∗

October 23, 2013

Abstract

Este art´ıculo propone una nueva estratégia de investigación para estimar el efecto causal de los mercados ilegales de drogas en la violencia. Para esto, utlizamos un panel de datos a nivel municipal en Colombia que cubre el per´ıodo 1994-2008. Para estimar los determinantes de la aptitud del suelo para el cultivo de hoja de coca, utilizamos los resultados de una encuesta a cultivadores de UNODC. Con estos resultados, con-stru´ımos un ´ındice de aptitud del suelo para el cultivo de hoja de coca que depende de la altitud, la erosión, la calidad del suelo y la precipitación promedio. Nuestro ´ındice exógeno de aptitud del suelo predice la presencia de cultivos de coca en el corte transversal, as´ı como su expansión durante el per´ıodo 1994-2008. Adicionalmente, tras el fuerte incremento de la demanda externa por coca´ına colombiana, mostramos que los cultivos de coca se incrementaron desproporcionalmente en municipios con un valor alto del indice de aptitud del suelo. La interacción entre choques de demanda exter-nos por coca´ına colombiana y el ´ındice de aptitud del suelo es un instrumento que explotamos para desentrañar el impacto causal del tamaño de los mercados ilegales de droga sobre los niveles de violencia en Colombia. Usando diferentes medidas de cultivos il´ıcitos, encontramos que un incremento del 10% en el valor de los mercados de coca en un municipio, causan un aumento de la tasa de homicidios de 1.25%, del desplazamiento forzado de 3%, de ataques de grupos ilegales de 2% y de incidenetes con minas antipersona del 1%. Nuestra evidencia es consistente con el hecho de que ∗_{Mej´ıa: Universidad de los Andes, e-mail: [email protected]. Restrepo: Autor encargado de}

cor-respondencia, Massachusetts Institute of Technology, e-mail: [email protected]. Los autores agradecen a Daron Acemoglu, Josh Angrist, Adriana Camacho y Camilo Garc´ıa por sus valiosos comentarios. Agrade-cemos también a Ana Mar´ıa Ibáñez, Margarita Gáfaro y Fabio Sánchez por facilitarnos gran parte de los datos utilizados en este trabajo. Mar´ıa José Uribe, Nicolás Idrobo y Catalina Ulloa hicieron un excelente trabajo como asistentes de investigación. Todos los errores son responsabilidad exclusiva de los autores.

la prohibici´on crea rentas econ´omicas para grupos criminales en mercados ilegales, y con el hecho de que estas rentas causan incrementos en los niveles de violencia, espe-cialmente cuando estos grupos se disputan entre ellos y con el gobierno el control de territorial de lugares aptos para producir drogas.

Palabras clave: Violencia, Mercados ilegales, Cocaina, Colombia. C´odigos JEL: D74, K42.

Arbustos y balas:

Mercados ilegales de coca´ına y violencia en Colombia

Daniel Mej´ıa y Pascual Restrepo

∗

October 23, 2013

Abstract

Arbustos y balas:

Mercados ilegales de coca´ına y violencia en Colombia

Daniel Mej´ıa y Pascual Restrepo

∗

October 23, 2013

Abstract

Arbustos y balas:

Mercados ilegales de coca´ına y violencia en Colombia

Daniel Mej´ıa y Pascual Restrepo

∗

October 23, 2013

Abstract

Arbustos y balas:

Mercados ilegales de coca´ına y violencia en Colombia

Daniel Mej´ıa y Pascual Restrepo

∗

October 23, 2013

Abstract

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1 Introduction

In a classic paper characterizing the nexus between illicit drugs and violence, Goldstein (1985) categorizes drug related violence into three types: First, through thepsychopharmacological channel, the consumption of drugs may lead to excitation, irrational behavior and violent behavior. Second, through theeconomic compulsive channel heavy drug users might commit property crime to support their costly habit. Finally, there issystemic violence, which occurs entirely in the supply side of the illicit drug markets. Systemic violence refers to the use of violence as a business tool, either to enforce contracts, protect property rights- which tend to be poorly defined in an illegal environment, gain market power by eliminating the competition, build a reputation or gain control of strategic resources needed to run the business. The practices of Al Capone and other famous Chicago mobsters during the alcohol prohibition era in the U.S. are the prototypical examples of systemic violence in an illegal market. But such examples are not only confined to the U.S. or the distant past: The Taliban in Afghanistan exercise systemic violence in order to control poppy fields, opium, and the heroin trade; systemic violence has considerably increased in Mexico since the upsurge of large drug trafficking organizations in the last 10 years; and Colombia has been submerged in high levels of systemic violence at least since the mid 1980s, when it became one of the world’s most violent countries following the explosion of drug cartels and, after their demise, the entry of Marxist guerrillas and right-wing paramilitary groups in the drug trade.

In this paper we provide evidence of, and quantify the extent of systemic violence caused by illegal cocaine production in Colombia since 1994. By doing so we can assess the ex-tent to which illegal drug markets are responsible for the high levels of violence observed in Colombia during the last two decades. Colombia is a natural place to investigate the relationship between illegal drug markets and systemic violence. First, Colombia has gone through long and pronounced cycles of violence and illicit drug production, with a significant degree of heterogeneity between municipalities growing coca and non-grower municipalities (see Figure1). Second, during our period of analysis (from 1994 to 2008), drug consumption was very small and concentrated in big cities. Furthermore, most of the cocaine produced in Colombia is exported, which implies that most (if not all) drug-related violence in Colombia is not caused by the consumption of psychoactive drugs but rather by the wholesale pro-duction and distribution of these substances, helping us isolate the role of systemic violence. Third, Colombia’s long lasting conflict has led to big efforts to collect reliable data on coca cultivation, cocaine production and violence.

Until 1994, Colombian cartels used to import most coca paste from Peru and Bolivia, which was subsequently processed into cocaine in facilities located in Colombia, and then

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0

200

400

600

800

Metric tons

1990 1995 2000 2005 2010

Year

Colombia Peru Bolivia

Cocaine production

30

40

50

60

70

Rate

1990 1995 2000 2005 2010

Year

Growers Others

Homicide rate

Figure 1: Cocaine production and homicide rate in Colombia.

shipped to North American and European markets. However, following intense interdiction campaigns introduced by the Fujimori administration in Peru in the beginning of the 1990s, cocaine producers adapted by moving coca cultivation activities to Colombia in order to avoid interdiction by Peruvian authorities. This process led to a vertical integration of all steps associated with cocaine production and trafficking in Colombia during the second half of the 1990s, located near coca growing areas. According to the United Nations Office for Drugs and Crime (UNODC), by the year 2000 Colombia had become the world’s largest cocaine producer and exporter in the world, supplying nearly 700 of the approximately 1,000 metric tons produced worldwide as shown in the left panel of Figure 1. Coca, the raw material necessary for cocaine production, is cultivated and processed in the rural areas of Bolivia, Peru and Colombia. In Colombia, some households located in the countryside and far from the main cities cultivate and harvest coca bushes. While about one third of the farmers involved in coca cultivation directly sell coca leaf to illegal armed groups, the remaining two thirds process it into coca paste or coca base through a simple process that includes the use of chemical precursors such as gasoline, cement and sulfuric acid. After carrying out this initial transformation they sell it to illegal armed groups that transform coca paste and base into cocaine chlorhydrate. The laboratories (cristalizaderos) used for processing coca leaf into cocaine are usually located close to the coca crops, since it is difficult to transport the large amounts of coca leaf required to extract the alkaloid and produce cocaine. Cocaine produced in Colombia is then sold to international drug trafficking organizations, who can also obtain the product from other source countries such as Peru and Bolivia. Most of the cocaine produced in Colombia is then trafficked and consumed in the U.S. or Europe1

. There are two main armed groups that are involved in the cultivation and production of

1

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cocaine in Colombia: Paramilitary groups and the FARC. These groups “protect” farmers in the territories they control from government eradication efforts by setting up land mines to isolate crops, by forcefully avoiding the entry of the armed forces, or by shooting at the airplanes used in aerial spraying of illicit crops. The FARC and paramilitaries also fight each other and the state over the control of productive areas for coca cultivation, and threaten or attack local populations to gain absolute control of the local cocaine trade. By doing so, these groups earn the rents associated to the control of land suitable for coca cultivation and cocaine production, a scarce and inelastic factor. Therefore, municipalities - or, more generally, areas - which are highly suitable for cocaine production tend to be contested by armed groups who resort to violence as a tool for territorial control, the enforcement of con-tracts, the protection of effective property rights, and rent extraction. The link between coca cultivation and violence is widely recognized in Colombian policy circles. The involvement in the drug trade of the FARC and the paramilitaries is well documented (see Rangel (2000), Rabasa and Chalk (2001), and Villalon (2004)), and these groups cause most of the violence in rural areas of the country.

The main argument behind our story is that prohibition creates large rents for those willing to take the risk of supplying the market (Paramilitaries, the FARC or other armed groups), and these rents cause systemic violence as different armed groups fight each other, the government, and civilians for their control and extraction. Violence becomes a profitable strategy in illegal markets precisely because property rights are poorly defined in such envi-ronment and because there are no alternative ways to enforce contracts. This is why armed groups end up using violent means to enforce contracts and secure de facto property rights over coca cultivation regions and cocaine trafficking routes. Furthermore, as some studies have demonstrated, the exercise of prohibition itself often leads to more violence, as illegal groups engaged in the drug business resist enforcement or fight back to regain control of key locations to run their business (see Dell (2013) and Calderon, Diaz-Cayeros and Magaloni (2012)). In our view, illegal drug markets played a key role in Colombia’s violent past and present. Drug trafficking brought the violence of Cartels, and with it a tripling of the homi-cide rate from the late 70s to 1990, when it reached 70 homihomi-cides per 100.000 inhabitants (Gaviria (2000)). From 1994 onwards, as cultivation shifted from Peru and Bolivia to Colom-bia, it brought violence to the countryside and the surge of new paramilitary armed groups involved in cultivation and production, or the involvement of existing insurgent guerrilla groups in the business. As a result, violence persisted and even increased in municipalities involved in cultivation (grower municipalities), as shown in the right panel of Figure1.2

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Another interpretation is that the presence of production and cultivation are not bringing violence, but both are symptoms of the underlying lack of state presence and dysfunctional organization of the Colombian

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In this paper we identify the causal effect of drug production on violence– or the pres-ence of systemic violpres-ence– using an instrument able to predict within municipality variation in cultivation in Colombia. First, we construct a coca suitability index by using a nation-ally representative household survey conducted by UNODC between 2005-2010, where coca growers were asked about their planting techniques and different measures of the yields they obtain. We combine this survey with geographic and weather information in order to esti-mate the determinants of the suitability of each municipality for coca cultivation. The results from this initial exercise reveal a strong and robust non-linear relationship between different measures of coca yields and geographic and weather information available at the munici-pality level, including altitude of the municimunici-pality (meters above sea level), a soil erosion index, a soil aptitude index, and a precipitation index (rainfall). Using the results of these estimations we construct a suitability index for coca cultivation as the predicted productivity in coca cultivation activities for 1,052 municipalities in Colombia. Our suitability index is a good predictor of the cross sectional location of crops and their expansion between 1994 and 2000. By interacting our suitability index with different proxies of external demand shocks for Colombian cocaine, we construct a time varying instrument that allows us to estimate the causal effect of coca related activities on several outcomes in a panel of Colombian mu-nicipalities from 1994 to 2008. The precise mechanism driving our instrumental variables estimations is as follows: External demand shocks for Colombian cocaine increase production in municipalities with a high suitability for coca cultivation relative to the national mean, and following the demand shock we also observe an increase in violence in high suitability municipalities relative to the national mean. Our 2SLS estimates interpret the (relative) increase in violence as being caused by the (relative) increase in the production of cocaine.

Our preferred estimates suggest that if coca cultivation and production had not shifted to Colombia after 1994, or this was a legal and non-violent business, the homicide rate in Colombia would be 25% lower, which translates into 5.700 homicides less per year (during our period of analysis there were on average 22.817 homicides per year). The counterfactual homicide rate in a Colombia without the systemic violence brought by the upsurge in culti-vation would be 27, rather than the current 36 per 100.000 inhabitants. Though high, this counterfactual homicide rate is close to the typical Latin American country level. Forced displacement would be down by 60%, attacks by armed groups by 36% and incidents with landmines’ explossions by 20%. These are large effects that imply that the drug trade does impose a heavy burden in terms of violence in producer countries, and that it brought

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temic violence responsible for a large share of the country violence. This evidence suggests that the war on drugs imposes significant collateral costs upon source and transit countries in terms of violence. These costs should be added to other monetary costs of the current prohibitionist strategy when assesing its cost effectiveness. In our view, the main cost of prohibition to producer and transit countries is not the direct cost of designing and imple-menting anti-drug strategies, but the high levels of systemic violence caused by illegal drug markets and the so-called “war on drugs”, as the ones documented for Colombia in this paper.

The existing empirical evidence concerning the relationship between illegal drug markets and violence is mixed. Cross-country evidence suggests that homicide rates are positively related to the intensity of drug enforcement (see Miron (2001)). Within-country analyses provide different results. Evidence from Afghanistan indicates that violence by armed groups increases opium cultivation by destroying the infrastructure required for legal production (see Lind, Moene and Willumsen (2008)). D´ıaz and Sanchez (2004) obtain a similar result for the Colombian case: The territorial expansion of armed groups in Colombia has led to increasing levels of coca cultivation. Using a panel of Colombian municipalities, a related paper finds that drug enforcement, measured by drug-related captures, is not related to violence (see Medina and Mart´ınez (2003)). However, none of these findings exploit an exogenous source of variation in conflict or enforcement, or addresses measurement error issues, so their results cannot be interpreted as causal.

The relationship between illegal markets and violence is not necessarily intrinsic to the nature of illegal drugs. In fact, a paper by Chimeli and Soares (2010) shows that violence increased after the Brazilian government prohibited the extraction and trade of mahogany, a tropical wood grown in the Brazilian Amazon. More precisely, the authors show how prohibition led to a disproportionate increase in violence in those Brazilian states and mu-nicipalities that had a higher share of mahogany extraction prior to the regulatory change; in states that reported higher extraction of “other tropical timber species” following prohi-bition3

; and in municipalities where mahogany extraction was a natural phenomenon. The paper exploits variation in the legal status of a market, and shows that the illegal status is a key determinant of systemic-type violence, while the type of goods being produced and traded is irrelevant. While Chimeli and Soares (2010) exploit the extensive margin of the relationship between illegal markets and violence, the focus of our paper is on the intensive margin: How an increase in the value of an illegal market affects different violent outcomes. In a study that is similar to ours, Angrist and Kugler (2008) explore the coca-conflict

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Chimeli and Soares (2010) provide convincing evidence that mahogany extraction continued after pro-hibition, only that it was reported as the extraction of “other tropical timber species”.

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nexus in Colombian and find that coca cultivation causes conflict without significantly im-proving economic opportunities. Angrist and Kugler (2008) exploits the exogenous upsurge in coca cultivation following the closure of the air bridge connecting cultivation areas in Bo-livia and Peru with cocaine processing facilities in Colombia in 1994. The aerial interdiction campaigns by Peru and the U.S. led to an increase in the demand for coca cultivation in Colombia. Between 1994 and 2000, traditional coca growing states (e.g., those departments that had coca cultivation in 1994) saw an increase in coca cultivations and subsequently became considerably more violent. We build heavily on their work and choose a different identification strategy which is still similar in spirit. We also use municipal data and analyze other potential outcomes. Unlike them, our focus is strictly on violence and not in labor market outcomes. Another related paper is Dube and Vargas (2013), who use a similar identification strategy to disentangle the role of different commodity price shocks on civil conflict. Our paper adds to this literature by showing that demand shocks for illegal goods whose property rights are ill defined tend to increase violence. This is in contrast to other goods, such as coffee, whose price shocks tend to reduce violence in growing areas.

The rest of the paper is organized as follows: Section 2 describes our identification strategy, the estimation framework and the data used. Section 3 presents the results of our estimations and the last section concludes.

2 Estimation framework and data

2.1 Description of our data

Our main data set consist of a panel of 1,052 Colombian municipalities for the period 1994-2008. For each municipality we have a coca suitability index, which measures its comparative advantage for coca cultivation based on geographic characteristics (altitude, soil erosion, precipitation and a measure of soil aptitude). The construction of the index is explained in detail in the next subsection. We have several measures of coca cultivation activities. First, we have coca cultivation figures from SIMCI4

, which are obtained from satellite images. Coca cultivation figures in Colombia are available at the municipality level from 1999 through 20085

. We supplement this data with an estimation of coca crops for the year 1994 at the municipality level from the Colombian National Police. We obtain the total number of

4

Sistema Integrado de Monitoreo de Cultivos Ilicitos, a UN Office based in Bogota in charge of monitoring illicit crops and drug production activities in Colombia.

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eradicated hectares per year in each municipality from 1994 to 2008 as another proxy for coca cultivation activities. The police reports separately the hectares eradicated manually and those that are sprayed with herbicides using small aircraft, the two primary methods used to confront coca cultivation in Colombia. Finally, we have the number of anti-narcotic operations from 1993 to 2008 in each municipality. The top panel in Table1shows summary statistics for these variables separately for municipalities with suitability indexes in different quartiles. As expected and motivated, municipalities with a high suitability index tend to have more coca crops and the police reports more eradication and anti-narcotic operations. Most of our data on violence comes from the Colombian Vice President’s Office (VPO), and is available for the entire period (1994-2008). In particular we have data from the VPO for homicides, attacks by illegal armed groups, incidents involving land mine explosions, massacres, kidnappings, and acts of terrorism at the municipal level. We calculate the rate for each of these violent events (e.g., number of incidents per 100,000 inhabitants per year). We supplement this information with data on forced displacement from CODES, as well as with information about the presence of illegal armed groups (AUC -paramilitaries- and the FARC) in each municipality. Table1 presents summary statistics for these variables. Two features are worth noting: First, Colombia is a very violent country with very high levels of violence. For instance, the average homicide rate in municipalities in the top quartile of the suitability index distribution is 76 per 100,000 inhabitants. Colombia is even a very violent country when compared with other Latin American countries with similar levels of development. For instance, the average homicide rate in other Latin American countries is 25 per 100,000 inhabitants, only comparable to the homicide rate of Colombian municipalities in the lowest quartile of the suitability index. The second important fact is that municipalities with a high suitability index are more violent than the average, suggesting that coca cultivation and cocaine markets may be responsible for these differences.

We obtain municipality level covariates from the CEDE (Centro de Estudios Economicos) municipal panel. Our covariates include exogenous geographic controls that do not vary over time. In particular we have data on altitude, erosion, soil aptitude - which is related to the presence of minerals and nutrients-, soil erosion, precipitation index, and other geographic characteristics, incluiding dummies for the production of several commodities.

2.2 The coca suitability index

In order to get a source of exogenous variation in coca cultivation we start by constructing a suitability index based on different exogenous geographic characteristics at the municipality level. We use several rounds of a survey conducted yearly by SIMCI among farmers growing

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Estimated productivity from UNODC.

Suitability based on observed characteristics.

Figure 2: Cocaine productivity in Colombia and our suitability measure.

coca in different municipalities in Colombia between 2005 and 2010. Growers were selected randomly using satellite images to pinpoint their location, so they constitute a representative sample for each of the Colombian regions and at the national level. The survey includes self reported data (backed up by geo-coded satellite images) on the productivity of coca crops at different stages, and information about the farmers’ location, including the municipality of residence. This allows us to match the data on productivity to geographical characteristics at the municipal level including altitude, soil erosion and aptitude, and a precipitation (rainfall) index. The total number of observations in our sample is 13,493. Each observation refers to a coca field and includes its location and productivity, and an identifier for the farmer who owns it or takes care of it. The fields in the sample are located in 64 (out of 1,052) municipalities scattered across the country, as shown in the left panel of Figure2, and belong to 1,678 different farmers. Gray municipalities are those in which no survey was conducted. The red color scale indicates different yields of coca crops on average in each municipality.

In order to understand the determinants of the productivity of coca cultivation, we esti-mate the following model:

(1) productivityhm=

β0+β1altitude_m+β2altitude 2

m+β3aptitude_m+β4aptitude 2

m

β5water_m+β6water 2

m+β7erosion_m+β8erosion 2

m+εhm

.

Table2shows estimates of equation1for different ways of measuring productivity of coca cultivation -productivityhm: “yield per harvest per hectare” in columns 1 and 3, and “yield at maturity age” in Columns 2 and 4, and for different specifications. In all estimations we cluster errors at the farmer level, since productivity shocks are likely to be correlated.

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The results are very similar if we cluster at the municipality level. Our results suggest that there is a robust quadratic relation between productivity and the geographic characteristics of municipalities included in the model. Productivity is low in municipalities at a low or high altitude, and reaches a maximum in municipalities located 1,000 meters above sea level. An intermediate level of humidity and erosion is also required to maximize productivity, while municipalities with the highest soil aptitude index (7 or 8) have the lowest productivity (this index is related to the amount of minerals and nutrients in the soil).

Using the results shown in Column 1, we create a measure of expected productivity of coca bushes for all Colombian municipalities6

. We call this the suitability index, since it measures how productive a municipality is for coca cultivation based only on its geographic characteristics. The suitability index varies across municipalities but not over time, and is computed as:

(2) sm =

β0+β1altitudem+β2altitude 2

m+β3aptitudem+β4aptitude 2

m

β5water_m+β6water 2

m+β7erosion_m+β8erosion 2

m.

.

We normalize the suitability index in terms of standard deviations from the mean to facilitate its interpretation. The right panel in Figure 2 shows a plot of the suitability index. Gray municipalities are those for which there is no data of the soil characteristics required to construct the index. The red color scale indicates different suitabilities, with lighter colored municipalities being the less suitable.

As a first check of the suitability index, we estimate the following simple cross sectional model for different proxies of coca cultivation at the municipal level, ymt:

(3) logymt =β0+β1s_m+γX_m+u_mt.

Here,Xm are additional municipality characteristics. We use different proxies for the extent of coca cultivation. First, we use coca cultivation from SIMCI. We also use the total number of eradicated hectares reported by the National Police, as well as aerial and manual eradi-cation separately. Finally, we use anti-narcotics operation as a measure of the extent of the drug trade in the area.

Table 3 shows our results. In Column 1 we estimate model 3 by pooling all years with data and clustering the errors at the municipality level. In Column 2 we estimate the same model using only cross sectional data for 1994. In Column 3 we use only data for 1998 and in Column 4 we use only data for 2008. Our results suggest that our suitability index does a good job in predicting the location of coca crops cross sectionally. This holds even after

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Table 2: Determinants of soil suitability for cocaine production.

Linear Logarithmic (1) (2) (3) (4)

Altitude 60.332∗∗∗ _51.552∗∗∗ _0.190∗∗∗ _0.156∗∗∗

(5.552) (6.724) (0.014) (0.017) Squared altitude -3.535∗∗∗ _-2.803∗∗∗ _-0.011∗∗∗ _-0.008∗∗∗

(0.350) (0.433) (0.001) (0.001) Aptitude index -124.241∗∗∗ _-43.730∗∗∗ _-0.370∗∗∗ _-0.188∗∗∗

(14.402) (16.594) (0.035) (0.043) Squared aptitude index 14.925∗∗∗ _3.379 _0.043∗∗∗ _0.017∗∗∗

(2.202) (2.429) (0.005) (0.006) Water index 627.599∗∗∗ _720.290∗∗∗ _0.792∗∗∗ _0.834∗∗∗

(110.153) (109.408) (0.286) (0.281) Squared water index -73.899∗∗∗ _-85.977∗∗∗ _-0.085∗∗ _-0.088∗∗

(15.035) (15.017) (0.040) (0.039) Erosion index 164.137∗∗∗ _37.486 _0.506∗∗∗ _0.213∗∗∗

(24.540) (28.454) (0.063) (0.076) Squared erosion index -34.473∗∗∗ _-8.404 _-0.099∗∗∗ _-0.033∗

(7.224) (7.820) (0.018) (0.020)

R-squared 0.156 0.214 0.194 0.221 Observations 13493 13493 13493 13493

Notes:The table reports OLS estimates of the determinants of coca productivity in a municipality. Columns 1

and 2 use a linear specification while columns 3 and 4 use a logarithmic specification. The data used comes from UNODC field survey. The dependent variable in columns 1 and 3 is cocaine produced per hectare cultivated in each harvest; while the dependent variable in columns 2 and 4 is cocaine produced per hectare at mature age. Soil characteristics are measured at the municipality level. Robust standard errors clustered at the household level are shown in parentheses. For the reported coefficients, those with∗∗∗_{are significant at the 1% level;}

those with∗∗_{are significant at the 5% level; and those with}∗_{are significant at the 10% level.}

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Table 3: The suitability measure and the expansion of activities related to coca cultivation

All years Only Only Only Change with data 1994 2000 2008 1994-2000

A. Logarithm of coca cultivation

Suitability index 0.313∗∗∗ _0.120∗∗∗ _0.389∗∗∗ _0.338∗∗∗ _0.268∗∗∗

(0.035) (0.031) (0.043) (0.037) (0.031) Observations 11572 1052 1052 1052 1052

B. Logarithm of total eradication

Suitability index 0.193∗∗∗ _0.021∗∗ _0.215∗∗∗ _0.290∗∗∗ _0.194∗∗∗

(0.023) (0.009) (0.032) (0.041) (0.031) Observations 15780 1052 1052 1052 1052

C. Logarithm of aerial eradication

Suitability index 0.155∗∗∗ _0.021∗∗ _0.186∗∗∗ _0.248∗∗∗ _0.165∗∗∗

(0.021) (0.009) (0.030) (0.035) (0.029) Observations 15780 1052 1052 1052 1052

D. Logarithm of manual eradication

Suitability index 0.082∗∗∗ _0.000 _0.059∗∗∗ _0.153∗∗∗ _0.059∗∗∗

(0.010) (.) (0.014) (0.034) (0.014) Observations 15780 1052 1052 1052 1052

E. Logarithm of Anti narcotic operations

Suitability index 0.082∗∗∗ _0.035 _0.044∗∗∗ _0.199∗∗∗ _0.011

(0.008) (0.024) (0.010) (0.022) (0.025) Observations 16612 1012 1042 1042 1012

Notes: The table reports OLS estimates of the cross sectional relationship between several proxies measuring

the extent of cultivation and production and our suitability index. The first column pools all years, the second one uses only 1994, the third one 2000, the fourth one 2008 and the last one shows if our measure predicts the expansion of cultivation between 1994 and 2000. Robust standard errors clustered at the municipality level are shown in parentheses. For the reported coefficients, those with∗∗∗_{are significant at the 1% level; those with}∗∗

are significant at the 5% level; and those with∗_{are significant at the 10% level.}

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15

we add municipality controls, including tax revenues, population and the rurality index in 1994, dummies for agricultural products, distance to markets, presence of tropical diseases, and dummies for tactical and strategic corridors for military operations. The results are not reported to save space.7

The last column of Table3explores if the suitability index predicts the geographic expan-sion of coca cultivation that took place in Colombia between 1994 and 2000 as a consequence of increasing interdiction campaigns in Peru and Bolivia. Our results show that the expansion of coca cultivation occurred mostly in municipalities with a high suitability index. These municipalities also experienced a larger increase in aerial and manual eradication, and in anti-narcotic operations. Thus, the index not only predicts the cross sectional location of coca crops, but also their expansion during the second half of the 1990s. For instance, coca cultivation grew 25% more between 1994 and 2000 in municipalities with a suitability index one standard deviation above the national average.

2.3 Demand shocks

We capture external demand shocks for Colombian cocaine using several proxies. First, we use a dummy for the post-1994 period, when the demand for cocaine shifted from Peru to Colombia. This shift was induced by an aggressive policy of shooting down non-identified planes (including a famous case of a plane carrying a group of missionary nuns) flying between both countries and that allegedly carried coca paste and base to be processed in Colombian laboratories located in the southwest region of the country. After 1995, importing cocaine from Peru became increasingly hard and costly and, as a result, coca cultivation in Colombia increased considerably as shown in Figure 1. This shock was used by Angrist and Kugler (2008) to set up a difference in difference estimation of the effect of coca cultivation on violence and labor market outcomes in Colombia.

Second, we use the seizure rate of cocaine in other source countries (Peru and Bolivia) as measures of exogenous demand shocks for Colombian cocaine. The intuition behind the use of cocaine seizures in other countries as a source of exogenous demand shocks for Colombian cocaine is that an increase in cocaine seizures in Peru and Bolivia should shift demand for cocaine away from these countries and towards Colombia, where the product becomes easier to smuggle - or cheaper in relative terms.

Third, we use the seizure rate of cocaine in downstream markets, including transit

coun-7

The predictive power of the index is not robust for 1994 once controls are included, but we do not think this is problematic since in this year coca cultivation was not a widespread phenomenon in Colombia as explained above. In 1994 there was no manual eradication, so this coefficient is estimated to be zero.

13

we add municipality controls, including tax revenues, population and the rurality index in 1994, dummies for agricultural products, distance to markets, presence of tropical diseases, and dummies for tactical and strategic corridors for military operations. The results are not reported to save space.7

2.3 Demand shocks

coun-7

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0

.02

.04

.06

.08

seizrate_peru

1990 1995 2000 2005 2010 Year

Seizure rate in Peru.

0

.05

.1

.15

.2

seizrate_bol

1990 1995 2000 2005 2010 Year

Seizure rate in Bolivia.

.02

.04

.06

.08

.1

.12

seizrate_other

1990 1995 2000 2005 2010 Year

Seizure rate in Sources.

.05

.1

.15

.2

.25

seizrate_transit

1990 1995 2000 2005 2010 Year

Seizure rate in transit.

.05

.1

.15

.2

enfUS1

1990 1995 2000 2005 2010 Year

Seizure rate in U.S.

Figure 3: Measures of demand shocks caused by external enforcement.

tries in Central America, Mexico and the U.S. The reasoning is that when transit or con-sumer countries increase cocaine seizures, traffickers and wholesale distributors located in these countries compensate their losses by demanding more cocaine from source countries. This requires an inelastic demand in wholesale and consumer markets, so that the quantities consumed are almost fixed. In this case, an increase in interdiction rates in transit or con-sumer countries increases prices and motivates traffickers to send more drugs to compensate for the extra fraction seized. As a result, it is expected that traffickers increase their demand for cocaine from source countries. Figure 3 shows the time series plots for cocaine seizures rates in other countries that we use as proxies for exogenous demand shocks for Colombian cocaine.

To check the predictive power of our external demand measures, we estimate the following model by OLS:

(4) lnCultmt =π0+π1s_m·d_t+θX_mt+κ_m+δ_t+e_mt.

Here, lnCultmt is the amount of coca cultivation in municipality mduring yeart, measured using the satellite images or eradication figures. The coefficient of the interaction term,

sm ·dt, measures the extent to which positive demand shocks for Colombian cocaine are reflected in higher levels of coca cultivation in municipalities with a high suitability index. Therefore, we expect positive demand shocks to appear with a positive estimate for π1. All

our estimations of equation 4 include time and year fixed effects and cluster the errors at the municipality level in order to take into account the autocorrelation of coca cultivation over time.

We present our estimates of the interaction term in equation 4 in Table 4. In panels A and C we use the demand shocks induced by changes in external enforcement. Our results we add municipality controls, including tax revenues, population and the rurality index in 1994, dummies for agricultural products, distance to markets, presence of tropical diseases, and dummies for tactical and strategic corridors for military operations. The results are not reported to save space.7

2.3 Demand shocks

coun-7

13

0

.02

.04

.06

.08

seizrate_peru

1990 1995 2000 2005 2010 Year

0

.05

.1

.15

.2

seizrate_bol

1990 1995 2000 2005 2010 Year

.02

.04

.06

.08

.1

.12

seizrate_other

1990 1995 2000 2005 2010 Year

.05

.1

.15

.2

.25

seizrate_transit

1990 1995 2000 2005 2010 Year

.05

.1

.15

.2

enfUS1

1990 1995 2000 2005 2010 Year

(4) lnCultmt =π0+π1sm·dt+θXmt+κm+δt+emt.

We present our estimates of the interaction term in equation 4 in Table 4. In panels A and C we use the demand shocks induced by changes in external enforcement. Our results

0

.02

.04

.06

.08

seizrate_peru

1990 1995 2000 2005 2010 Year

0

.05

.1

.15

.2

seizrate_bol

1990 1995 2000 2005 2010 Year

.02

.04

.06

.08

.1

.12

seizrate_other

1990 1995 2000 2005 2010 Year

.05

.1

.15

.2

.25

seizrate_transit

1990 1995 2000 2005 2010 Year

.05

.1

.15

.2

enfUS1

1990 1995 2000 2005 2010 Year

(4) lnCultmt =π0+π1s_m·d_t+θX_mt+κ_m+δ_t+e_mt.