International Studies Quarterly (2017) 61, 14–27
Do Good Fences Make Good Neighbors? Border Barriers and the Transnational Flow of Terrorist Violence NAZLI AVDAN University of Kansas AND
C H R I S T O P H E R F. G E L P I Ohio State University States traditionally build walls to repel the armies of adversaries and consolidate control over territory. More recently, the growth in violence by nonstate groups has led governments to use fences to prevent insurgent activity and transnational terrorism. This practice, which has accelerated since the end of World War II, challenges liberal expectations of a borderless world. We use a new and unique data set on twentieth century interstate border barriers to evaluate the effectiveness of fencing as a defense against transnational terrorist attacks. The strategic nature of barrier construction makes the assessment of causal effects complex. However, our analyses suggest that fences reduce the annual relative risk of a terrorist attack by at least 67 percent. Much of the literature on transnational terrorism focuses on variables such as democracy, development, and distance—that is, factors that are difficult for policy-makers to manipulate. But our analysis suggests that fencing may provide an effective policy tool for leaders seeking to insulate their states from transnational terrorist attacks.
Introduction The control of borders is a long-standing core function within states’ pursuit of security. States often restrict access to territory by imposing barriers designed to ward off the armies of other states, monitor the flow of goods, and to screen out undesirables (Andreas 2003a). Leaky borders allow a plethora of transnational threats to take root in poorly managed border hinterlands (Donaldson 2005). Anxiety over clandestine and unauthorized territorial access has magnified the primacy of border control in world politics (Andreas and Nadelman 2006; Naim 2005). Transnational threats to state actors run the gamut from the relatively innocuous—such as refugees and illegal migrants—to the more pernicious—such as organized crime, militants, and terrorists. All of these nonstate actors threaten state security by evading state surveillance (Andreas 2003a; Andreas and Nadelman 2006; Andreas and Price 2001). Among these various transnational threats, however, none receives more scholarly attention, or evokes more expansive fears, than transnational terrorists. Transnational terrorism undermines the physical integrity of states and threatens to inflict the kind of damage once the exclusive preserve of state militaries. In consequence, terrorism has, for many, fundamentally transformed how states pursue security (Salehyan 2008). In particular, it calls into question the efficacy of territorial borders in securing the state. Nazli Avdan (PhD, Duke University, 2010) is assistant professor of political science at the University of Kansas (KU). Prior to KU, Dr. Avdan served as a research Fellow at the University of Oxford. Her teaching and research interests span nonstate violence and international conflict. Christopher Gelpi (PhD, University of Michigan, 1994) is chair of Peace Studies and Conflict Resolution at the Mershon Center for International Security and Professor of Political Science at The Ohio State University. Prof. Gelpi’s research and teaching focuses on US foreign policy, public opinion, and conflict. Authors’ note: Authors thank anonymous reviewers and the journal’s editorial board for constructive feedback.
The growing salience of border control is perhaps most strikingly illustrated by the installment of physical border barriers—fences and walls—across international borders.1 More striking still is the accelerated pace with which states erect these artificial barriers. Since the end of World War II, governments have constructed sixty-two new fences—and forty-eight of these since the end of the Cold War. According to our research on fence construction, ten out of forty-eight post-Cold War fences have the purported aim of stopping terrorism. And many additional states have voiced their intentions to seal their borders by building walls. For example, Iran is currently constructing a 435-foot-long fence against Pakistan, and Tehran explicitly names militancy and terrorism as reasons for the barrier (Ghasmalee 2011). Similarly, Israel announced in June 2014 that it would institute fences along its borders with Jordan and Syria to preclude infiltration by radical Islamist militants (“Israel to Fortify” 2014). And following the Reyhanli terrorist attacks of May 2013, Turkey began wall construction on its southeastern border with Syria (Afanasieva 2014). The international relations literature frequently focuses on the impact of borders on interstate conflict (for example, Goertz and Diehl 1992; Huth 1996) and interstate commerce (for example, Simmons 2005), but this literature generally ignores the impact of border management strategies such as barrier construction. Moreover, existing studies that address barrier construction as counterterrorism policy often focus on fencing as a strategy for mitigating the widespread public anxiety associated with terrorism (Lahav 2004). Terrorism presents, after all, as much a psychological as an 1 Myriad terms exist to refer to artificial barriers: walls, fences, fortifications, lines, and separation barriers, among others. Whereas the use of these terms sometimes indicates how these structures differ—for example, walls are solid, relatively permanent, and continuous whereas fences may be discontinuous and temporary—in this article we make no distinction among these structures. Thus, the words fences, walls, and barriers are used interchangeably throughout the article.
Avdan, Nazli and Christopher F. Gelpi. (2017) Do Good Fences Make Good Neighbors? Border Barriers and the Transnational Flow of Terrorist Violence. International Studies Quarterly, doi: 10.1093/isq/sqw042 C The Author (2016). Published by Oxford University Press on behalf of the International Studies Association. V All rights reserved. For permissions, please e-mail:
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objective threat (Crenshaw 1986). In an effort to assuage fears, governments strive to deploy symbolic and visible measures that reassert state authority through vigilance. Border barriers fit the bill: they permit states to guard entry on site before individuals can access states’ territories. A scared public is also more likely to accept, and even champion, border closure (Lahav 2010). Border barriers may well increasingly emerge as an attractive option to allay such fears, but they also come with a hefty price tag. For instance, Customs and Border Protection (CBP) spent over $2.4 billion between 2006 and 2009 on 670 miles of the US-Mexico fence (Sais 2013).2 Nonetheless, states may be more than willing to construct walls because they simultaneously underestimate the price tag of antiterrorism policies while overestimating their effectiveness (Donohue 2008). The combination of the high cost and psychological attractiveness of walls raises the urgency of understanding the effectiveness of these barriers in stemming the flow of transnational terrorism. A small stream of scholarship devotes attention to border management (Carter and Goemans 2011; Gavrilis 2008), and a handful of studies examine border walls specifically (Carter and Poast 2015; Hassner and Wittenberg 2015). But even this limited body of work focuses on the causes of border walls rather than the consequences. Thus we know very little about whether these barriers do in fact mitigate terrorist violence. Our article investigates a simple but important question: Do the ends justify the means? That is, are border fences effective policy tools in reducing the incidence of transnational terrorist attacks? Our analyses indicate that once one accounts for the strategic placement of fences, these barriers have a substantial mitigating impact on the flow of transnational terrorism. Specifically, fences reduce the annual relative risk of a terrorist attack by at least 67 percent. We conclude with a brief discussion of the theoretical and policy implications of our results.
Fences and Walls in World Politics Barrier construction has gained steam since the end of the Cold War, but man-made barriers are not completely new to world politics (Sterling 2009). In the twentieth century, states generally used walls as strategic defenses in anticipation of, or during, conventional warfare. The illfated Maginot Line, for example, sought to block German forces at the French border. Other states erected barriers to consolidate their authority over recently seized land. Israel, for example, built the Bar-Lev Line to fortify the east bank of the Suez Canal after gaining control of the Sinai Peninsula in the 1967 War. States also used walls to counter insurgency during war. France built the Morice line in 1956 to stymie National Liberation Front forces during the Algerian war of independence. Finally, walls have also demarcated ideological rivals. The Berlin Wall reified the ideological split between the capitalist West and the communist East and its demise inaugurated the dissolution of the Soviet bloc. The longest standing wall, the Korean demilitarized zone line, is a stark reminder of the enduring rivalry between North and South Korea. However, many modern-day barriers are primarily intended not for military purposes. Rather, states construct them to enhance frontier control by regulating mobility 2 Although not directly tied to terrorism, champions of greater USMexican border security often invoke the threat of terrorism as additional justification for their preferred policies.
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across borders. In fact, according to Donaldson (2005), new boundary defense and security measures represent a transition from defense to policing, as the dominant security paradigm alters to include threats from individuals and irregular forces (Cronin 2002). Barriers intended primarily for geomilitary defense now represent an aberration rather than the norm. Instead, walls come up to deny territorial access to clandestine transnational actors, “defined as non-state actors who operate across national borders and who attempt to evade law enforcement efforts” (Andreas 2003b, 78). States that erect border fences, especially when coupled with surveillance technology and border patrol, generally seek to dampen the threat of terrorist infiltration by reducing border porousness.3 The expectation, of course, is not that they will eradicate cross-border terrorism but rather, more modestly, that they may reduce the number of incidents. In the fight against terrorism, building walls may also represent a more attractive and feasible strategy when compared to risky endeavors such as air campaigns and ground incursions into neighboring territory (Staniland 2006). Terrorist actors are notoriously hard to identify, detect, and root out from strongholds, rendering campaigns to dismantle bases or decapitate leadership costly and sometimes unfeasible. In fact, the failure of more offensive counterterrorism measures prompted India’s fence against Pakistan in1993 and Israel’s West Bank fence in 2003 (Jellissen and Gottheil 2013). Despite these anecdotal examples, scant research exists on the effectiveness of border walls. At best, current scholarship reassures us that walls effectively assuage public anxiety over transborder threats (Andreas 2000; Sterling 2009; Jones 2012a). For example, the Secure Fence Act of 2006, which authorized 700 additional miles of fence along the US border with Mexico, stirred much controversy on feasibility and effectiveness. In response, Secretary of the Department of Homeland Security, Michael Chertoff, defended the fence by noting, “I think the fence has come to assume a certain kind of symbolic significance which should not obscure the fact that it is a much more complicated problem than putting up a fence which someone can climb over with a ladder or tunnel under with a shovel” (Jones 2012b). But the public relations success of border barriers rests on empirical evidence that is—at best—a thin veneer. Terrorist campaigns continue in Palestine and Kashmir, and even the apparent success of barriers such as the Israeli wall has largely been to change the tactical nature rather than the overall number of terrorist attacks. More generally, if we compare borders that are fenced to those without barriers, it is clear that fenced borders experience substantially more violence. This positive association may, of course, be due to the fact that fencing is not randomly applied to borders but is often a strategic response to terrorist threats. But a number of scholars go further to argue that fencing may actually exacerbate conflict between neighboring states (Donaldson 2005; Sterling 2009). The paucity of data and severe problems of selection bias complicate any analysis of the stopping power of fences (Hassner and Wittenberg 2015). Governments are reluctant to reveal data on illegal border crossings, leaving 3 States may augment border security through electrified fences, the deployment of military forces, or minefields. However, these measures may be enacted to reduce border vulnerability independent of the installation of fences. For example, land mines are put in place as a lethal alternative to fences: Bosnia-Herzegovina, Cambodia, and Angola are examples of heavily mined states that have not installed barriers.
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Do Good Fences Make Good Neighbors?
scholars with no reliable metric to assess the success of barriers (Carter and Poast 2015). States also may simultaneously deploy multiple strategies to contain terrorism, which further complicates our ability to discern the efficacy of border fences. For example, in addition to constructing the West Bank barrier, Israel reoccupied the West Bank and encircled the Palestinian population. These strategies may also have reduced the incidence of terrorism. This possibility has been a rallying cry for critics of the West Bank barrier who argue that these initiatives were equally, if not more, effective in reducing terrorism than the barrier (see, for example, Nissenbaum 2007). Thus scholars, policy-makers, and members of the public continue to struggle with the difficult task of assessing whether violent fenced borders are relatively less violent than they would be in the absence of the barrier. Our methodological approach helps us to disentangle the causal impact of fences from strategic self-selection. However, we acknowledge at least two important caveats at this stage.4 First, because we focus on the occurrence (and volume) of terrorist incidents, our approach does not capture the psychological magnitude of attacks. For instance, while the fatality rate from the rockets pales in comparison to that from the suicide campaign, the terrorizing force of Hamas remained intact after the installation of the West Bank barrier. Second, our methodological design permits us to assess the average effectiveness of fences despite cross-sectional and temporal variation in alternative counterterrorism tools, but we are not able to analyze the efficacy of fences compared to other strategies, nor are we able to examine the interactive effects of barriers with additional policy measures.
Theorizing the Effectiveness of Fences We propose four complementary mechanisms through which border barriers may staunch the flow of terrorist violence: 1) denying terrorists’ ability to inflict costs, 2) amplifying the effectiveness of counterterrorist campaigns, 3) limiting illicit trafficking that funds terrorist activity, and 4) undermining the recruiting capacity of terrorist groups. First, fences and walls have long been used to prevent military penetration, and this military denial function may now be repurposed to address clandestine nonstate threats. Barriers may compel terrorist networks to reroute their activities, force them to take longer routes to reach targets, or even opt for less valuable targets. Domestic intelligence in Israel claimed that the West Bank Security Barrier was highly effective because “it forced terrorists to follow a circuitous route around the barrier in order to reach targeted Israeli cities (giving the security forces enough time to locate and arrest the terrorist cell en route)” (Morag 2005, 309). This claim was substantiated by the Palestinian Islamic Jihad leader Ramadan Abdallah Shalah, who admitted that “it limits the ability of the resistance to arrive deep within [Israeli territory] to carry out suicide bombing attacks” (Hassner and Wittenberg 2015, 180). Second, a border barrier may function as a force multiplier that facilitates offensive tactics by allowing states to shift forces elsewhere or by providing a respite from attacks so that states can plan and execute counterterrorist measures (Sterling 2009). For example, India justifies the extension of its fence with Pakistan partially on the grounds that a fortified border aids covert measures 4
We thank our reviewer for underscoring both caveats.
intended to root out militancy in Kashmir and Jammu districts. Similarly, Israeli leaders view the West Bank and Gaza barriers as a component of a larger counterterrorism plan that combines both defensive and offensive features (Morag 2005). Moreover, security barriers enable states to extend monitoring capabilities into neighboring states’ border zones. Border hinterlands may become less hospitable as terrorist sanctuaries when states combine fences with counterterror operations and when local cooperation regimes are in place where both states partake in joint missions to secure the border (Gavrilis 2008). For example, Israeli Prime Minister Netanyahu defended plans to build a massive fence along the border with Jordan by arguing that the fence would prevent ISIS operatives from spreading into the Jordan Valley. Stressing concerns that ISIS militants could extend operations into Jordan, he noted “We must be able to stop the terrorism and fundamentalism that can reach us from the east at the Jordan line and not in the suburbs of Tel Aviv” (“Netanyahu” 2014). The fence also bolsters Jordan’s ability to monitor the border zone in collaboration with Israel. In the absence of a fence, such zones can turn into sanctuaries for terrorist networks, hotbeds of violence from which frequent attacks are mounted across borders (Braithwaite and Li 2007). Third, projecting monitoring capacity becomes even more important when contiguous states are weak or failing and lack the capabilities to regulate illicit activities in peripheral regions (Jones 2012a). By closing off borders, states may hamper other types of illicit activity and thereby weaken the terrorist network. With this in mind, Iran is in the process of completely walling off its borders with Afghanistan and Pakistan and stresses that the border zone is not only a breeding ground of militancy but also serves as a prominent global drug trafficking route (Lewis 2011). Permeable and unregulated borders enable terrorist actors to surreptitiously obtain funding and resources (Andreas 2004). Hence, impediments to illicit activity are not trivial. On Turkey’s troubled southeastern borders, for example, the greatest beneficiary of organized crime activity—smuggling of drugs and contraband arms and human trafficking—has been the separatist terrorist group € Partiya Karkaren Kurdistan (Ulsever 2007). Finally, a temporary paralysis of the terrorist group may curtail its efforts at recruiting new members and additionally mute support for its cause. Perceptions of brazenness against the target government can broaden the base of support and bring in new members, especially in an environment where multiple nonstate groups compete for public support (Bloom 2004). Such limitations should therefore impose costs on terrorist activity beyond logistical limitations. As noted above, we view these three mechanisms as complementary. They may operate individually or in combination at various times. Together, however, they yield the net expectation that the construction of border fences will reduce the incidence of transnational terrorism. H1: The presence of a border barrier will reduce the probability of transnational terrorist violence from the neighbor on the building state’s territory. At the same time, numerous scholars and observers argue that the stopping power of border barriers has been overstated. For example, much of the literature on globalization and the erosion of state sovereignty contends that controlling border traffic is a quixotic effort rooted in outdated notions of sovereignty that have become
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technologically infeasible (Adler and Barnett 1998; Anderson 1997; Held et al. 1999; Rosecrance 1996; Naim 2006; Salehyan 2008). Thus, in a sense, the globalization of security literature provides a theoretical underpinning to our null hypothesis that fences will have no impact on the incidence of transnational terror. Several initial empirical studies of fencing find little or no independent impact of these barriers on transnational violence, further substantiating the expectations of the globalization of security literature (Hassner and Wittenberg 2015; Jellissen and Gotthiel 2013). Additionally, fencing advocates may have exaggerated the benefits of barriers because the fences cause a change in terrorist tactics rather than an overall reduction in the incidence of violence. For example, the Gaza fence led Hamas to switch to using long-range rockets, partially (or perhaps largely) overturning the effectiveness of the fence. Thus, organizations may substitute new tactics, which would manifest as no discernible change in the volume of attacks. Finally, some scholars even argue that fences may exacerbate the problem they seek to ameliorate (Donaldson 2005, 183–84; Sterling 2009). These scholars and policy elites contend that the imposition of a fence aggravates neighboring states. In particular, an artificial barrier may be interpreted as an aggressive land grab if the location of the border is under contention. For instance, while India contends that its fence across the Line of Control is designed to counter smuggling and militant infiltration, the Pakistani government views the fence as a bid to redraw the line according to India’s territorial ambitions. And even without prior territorial disputes, a barrier might antagonize the neighboring country. For example, while Botswana claims that the 300-mile fence on its border with Zimbabwe is intended to keep out cattle, Zimbabwe has reinterpreted Botswana’s act as an attempt to wall off Botswana from refugee flows (Donaldson 2005). Insofar as fence construction infuriates the population in neighboring states, it can inadvertently strengthen the terrorist cause as aggrieved segments of society view the barrier as a symbol of oppression and hostility. H2: The presence of a border barrier will increase the probability of terrorist violence from the neighbor on the building state’s soil.
Data and Research Design Transnational Terrorist Attacks
We code the occurrence of incidents from the International Terrorism: Attributes of Terrorist Events (ITERATE) data from 1968 to 2007 (Mickolus et al. 2007). ITERATE records terrorist attacks based on sources such as Reuters, Associated Press, United Press International, Foreign Broadcast Information Services, Daily Reports, and major US newspapers. In order to qualify as a transnational terrorist incident, an attack must reach across national boundaries either through the nationality of its perpetrators, its location, the nationality of its victims, the mechanics of resolution, or the ramifications of the incident (Mickolus et al. 2007). Our unit of analysis is the dyad year. Each dyad year identifies one state as the potential target of attack and a second state as the origin country from which the flow of terrorist violence may originate. Because our goal is to analyze the role that border barriers play in flows of transnational terrorism, we restrict our analysis to contiguous dyads. States recorded as the start location of the attack
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were designated as target states.5 To designate origin states, we harnessed information from ITERATE about groups responsible for terrorist events. Specifically, we relied on information from the Terrorist Organization Profiles (TOPS) database to identify the base countries of operation.6 Additionally, we augmented the TOPS information on terrorist bases by drawing upon a few other reliable sources: the Global Terrorism Database, Terrorism in Western Europe, Events Data, and the National Consortium for the Study of Terrorism and Responses to Terrorism (LaFree 2010).7 If a terrorist attack occurred against a target state in a given year from a group operating in the origin state, we coded the incident variable as 1, and we coded the case 0 in the absence of an attack.8 For example, Al Zulfiqar, a terrorist group operating in Afghanistan and India, carried out an attack in the United Kingdom in 1979. Our coding procedures count this event as an attack from Afghanistan and India against the United Kingdom, yielding two directed dyad cases for 1979. This coding procedure also permits us to include attacks where terrorist groups straddle state boundaries. Again, to provide an example, Lashkar-e-Tayyiba is networked across India, Pakistan, and Kashmir. Because we exclude nonstate territories from the analysis, Kashmir is not accounted for in the main analysis. However, an attack attributed to this group in a given year against India is coded as an attack originating from Pakistan against India. Our final data set includes a total of 18,845 dyad years, with 449 dyadic incidents. Specifically, we identify 132 different targets of transnational terrorist attacks between 1968 and 2007. Contiguous dyads with the highest volume of attacks during this time span were the United Kingdom–Ireland (twenty-two incidents), France–Spain (nineteen incidents), Israel–Lebanon (nineteen incidents), Lebanon-Syria (fourteen incidents), Venezuela– Colombia (fourteen incidents), and Turkey–Iraq (thirteen incidents). Fenced Interstate Borders
We began our compilation of systematic and comprehensive border fencing data with the International 5 Young and Findley (2011) argue that both nationality- and location-based specifications are appropriate for studying transnational terrorism in a directed dyadic framework. In the original ITERATE data, for the 1968–2007 time span, 386 of 719 transnational incidents in a given state involved citizens of that state. In other words, there is a 53 percent overlap in location and nationality-based operationalizations when all three nationalities recorded by ITERATE are taken into account. 6 TOPS was originally maintained by the Memorial Institute for the Prevention of Terrorism; it can now be accessed at http://www.start.umd. edu/tops/. 7 It is standard among terrorism scholars to code the origin according to the nationality of perpetrators, as recorded by ITERATE. However, we believe that coding according to bases of operation is better suited to capturing our theoretical propositions. Most importantly, our central focus is on the impact of fences, which requires that we focus on the flow of violence across borders rather than the nationality of the perpetrators. More generally, the nationalitybased indicator reveals information on the smaller cadre of terrorist operatives executing the particular attack. However, the causes of terrorist violence often far precede the specific national identities of the attackers, and their nationalities of origin may have little to do with the logistical planning, training, and execution of the attack. Thus we contend that identifying the states that provide training and logistical support for terrorist activity (whether willingly or not) is a useful way to model the link between state characteristics and the flow of transnational terrorism. 8 As described below, we also analyzed the log of the total number of attacks in each dyad-year.
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Do Good Fences Make Good Neighbors?
Boundaries Research Unit’s (IBRU’s) online archives on international borders at the University of Durham. We sought to identify all interstate borders with barriers, to determine which state in the dyad initiated fortification of the border, and to code the initial year of construction. We performed a keyword search for “walls,” “fences,” “barriers,” and “fortifications” using IBRU’s Boundary & Security Bulletin in order to compile our list.9 While their published bulletin runs up to 2001, the IBRU’s online search also captures current news on borders. We supplemented our data from the IBRU with boundary-specific news from Borderbase and Wikipedia’s list of separation barriers.10 Additionally, we cross-checked cases using general internet searches.11 Finally, we referred to the cases identified by Jones (2012a) and Jellissen and Gottheil (2013) to ensure the keyword search had not missed cases. Notably, our operationalization of fence construction is directional in that it distinguishes between the building state and the neighbor. That is, our measure takes into account who imposed a fence against whom. For example, the US-Mexico dyad is coded as 1 for the years in which the United States has a fence in place, but the Mexico-US dyad remains coded as unfenced for these years because Mexico did not construct a fence to prevent flow from the United States. Our indicator for fences takes the value of 1 if a physical barrier was present in a given year and 0 otherwise. For example, Bulgaria installed a fence against Turkey in 1946 but dismantled the fence in 1989. Thus, we would code the Bulgaria versus Turkey border with a value of 1 from 1946 to 1989, and a value of 0 from 1990 onward. We code fences based upon the date when construction begins because we found more consistent and reliable data on the initiation of the fencing projects than on their completion. We understand that fence construction projects may languish for several years before work on the wall is complete. To illustrate, Iran began construction of a fence along its border with Afghanistan in the late 1990s. The initial fence was completed in 2000 but further fencing resumed in 2006, and as of 2015 construction was still ongoing (Hassner and Wittenberg 2015).12 However, we expect that a fence will exert some impact even before construction is complete. Moreover, our coding procedure provides us with a conservative estimate of the impact of barriers. In total, states began construction on sixty-one physical borders barriers between 1900 and 2013.13 States began construction on nearly three-quarters of these barriers (forty-five of sixty-one) since the end of the Cold War in 1989. Table 1 displays the list of border fences from 1900 9
https://www.dur.ac.uk/ibru/publications/bulletin/. http://en.wikipedia.org/wiki/Separation_barrier, accessed July 5, 2014; July 22, 2015. http://nicolette.dk/borderbase, accessed May 20, 2011; July 20, 2014. 11 A number of additional online pages proved informative. Among these were a general commentary on the practice of fencing: http://subtopia.blog spot.co.uk/2007/04/border-to-border-wall-to-wall-fence-to.html; the GreekTurkish border: http://www.novinite.com/view_news.php?id¼146114; the Pakistan-Afghanistan case: http://www.guardian.co.uk/world/2005/sep/14/ pakistan.afghanistan; and Russia’s borders: http://geocurrents.info/geopoli tics/international-land-borders-hard-and-soft. 12 Also see http://www.irantracker.org/analysis/iranian-influence-afghani stan-recent-developments. 13 Including political units without sovereign status yields a total of fortyeight fences over this period. One directed dyad contains two cases: Spain fenced its border with Morocco at two frontier cities, Ceuta and Melilla, to stem illegal migration. Because our directed-dyadic framework drops duplicate cases, we only take into account the earlier of these constructions, the Ceuta fence, constructed in 1993. 10
to 2013. While our data on fences spans more than a century, the ITERATE data set only includes data on transnational terrorist attacks between 1968 and 2007. Thus Table 1 identifies the fences that are included in our analysis of the impact of border fencing on transnational terrorism by displaying them in italics. We identify thirty-five fences (including the Melilla fence) between 1968 and 2007.14 Finally, at the bottom of the table, we list fences erected after 2007, which are excluded from the current analysis. We identify twelve new fences. Our analysis also excludes fences among dyads that do not have direct land contiguity: the US-Cuba dyad, for example, where the fence refers to the wall across Guantanamo Bay. Importantly, our analysis also excludes three fences across territorial boundaries in which one of the parties is not a sovereign state: IsraelGaza, Israel-West Bank, and Spain-Western Sahara.15
Results We begin with a simple description of fences and the incidence of transnational terrorist activity between contiguous states. Table 2 displays the frequency of terrorist attacks across fenced and unfenced borders for each dyad year. As noted above, our analysis includes 18,845 border-years between 1968 and 2007, and we observe 449 transnational terrorist attacks. Transnational terrorist attacks occurred in 2.34 percent of the unfenced borderyears, while they occurred in 3.45 percent of the fenced border-years. Thus fencing is associated with about a 1.1 percent increase in the likelihood of an attack per borderyear, which falls short of traditional standards of statistical significance (p < .111). This increase may seem rather modest but is substantial in the context of the relative rarity of terrorist attacks. A 1.1 percent increase in the probability of an attack, for instance, translates into nearly a 50 percent increase in the relative risk of an incident. Moreover, this 50 percent increase in the relative risk of an attack recurs for each year that the border remains fenced. Thus at first blush our data supports our second hypothesis that fencing is an ineffective defense against terrorism and may even exacerbate the problem. Of course, terrorist attacks are caused by many factors other than the presence of fencing, and many—if not most—of these factors may be correlated with the presence of a fence. The standard method of coping with this problem—in the absence of the ability to conduct a randomized experiment—is to include various control variables in a multivariate model of terrorist attacks. Consequently, we apply rare event logit analysis (King and Zeng 2001) of transnational terrorist attacks between contiguous states that includes the presence of a fence, along with control variables that the literature on transnational terrorism frequently employs (Young and Findley 2011; Gelpi and Avdan 2015). These logit results (displayed in Table A of the supplementary file) continue to suggest a positive association between fences and terrorist attacks. Moreover, this analysis indicates that the positive association is statistically significant. 14 However, our analysis does utilize some information on earlier fences. In particular, our analyses account for fences constructed prior to 1968 even if they were dismantled prior to the period under examination. 15 We record the walls between territorial units in our list. Unfortunately, however, due to data unavailability on all our covariates for nonstate territorial units, these cases drop out of our analysis. Because Israel’s walls on the West Bank and Gaza elicit publicity and controversy, we draw upon these cases as anecdotal examples. However, we note that our empirical analysis cannot speak specifically to the Israel-Palestine conflict.
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Table 1. List of border fences Builder Early twentieth century fences Norway Finland Russian Federation Russia (Soviet Union) Russia (Soviet Union) Russia (Soviet Union) France Greece Vietnam German Democratic Rep. Czechoslovakia Czechoslovakia Bulgaria Russia (Soviet Union) Korea, Rep. Algeria (French) Algeria (French) Zimbabwe Israel Israel South Africa Nigeria India South Africa Kuwait Russian Federation Russian Federation Russian Federation Russian Federation India Spain Botswana Spain Uzbekistan Iran, Islamic Rep. Israel Thailand Turkmenistan Turkmenistan Uzbekistan India Zimbabwe Lithuania Pakistan United States China Jordan Kazakhstan Saudi Arabia Saudi Arabia Saudi Arabia United Arab Emirates United Arab Emirates Recent fences Builder Egypt Myanmar Saudi Arabia Saudi Arabia Saudi Arabia Kazakhstan Azerbaijan Greece
Neighbor
Year built
Year dismantled
Sweden Russia (Soviet Union) Estonia Latvia Lithuania Poland Germany Bulgaria China Rep. of Germany Austria Rep. of Germany Turkey Finland Korea, Dem. Rep. Morocco Tunisia Zambia Egypt Syria Mozambique Cameroon Bangladesh Swaziland Iraq China Korea, Dem. Rep. Mongolia Norway Pakistan Morocco (Ceuta) Namibia Morocco (Melilla) Kyrgyz Republic Afghanistan Lebanon Malaysia Kazakhstan Uzbekistan Afghanistan Myanmar Botswana Belarus Afghanistan Mexico Korea, Dem. Rep. Iraq Uzbekistan Iraq Jordan Kuwait Oman Saudi Arabia
1901 1920 1922 1922 1922 1922 1930 1936 1946 1947 1947 1947 1947 1947 1953 1957 1957 1966 1968 1973 1975 1981 1986 1986 1991 1991 1991 1991 1991 1992 1993 1997 1998 1999 2000 2000 2001 2001 2001 2001 2003 2003 2005 2005 2005 2006 2006 2006 2006 2007 2007 2007 2007
1920 1939 1939 1939 1939 1939 1940 1941 1989 1989 1989 1989 1989 1989
Neighbor Gaza Bangladesh Oman Qatar United Arab Emirates Kyrgyz Republic Armenia Turkey
2009 2009 2009 2009 2009 2010 2011 2011
1962 1962 1973
(Continued)
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Do Good Fences Make Good Neighbors? Table 1. (continued)
Builder Israel South Africa Turkey Uzbekistan
Neighbor
Year built
Jordan Lesotho Syria Tajikistan
2011 2013 2013 2013
Year dismantled
Note: The cases in italics are omitted from the analysis. While ITERATE provides data on these cases, data on other covariates are missing.
Table 2. Fenced borders and terrorist incidents among contiguous dyads
Terrorist Incident
Fenced Border
No
Yes
Total
No (No.) Column Pct. (%) Yes (No.) Column Pct. (%) Total (No.)
17,983 97.66 432 2.34 18,415
475 96.55 17 3.45 492
18,458 449 18,907
Note: Pearson Chi-squared (1 d.f.) ¼ 2.54; p < .111.
While logit models are a standard way to account for spurious correlations in observational data, the assumptions inherent in this approach leave these models vulnerable to a number of threats to valid causal inference. For example, multivariate models restrict the effects of confounding variables to be linear—except as specified ex ante by the analyst (King and Zeng 2006). Moreover, the coefficients estimated from these models can be based on comparisons of highly dissimilar cases and extrapolations outside the observed range of data (King and Zeng 2007). Statistical matching is an alternative method for estimating causal effects from observational data (Ho et al. 2007). Matching seeks to evaluate the treatment effects of variables by approximating the design of randomized experiments. Specifically, matching algorithms identify a set of control cases that are as similar as possible to the treated cases on a set of relevant covariates. By creating treatment and control groups that are balanced across a set of covariates, the analyst can account for any confounding effects of the covariates without any restrictive assumptions about functional form. Statistical matching can produce substantially more robust causal inferences regarding treatment effects than standard linear models, especially when many treated and untreated cases may be highly dissimilar on a variety of dimensions (King and Zeng 2006, 2007) and when the “curse of dimensionality” makes the estimation of multivariate models difficult (De Marchi 2005). Both of these conditions apply to the study of transnational terrorism, making this approach especially applicable to studying the “treatment” effect of border fencing. The average treatment effect (ATE) is the average difference between predicted and observed values for the treatment and control groups. The average treatment effect on the treated (ATT) estimates treatment effects by only examining the treatment effects for the treated group. In the event that the treated (fenced) and control groups are very different from one another in the full population, ATT may provide a more robust estimate of causal inference that does not rely on the extrapolation of treatment effects outside the observed range of variation on the control variables for the treated groups. Of course, statistical matching is not a panacea for extracting causal inferences from observational data. In particular,
matching cannot account for unobserved confounding variables and it cannot account for simultaneity bias. Fortunately, this latter type of bias seems relatively unlikely to affect our analysis. Specifically, a terrorist attack in a particular year is unlikely to result in the presence of a barrier in that same year since barrier construction is generally a substantial undertaking that requires planning and time for execution. Thus while terrorist attacks undoubtedly cause the construction of fences, we can account for this process by controlling for attacks in prior years. One of the greatest challenges for the statistical matching approach to causal inference is that we lack a method for selecting the “optimal” matching of treated and control cases given a particular set of confounding covariates. Instead, analysts must evaluate the results of various matching algorithms in order to determine which method will provide them with the highest degree of balance between treated and control cases. In our analysis of transnational terrorism, we compare two of the most commonly used algorithms: propensity score matching and nearest neighbor matching. Propensity score matching uses the set of confounding covariates to estimate a model of the propensity to receive treatment. The algorithm then matches each treated case to one or more control cases with the most similar propensity to receive treatment (Rosenbaum and Rubin 1985). To ensure that dissimilar cases are not matched, we specify a “caliper” that sets a maximum difference in propensity scores for matched cases. We drop treated cases with no sufficiently similar control cases from the analysis. Nearest neighbor matching, on the other hand, estimates a propensity score but then matches the treated cases to controls based on minimizing the distance between cases on the propensity score and each of the individual covariates in the model (Caliendo and Kopeinig 2008). As with propensity score matching, we are able to specify a maximum distance caliper to prevent matches between dissimilar cases. The advantage of nearest neighbor matching is that the algorithm directly accounts for the correlation among specific covariates rather than focusing solely on the overall propensity to be treated. Finally, to account for any residual bias, we regress the matched cases on the matching variables once again to create counterfactual predicted values for the treatment and control groups. We select confounding covariates based on their prevalence in existing directed dyadic models of transnational terrorism (Young and Findley 2011; Gelpi and Avdan 2015). In the interest of brevity, we provide only a short discussion of the covariates included in our model.16 16 One additional covariate that we account for is the history of fencing on the border. Our data set does not include any borders that are referenced after a fence is dismantled. Since a dismantled fence perfectly predicts that a border will not currently be treated, we drop all dyad-years with dismantled fences. This procedure amounts to perfect matching on a lack of dismantled fencing and prevents us from conflating never-fenced dyad-years and previously fenced dyad-years as control cases.
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C H RI S T OP H E R F. G E L P I
21
History of Terrorism: States generally construct fences in response to a history of terrorist attacks. This variable represents perhaps the most important confounding variable when estimating the causal impact of fencing. As a result, we account for the annual sum of terrorist attacks across an interstate border lagged by one year. Insofar as the past volume of terrorism correlates with future attacks, including this variable also addresses temporal dependence within the dyad.17 In an alternative specification (displayed in the supplementary docu ment), we also added peace years—defined as the number of years elapsed since the most recent attack in the dyad—as a potentially confounding covariate. This specification does not significantly alter the estimated impact of fences. Disputed Border: Another important confounding variable in assessing the causal impact of border fencing is the presence of an interstate dispute regarding the border in question. An interstate border dispute may both cause states to build barriers and cause terrorist groups to engage in attacks across the border. We code for the presence of a disputed border based on Simmons’ (2005) update of Huth’s (1996) measure. Huth codes territorial disputes as present when a state: 1) expresses disagreement over the location of the border, 2) challenges the sovereignty of another state over some portion of territory within the border, 3) seizes control over a part of the border and refuses to withdraw, or 4) does not recognize the independence of another country (for example, a colonial territory). Huth considers a border dispute resolved upon the formal recognition of the legitimacy of the border arrangement (even if there is no formal treaty). Interstate Militarized Disputes: As noted above, states may erect fences to address both interstate and transnational security threats. Moreover, interstate militarized activity may provoke transnational terrorist responses—especially if there is a substantial power disparity across the border in question. We code for the presence of an interstate militarized dispute (MID) based on the Correlates of War (COW) MIDs data set (version 4.0) (Palmer et al. 2015). Alliance: Plu¨mper and Neumayer (2010) demonstrate that terrorists are more likely to attack powerful allies of home governments. We measure the impact of alliance ties based on the Correlates of War data set on alliances. Specifically, we record a value of 1 if the target and origin states have a COW alliance of any kind (defense pact, entente, or neutrality pact). Relative Power: Since terrorism is often a weapon wielded by weak states against stronger enemies (Fortna 2010, 9), powerful states are likely to experience a higher volume of attacks. Terrorist groups have incentives to attack powerful states for the publicity gains these incidents afford (Plu¨mper and Neumayer 2010). We account for the military capabilities of the target and origin states based on the Composite Index of National Capabilities from the Correlates of War (COW) data set on national capabilities. We constructed all variables based on COW data with the EUGene software program (Bennett and Stam 2000). Population: Populous states are likely to be more attractive targets for terrorist attacks, simply by virtue of their
size. In line with previous scholarship and to guard against undue influence from outliers, we take the natural log of the state’s population. Data for population comes from the World Bank’s World Development Indicators database (World Bank 2008). Democracy: Despite ongoing debate around the nature of the relationship between regime type and terrorism, the more popular view leads us to expect democratic regimes to attract terrorism (Chenoweth 2010; Gassebner and Luechinger 2011; Li 2005; Wade and Reiter 2007). There is also evidence that nondemocratic countries are more likely to be sources of transnational terrorism (Blomberg and Hess 2008; Young and Findley 2011). Accordingly, we include the Polity IV democracy score for both the target and origin state. We measure the democracy of both target and base states with scores from the Polity IV Project (Marshall and Jaggers 2000). Following standard practice for the use of Polity data, we measure the overall level of democracy in both target and base states by subtracting the autocracy score from the democracy score. Wealth: If terrorism is a weapon of the weak, economically advanced states are more likely to be targets of terrorism (Krueger and Laitin 2008). Furthermore, democracy and wealth might, in concert, incentivize terrorism (Gassebner and Luechinger 2011). We measure the wealth of the target state as the natural log of the gross domestic product (GDP) of the target state.18 We rely on the World Bank’s database for annual estimates of GDP. We also include the GDP per capita of the origin state. This indicator not only taps into the impact of poverty in generating outflows of terrorism but also serves as a proxy for the monitoring capacity of the origin state. Colonial Ties: The colonial experience may provide fodder for holdover grievances, increasing the likelihood of terrorist violence. Moreover, a colonial heritage may serve as an indicator of cultural proximity. We measure colonial history with a dummy variable that is coded 1 if any of the target country-based dyads share a colonial past (Alesina and Dollar 2000). Ethnic Ties: Ethnically homogeneous states experience terrorism less frequently, while ethnic fractionalization is associated with terrorist violence (Basuchoudhary and Shughart 2010). We rely on Huth and Allee’s (2002) dichotomous measure for ethnic ties in a dyad and update this measure to 2007. Our measure of ethnic ties equals 1 if the dyad possesses ethnic conationals in the target country. Civilizational Ties: In the wake of the collapse of the Cold War, Samuel Huntington (1993) formulated the “Clash of Civilizations” hypothesis about military conflict in the post-Cold War world. While Huntington (1993) does not clearly articulate the underlying causal mechanism, such a clash might plausibly be motivated by negative out-group stereotyping. These negative attitudes toward civilizational “others” might result both in transnational violence and a greater prevalence in border barriers. While the existing empirical literature suggests no empirical link between civilizational differences and interstate conflict (Chiozza 2002; Russett, Oneal, and Cox 2000), it seems possible that these cultural divides might be more likely to fuel transnational violence at the societal level. Thus we include a dummy variable indicating when
17 In order to address spatial dependence, we estimate a model that forces exact matching on the identities of the target and origin states. This is analogous to estimating a model with fixed effects. Our results remain unchanged.
18 The matching model we display here substitutes logged GDP per capita of the target state for the logged GDP; this specification obtains better balance and has more cases with common support.
22
Do Good Fences Make Good Neighbors? Propensity score
Nearest Neighbor
20
17.1 15
13.5 11.2 9.3
9.1
10
8.8
7.3 5.8
4.7
5
4.5
Percent Sample Bias
2.2 0
0
0.8
0
0.8
0 -0.8
4.2 2.9 0.4
0
0
0
-1.9
-5
-7.5
-10
-15
-20
-19.3
-25
Propensity Score: Mean Bias = 7.4%; Median Bias = 7.3%; p
