The Illicit Drug Business and Terrorism:

Panel Causality and Time-Series Evidence

Friedrich Schneider* and Daniel Meierrieks†

Abstract

In this contribution we examine the causal linkages between the illicit drug business and

terrorist activity for the Cold War and post-Cold War era. We study the drug-terror nexus for

different types of drugs (cocaine, heroin and methamphetamine) and for terrorist activity

originating from various parts of the world. Using panel causality tests and further tools of time-

series analysis, we find that the relationship between drug prices and terrorist activity is

complex. The causal dynamics of the drug-terror nexus seem to be influenced by the drug

considered (with more profitable drugs being more important) as well as by location, with the

latter determining the access of terrorist groups to the global drug supply chain, but also

correlating with economic, institutional and geographical conditions that may influence the

attractiveness of the drug business to terrorist organizations. Our results suggest that the drug-

terror nexus is particularly relevant to Latin America, the Middle East and Northern Africa and

Central and South East Asia, but that the interaction between the illicit drug business and

terrorism does not matter to Sub-Saharan African and Western countries. In sum, anti-drug and

anti-terror measures may therefore beneficially reinforce each other for some parts of the world,

but such measures cannot be expected to crowd out terrorism and/or the illicit drug business on

their own.

JEL Classification: C22; C23; D74; F50

Keywords: illicit drugs; terrorism; causality; crime-terror nexus

Total Word Count: 10,851

* Corresponding Author. University of Linz, Altenbergerstrasse 69, 4040 Linz, Austria. Phone:

+43-(0)732-2468-8210. Fax: +43-(0)732-2468-8209. E-mail: friedrich.schneider@jku.at.

† University of Freiburg, Wilhelmsstraße 1b, 79098 Freiburg, Germany. Phone: +49-(0)761-

203-67653. Fax: +49-(0)761-203-67649. E-mail: daniel.meierrieks@vwl.uni-freiburg.de.

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1. Introduction

In popular discourse it is often claimed that terrorist organizations engage in illicit drug trafficking

to finance their activities. In other words, it is suggested that the drug business fuels terrorism. For

instance, U.S. President George W. Bush in December 2001, shortly after the 9/11 terrorist attacks,

argued as follows (Bush, 2001):

“It’s so important for Americans to know that the traffic in drugs finances the work of

terror, sustaining terrorists, that terrorists use drug profits to fund their cells to commit acts

of murder. If you quit drugs, you join the fight against terror in America.”

On the other hand, some analysts suggest that it is the very prevalence of terrorism and conflict

that makes possible—or at least greatly facilitates—the drug business. For instance, the French

journalist and drug expert Alain Labrousse in a 1999 report argued that conflict may have paved

the way for drug trafficking in the past, citing examples from a number of terror-ridden countries

(Labrousse, 1999):

“[Conflicts] in Colombia, Afghanistan and Angola, were under way before the Cold War

ended. […] In other cases, the collapse of Communist regimes caused new conflicts, in the

former Yugoslavia, Azerbaijan-Armenia, Georgia (Abkhazia, Ossetia), Chechnya and

Tajikistan. These conflicts, which resulted in a weakening, and in some instances

dislocation, of states also led to the development of drug trafficking.” [emphasis added]

As we will show in the next section of this contribution, the correlation between the drug business

and terrorism has not gone unnoticed in the academic literature. However, there exists little

systematic empirical evidence regarding the causal linkages between the drug business and

terrorism. As the previous discussion suggests, such linkages may be complex, with terrorism

being possibly fueled by drug money and the drug trade—possibly at the same time—being

dependent upon the instability terrorism creates to thrive. Our contribution therefore aims to fill

this gap in the literature by providing empirical tests analyzing the causal interactions associated

with the drug-terror nexus. Here, our analysis is designed to provide a particularly rich picture of

this nexus by considering the relationship between different types of drugs (cocaine, heroin and

methamphetamine) and terrorist activity in different locations, i.e., parts of the world. In so doing,

our study ought to inform the actions of policymakers who want to reduce terrorist activity—and

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the (organized) criminal activity potentially linked to it—by confronting the drug-terror nexus.

Related policies may help to consequently reduce the potentially sizable socio-economic costs

academic research has attributed to both terrorist and (organized) criminal activity (e.g.,

Skaperdas, 2001; Frey et al., 2007; Schneider, 2012).

The remainder of this contribution is organized as follows. In Section 2 we discuss in more detail

the potentially complex causal linkages between the drug business and terrorist activity. In Section

3 we introduce the data and empirical methodology to examine the drug-terror nexus. Our

empirical findings are reported and discussed in Section 4. Section 5 concludes.

2. The Drug Business and Terrorist Activity

2.1 The Causal Link from the Drug Business to Terrorism

Terrorism is a costly venture. On the one hand, there are costs associated with financing terrorist

operations, i.e., attacks; on the other hand, there are costs linked to keeping a terrorist organization

functioning such as expenses for recruitment, technical equipment and bribes (Freeman, 2011).

Terrorist groups may obtain financial resources through various ways. They may rely on legal

activities (i.e., operating legitimate businesses) or on donations by foreign states (state sponsorship

of terrorism) or by private individuals (i.e., charitable donations by the domestic populace or

foreigners sympathetic to the terrorists’ cause) (Freeman, 2011). Furthermore, terrorist

organizations may engage in criminal activity to gain the financial resources necessary to finance

their activities.1 Involvement in crime by terrorist groups has a number of advantages for terrorist

groups such as operational independence from (domestic or foreign) sponsors and a comparatively

high profitability from crime which often also only requires minimal skills to be carried out

successfully (Freeman, 2011). Besides “extortion […], kidnapping and ransom, theft, smuggling,

1 An important distinction between a terrorist and a criminal organization is that the former has

political objectives (where money is used as a means to achieve political goals), while the latter

has predominantly financial motives (so that money is an end rather than means). However, the

reduction of state sponsorship of terrorism after the end of the Cold War has led to an increasing

reliance of terrorist groups on illegal sources of finance (Hutchinson and O’Malley, 2007). This

has resulted in a discussion whether the lines between terrorism and organized crime have become

increasingly more blurred (e.g., Makarenko, 2004; Hutchinson and O’Malley, 2007).

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petty crime, and pirating and counterfeiting goods” (Freeman, 2011: 466), terrorist groups may

also be involved in the drug business.

The involvement in drug trafficking provides a number of possibilities for terrorist groups to make

a profit. For one, terrorist organizations may gain income from selling drugs themselves. For

another, terrorist organizations may provide “services” to groups and individuals at various places

in the drug supply chain, taxing them for their “services” in return. The “services” terrorist

organizations provide to other players in the drug business primarily include protection (i.e.,

extorting money from drug farmers, storage agents, refiners and drug dealers in return for

protection from, e.g., law enforcement) and the provision of infrastructure and transportation (e.g.,

trucks and roads controlled by a terrorist group) to facilitate the drug trade. The income generated

by such involvement of terrorist groups in the drug trade may consequently be used to finance

terrorist activity. This is what Piazza (2011: 299) calls the “[…] cash argument […] The illicit

drug trade produces sizeable cash revenues that terrorist groups extract […] and then use […] to

expand their operations and launch more frequent attacks.” Indeed, numerous examples suggest

that direct involvement in the drug trade produces income for terrorist groups and subsequently

feeds terrorism. For instance, Silke (2000) argues that involvement in the drug business has

allowed loyalist groups active in the Northern Ireland conflict (such as the Ulster Volunteer Force)

to sustain their terrorist campaign. Roth and Sever (2007) find that the Kurdish Partiya Karkerên

Kurdistan (PKK) collects much of its income from the drug trade taking place in the Golden

Crescent.2 As further evidence of the cash argument, Piazza (2012) finds that in Afghanistan on a

provincial level higher opium production leads to more terrorist activity with more casualties.

Similarly, using data for 170 countries between 1986 and 2006 Piazza (2011) finds that the illicit

production of drug is associated with the generation of higher levels of terrorist activity also on

national levels.

What is more, even if direct involvement in the drug business by terrorist organizations is limited,

the creation of auxiliary illegal markets that aid the drug business may also (indirectly) aid

2 The Golden Crescent is one of Asia's two principal areas of illicit opium poppy production,

stretching across Afghanistan, Iran and Pakistan. The other area of opium production is the Golden

Triangle, primarily located in the countries of Myanmar, Laos and Thailand.

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terrorism. Kleinman (2004) argues that terrorist organizations may rely on markets that provide

illegal “services” such as weapons acquisition, the forging of documents and money laundering to

criminal organizations active in the drug trade. When terrorist groups use these “services” (that

primarily exist to support the drug trade), this may consequently also facilitate terrorism.

Furthermore, terrorist organizations may gain additional income from participating in the auxiliary

markets (such as the weapons market) that arise due to the drug trade. This provides an additional

causal mechanism linking drug trafficking to terrorism.

Kleinman (2004) also suggests that terrorism may benefit from the fact that law enforcement

agencies (the police, intelligence agencies, the military) may divert resources away from the fight

against terrorism to the fight against drug production and trafficking. A lack of public resources

spend on counter-terrorism is consequently expected to make it easier to organize and carry out

terrorist activity. This effect ought to be particularly strong when terrorist organizations are only

marginally linked to the drug market, as in this case the likelihood that counter-drug activities also

serve as counter-terrorism measures is expected to be particularly low (e.g., because reducing the

drug trade is then not anticipated to affect the resource base of a terrorist group).

Finally, it is also possible that terrorist activity does not increase due to the involvement of a

terrorist group in the drug trade, but as a consequence of opposition to it. Indeed, Schneider et al.

(forthcoming) find that vigilantism may be source of terrorism. Here, the perceived lawlessness

and state illegitimacy that tend to be associated with a large drug business dominated by organized

crime may give rise to (vigilante) terrorist groups that purport to make a stand against such

developments. For instance, Monaghan (2002) discusses how Republican terrorist groups active

in the Northern Ireland conflict (such as the Republican Action Against Drugs) deliberately

targeted drug dealers.3 Opposing the drug trade may increase popular support for the terrorists’

cause, given the obvious negative social consequences drug trafficking and abuse carry for affected

communities (Monaghan, 2002). While this latter economic transmission mechanism—from drug

trade to vigilantism to terrorist activity—differs substantially from the previously discussed

mechanisms, it, however, still suggests that causation ought to run from the drug business to

terrorism. What is more, the causal effect is still expected to be positive, i.e., terror-enhancing.

3 Another example is the South African terrorist group People Against Gangsterism and Drugs.

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Summing up this subsection, we expect the drug business to have a causal effect on terrorist

activity by generating income for terrorist group, providing them with access to services and black

markets that facilitate terrorism, diverting resources away from counter-terrorism policy measures

(focusing on counter-drug measures instead) or creating grievances terrorist groups may tap into

to boost popular support by styling themselves as anti-drug vigilantes. Given these lines of

reasoning, we shall test the following hypothesis (H1) in our following empirical analysis:

Hypothesis 1 (H1): Drug business activity has a causal effect on terrorism. An increase in

drug business attractiveness (higher drug prices) translates into stronger terrorist activity.

2.2 The Causal Link from Terrorism to the Drug Business

In addition to the previously discussed causal linkages from the drug business to terrorism,

terrorism may also affect the drug business, which implies a causal effect running from terrorist

activity to drug trafficking.

First, more terrorism implies an increased need for cash to finance operations (Freeman, 2011).

This may mean that more terrorist activity is anticipated to translate into a stronger involvement

in the drug business by a terrorist group to raise money. What is more, more terrorist activity may

also imply more control of a terrorist organization over infrastructure and possibly territory. This

is also expected to facilitate the drug trade, while generating income for the terrorist group.

Terrorism is furthermore expected to produce economic damage. Previous research (e.g., Gupta et

al., 2004; Frey et al., 2007; Sandler and Enders, 2008; Meierrieks and Gries, 2013) suggests that

terrorism may be harmful to economic growth and investment by, e.g., destroying an economy’s

capital stock, causing inefficient investment decisions (due to the risk associated with terrorism)

and adversely affecting industries (such as the tourism sector) that are especially exposed to it.4

4 The negative economic effects of terrorism are usually stronger in developing economies which

exhibit lower levels of macroeconomic robustness to economic shocks from terrorism (Sandler

and Enders, 2008; Meierrieks and Gries, 2013). At the same time, drug production primarily takes

place in developing countries, which suggests that the effect of terrorism on ordinary economic

activity may indeed be relevant to the drug-terror nexus.

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As a consequence, terrorist conflict may constrain ordinary (legal) economic activity for civilians

affected by the conflict and consequently make it more attractive for them to engage in criminal

activity. Here, involvement in the drug business may be especially appealing to those civilians

because it does not require special education (Ross, 2003). In other words, terrorism may also

foster—rather indirectly—the drug business by shifting the preferences of individuals (civilians)

affected by the conflict in ways that make an involvement in the drug trade more attractive. This

is particularly true because the drug business usually also generates income from low-skilled labor

for local communities (rather than for external players) (Ross, 2003).

Terrorism may also undermine institutions and state legitimacy. Indeed, besides producing

economic damage, politico-institutional destabilization is another goal of terrorism, given that

destabilization is likely to aid the terrorists’ cause and increase their popular appeal (e.g., Schneider

et al., forthcoming). For instance, terrorism may result in human rights violations by the

government (Dreher et al., 2010), which is likely to lower the state’s legitimacy and control over

its population. The institutional decline due to terrorism may consequently also fuel the drug trade.

For one, it correlates with low state control over its territory and population. This “lawlessness” is

likely to facilitate any criminal activity, including drug production and trafficking. For another,

low state control may also give rise to corruption on the part of public officials (Kleinman, 2004).

This ought to be another mechanism that fuels (organized) criminal activity and, consequently, the

drug business.

Finally, just as criminal activity may divert public resources away from the fight against terrorism,

the opposite may also be true. For instance, the fight against terrorism has been found to increase

military spending (Gupta et al., 2004), which in turn may depress public spending on other policy

fields, including the police and counter-drug efforts. This is likely to facilitate drug cultivation and

the drug trade. That is, competition over scarce public resources that results in increased counter-

terrorism but reduced counter-drug activity by the state may make the drug business comparatively

more attractive for (organized) crime as well as local communities located in areas suited for drug

production and smuggling (Kleinman, 2004).

Summing up this subsection, we anticipate terrorism to affect the drug business as it constitutes a

potentially important source of income for terrorist groups; more terrorist activity thus ought to

lead to a stronger involvement in the drug business. Furthermore, terrorism may also influence

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drug business dynamics by affecting the cost-benefit considerations of the various drug business

players by, e.g., constraining ordinary economic activity, undermining state institutions and

legitimacy and diverting public resources away from counter-drug policy measures. Given these

lines of reasoning, we shall test the following hypothesis (H2) in our following empirical analysis:

Hypothesis 2 (H2): Terrorist activity has a causal effect on the drug business. An increase

in terrorist activity translates into higher drug business attractiveness (higher drug prices).

2.3 Further Discussion

The previous two subsection have established that—through a number of transmission channels—

there may be a causal effect of the drug trade on terrorism and vice versa. That is, the drug-terror

nexus is potentially complex. What is more, for our subsequent analysis of the drug-terror nexus

the type of drug and location of terrorist activity may also matter.

First, the profitability of the drug business is likely to correlate with the type of drug that is traded.

Arguably, drugs ought to be more profitable when, e.g., the cultivation of raw material used in

their production is restricted to certain areas (e.g., opium poppy and coca production), when the

drug production process itself is expensive and when supply chains are long (calling, e.g., for the

costly smuggling of drugs). This makes more profitable drugs more likely to interact with terrorist

activity. For instance, they are expected to yield more income for terrorist organizations involved

in their trading, which consequently ought to finance stronger terrorist activity.

Second, the nature of the drug-terror nexus may possibly also depend on location. For one, it is

likely that terrorist organizations operating in areas in which the drug trade prevails (e.g., in the

form of drug cultivation or smuggling) share closer links to the drug economy. For another,

terrorist organizations operating in areas where socio-economic conditions are poor and opposing

states are weak (i.e., the developing world) may share especially close ties to the drug economy.

For instance, weak states are less likely to suppress terrorist and criminal organizations and inhibit

their cooperation (e.g., Hutchinson and O’Malley, 2007). Weak states are also more likely to see

corruption and economic underdevelopment, which facilitate both the activity of terrorist groups

and organized crime engaged in the illicit drug trade. This makes it more likely that we can observe

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causal effects of the drug business on terrorism (and vice versa) in those parts of the world

characterized by relative state fragility and lower development levels.

3. Data and Methodology

3.1 Data

To empirically examine the possible causal linkages between terrorism and the drug business and

test hypotheses H1 and H2, we compile quarterly data on terrorist activity and three different

drugs (cocaine, heroin and methamphetamine) for the periods between 1981:1-1992:4 and between

1994:1-2007:4 for five world regions (Latin America and the Caribbean, the Middle East and

Northern Africa, North America and Western Europe, Sub-Saharan Africa, Central and South East

Asia).5 Our dataset thus allows for an in-depth examination of the drug-terror nexus, so as to also

consider possible qualifications (related to different drug types and terrorism location) to this

nexus. The summary statistics are reported in Table 1.

- Table 1 here –

Terrorist activity is indicated by the number of terrorist incidents per quarter.6 The terrorism data

are drawn from Enders et al. (2011). Following Enders et al. (2011: 321), terrorism is defined as

“the premeditated use or threat to use violence by individuals or subnational groups against

noncombatants in order to obtain a political or social objective through the intimidation of a large

audience beyond that of the immediate victims”. Enders et al. (2011) use terrorism data provided

by the Global Terrorism Database (GTD) which since 1970 has tracked global terrorist activity

by analyzing publicly available sources (e.g., newspaper articles, government reports). Enders et

al. (2011) deal with some methodological problems (e.g., coding issues) associated with the GTD,

5 A country list is given in the appendix. We do not consider countries in other parts of the world

(Oceania, Eastern Europe, East Asia) because these countries did not see noticeable terrorist

activity during our observation period.

6 This includes domestic and transnational terrorist incidents. Domestic terrorism only involves

one country, while transnational terrorism affects multiple countries.

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making their data superior to the GTD raw data.7 We also follow their recommendation (Enders

et al., 2011: 324-325) to further correct the terrorism series for possible under- and over-reporting

of terrorism during specific time periods. Finally, we take the natural logarithm of the quarterly

terrorism time series for each world region so as to make the series more robust to outliers.

The GTD data—and thus the data provided by Enders et al. (2011)—is incomplete for the year

1993, as the original data for this year was lost by the research group overseeing the GTD during

an office move. Given this problem, for each world region we create two distinct samples covering

the two time periods 1981:1-1992:4 and 1994:1-2007:4. Fortunately, the break in the GTD data

also coincides with a major break in the international political system, the end of the Cold War.

The end of the Cold War meant geographical as well as ideological changes in the patterns of

terrorism. These changes can also be seen in Figure 1. For instance, while during the Cold War

Latin America and Western Europe were strongly hit by left-wing terrorism, this activity receded

after the end of the Cold War. Conversely, the end of the Cold War saw an increase in Islamist

terrorist activity located primarily in the Middle East, Africa and Asia (Enders et al., 2011, 2014).

By considering in our analysis two distinct time periods we are able to capture these shifts in

terrorism more precisely, where such shifts may also influence the dynamics of the drug-terror

nexus.

- Figure 1 here -

To indicate drug business activity, we use data on (logged) estimated U.S. prices of powder

cocaine, heroin and d-methamphetamine on the national level, where the data are extracted from

a report by Fries et al. (2008) to the U.S. Office of National Drug Control Policy. A major

advantage of these data is that they are available on a quarterly basis and for different types of

drugs.8 Fries et al. (2008) use records from the System To Retrieve Information from Drug

Evidence (STRIDE) database maintained by the U.S. Drug Enforcement Administration to develop

their dataset. Given that the use of STRIDE raw data may be problematic due to a lack of

representativeness and randomness (Caulkins, 2007), Fries et al. (2008) make a number of

7 The GTD raw data is available at http://www.start.umd.edu/gtd/.

8 To the best of our knowledge, no comparable dataset is available for the drug markets in Europe,

let alone the Middle East, Africa or Asia.

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adjustments to the STRIDE data (e.g., by eliminating extreme outliers) and consequently use this

adjusted data to obtain (consistent) national estimates for quarterly prices of various drugs by

means of statistical analysis.9 Given the clandestine nature of the drug market, data on drug prices

(as well as on drug use and purity) is obviously always imperfect (Caulkins, 2007). This is also

acknowledged by Fries et al. (2008: 9); at the same time, however, they also make clear that their

price estimates still provide valuable and methodologically sound information about drug business

dynamics:

“The times series generated by the […] methodology [of Fries et al. (20008)] thus should

not be interpreted as precise estimates of true nationwide averages of prices […] On the

other hand, and more importantly, there are a number of reasons why relative changes in

[the estimated] time series, manifested as strong features and trends, can be interpreted as

plausible indicators of illicit drug market dynamics. Among these are internal consistencies

within the STRIDE database, robustness across analysis methods, and general

compatibility with external data sources.”

For our contribution we follow the argument by Fries et al. (2008). On the one hand, we

acknowledge that the time-series data we use can reflect the drug business only imprecisely. On

the other hand, it is—for the time being—still the best data available. Thus, we consequently use

data on U.S. drug prices to study the global drug-terror nexus. Similar to Piazza (2011), we argue

that U.S. drug prices reflect the attractiveness of the global drug business. This idea is not only

owed to data limitations, but also borne out of the observation that the U.S. drug market is the

largest drug market in the world that also tends to offer the highest prices (e.g., Reuter and

Greenfield, 2001). Here, strong fluctuations in prices between quarters—as shown in Figure 2—

are expected to be largely driven by drug supply, given that demand for drugs is naturally rather

inelastic. Consequently, these differences in price levels are expected to matter to the causal nexus

between the drug business (indicated by U.S. drug prices) and terrorism (indicated by regional

numbers of terrorist incidents). As hypothesized above, higher prices are expected to induce more

terrorist activity, e.g., as more income from the drug business ought to translate into a higher

9 The estimation procedure, a complex series of nested regression models with a multitude of

parameters to be estimated, is described in detail in Fries et al. (2008).

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capacity of terrorist groups to conduct operations. At the same time, more terrorism is expected to

coincide with higher drug prices. For example, more terrorist activity means that terrorist groups

are more likely to participate in the drug business (to raise revenues), which consequently ought

to result in higher prices to guarantee stable profits for the other actors (e.g., producers, dealers)

involved in the drug business.

- Figure 2 here -

3.2 Empirical Methodology

We use several econometric techniques to assess the causal interactions between terrorist activity

in various parts of the world and the patterns of U.S. drug prices. First, we run tests for

heterogeneous panel causality, following Dumitrescu and Hurlin (2012). Their method involves

running a series of bivariate regressions with panel data to detect Granger causality (Granger,

1969), i.e., to assess whether the inclusion of one time series (indicating, say, terrorism) is useful

in forecasting another time series (indicating, say, drug prices) when the regression model also

includes information on lagged values of the time series to be forecasted.10 As any test for Granger

causality requires the time series to be stationary (Granger, 1969), we run pre-tests for panel

integration (panel unit root tests) and, possibly, for panel cointegration.

The main advantage of the Dumitrescu and Hurlin (2012) method is that it allows the regression

coefficients to be different across cross-sections (in our case, world regions). Allowing for

heterogeneous regression coefficients allows us to test for heterogeneous panel non-causality—

where there is at least one and at most N-1 cross-sections for which causation is present—against

the null hypothesis of homogeneous non-causality for any cross-section. The hypothesis of the

Dumitrescu and Hurlin (2012) method is thus less restrictive than classical Granger causality tests

where regression coefficients are constrained to be equal for all cross-sections, which means to

test the hypothesis of homogeneous causation against the null of non-causality. The assumption of

10 The method of Dumitrescu and Hurlin (2012) has so far not been extended to consider more

complex (multivariate) systems. That is, we cannot consider further control variables in our

analysis, meaning that our results may be affected by the omission of relevant covariates. We

therefore invite future research to consider the robustness of our findings to the inclusion of further

covariates, once related empirical tools become available.

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heterogeneous causation by Dumitrescu and Hurlin (2012) is particularly suited to our analysis of

the drug-terror nexus. As we discussed before, it is likely that the drug business and terrorism

interact differently for different parts of the world due to, e.g., varying levels of access of terrorist

groups to the drug supply chain.

Given our previous discussion of the theoretical mechanisms underlying the drug-terror nexus, it

is thus likely that we detect evidence in favor of heterogeneous causation between drug prices and

terrorism. However, as discussed by Dumitrescu and Hurlin (2012: 1459), “[…] the rejection of

the null of Homogeneous Non Causality does not provide any guidance with respect to […] the

identity of the particular panel units for which the null of non causality is rejected.” In other words,

further tests are necessary to identify those panel units (in our case, world regions) for which

Granger causality is truly present. Thus, after the panel causality tests we proceed with fitting and

estimating a series of vector-autoregressions (VAR) for the individual drug and terrorism time

series, so as to test for Granger causality for each individual pair of time series. The VAR approach

has been used in numerous works of applied economic research; it is discussed in, e.g., Stock and

tools of time-series analysis (variance decomposition, impulse responses) that shall help us to

better quantify and understand the potentially complex causal linkages between terrorism and drug

trafficking.11

4. Empirical Results

4.1 Panel Causality Tests

The panel unit root tests are reported in Table 2. The test results strongly indicate that the series

for terrorism and drug prices are stationary. These findings suggest that we do not need to consider

11 In so doing, we follow the suggestions of Stock and Watson (2001: 104):

“Standard practice in VAR analysis is to report results from Granger-causality tests,

impulse responses and forecast error variance decompositions. […] Because of the

complicated dynamics in the VAR, these statistics are more informative than are the

estimated VAR regression coefficients or R2 statistics, which typically go unreported.”

14

the issue of panel cointegration which would only matter to non-stationary series.12 Also, there is

no need for transformation; we can use the data in levels. The only exception is the price of

methamphetamine for the 1994:1-2007:4 period, for which the test results suggest that this series

is non-stationary. The series becomes stationary after taking the first-difference (test results not

shown). For this one series we will therefore use the first-differenced instead of level data for the

following causality analysis.

- Table 2 here -

The subsequent panel Granger causality tests are reported in Table 3. Due to missing evidence in

favor of a long-run (cointegrating) relationship, we only consider the potential causal effect of

terrorism on drug prices (and vice versa) for a lag length between one and four quarters. The

causality tests results suggest that (i) there is a robust bidirectional causal relationship between the

U.S. price of cocaine and the prevalence of terrorism for both considered time periods, (ii) that

heroin prices causally influence terrorist activity for both the 1981:1-1992:4 and 1994:1-2007:4

period, while there is no evidence that terrorism causally affects the price of heroin and (iii) that

terrorist activity does not Granger-causes the price of methamphetamine and vice versa. With

respect to our two hypotheses, the panel causality findings suggest that H1 and H2 find support

for the cocaine-terror relationship, H2 (but not H1) is supported for the heroin-terror relationship,

while our findings are neither supportive of H1 nor H2 for the methamphetamine-terror

relationship.

- Table 3 here -

The panel Granger causality tests suggest the cocaine-terrorism relationship is particularly strong.

Given the nature of the causality tests we employ (testing the null hypothesis of non-causality

against the alternative of heterogeneous causation), we shall examine in the next subsection for

which world regions this relationship matters. Similarly, we shall analyze for which parts of the

world the causal effect of heroin prices on terrorism matters; however, we will not study the other

direction of causation as there is no evidence for a causal effect of terrorism on heroin prices.

12 Further panel unit root tests (e.g., Breitung’s t-test) and unit root tests for individual time series

(e.g., the Augmented Dickey-Fuller test) provide similar results.

15

Given the missing evidence for causality for the methamphetamine-terrorism relationship in

general, consequently we shall not further consider this variable pair. Here, the missing causal

relationship between methamphetamine prices and the patterns of terrorism is intuitive. For one,

the price of methamphetamine has always been lower than the price of cocaine and heroin, which

means a lower potential for profitability. For instance, the average price of methamphetamine for

the 1981:1-1992:4 period was $225 per gram, while the price of heroin during the same time period

was on average almost six times higher ($1,320 per gram). Also, methamphetamine is commonly

produced in clandestine laboratories (“meth labs”) in proximity to consumers. This is because

methamphetamine production, unlike cocaine and heroin production, does not need herbal inputs

(e.g., coca leaf). This eliminates to a very large extent the need for drug smuggling, which in turn

makes it less likely for terrorist groups to benefit from the methamphetamine business because,

e.g., there is less opportunity to “tax” other actors in the methamphetamine supply chain. In sum,

there are neither sufficient incentives (due to low prices) nor opportunities (due to the production

and distribution of methamphetamine) for terrorist groups to benefit from the methamphetamine

business. In a more general sense, this is consistent with our earlier voiced expectation that the

dynamics of the illicit drug-terror nexus are likely to be dependent upon the type of drug we

consider.

4.2 Vector-Autoregression Findings

4.2.1 Time-Series Granger Causality Tests

In the following subsections we use further tools of time series analysis to consider those variable

pairs for which the panel Granger causality tests indicate robust evidence in favor of a rejection of

the null hypothesis of homogeneous non-causality, i.e., for the cocaine-terror relationship and for

the causal effect of heroin prices on terrorist activity; given a lack of evidence to reject the null

hypothesis of non-causality for the causal effect of terrorism on heroin prices and for the

methamphetamine-terror relationship in general, we do not consider these variable pairs any

further. We first report in Table 4 the Granger causality test results for each world region and drug-

terrorism variable pair of interest.

- Table 4 here -

First, for Latin America we find that there is no causal association between U.S. heroin prices and

terrorism. The causal relationship between cocaine and terrorism, by contrast, is important to the

16

Latin American region, where causation runs in both directions for both time periods considered.

Thus, H1 and H2 only find support for the Latin American region when we consider the cocaine-

terror relationship. This findings is highly intuitive and consistent with the idea of Latin America

as a world region plagued by cocaine “narco-terrorism”, i.e., terrorism closely linked to the cocaine

business. Coca production is native to many countries in Latin America (e.g., Colombia, Peru),

which may yield income to Latin American terrorist groups consequently used to finance

terrorism. Also, as found by Chandra et al. (2014), most cocaine enters the U.S. from the South

(i.e., crossing the border in Texas or California). This makes it possible for terrorist groups

operating in Latin American countries along drug smuggling routes (e.g., Mexico) to also benefit

from the smuggling of cocaine to the United States, e.g., by providing protection and other

“services” to other actors in the drug business (e.g., Hernandez, 2013).

Second, there is evidence that the drug-terror nexus is also relevant to the Middle East and

Northern Africa. We find that (i) terrorism in this part of the world affects the price of cocaine in

the U.S., (ii) the price of cocaine in the Unites States affected terrorism in the Middle East and

Northern Africa for the 1981:1-1992:4 period and (iii) the U.S. price of heroin causally affects

terrorism in the MENA region for both the 1981:1-1992:4 and 1994:1-2007:4 period. Overall, this

finding is consistent with the notion that the MENA region serves as a hub for the illicit drug

business, e.g., with drug being produced in Central Asia (heroin production in the Golden Crescent

and Golden Triangle) and then forwarded to Western Europe and the U.S. via the MENA region.

For instance, the Turkish PKK and the Lebanese Hezbollah have actively participated in drug

trafficking and generated large income from these activities (Roth and Sever, 2007; Hernandez,

2013). This income is likely to translate into increased terrorist activity, which explains the causal

effect from drug prices to terrorism. At the same time, our findings suggest that more terrorism

also affects drug prices. For the MENA region this is likely due to the fact that terrorist conflict

means more need for financial resources (leading to more involvement by terrorist groups in the

drug trade, which should drive up prices). The economic viability of the drug-terror nexus in the

MENA region is certainly also strengthened by state fragility and lack of states’ control over their

territory, which makes the drug business comparatively more attractive and curtails governmental

anti-drug and anti-terrorism measures. For instance, these factors have mattered to the drug

economy in the Lebanon (a notoriously fragile state plagued by civil war in the past) and

geographically inaccessible areas such as Kurdistan and the deserts of Northern Africa.

17

Third, we also find moderate evidence that the drug-terror nexus matters to Central and South East

Asia. For one, we find that terrorism affects U.S. cocaine prices for both time periods (but not vice

versa). For another, the price of heroin in the United States had a causal effect of terrorism in

Central and South East Asia for the post-Cold War era. The former finding may suggest that

Central and South East Asia (similar to the MENA region) are important hubs for cocaine

trafficking, being part of a “new silk road” that goes from Asia (via the MENA region) to the

Western markets (Howard and Traughber, 2008). The nexus between cocaine trafficking and

terrorism may furthermore be strengthened by the fact that coca is also cultivated in parts of South

East Asia (e.g., Indonesia); yet, coca production in South East Asia does not reach Latin American

dimensions. More important than the production of coca is the cultivation of opium poppy in

Central and South East Asia (primarily in the Golden Crescent and the Golden Triangle), which

is used in the production of heroin. This explains why U.S. heroin prices affect terrorist activity in

this part of the world. This finding also consistent with Piazza (2012) who finds that opium

production affects terrorist activity in Afghanistan. Here, the causal effect of U.S. heroin prices on

terrorism in Central and South East Asia is only significant for the 1994:1-2007:4 period. This has

likely to do with the collapse of state authority after the end of the Cold War in this part of the

world, which created many new states with weak institutions, high levels of corruption and dismal

economic conditions, all of which in turn contributed to a growth of local drug economies and the

use of drug money to finance terrorist activity (e.g., Howard and Traughber, 2008).

Finally, our Granger causality test results indicate that drug prices and terrorism share no causal

relationship for Sub-Saharan Africa and Northern America/Western Europe, regardless of which

drug type or time period we consider. Thus, both H1 and H2 are soundly rejected for these parts

of the world. These findings suggest that the drug-terror nexus does not matter to these parts of

the world. For Sub-Saharan Africa this is likely due to the fact that this part of the world is

farthermost from traditional drug production areas and smuggling routes. Also, the drug market in

Sub-Saharan Africa ought to be smaller and less profitable due to lower levels of economic

development. Consequently, terrorist groups are not expected to systematically benefit from or be

affected by the drug business. Rather, terrorist groups operating in Sub-Saharan Africa tend to

resort to other illicit means of financing such as piracy, kidnapping and diamond and human

trafficking (e.g., Ross, 2003; Hübschle, 2011; Shortland and Vothknecht, 2011).

18

For Northern America/Western Europe it is similarly likely that terrorist organizations use other

means apart from drug trafficking to finance themselves, which in turn explains why there is little

causal relationship between drug prices and terrorist activity in the developed world. For one,

terrorist groups operating in this part of the world are usually rather small, meaning that they lack

the capacity to participate in the drug business and cooperate with organized crime groups.13

Instead, small terrorist groups in the West have relied on other means of financing such as bank

robberies, extortions and (especially during the Cold War era) sponsorship from foreign countries.

Interestingly, though, while the drug business does not seem to have stimulated terrorist activity

by groups based in Northern America and Western Europe, the drug business taking place in this

part of the world (i.e., in those parts of the world with the most profitable drug markets) is still

likely to have benefitted terrorist groups operating in other parts of the world. For instance, drug

trafficking in Western Europe is to a large extent controlled by non-European ethnic groups such

as Turks and Colombians (Paoli and Reuter, 2008). This in turn would allow non-European

terrorist groups from, e.g., Turkey or Colombia to benefit from the drug business in Western

Europe by infiltrating local European communities that share the terrorist group’s kinship or

political ideology. For example, this indeed appears to be true for the case of the Turkish PKK. As

found by Roth and Severs (2007: 907-908): “The PKK not only is directly involved in transporting

and marketing narcotics in Europe but also extracts so-called revolutionary taxes from narcotics

traffickers and refiners in order to finance terrorist actions.” In other words, it seems likely that the

drug profits generated in Western Europe and Northern America fuel conflicts in other parts of the

world such as the Middle East and Latin America. However, we cannot unearth such linkages

within our empirical framework, which leaves an interesting field of study to future research.

4.2.2 Variance Decompositions

In the previous subsection we have established that the drug-terror nexus is complex, meaning that

its dynamics vary for the drug type and world region considered. To consider the strength of the

13 For instance, groups like the German Red Army Faction or the Italian Red Brigades at their peak

only had a few dozen operatives (Jones and Libicki, 2008). Western terrorist groups of noticeable

size have generally been very rare (Jones and Libicki, 2008). However, those groups that were

large enough were also able to partake in the drug business. For instance, the Provisional Irish

Republican Army also to some extent benefitted from the drug business.

19

various causal interactions, in this subsection we present the variance decompositions associated

with the VARs estimated for the Granger causality tests presented in the previous subsection. As

outlined in Stock and Watson (2001) and Enders (2010), variance decompositions indicate the

amount of information each variable contributes to the other variables in the vector-autoregression,

i.e., the forecast error variance of each of the variables that can be explained by exogenous shocks

to the other variables. Or, as put by Stock and Watson (2001: 106): “The forecast error

decomposition is the percentage of the variance of the error made in forecasting a variable […]

due to a specific shock […] at a given horizon […] Thus, the forecast error decomposition is like

a partial R2 for the forecast error, by forecast horizon.” Here, the more the independent variable

contributes to explaining the forecast error variance of the dependent variable in a bivariate VAR,

the stronger is the causal effect of the independent on the dependent variable.

The variance decompositions are reported in Table 5.14 In sum, the variance decompositions are

in line with the Granger causality test results and indicate that the drug-terror nexus also

quantitatively matters to some parts of the world.

- Table 5 here -

For Latin America we find that the causal effect of cocaine prices on terrorist activity in Latin

America (and vice versa) is indeed also economically substantive. For instance, for the 1994:1-

2007:4 period an exogenous shock to terrorism after eight periods (i.e., two years) explains 27.6

per cent of the forecast error variance of U.S. cocaine prices. By contrast, the effect of heroin

prices on terrorism is negligible. For example, for the 1981:1-1992:4 period a shock to heroin

prices in the U.S. after eight periods explains only 1 per cent of the forecast error variance of

terrorist activity in Latin America.

Similarly, we find that the nexus between drug prices and terrorist activity also tends to be not

only statistically significant but also economically substantive for the MENA region and Central

and South East Asia. For instance, for the 1994:1-2007:4 period an exogenous shock to U.S. heroin

prices explains 9.6 per cent of the forecast error variance of terrorist activity in Central and South

East Asia after eight quarters have passed.

14 The variance decompositions show little sensitivity to changes of the Cholesky ordering.

20

By contrast, and again consistent with the Granger causality test results, there are little substantive

effects associated with the drug-terror nexus for Northern America and Western Europe and Sub-

Saharan Africa. For instance, considering the 1994:1-2007:4 period we find that shocks to both

U.S. cocaine and heroin prices explain about 2 per cent of the forecast error variance of terrorist

activity in North America and Western Europe, regardless of which forecast horizon we consider.

For Sub-Saharan Africa, the drug-terror relationship is even less pronounced. For example, an

exogenous shock to U.S. cocaine prices explains only about 1.3 per cent of the forecast error

variance of terrorism in this part of the world.

4.2.3 Impulse Responses

Another tool to examine the dynamics within the various VARs we estimate are impulse responses,

which give us a graphical representation of the strength and the direction of the estimated causal

effects (i.e., whether an effect is, for a given period, strictly positive, negative or meandering).

Here, “[i]mpulse responses trace out the response of current and future values of each of the

variables to a one-unit increase in the current value of one of the VAR errors, assuming that this

error returns to zero in subsequent periods and that all other errors are equal to zero” (Stock and

Watson, 2001: 106). For our analysis we use the impulse responses to assess how the dependent

variable responds to a one-time impulse of (one-unit shock to) the independent variable, with

values of both variables prior to the impulse held constant.

The various impulse response are reported in the appendix. For the sake of brevity and clarity, we

shall only very briefly summarize the impulse response findings in the main text. In sum, the

impulse response tend to suggest that shocks to drug prices (i.e., increases in the prices of cocaine

and heroin) lead to more terrorist activity and that terrorism impulses (i.e., increases in terrorism)

lead to higher drug prices. Again, this is what we expect given our discussion on Section 2 and in

line with our hypotheses H1 and H2.15 For instance, the impulse responses thus suggest that higher

prices induce more terrorism, presumably as more income from the drug business ought to

15 For some world regions and time horizons the impulse response suggest that—contrary to our

expectations—more terrorist activity may lead to lower drug prices and that higher drug prices

may drive down terrorism. We should not overstate these latter findings, though, as they are

usually not stable over time and/or statistically significant.

21

translate into a higher capacity of terrorist groups to conduct operations. Similarly, our findings

also indicate that more terrorism leads to higher drug prices; for instance, this may be due to the

fact that terrorism produces economic damage, which in turn raises the attractiveness of civilians

to participate in the drug business and could result in higher drug prices.

5. Conclusion

In this contribution we developed—building on existing research—two hypotheses on the causal

relationship between the illicit drug business and terrorist activity. For one, we argued that an

increase in drug business attractiveness (indicated by higher drug prices) ought to translate into

(i.e., cause) stronger terrorist activity. For another, we argued that an increase in terrorism ought

to lead to higher drug business attractiveness (i.e., higher drug prices). To test these hypotheses,

we employed tools of panel and time-series analysis to examine the causal linkages between the

drug business and terrorism, using quarterly data for two time periods (1981:1-1992:4 and 1994:1-

2007) and the five world regions affected the strongest by terrorism during these periods (Latin

America and the Caribbean, the Middle East and Northern Africa, North America and Western

Europe, Sub-Saharan Africa and Central and South East Asia). Our analysis of the drug-terror

nexus points to a complex relationship between the drug business and the prevalence of terrorism,

which can be summarized as follows:

It is important which drug is considered. Drug that yield high profits (cocaine, heroin) share a

closer relationship with terrorism than drugs that do not (e.g., methamphetamine).

Location also matters. Terrorism occurring in locations (world regions) that provide access to

the global drug supply chain, be it with respect to drug cultivation or drug smuggling, is more

strongly affected by drug price fluctuations (and vice versa).

Location is also likely to mater to the drug-terror nexus because it is likely to correlate with

economic, institutional and geographic conditions that further influence this nexus. For

instance, weak institutions (e.g., corruption, weak law enforcement), poor socio-economic

conditions (e.g., unemployment) and long porous borders and inaccessible state territory are

expected to reinforce the relationship between the drug business and terrorist activity.

In sum, we find that the drug-terror nexus is particularly strong for Latin America, the Middle

East and Northern Africa and Central and South East Asia. For one, these world regions harbor

the production of drug “cash crops” (cocaine mainly for Latin America, heroin mainly for

22

Central and South East Asia) and/or serve as hubs for the heroin and cocaine trade to the United

States and Europe, the most profitable drug markets. For another, these world regions also see

those politico-institutional and socio-economic deficiencies mentioned above that can be

expected to further encourage the drug-terror relationship.

By contrast, we do not find that the drug-terror nexus is relevant to Sub-Saharan Africa. While

institutional and economic circumstances in Sub-Saharan Africa would surely benefit drug-

terror interactions, it seems likely that Sub-Saharan Africa is simply too remote from the main

areas of drug production and trade for terrorism too be systematically swayed by the drug

business (and vice versa). This is why local Sub-Saharan terrorist and insurgent groups instead

resort to other forms of illegal activity (e.g., diamond and human trafficking) to gain financial

resources.

Finally, we do not find that the drug-terror nexus matters to terrorism in the West (i.e., Northern

America and Western Europe). Even though illicit drug markets in the West are large and

profitable, local (Western) terrorist groups tend to lack the capacity (e.g., due to insufficient

size) to gain a share in the drug business. However, it still seems likely that the illegal drug

business in the West benefits (substantially larger) foreign terrorist organizations that mainly

operate outside the West, an example being the Turkish PKK.

Our study has some implications for policymakers. First, anti-drug and anti-terror measures may

reinforce each other for some parts of the world, especially Latin America, the Middle East and

Northern Africa and Central and South East Asia. For instance, Schneider et al. (forthcoming)

argue that in the long run terrorism may be effectively fought through institutional reforms (e.g.,

a stronger rule of law and sound public good provision by the state). Such counter-terrorism

policies can also be expected to pay-off in terms of reducing drug business activity for those parts

of the world that see a close association between the illegal drug business and terrorism.

Furthermore, given the externalities terrorism and organized crime are likely to produce (thereby

also affecting the West), there exist incentives for Western countries to support such long-run

policy measures. However, given that the drug-terror nexus is not found to matter equally to all

parts of the world, it is unlikely that terrorism (the illicit drug business) can be successfully

23

marginalized by only counteracting the drug business (terrorism).16 Additional research is

necessary to advance our understanding of the linkages between organized crime and terrorism,

which may also help to unveil further sources of illegal funding—besides an involvement in the

drug business—terrorist organizations tap into to finance their operations. Such research can be

expected to further increase the effectiveness of governmental counter-terrorism (counter-drug)

measures.

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Figures and Tables

Figure 1: Terrorist Activity in Different Parts of the World, 1981-1992 and 1994-2007

Figure 2: Quarterly National Drug Price Development in the United States, 1981-2007

Variable (Time Period) N*T Mean Std. Dev. Min Max

1981:1-1992:4

Terrorism (Full Panel) 240 4.278 0.976 1.386 6.157

Terrorism (Latin America and the Caribbean) 48 5.614 0.313 4.703 6.157

Terrorism (Middle East and Northern Africa) 48 3.843 0.573 2.303 5.019

Terrorism (North America and Western Europe) 48 4.441 0.275 3.784 5.130

Terrorism (Sub-Saharan Africa) 48 3.483 0.720 1.386 5.088

Terrorism (Central and South East Asia) 48 4.012 1.041 1.609 5.610

Price of Cocaine (U.S.) 240 5.832 0.430 5.125 6.636

Price of Heroin (U.S.) 240 7.149 0.277 6.547 7.746

Price of Methamphetamine (U.S.) 240 5.383 0.257 4.928 5.991

1994:1-2007:4

Terrorism (Full Panel) 280 3.485 0.985 0.000 5.869

Terrorism (Latin America and the Caribbean) 56 2.968 1.008 0.693 4.974

Terrorism (Middle East and Northern Africa) 56 4.058 0.664 3.045 5.869

Terrorism (North America and Western Europe) 56 3.373 0.700 1.792 4.511

Terrorism (Sub-Saharan Africa) 56 2.685 0.790 0.000 3.961

Terrorism (Central and South East Asia) 56 4.340 0.594 3.045 5.687

Price of Cocaine (U.S.) 280 5.034 0.185 4.674 5.489

Price of Heroin (U.S.) 280 6.129 0.184 5.795 6.565

Price of Methamphetamine (U.S.) 280 4.812 0.364 4.045 5.705

Note: All variables in natural logarithms.

Table 1: Summary Statistics

Variable (Time Period) Levin-Liu-Chu Test Statistic Im-Pesaran-Shin Test Statistic

1981:1-1992:4

Terrorism (Full Panel) -7.458*** -6.927***

Price of Cocaine (U.S.) -7.556*** -4.639***

Price of Heroin (U.S.) -12.783*** -12.524***

Price of Methamphetamine (U.S.) -9.831*** -7.707***

1994:1-2007:4

Terrorism (Full Panel) -7.453*** -7.955***

Price of Cocaine (U.S.) -14.596*** -12.131***

Price of Heroin (U.S.) -11.060*** -8.500***

Price of Methamphetamine (U.S.) 0.650 -1.152

Notes: Levin-Liu-Chu test assumes a common unit root process, while the Im-Pesaran-Shin test assumes individual unit root processes.

Individual effects and linear trends included as exogenous variables. Automatic lag length selection through Schwarz Information

Criterion. *** p<0.01 (indicating the rejection of the null hypothesis, i.e., a common or individual unit root process).

Table 2: Panel Unit Root Tests

Null Hypothesis (Ho) Period Zbar Statistic for different lag lengths

t=1 t=2 t=3 t=4

Terrorism does not homogeneously causes price of cocaine 1981:1-1992:4 2.317** 0.493 -0.473 -0.038

1994:1-2007:4 3.460*** 2.592*** 0.907 2.331**

Terrorism does not homogeneously causes price of heroin 1981:1-1992:4 0.941 -0.090 -1.082 1.738*

1994:1-2007:4 0.500 -0.321 -0.320 0.712

Terrorism does not homogeneously causes price of 1981:1-1992:4 -0.980 -1.005 -1.449 -0.633

Methamphetamine 1994:1-2007:4 1.664* 0.726 0.363 0.051

Price of cocaine does not homogeneously causes terrorism 1981:1-1992:4 4.397*** 2.937*** 2.195** 1.665*

1994:1-2007:4 1.683* 2.170** 2.084** 1.888*

Price of heroin does not homogeneously causes terrorism 1981:1-1992:4 3.397*** 2.331** 1.067 0.572

1994:1-2007:4 8.534*** 2.278** 0.319 1.125

Price of methamphetamine does not homogeneously causes 1981:1-1992:4 0.116 0.939 0.766 0.180

terrorism 1994:1-2007:4 -0.218 -1.442 -0.984 -1.055

Notes: Price of methamphetamine for 1994:1-2007:4 in first differences. All other variables in levels. * p<0.1, ** p<0.05, *** p<0.01

(indicating the rejection of the null hypothesis, i.e., homogeneous panel Granger non-causality).

Table 3: Heterogeneous Panel Causality Test Results

Null Hypothesis (Ho) Period Granger-Wald Test Statistics

LAC MENA NAWE SSA CSEA

Terrorism does not

Granger-

1981:1-1992:4 4.165*** (8) 6.573*** (7) 0.202 (1) 1.456 (2) 4.565** (1)

cause price of cocaine 1994:1-2007:4 9.403*** (5) 3.192** (2) 2.400 (1) 0.470 (1) 5.7775*** (2)

Price of cocaine does not 1981:1-1992:4 10.543*** (8) 3.366** (7) 2.511 (1) 1.672 (2) 0.781 (1)

Granger-cause terrorism 1994:1-2007:4 3.943*** (5) 0.585 (2) 0.075 (1) 0.966 (1) 1.069 (2)

Price of heroin does not 1981:1-1992:4 0.617 (1) 3.293** (7) 0.879 (1) 1.509 (1) 0.112 (1)

Granger-cause terrorism 1994:1-2007:4 0.001 (1) 5.509** (1) 0.843 (1) 1.258 (1) 2.630* (2)

Notes: All VAR include a time trend. Lag length for underlying VAR in parentheses. Optimal lag length determined via Akaike Information

Criterion. LAC=Latin American and the Caribbean. MENA=Middle East and Northern Africa. NAWE=Northern America and Western

Europe. SSA=Sub-Saharan Africa. CSEA=Central and South East Asia. * p<0.1, ** p<0.05, *** p<0.01 (indicating the rejection of the null

hypothesis, i.e., Granger non-causality).

Table 4: Granger Causality Test Results for Individual Time Series

Considered Forecast Sub-Sample and Variable Pair

Decomposition Horizon LAC MENA NAWE SSA CSEA

Terror Coc./Her. Terror Coc./Her. Terror Coc./Her. Terror Coc./Her. Terror Coc./Her.

1981:1-1992:4

For Terrorism t=2 91.919 8.081 95.665 4.335 95.368 4.632 99.923 0.078 99.029 0.972

(VAR with Cocaine) t=4 78.206 21.794 83.716 16.284 94.875 5.125 93.199 6.801 97.702 2.298

t=8 68.071 31.930 72.763 27.237 94.832 5.168 92.372 7.628 97.200 2.800

For Cocaine t=2 5.133 94.867 1.759 98.241 0.346 99.654 6.211 93.789 4.897 95.103

(VAR with Terrorism) t=4 18.815 81.185 24.376 75.625 0.386 99.614 10.613 89.387 11.875 88.125

t=8 33.573 66.427 35.323 64.677 0.389 99.611 10.739 89.261 14.490 85.510

For Terrorism t=2 99.191 0.809 79.524 20.476 92.179 7.821 93.832 6.168 98.956 1.044

(VAR with Heroin) t=4 98.994 1.006 75.032 24.968 92.115 7.885 93.210 6.790 98.809 1.192

t=8 98.976 1.024 66.695 33.305 92.114 7.886 93.193 6.807 98.786 1.214

1994:1-2007:4

For Terrorism t=2 95.834 4.166 98.692 1.308 97.464 2.536 99.019 0.981 98.695 1.301

(VAR with Cocaine) t=4 84.717 15.283 98.682 1.318 97.464 2.536 98.725 1.275 98.345 1.655

t=8 81.199 18.801 98.712 1.288 97.464 2.536 98.692 1.301 98.290 1.710

For Cocaine t=2 3.720 96.281 2.301 97.700 2.298 97.703 0.424 99.576 12.617 87.383

(VAR with Terrorism) t=4 22.466 77.534 5.748 94.253 2.298 97.703 0.687 99.313 13.043 86.957

t=8 27.618 72.382 7.360 92.640 2.298 97.703 0.717 99.283 13.058 86.942

For Terrorism t=2 99.978 0.002 82.074 17.926 97.880 2.121 98.895 1.105 98.217 1.783

(VAR with Heroin) t=4 99.978 0.002 78.777 21.223 97.768 2.232 98.054 1.946 91.569 8.431

t=8 99.978 0.002 78.448 21.552 97.766 2.234 97.857 2.143 90.436 9.565

Notes: Results for variance decompositions computed from VARs with the same lag order and specification as described in Table 4. Cholesky ordering

(cocaine/heroin, terrorism). Results show little sensitivity to change in Cholesky ordering. LAC=Latin American and the Caribbean. MENA=Middle East

and Northern Africa. NAWE=Northern America and Western Europe. SSA=Sub-Saharan Africa. CSEA=Central and South East Asia.

Table 5: Forecast Variance Decompositions

Appendix A. Country List

Latin America and the Caribbean: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, French

Guiana, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela; Bahamas, Belize, Costa Rica,

Cuba, Dominican Republic, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Nicaragua,

Panama, Puerto Rico, Trinidad and Tobago.

Middle East and Northern Africa: Algeria, Bahrain, Cyprus, Egypt, Iran, Iraq, Israel, Jordan,

Kuwait, Lebanon, Libya, Morocco, Yemen, Oman, Qatar, Saudi Arabia, Syria, Tunisia, Turkey,

United Arab Emirates, West Bank and Gaza Strip, Western Sahara.

North America and Western Europe: Canada, Mexico, United States; Austria, Belgium, Denmark,

Finland, France (with Corsica), (West) Germany, Great Britain and Northern Ireland, Greece,

Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland.

Sub-Saharan Africa: Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde,

Central African Republic, Chad, Comoros, Congo (Brazzaville), Congo (Kinshasa), Djibouti,

Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea‐Bissau, Ivory Coast,

Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Namibia, Niger,

Nigeria, Zimbabwe, Rwanda, Sao Tome and Principe, Senegal, Sierra Leone, Somalia, South

Africa, Sudan, Swaziland, Tanzania, Togo, Uganda, Zambia.

Central and South East Asia: Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines,

Singapore, Vietnam, Thailand; Afghanistan, Bangladesh, Bhutan, India, Maldives, Mauritius,

Nepal, Pakistan, Seychelles, Sri Lanka, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan,

Uzbekistan.

Appendix B. Impulse Responses

Impulse Responses: Latin America

a) Cocaine-Terrorism, 1981:1-1992:4 b) Heroin-Terrorism: 1981:1-1992:4

c) Cocaine-Terrorism, 1994:1-2007:4 d) Heroin-Terrorism: 1994:1-2007:4

Impulse Responses: Middle East and Northern Africa

a) Cocaine-Terrorism, 1981:1-1992:4 b) Heroin-Terrorism: 1981:1-1992:4

c) Cocaine-Terrorism, 1994:1-2007:4 d) Heroin-Terrorism: 1994:1-2007:4

Impulse Responses: Northern America and Western Europe

a) Cocaine-Terrorism, 1981:1-1992:4 b) Heroin-Terrorism: 1981:1-1992:4

c) Cocaine-Terrorism, 1994:1-2007:4 d) Heroin-Terrorism: 1994:1-2007:4

Impulse Responses: Sub-Saharan Africa

a) Cocaine-Terrorism, 1981:1-1992:4 b) Heroin-Terrorism: 1981:1-1992:4

c) Cocaine-Terrorism, 1994:1-2007:4 d) Heroin-Terrorism: 1994:1-2007:4

Impulse Responses: Central and South East Asia

a) Cocaine-Terrorism, 1981:1-1992:4 b) Heroin-Terrorism: 1981:1-1992:4

c) Cocaine-Terrorism, 1994:1-2007:4 d) Heroin-Terrorism: 1994:1-2007:4