Economic sanctions and the duration of civil conflicts Author(s): Abel EscribĂ -Folch Source: Journal of Peace Research , march 2010, Vol. 47, No. 2 (march 2010), pp. 129-141 Published by: Sage Publications, Ltd. Stable URL: https://www.jstor.org/stable/25654550 JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at https://about.jstor.org/terms Sage Publications, Ltd. is collaborating with JSTOR to digitize, preserve and extend access to Journal of Peace Research This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms Research article journal of RESEARC II Journal of Peace Research 47(2) 129-141 Economic sanctions and the duration or ?71,6 Aud;or EUp, (2) that is, if the utility of a settlement exceeds the expe of fighting; or unless the expected costs of fighting e overall expected utility of victory, so one party gives u and accepts defeat: peUv + {l-pe)UD 0. Therefore, according to our setting, this makes the right-hand side in (2) decrease and the right-hand side in (3) increase, making war termination more likely. For instance, a trade embargo may decrease the exports of goods, thereby affecting the resources available to the government. As for the rebel side, sanctions are usually aimed at limiting the funding that some of these groups obtain through contraband. For example, it is argued that the Lancas ter House agreement (1979) that put an end to the conflict in Rhodesia was in part made possible by the extensive UN sanc tions, imposed in 1966, that forbade trade (the insuring of commodities or goods, exports and imports from Rhodesia) as well as financial exchange with the target country, and so weakened Ian Smith's government and forces. The diamond embargo recently imposed on Ivory Coast (2005) is intended to reduce the revenues raised from export and production by the rebels of the New Forces (Wallensteen, Eriksson & Strandow, 2006). Diamond sanctions have been imposed against UNITA in Angola (along with petroleum sanctions), Sierra Leone and Liberia. It is argued that the 2001 diamond sanctions on Liberia were effective in reducing government revenues and, consequently shortening the conflict (Wallens teen, Eriksson & Strandow, 2006). If properly enforced, all of them are principally designed to cut to some extent the flow of monetary and military resources into the hands of the con tending parties (especially the rebels). So let us frame the following guiding hypotheses, relying on both the arguments against the usefulness of sanctions and on the three basic mechanisms just mentioned above in favour of sanctions' role in shortening conflicts: Hla: Sanctions, as a sort of external intervention, are negatively related to the probability of war end. lb: The duration of civil war is decreased by the imposition of sanctions. The debate over sanctions does not only revolve around whether they are effective or not. The apparent reliance for sanctions' success on the costs they impose on targets com pelled governments and scholars to discuss and assess the type of cost that should be inflicted, and on what actor or group those costs should be concentrated in order to maximize effec tiveness. In this case, comprehensive sanctions must be distin guished from the so-called smart - or targeted - sanctions. The former are intended to maximize general costs on target. Advo cates of smart sanctions assert that instead, targeted measures maximize the cost on the specific group whose obedience is sought while avoiding causing the general population to suffer. Kaempfer & Lowenberg state that 'the sanctions which are most likely to precipitate the desired political change in the tar get country are those which concentrate income losses on groups benefiting from the target government's policy' (1988: 792). For instance, Dashti-Gibson, Davis & Radcliff (1997) find that when senders seek to achieve policy changes, the imposition of financial sanctions is an important determi nant of success. On the contrary, Gershenson (2002) formally shows that it is the strength of sanctions that affects the alloca tion of resources to conflict and the utility of the contending parties. In fact, the existing evidence suggests that comprehen sive sanctions are more effective (Cortright & Lopez, 2002), This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms Escriba-Folch 133 and many studies have identified th imposed on the target, the higher th coercion episodes (Hufbauer, Sch Hufbauer et ah, 2007; Dashti-Gibs 1997; Drury, 1998; Nooruddin, 2002). partial evidence on some specific types to support the more pessimistic view a tiveness. For instance, following a com some UN arms embargoes, such meas largely irrelevant (Tierney, 2005). The failure include the exemption of Secu from the restrictions, the incentives t weak enforcement, late application a power asymmetries between parti 2002; Tierney, 2005). In clear contras tends that arms embargoes, given th actors' military power, should be the m geted measure - if properly impleme likelihood of conflict resolution by, a the convergence of beliefs over each p offers quantitative evidence of the p tions on two cases, Liberia and Ivory I attempt to evaluate the relationship b of measures - such as total economic e goes, trade restrictions and aid cuts (m in sanction episodes) - and the durat above statements are summarized in th H2: Sanctions that maximize costs on the goes) should decrease the duration of civ Another way of studying and classify focusing on the senders. Internation multilateral or unilateral or, more sp either by international institutions or small coalition of them). Some eviden view that unilateral sanctions tend to multilateral ones (Drezner, 1999; Hufb 1990; Kaempfer & Lowenberg, 1999), p above-mentioned problems in targeted embargoes - namely, free-riding and en Nevertheless, a more recent study, re finds that multilateral sanctions have a tive (Bapat & Morgan, 2007).4 Drezne possibility that the key variable is no multilateral or not but whether those m imposed by an international organiza backsliding and ensures the maintenan to cooperate with the sanctioning col increases the senders' capability of i 4 Most of the analyses of sanction duration an Hufbauer, Schott & Elliott's (1990) dataset. 5 Bapat & Morgan (2007) also find that the succe if they are conducted through an international in on the target countr cause of the success o Apart from this cap ment of an internat has other implicatio a signal that an outsi the terms of a pote been true of some which have been fol peacekeeping operat the peace agreement the UNOMSIL in S dia. The reduction of of a settlement (BUs failure to fulfil the hold. In the light o hypothesize: H3: Sanctions that ar tional organization s internal conflict dur Furthermore, I will sanction senders on t victory vs. negotiat tially assess the role peace. The same will Data and meth In order to answer on civil wars cover on intrastate conf Laitin (2003), Hum and include 87 civil Since the data have better control for the is under economic s With regard to the d analysis I use a binar ends in a given yea coded 1 if the war e year. For the second used by Humphrey flict termination an is ongoing in that y 6 The list constructed by meet the following prim agents of the state and o least 1,000 over its cours 100 were killed on both s (2003). 7 Humphreys compiled it from Walter (2002). This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms 134 journal ?/Peace Research 47(2) military means, and 2 if the war ends through a negotiated settlement. Data on sanction episodes are taken from Marinov's (2005) dataset, which recast Hufbauer, Schott & Elliott's (1990) data set in country-year format and updated it. These data have been contrasted and widened using the Threat and Imposition of Sanctions (TIES henceforth) dataset, which collected data on threats and sanction implementation during the period 1971-2000 (Morgan, Krustev & Bapat, 2006). Hufbauer, Schott & Elliott's (1990) dataset covers 116 cases of sanctions (between 1914 and 1990), whereas the TIES dataset includes 529 instances of sanctions imposition (Bapat & Morgan, 2007). Moreover, the TIES dataset classifies episodes accord ing the type of measure applied. Thus, I have constructed two more variables: The first, 'Institutional sanction', takes the value 0 if no sanction is imposed, 1 if a country is under sanc tions not imposed by an international institution, and 2 if a country is under sanctions imposed by an international insti tution in a given year. The second variable distinguishes between the main types of measure adopted: total economic embargoes, multilateral arms embargoes (UN, EU and other multilateral embargoes),8 restrictions on imports and exports, the termination of foreign aid and other measures (such as asset freezes, travel bans, suspension of agreements and block ades). Finally, I have also constructed a variable that distin guishes between threats of sanctions and imposed sanctions. As mentioned above, the analyses on sanctions effectiveness may suffer from selection bias, which lies in the fact that threats of sanctions might be more successful than imposed ones but they are generally not observed. So, following Drez ner (2003), to test the selection argument, we need to study those cases in which sanctions are threatened but not imple mented. Fortunately, the new TIES data set contains informa tion on threat episodes that did not end up with the imposition of sanctions. Therefore, our variable 'sanction threat' is coded 0 if no threat or sanction is applied, 1 if a coun try is threatened but eventually sanctions are not imposed, and 2 if sanctions are imposed. We consider a number of control variables that refer to commonly identified factors included in recent studies on civil war duration. Geographical characteristics of the country are argued to influence war viability and actors' capacity (DeRouen & Sobek, 2004; Buhaug, Gates & Lujala, 2005). Both the per centage of the terrain that is mountainous and forested and the number of bordering states are frequently argued to increase the ability of the rebels to resist. As for the government's capac ity, we include the size of the army (per 1,000 inhabitants), 8 The TIES dataset does not include a category for arms embargoes, so given the policy relevance of international arms embargoes, I have constructed a dummy for arms embargoes imposed by international organizations. Data have been taken from Fruchart et al. (2007) and the SIPRI website: www.sipri.org/contents/armstrad/embargoes.html. 9 These variables have all been compiled from DeRouen & Sobek (2004). obtained by dividing the size of the army by the total population.9 Some researchers point to the potential polarizing effect of ethnic fractionalization (Montalvo & Reynal-Querol, 2007), and a high degree of fractionalization may hamper cooperation on the rebel side. Collier, Hoeffler & S?derbom (2004) and Elbadawi & Sambanis (2000) find a non-linear relationship between ethnic diversity and war duration. Therefore, I con trol for the degree of ethnic diversity and this potential curvi linear pattern using Fearon's (2003) variable, which measures the probability that two randomly selected persons from a given country will not belong to the same ethnic group. On the socio-economic side, I include the logarithm of the country's population and per capita GDP. The presence of natural resources and primary commodities has been shown to have an effect on both the onset and the duration of civil war (Collier, Hoeffler & S?derbom, 2004; Ross, 2004). I use several measures: first, 'mineral resources', which takes the value 1 if the average ratio of ore and mineral exports in any year for which a country has data exceeded 50% of total merchandise exports, and 0 otherwise.10 The second variable, 'oil-producing country', is coded 1 for those country-years in which fuel exports exceeded one-third of total export revenues, and 0 otherwise.11 I have also used the variables on oil produc tion and reserves and diamond production (expressed both in total production and in per capita terms) developed by Humphreys (2005). To capture the possibility of financing through contraband, the dummy variable constructed by Fearon is included. It is coded 1 if there is 'evidence of major reliance by the rebels on income from production or trafficking in contraband' (2004: 284), and 0 otherwise. As stressed above, Pape (1997, 1998) argues that sanctions do not work, since any policy effect observed so far is actually due to the use of force that sometimes accompanies sanctions. To control for this possibility, I include the dummy variable 'military intervention', which is coded 1 for each country year in which some sort of military intervention, as categorized by Regan (2000), takes place. Other relevant controls are: the logarithm of the average number of deaths per year as compiled by Fearon (2004). And, also compiled from Fearon (2004), some dummies capturing the type of ongoing civil war are considered. The first is 'ethnic war', which takes value 1 if the ongoing war is of an ethnic nature.12 The second dummy takes value 1 if the war is clas sified as a 'sons of the soil' conflict. These are wars in which the state is dominated by an ethnic group facing population pressure. When members of this group migrate to less populated areas, often with the support of the state, the ethnic 10 Variable compiled from Gandhi & Przeworski (2006). 11 Compiled from Fearon & Laitin (2003). 12 We have coded as 1 only those cases with value 3, excluding those considered by Fearon to be mixed or ambiguous. This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms Escriba-Folch_135 10 20 30 40~ Years in progress -No sanctions Under sanctions I Figure 1. Proportion of civil wars ongoing by year minorities living in those regions often take up arms against the migrants and the state. The methodology employed consists basically in logistical regressions, both binary, to analyze the likelihood of conflict ter mination, and multinomial, to analyse the mode in which the war ends (military victory or negotiated settlement). As usual when duration is analysed using discrete-time data, the potential time dependence in the data is corrected by including natural cubic splines on the right-hand side of the equation to be esti mated (Beck, Katz & Tucker, 1998). Errors have been clustered. Analyses and results Civil war termination and economic sanctions I begin by enquiring whether sanctions have any effect on the length of intrastate conflicts in a simple manner. Figure 1 portrays, using the non-parametric Kaplan?Meier estimate, the survival curves of those conflicts under sanctions versus those not under sanctions. The differences between the groups are substantial and suggest a significant correlation between the two variables. As the plot reveals, the proportion of ongoing wars is clearly smaller for those cases targeted by international economic sanctions.13 This preliminary evidence suggests that international sanctions are related to the decline of the survival rate of intrastate wars. Moving on to the multivariate analyses, Table I reports the estimated coefficients of the binary logistic regressions used to estimate the impact of economic sanctions with the aim of testing our first hypotheses. In Columns 1-3, I include the sanctions dummy, while in Columns 4 and 5, I include the variable 'sanctions duration', which is a measure that 13 The variable 'sanction' includes only sanctions actually imposed, not threats. 1 Therefore, in this case, sanctions are not considered just as a constant variable, but as a steadily increasing value over time, as it is assumed that the higher the number of years a given country is targeted, the higher are the accumulated costs. See Collier, Hoeffler & S?derbom (2004) for a similar methodology applied to outside interventions. cumulates the number of years a country has been under sanc tions in a given year.14 The results serve to reject Hypothesis la and confirm Hypothesis lb: both sanctions and their dura tion (in years) are significantly associated with a higher likeli hood of civil war termination. These results are robust to the inclusion of the variable 'military intervention' and to the use of alternative measures of natural resource availability. Note that the effect of a military intervention is negative, as previous research had already indicated, but not significant. Being under sanctions involves an increase of 0.044 in the probabil ity of conflict termination (according to the estimates in Column 1), while a one-unit change in the time a country has been targeted by sanctions increases the probability of war termination by 0.0041 points (Column 4).15 The computed probability of civil war termination when a country has been just one year under coercive sanctions is 0.0384, whereas the probability of termination for a country that has been targeted for five years is 0.0572. Column 6 includes the distinction between sanction threats and effectively imposed sanctions. The number of observations is reduced in this case, as the sample is restricted to the TIES data, so it starts in 1971. Threats that did not end with the imposition of sanctions have an important positive effect on the likelihood of conflict end, but the relationship is not statistically significant, probably due to the reduced number of such instances in our sample. I now move on to examine the effects of different types of sanctions. In the first column of Table II, the estimates use the categorization of sanctions according to the kind of measure adopted against the target. This model is restricted to the TIES sample (from 1971), so the number of observations is lower. The results tend to confirm Hypothesis 2 and make clear that it is basically comprehensive sanctions directed towards cut ting the total flow of funds to the rival parties that have signif icant and negative effects on the duration of intrastate conflicts. The examination of the marginal effects of each of the types included in the regression reveals that comprehensive sanctions (total embargoes) are the most effective measure in shortening civil wars, followed by trade restrictions (of exports and imports), which include commodity sanctions.16 Concre tely, the increases in the probability of war termination when those dummies change from 0 to 1 are 0.30 and 0.075, respec tively. Multilateral arms embargoes do not appear to have any significant effect on civil war duration. With regard to whether sanctions are imposed by an inter national institution, the results in Column 2 reveal that, when no further distinction is introduced in the dependent variable, the impacts of both kinds of sanctions are almost identical in size. The changes in the likelihood of war termination are 0.050 and 0.057 when these two dummy variables increase 15 The rest of the variables are held constant at their means. 16 Trade restrictions are almost significant; the />-value of this variable is just 0.105. This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms 136 journal ?/Peace Research 47(2) Table I. Sanctions and civil war duration (logistic regression) Event: Civil war end = 1 Independent variables (1) (2) (3) (4) (5) (6) Intercept Mountains Forests Log population Log GDP per capita Mineral exporting Oil exporting Oil production Diamond production Ethnic fractionalization (Ethnic fractionalization)2 Contraband Number of borders Army size (log) Deaths/year Ethnic war Sons of soil war Military intervention Economic sanctions Sanction duration Threat Imposed sanction Duration splines Observations Log-pseudolikelihood Pseudo R-squared 2.32 (1.86) -0.007 (0.006) -0.001 (0.009) -0.119 (0.231) -0.546** (0.250) 2.13*** (0.789) 0.285 (0.419) 7.09*** (2.52) -8.02*** (2.65) -1.65*** (0.527) -0.066 (0.078) -0.353* (0.184) 4.13e-06* (2.18e-06) 0.563 (0.470) _2 \ 1 *** (0.730) 0.847*** (0.293) yes 663 -151.90 0.1309 2.59 (1.65) -0.003 (0.007) 0.006 (0.009) -0.070 (0.236) -0.635** (0.287) 6.32 (6.33) 1.67** (0.845) 5.45* (2.94) -6.28** (3.14) -1.44** (0.583) -0.094 (0.085) -0.338* (0.195) 3.93e-06* (2.17e-06) 0.540 (0.463) -2.08*** (0.740) 0.885*** (0.291) yes 619 -148.01 0.1232 2.23 (2.15) -0.009 (0.007) 0.003 (0.011) -0.202 (0.263) -0.398 (0.292) 2.73** (1.19) 0.245 (0.436) 6.44* (3.40) 7.42** (3.36) -1.68*** (0.614) -0.033 (0.082) -0.393* (0.226) 6.21e-06** (2.54e-06) 0.512 (0.580) -2.06*** (0.750) -0.606 (0.541) 0.883*** (0.316) yes 638 -138.34 0.1359 3.87* (2.33) -0.008 (0.007) -0.003 (0.010) -0.120 (0.244) -0.794** (0.315) 2.97*** (1.01) 0.603 (0.484) 10.48*** (0.343) -11.99*** (3.68) -1.77*** (0.624) -0.112 (0.090) -0.334* (0.202) 4.10e-06* (2.26e-06) 0.598 (0.503) -2.32*** (0.662) 0.104*** (0.028) yes 663 -150.34 0.1398 3.53 (2.65) -0.009 (0.008) 0.002 (0.011) -0.225 (0.285) -0.608* (0.328) 3.65*** (1.41) 0.557 (0.499) 10.24** (4.81) -11.77** (4.83) -1.79** (0.717) -0.069 (0.095) -0.405* (0.238) 6.24e-06** (2.67e-06) 0.636 (0.595) -2.24*** (0.679) -0.566 (0.565) 0.096*** (0.029) yes 638 -137.46 0.1414 2.34 (2.18) -0.017* (0.009) -0.004 (0.012) -0.383 (0.289) -0.304 (0.328) 2.83** (1.30) -0.161 (0.521) 9.19** (4.22) -10.48** (4.27) -1.45** (0.604) 0.099 (0.084) -0.336 (0.290) 0.00001*** (4.l4e-06) 0.619 (0.614) -1.85*** (0.533) -0.563 (0.529) 1.34 (1.06) 0.921*** (0.341) yes 565 -123.27 0.1615 Robust standard errors in parentheses. ***/><.01; *><.05; > < .01; *> < .05; > < .10. As for the rest of the variables, their estimated patterns con form to some of the evidence already provided by previous research. In line with Humphreys's (2005) results, the produc tion of diamonds and the export of minerals tend to shorten civil wars. Confirming Fearon's (2004) findings, I also find that contraband hinders conflict resolution and that 'sons of the soil' wars tend to last longer than other types of conflict. Ethnic wars are slightly shorter, but the effect is not significant. Furthermore, the size of the army is related to longer wars (as already observed by DeRouen & Sobek, 2004), while the number of fatalities, as well as the GDP per capita, tend to shorten wars. I find a curvilinear relationship between ethnic fractionalization and conflict duration, too. The geographic characteristics of the country do not have any significant effect in these pooled regressions (only mountainous terrain in Column 6). Civil war outcomes and the effect of sanctions Not all civil wars end in the same way, so outcomes may need to be treated as competing risks. According to our sample, and following the codification developed by Walter (2002), 49 of the 66 civil conflicts that finished within the period under study ended because of a military victory of one of the sides, while 17 ended through a negotiated settlement. I want to investigate whether sanctions imposed by an international institution are more conductive to negotiated settlements, whereas those that do not involve an international organiza tion are more prone to lead to military victories. The method employed to test this proposal is, in this case, multinomial logit. The estimates are reported in Table III. The likelihood of each war outcome is strongly influenced by the existence of sanctions in the direction pointed out (see Models 1 and 2). As is clearly revealed, although sanctions generally help to reduce conflict length, they do so with varying consequences. Sanctions imposed by international institutions significantly increase the probability of reaching a negotiated settlement that brings the conflict to an end. Increased cooperation between senders augments the costs and efficacy of sanctions episodes. Moreover, the intervention of an international orga nization signals the parties that an outside actor may intervene to guarantee the terms of a potential settlement (Walter, 1997), so the utility of a pact increases as the likelihood of a unilateral defection is diminished by a third actor. On the other hand, those sanctions unilaterally imposed by individual countries or a small coalition have an important impact on the probability of a civil war ending through military means. One possible reason (needing further study) may be that those sanc tions not under the direction of an international multilateral institution may be biased and possibly inspired by the domes tic interests of the primary sender. In Model 3, a further refinement to our variable on multi lateral sanctions has been introduced. It can be argued that sanctions imposed by international institutions will tend to be more effective if the target country is itself a member of the multilateral institution. Greater diplomatic contact, military This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms 138 journal of Peace Research 47(2) Table III. Civil war outcome and international sanctions (multinomial logit) y = 1, conflict resolved through military y = 2, conflict resolved through negotiated means settlement Independent variables (1) (2) (3) (1) (2) (3) Intercept 2.03 1.22 (1.76) (2.12) Mountains 0.008 0.004 (0.010) (0.010) Forests 0.020* 0.023* (0.012) (0.012) Log population 0.006 -0.073 (0.270) (0.292) Log GDP per capita -0.705** -0.539 (0.331) (0.368) Oil production 14.78** 12.72* (6.51) (6.86) Diamond production 1.55 1.80 (1.05) (4.44) Ethnic fractionalization 4.84 6.25 (4.61) (8.35) (Ethnic fractionalization)2 -4.96 -6.19 (4.69) (7.88) Contraband -1.42** -1.37** (0.633) (0.684) Number of borders -0.235* -0.186 (0.122) (0.126) Army size (log) -0.283 -0.319 (0.273) (0.324) Deaths/year 2.08e-06 3.89e-06 (3.11e-06) (3.96e-06) Ethnic war 0.516 0.598 (0.570) (0.674) Sons of soil war -2.56** -2.45** (1.20) (1.19) Military intervention -0.293 (0.588) Non-institutional sanction 1.17*** 1.19*** (0.367) (0.385) International institution sanction 0.654 0.582 (0.761) (0.935) Int. institution sanction (no member) Int. institution sanction (membet) Model 1 Duration splines yes Observations 612 Log-pseudolikelihood -159.91 Pseudo R-squared 0.1692 1.27 5.25 7.19 6.00 (2.13) (4.43) (6.05) (6.32) 0.004 -0.044 -0.046 -0.045 (0.010) (0.038) (0.046) (0.048) 0.023* -0.030 -0.047** -0.056* (0.012) (0.022) (0.019) (0.029) -0.074 -0.816 -1.02 -1.17 (0.289) (0.504) (0.749) (0.827) -0.542 -0.222 -0.060 0.331 (0.369) (0.559) (0.686) (0.696) 12.79* -25.45 -34.33 -80.32 (6.85) (23.13) (34.49) (54.75) 1.89 3.16* 2.67 10.93 (4.59) (1.66) (5.29) (7.17) 6.25 6.01 2.57 3.51 (8.31) (7.30) (11.49) (14.31) -6.20 -10.16 -7.86 -9.96 (7.84) (8.29) (13.37) (16.75) -1.38** -0.954 -0.701 -1.01 (0.689) (0.841) (0.904) (0.978) -0.187 0.382* 0.489* 0.708** (0.128) (0.232) (0.294) (0.351) -0.322 -0.744** -0.836* -1.20* (0.322) (0.380) (0.440) (0.687) 3.88e-06 -6.13e-06 -2.36e-06 -8.90e-06 (3.96e-06) (0.00002) (0.00003) (0.00004) 0.601 0.784 0.366 0.197 (0.672) (0.893) (1.18) (1.34) -2.45** -1.97 -1.93 -2.49 (1.17) (2.02) (2.51) (3.11) -0.292 -1.63* -1.67* (0.587) (0.865) (0.896) 1.19*** 0.374 0.566 0.645 (0.381) (0.600) (0.557) (0.451) 1.84** 2.32* (0.922) (1.23) 0.553 0.116 (1.49) (0.883) 0.561 3.45** (0.981) (1.59) 2 3 yes yes 589 589 -142.65 -141.64 0.1873 0.1931 Robust standard errors in parentheses. **>< .01; **/>< .05; >< .10. Cooperation and commercial interdependence are likely to found among the members of some multilateral organizations To test this straightforward proposition, I have recoded th variable used in Model 1 by dividing the sanctions impose by an international institution into two extra dumm variables: the first is coded 1 if t by an international institution b tution, and the second is coded tioned by an international instit coefficients of the newly created This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms Escriba-Folch_139 expectations. Note first that the strong positive impact of institutional' sanctions on military victory is not altere contrast, for those countries belonging to the institut imposing the sanctions, the impact of such coercive mea is great and significant. The estimated probability of a ne ated settlement is 0.0008 when no sanction is present; i country is targeted by sanctions of an international instit it belongs to, the probability of a negotiated terminati 0.024. On the other hand, a country under institutional sanctions faces a probability of 0.074 of ha the conflict resolved through military means, while if no tion is imposed, the likelihood is just 0.023. Table IV shows the results of the effects of the types of sure sanctions involve on war outcome. These results sh be carefully interpreted as they are quite sensitive to sa size, which in this case is restricted to the TIES data (f 1971). To increase the number of observations, the vari 'log GDP per capita' has been ruled out, since it was not nificant anyway, and we use the natural resources dumm The evidence suggests that the only measures effectiv shortening conflicts are total embargoes, which increas likelihood of both a military victory and a settlement. In trast, international arms embargoes have a negative and si icant impact on the probability of a military victory. T result gives credit to those arguing that this type of san has been irrelevant at best, and even counterprodu (Tierney, 2005). Multilateral arms embargoes may balance the power between parties, thereby making victory likely. On the other hand, multilateral arms embargoes had a positive, albeit not significant, effect on the likel of a settlement.17 This latter finding supports to some the proposition that arms embargoes decrease uncertainty each party's power. Other results of these tables merit comment: military in ventions significantly reduce the likelihood of a settlem The inclusion of this variable reduces the sample some and slightly alters some of the results. Again, contrab reduces the prospects of conflict termination, especially t of a military victory, as it allows the rebels to finance activities. The number of borders has contradictory eff On the one hand, it serves to hinder a military victory ably, by government forces), since it eases the maintenanc rebel bases outside the boundaries of the state; but, on other hand, it increases the likelihood of a negotiated r tion, as in DeRouen & Sobek (2004). The size of the a also represents a significant obstacle to a negotiated resolu of conflicts, as it may tend to make the government ove mate its relative strength, pe, and the probability of wi (Mason & Fett, 1996). Natural resources, both diamond oil, are again related to shorter wars, although through di ent mechanisms. Abundant forest areas increase the likel of a military victory and hinder negotiated settlements. 17 The coefficient is almost significant at the 0.10 level; the Rvalue is Table IV. Types of sanction and logit) Event: Civil war outcome = j Military Negotiated Independent variables victory settlement Intercept -0.167 9.09 (0.278) (6.15) Mountains -0.012 -0.041 (0.012) (0.043) Forests 0.003 -0.081* (0.015) (0.043) Log population -0.481* -1.12** (0.261) (0.568) Mineral exporting 4 71*** 6.45** (1.81) (2.60) Oil exporting 0.257 0.441 (0.566) (1.57) Ethnic fractionalization 14.68 0.739 (9.53) (14.06) (Ethnic -15.84* -5.58 fractionalization)2 (9.27) (15.22) Contraband -1.53** -3.08 (0.748) (2.14) Number of borders 0.141 0.665** (0.114) (0.302) Army size (log) -0.663* -1.56*** (0.372) (0.498) Deaths/year 0.00001** 1.15e-06 (5.64e-06) (0.00004) Ethnic war 1.16 -0.373 (0.761) (1.25) Sons of soil war -2.36*** -2.56 (0.666) (2.34) Military intervention -0.656 -1.34*** (0.629) (0.490) Total embargo 2.04*** 6.03*** (0.634) (1.98) Aid termination 0.781 0.692 (0.479) (1.42) Trade restrictions 0.508 1.60 (0.671) (2.08) Multilateral arms -1.48** 1.71 embargo (0.673) (1.05) Other sanctions 0.538 1.02 (1.10) (1.45) Duration splines Yes Observations 592 Log-pseudolikelihood -141.65 Pseudo R-squared 0.2152 Robust standard errors in parentheses. ***/>< .01;**/>< .05; >< .10. Concluding remarks Studies of the efficacy of economic sanctions have t analyze it in a rather general way and have used con variables that often assess the success of a sanction This content downloaded from 134.117.10.200 on Tue, 23 Feb 2021 10:39:01 UTC All use subject to https://about.jstor.org/terms 140 journal a/Peace Research 47(2) on an ordinal scale. In this work, I sought to explore the effect of sanctions in a very specific context, civil war duration, using a time-series cross-sectional dataset and a direct measure of event occurrence, civil war termination and outcome. I hypothesized that sanctions would have a significant neg ative effect on intrastate conflict duration, mainly due to three basic mechanisms: convergence of parties' beliefs over power, reduced utility of victory and financial pressure that reduce parties' viability of continued fighting. Our second proposi tion contended that those sanctions maximizing the costs to the target would be more effective than other types of targeted measures in bringing war to an end. Finally, I further proposed that those sanctions imposed by an international institution would be more effective in augmenting the probability of intrastate conflict termination. Our empirical evidence using new data on sanctions shows that, effectively, sanctions have had a significant and negative impact on intrastate conflict duration. Moreover, this effect grows the more years a given country is targeted. These results are robust to the inclusion of a variable controlling for external military interventions. Moreover, the empirical evidence seems to suggest that the most successful measures so far have been total economic embargoes. Such measures are shown to increase the likelihood of both military victory and negotiated settlement, while international arms embargoes are found only to significantly decrease the likelihood of a military victory by one of the parties. Regarding the debate about the efficacy of sanctions imposed by international institutions or not, this article has shed light on the distinctive effect of both types of sanction. Although the coefficients for sanctions backed by international institutions and those which are not are extremely similar in size in the general models of war duration, I find that sanctions imposed by international institutions significantly increase the likelihood of conflict resolution, especially if the targeted country is a member of the organization. In contrast, sanctions applied by other bodies are much more conducive to military victories. In sum, the article has several policy implications. First, it suggests that, overall, sanctions have been relatively useful in helping to shorten civil wars, as the statistical association sug gests. Yet, this role needs to be improved. Concretely, our results suggest that any coercive measures should preferably be conducted by international organizations, especially if we are interested in promoting conflict resolution. Concerning the measures imposed, the evidence suggests that maximizing costs via embargoes is more effective than other sanction types. Multilateral arms embargoes can also result in increased chances of negotiated settlement, although implementation problems so far have limited their effectiveness, as remarked by many scholars. Replication data The data used in this article can be found at http:// www. prio. no/j pr/datasets. Acknowledgements I thank Clifton Morgan for sharing the data on sanctions and the editor, T?nia Verge and three anonymous referees for very helpful comments. 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