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Partition as a Solution to Ethnic War: An Empirical Critique of the Theoretical Literature

Published online by Cambridge University Press:  13 June 2011

Nicholas Sambanis
Nicholas Sambanis
Affiliation:
Yale University

Abstract

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Theorists of ethnic conflict have argued that the physical separation of warring ethnic groups may be the only possible solution to civil war. They argue that without territorial partition and, if necessary, forced population movements the war cannot end and genocide is likely. Other scholars have counterargued that partition only replaces internal war with international war, that it creates undemocratic successor states, and that it generates tremendous human suffering. This debate has so far been informed by very few important case studies. This article uses a new data set on civil wars to identify the main determinants of war-related partitions and estimate their impact on democratization, on the probability that war will recur, and on low-level ethnic violence. This is the first large-N quantitative analysis of this topic, testing the propositions of partition theory and weighing heavily on the side of its critics. Most assertions of partition theorists fail to pass rigorous empirical tests. The article also identifies some determinants of democratization after civil war, as well as the determinants of recurring ethnic violence. These empirical findings are used to formulate an alternative proposal for ending ethnic violence.

Type
Research Article
Information
World Politics , Volume 52 , Issue 4 , July 2000 , pp. 437 - 483
Copyright
Copyright © Trustees of Princeton University 2000

References

1 Kaufmann, Chaim, “Possible and Impossible Solutions to Ethnic Civil Wars,” International Security 20 (Spring 1996)CrossRefGoogle Scholar; idem, “When All Else Fails,” International Security 23 (Fall 1998); Mearsheimer, John J. and Evera, Stephen Van, “When Peace Means War,” New Republic (December 1995).Google Scholar

2 Horowitz, Donald L., Ethnic Groups in Conflict (Berkeley: University of California Press, 1985), 588.Google Scholar See also Lijphart, Arend, Democracy in Plural Societies (New Haven: Yale University Press, 1977), 44–47Google Scholar; Dahl, Robert A., Polyarchy: Participation and Opposition (New Haven: Yale University Press, 1971), 121Google Scholar; and Huntington, Samuel P., “Civil Violence and the Process of Development,” Adelphi Paper no. 83 (London: International Institute for Strategic Studies, 1971), 14.Google Scholar Horowitz also discusses dangers of partition (pp. 588–91).

3 Kaufmann, (fn. 1, 1996), 137, 139.Google Scholar

4 See Jervis, Robert, “Cooperation under the Security Dilemma,” World Politics 30 (January 1978).CrossRefGoogle Scholar Such suspicion and fear would be supported by actual or perceived state collapse, which transforms the domestic political environment into a near anarchic environment.

5 Posen, Barry, “The Security Dilemma and Ethnic Conflict,” Survival 35 (Spring 1993).CrossRefGoogle Scholar

6 Kaufmann, (fn. 1, 1996), 139–47.Google Scholar

7 Ibid., 150.

8 Partition theorists also approach the problem in this way: they do not discuss partition as a preventive measure before war occurs but rather analyze it as a strategy to end civil war after it occurs—“when all else fails,” as Kaufman (fn. 1, 1998) puts it. Peaceful partitions therefore cannot offer any information on my main research question—war recurrence—since a war is a necessary precondition for war recurrence. My research design is therefore the equivalent of a biostatistician's inquiry into the effects of medical treatment for illness: suffering from that illness is a precondition for inclusion in the study. Studying the relationship between initial war occurrence and partition would be an interesting extension of my study. The research question would have to be reformulated, as would the data set. The dependent variable could no longer be war recurrence or residual violence and one would need a theory of civil war occurrence that included partition as a potentially important determinant of civil war (or civil peace). Such a study would analyze a random sample of countries (or the entire population of countries) and would have to include both countries that experienced war and countries that were at peace. To identify whether partition causes war, one could code a binary variable denoting if the country was partitioned and use it as a regressor in a model of the onset of war. Alternatively, one could estimate two separate regressions on partitioned and nonpartitioned countries and compare the coefficients. In terms of the medical research example above, this study would effectively ask: how does factor x affect one's chances of becoming ill?

9 On ethnic diffusion cooperation, see Byman, Daniel L., “Divided They Stand: Lessons about Partition from Iraq and Lebanon,” Security Studies 7 (Autumn 1997).CrossRefGoogle Scholar On security guarantees and ethnic war termination, see Walter, Barbara F., “The Critical Barrier to Civil War Settlement,” International Organization 51 (Summer 1997).CrossRefGoogle Scholar Neither Byman nor Walter is a critic of partition theory (Byman in fact supports partition under certain conditions). Some of their arguments, however, can be read as in direct critiques of the theory.

10 Kumar, Radha, “The Troubled History of Partition,” Foreign Affairs 76 (January-February 1997).CrossRefGoogle Scholar

11 Ibid.; see also Etzioni, Amitai, “The Evils of Self-Determination,” Foreign Policy 89 (Winter 1992–93)Google Scholar; and Schaeffer, Robert, Warpaths: The Politics of Partition (New York: Hill and Wang, 1990).Google Scholar

12 Byman (fn. 9).

13 Ibid.; and Schaeffer (fn. 11).

14 Etzioni (fn. 11); Buchanan, Allen “Self-Determination and the Right to Secede,” Journal of International Affairs 45 (Winter 1992).Google Scholar

15 Kaufman (fn. 1, 1998).

16 Lake, David A. and Rothchild, Donald, eds., The International Spread of Ethnic Conflicts (Princeton: Princeton University Press, 1998).Google Scholar More research is needed to fully appreciate the impact of historical examples and of precedential reasoning in ethnic conflict.

17 See Horowitz, (fn. 2), 588–91 and chaps. 2, 6.Google Scholar

18 Ibid., 589, emphasis added.

19 See, among others, Lake, David A. and Rothchild, Donald, “Containing Fear: The Origins and Management of Ethnic Conflict,” International Security 21 (Fall 1996)CrossRefGoogle Scholar; Gagnon, V. P., “Ethnic Nationalism and International Conflict: The Case of Serbia,” International Security 19 (Winter 1995)Google Scholar; de Figueiredo, Rui J. P. and Weingast, Barry R., “The Rationality of Fear: Political Opportunism and Ethnic Conflict,” in Walter, Barbara and Snyder, Jack, eds., Civil Wars, Insecurity, and Intervention (New York: Columbia University Press, 1999).Google Scholar

20 David Laitin, “Somalia: Civil War and International Intervention,” in Walter and Snyder (fn. 19); and Jack Snyder and Robert Jervis “Civil War and the Security Dilemma,” in Walter, and Snyder, (fn. 19), 19–24.Google Scholar

21 I do not develop a theory of ethnic cooperation in this paper. I only summarize relevant theoretical arguments to frame my empirical analysis. Thus, this section is not designed to resolve all doubt about the possibility of ethnic cooperation after civil war.

22 Snyder and Jervis (fn. 20), 18. On power sharing, see Sisk, Timothy, Power Sharing and International Mediation in Ethnic Conflicts (Washington, D.C: United States Institute of Peace, 1996).Google Scholar

23 Lake and Rothschild (fn. 19).

24 Snyder and Jervis (fn. 20).

25 In Walter's (fn. 9) argument, the security dilemma depends on an asymmetry of power between the government and rebels. Walter notes that credible external security guarantees are effective, though difficult. The difficulty in proving the credibility of the third party's commitment amounts to indirect support for the partition thesis, though only if partition is proven to be more credible and less difficult to implement than a brokered settlement.

26 De Figuereido and Weingast (fn. 19).

27 The rationalist school is well represented by Blainey, Geoffrey, The Causes of War (New York: Free Press, 1973)CrossRefGoogle Scholar; and Fearon, James, “Rationalist Explanations for War,” International Organization 49 (Summer 1995).CrossRefGoogle Scholar War should reveal any private information about relative power and resolve, making it less rational for parties to resort to war again rather than to strike a more efficient bargain short of war. That said, we should also consider other explanations of war and weigh them against this argument.

28 Snyder and Jervis (fn. 20); and Laitin (fn. 20).

29 Byman (fn. 9). This argument can backfire. Ethnic balancing can also paralyze the state. For such an argument, see Wagner, Harrison, “The Causes of Peace,” in Licklider, Roy, ed., Stopping the Killing (New York: New York University Press, 1993).Google Scholar Wagner argues that because military victory results in unitary political systems, it will be more stable than any peace agreement based on ethnic balancing. Indeed, the occurrence of an ethnic war suggests a precedent of failed ethnic balancing. In this paper, I present empirical results about the relationship of ethnicity to postwar violence, but that relationship also demands better theorizing.

30 See, e.g., Paul Collier, Ibrahim Elbadawi, and Nicholas Sambanis, “How Much War Will We See? Estimating the Probability of Civil War in 161 Countries” (Manuscript, World Bank, February 2000).

31 Dropping those cases did not affect any of the results presented in later sections.

32 This definition is nearly identical to the definition of a civil war in David Singer, J. and Small, Melvin, Correlates of War Project: International and Civil War Data, 1816–1992 (Ann Arbor, Mich.: ICPSR, 1994)Google Scholar; idem, Resort to Arms (Beverly Hills, Calif.: Sage Publications, 1982); and Licklider, Roy, “The Consequences of Negotiated Settlements in Civil Wars, 1945–1993,” American Political Science Review 89 (September 1995).CrossRefGoogle Scholar Unlike them, my coding of wars does not presume one thousand deaths per year, but rather uses the one thousand deaths as the threshold for the entire war. In fact, however, most of my cases have caused one thousand deaths annually. My coding decision was based on the arbitrariness of setting one thousand as the annual death criterion and on the lack of available data on annual deaths in the Correlates of War project. Indeed, the codebook of the ICPSR study, which includes the international and civil war data files for the Correlates of War Project, does not mention an annual death threshold and no annual death data are made available by the authors.

33 My sources for coding wars include Singer and Small (fn. 32, 1994); Licklider (fn. 32); idem (fn. 29); Wallensteen, Peter and Sollenberg, Margareta, “Armed Conflicts, Conflict Termination, and Peace Agreements, 1989–1996,” Journal of Peace Research 34, no. 3 (1997)Google Scholar; Esty, Daniel C. et al., “The State Failure Project: Early Warning Research for US Foreign Policy Planning,” in Davies, John L. and Gurr, Ted Robert, eds., Preventive Measures: Building Risk Assessment and Crisis Early Warning Systems (Boulder, Colo., and Totowa, N.J.: Rowman and Littlefield, 1998)Google Scholar; Mason, David and Fett, Patrick, “How Civil Wars End: A Rational Choice Approach,” Journal of Conflict Resolution 40 (December 1996)CrossRefGoogle Scholar; Regan, Patrick, “Conditions for Successful Third Party Interventions,” Journal of Conflict Resolution 40, no. 1 (1996)Google Scholar; Walter (fn. 9); SIPRI, SIPRI Yearbook (http://editors.sipri.se/pubs/yearb.html); Human Rights Watch, World Report (New York and Washington, D.C.: Human Rights Watch, various years).Google Scholar Secondary texts consulted include Rotberg, Robert I., ed., Burma: Prospects for a Democratic Future (Washington, D.C.: Brookings Institution, 1998)Google Scholar; Stuart-Fox, Martin, A History of Laos (Cambridge: Cambridge University Press, 1998)Google Scholar; Callahan, David, Unwinnable Wars (New York: Hill and Wang, 1997)Google Scholar; Iatrides, John O., “The Doomed Revolution: Communist Insurgency in Postwar Greece,” in Licklider, (fn. 29); Doyle, Michael W., Orr, Robert, and Johnstone, Ian, eds., Keeping the Peace (Cambridge: Cambridge University Press, 1997)Google Scholar; Deng, Francis M., War of Visions: Conflict of Identities in the Sudan (Washington, D.C.: Brookings Institution, 1999)Google Scholar; McDowall, David, A Modern History of the Kurds (New York: St. Martin's Press, 1996)Google Scholar; and Sambanis, Nicholas, “United Nations Peacekeeping in Theory and in Cyprus: New Conceptual Approaches and Interpretations” (Ph.D. diss., Princetony University, 1999).Google Scholar The most important difference between my coding and that of others concerns the periodization of wars. I have broken what is a single observation of war in other data sets into more than one observation; or, conversely, I have collapsed two or more observations in one by uniformly applying this rule: a war is coded as a single observation if the parties and issues are the same, if the war events are not separated by a substantial period of nonviolence, and/or if the parties sign a peace agreement or agree to a major truce.

34 The document can be downloaded from http://www.worldbank.org/research/conflict/data.htm.

35 Kaufmann, (fn. 1, 1998), 125.Google Scholar

36 See Kaufmann, (fn. 1, 1998), 125, fn. 21.Google Scholar

37 Kaufmann (fn. 1, 1996).

38 Kauffman (fn. 1, 1998).

35 Ibid.

40 It is well known to scholars of the Cyprus problem that Turkey and the Turkish Cypriote constituted and acted as a single party both during the violent part of that conflict (1963–74) and during the subsequent negotiation phases; see Sambanis (fn. 33).

41 Kaufmann (fn. l, 1996 and 1998). Other studies also use the broad definition, given that the distinction between secession and partition seems artificial. See, among others, Horowitz (fn. 2); and Heraclides, Alexis, The Self-Determination of Minorities in International Politics (Portland: Frank Cass, 1991)Google Scholar; both use the terms partition and secession interchangeably.

42 I consider only post—World War II cases because of the paucity of economic data from before 1945. Thus, I exclude the partition of Ireland. Cases of peaceful partition are also excluded, for example, Macedonia (1992), Czechoslovakia (1993), and Singapore (1965). I exclude one case (Iraq) that I believe was erroneously classified as a partition in Kaufmann (fn. 1, 1998). I exclude Iraq (1991) because there is no recognized, functional, or even autonomous Iraqi Kurdistan and the territory and its population would have been within reach of the Iraqi military had it not been for the U.S.-enforced no-fly zone.

43 My coding of cases of partition incorporated suggestions made by anonymous referees.

44 One might argue that the “real” number of partitions is smaller, since several of them occurred in either the former Yugoslavia or the former USSR. This would imply that these partitions may not be independent of one another. Thus, I cluster all same-country observations in my statistical analysis, relaxing the assumption of independence for those observations and allowing for nonconstant variance within clusters.

45 See, for example, Collier, Paul and Hoeffler, Anke, “Justice-Seeking and Loot-Seeking in Civil War” (Manuscript, World Bank, February 1999)Google Scholar; Doyle, Michael W. and Sambanis, Nicholas, “International Peacebuilding: A Theoretical and Quantitative Analysis” (Manuscript, Princeton University and the World Bank, February 2000)Google Scholar; Collier, Paul, “On the Economic Consequences of Civil War,” Oxford Economic Papers 51 (1998)Google Scholar; and Mason and Fett (fn. 33).

46 The coding of the WARTYPE variable was not easy. There are substantial differences in the various sources and data sets I consulted. I used two main sources for this variable: Licklider (fn. 32); and Esty et al. (fn. 33). I coded the variables TYPELICK (Licklider's war-issue variable) and TYPESTF (the State-Failure Project's war-type variable) to facilitate comparisons across cases. Where those two sources differed, I coded WARTYPE based on majority opinion in other data sets, including Regan (fn. 33); and Mason and Fett (fn. 33).

47 This hypothesis (with an emphasis on the proportion of young men) has been posited with reference to the causes of civil war by Collier and Hoeffler (fn. 45); and Bates, Robert H., “Ethnicity, Capital Formation, and Conflict,” CID Working Paper no. 27 (Harvard University, October 1999).Google Scholar

48 For example, Collier and Hoeffler (fn. 45).

49 Given such problems, quantitative analysts of civil wars must be highly transparent in their coding of these variables. Moreover, it is necessary for those building data sets of civil war to coordinate their efforts and exchange information. I will use my WARTYPE variable in the rest of the analysis since I generated it with reference to as many sources as I could consult for each case. I tried to reflect majority opinion about the coding of each case, where there was disagreement between my main sources.

50 If we drop WARTYPE, then EH becomes nonsignificant but remains negative.

51 I proxy the size of ethnic groups by interacting the ethnic heterogeneity index EH with the log of population size (LOGPOP).

52 Measuring these variables at the start of the war not only prevents problems of reverse causality but also captures any impact that these variables might have had on causing the civil war in the first place. Thus, the inability to find significance for the economic variables in model 2 may be due to a selection effect (since all the countries in my sample are countries that experienced war and may there fore share the same socioeconomic background). Thus, the analysis of partition and war recurrence must focus here on war-related variables that would be expected to differ significantly across countries.

53 See Collier and Hoeffler (fn. 45). The precise relationship between partition and economic variables is undertheorized, so I will not explore this further, but this counterintuitive finding is worth further study. It may be that relatively richer countries can support partition, since the prospects of economic viability of the successor state will be greater.

54 These signs do not change if I drop the cases of ongoing war. The direction of this correlation, however, may result from measurement error or selection effects. Measurement error is possible because reliable data were often not available for the relevant years. Or it may be due to collinearity between income inequality and energy consumption, since I used GDP data to impute missing values of both of these variables.

55 Kaufmann, (fn. 1, 1998), 124.Google Scholar

56 The original data on democracy were compiled by Keith Jaggers and Ted Robert Gurr, Polity 98 Project (http://www.bsos.umd.edu/cidcm/polity/). I added their democracy and autocracy scores as follows: GURR = [DEMOCRACY + (10-AUTOCRACY)]. The resulting variable ranges from 0 to 20. The Polity 3 data end in 1994, so I imputed thirty-five missing values using the political rights index of the Freedom House project after I established that there was a very close correlation between Gurr's democracy index and Freedom House's political rights index. See Freedom House, Freedom in the World (London: Freedom House, 1999).Google Scholar

57 This list includes not only ethnic partitions but also all other cases of partition in my data set. Subsequent analysis focuses directly on partitions that resulted from ethnic wars and therefore excludes a number of partitions (for example, the Koreas, Vietnam, and Taiwan). However, I test the robustness of my results by including all wars and partitions.

58 I selected these variables based on theoretical arguments regarding the determinants of the level of democratization after civil war, drawing on Doyle and Sambanis (fn. 45), among others. Also the relationship between economic variables and democracy has been the focus of numerous studies in the economics and political science literatures; see, e.g., Burkhart, Ross E. and Lewis-Beck, Michael S., “Comparative Democracy: The Economic Development Thesis,” American Political Science Review 88 (December 1994).CrossRefGoogle Scholar

59 These regression results are robust for a large number of specifications.

60 Hausman, J., “Specification Tests in Econometrics,” Econometrica 46 (1978), 1251–71.CrossRefGoogle Scholar On the use of the Hausman test to test exogeneity, see Baltagi, B. H., Econometrics (New York: Springer-Verlag, 1998), 291CrossRefGoogle Scholar; and Stata Corporation, Stata Reference Manual: Release 6 (College Station, Tex.: Stata, 1999), 2: 7–13.Google Scholar In the formula above b is the coefficient vector from the consistent estimator and B the coefficient vector from the efficient estimator and Vb, and VB are their respective covariance matrices.

61 Given the paucity of data to answer this important question, a worthwhile project would be to conduct a comparative case study of the political institutions of all these successor states.

62 This is not a well-known case. In 1963 a “green line” was established in the capital city of Nicosia, partitioning the Greek Cypriot and Turkish Cypriot sectors. After 1964 the partition was expanded, and more than 30 percent of the Turkish Cypriot population moved to defensible, self-administered enclaves. These enclaves forcibly excluded the Greek Cypriot population and their demilitarization and defortification was part of the mandate given to a UN peacekeeping force—UNFICYP (see UN doc. S/5764, 15 June 1964, para. 61). The UN secretary-general often noted in his report that the enclaves gave the Turkish Cypriote “complete military and administrative control” of several areas (S/6228, para. 50). In 1965 the secretary-general noted that the enclave fortifications “contribute to maintaining tension at high pitch” and UNFICYP “insists on their removal” (S/6228, para. 51). Within six months in 1967, 52 new positions were built by the Greek Cypriot National Guard and 130 by the Turkish Cypriote (S/8286, December 8, 1967, para. 50). The secretary-general noted that “this ceaseless building of fortifications … [would] result in the Island being criss-crossed and honeycombed with defences [sic]” (S/8286, para. 49). Thus, the island was effectively partitioned between 1963 and 1967. On the Cyprus conflict during the critical years between 1963 and 1974, see Patrick, Richard, Political Geography and the Cyprus Conflict, 1963–1971 (Waterloo, Canada: Department of Geography, University of Waterloo, 1976)Google Scholar; the work includes maps of the pre-1974 enclaves. See also Joseph, Joseph, Cyprus: Ethnic Conflict and International Solution (New York: St. Martin's, 1997)Google Scholar; and Sambanis (fn. 33).

63 This table includes cases of nonethnic partition. I also ran these cross-tabs excluding nonidentity (ethnic/religious) wars, and the results were not significantly affected.

64 I estimate probit models with clustered same-country observations and robust standard errors. Since partition theory has focused on ethnic wars and since I found the type of war to be a significant determinant of partition, I dropped cases of nonidentity wars from my analysis, but I do report some results of interest as they apply to all civil wars.

65 Following are the explanatory variables and the researchers who identified their importance: war duration, Mason and Fett (fn. 33); size of the government's military, Mason and Fett (fn. 33); war outcomes, Licklider (fn. 32) and Walter (fn. 39); ethnic heterogeneity and population size, Collier and Hoeffler (fn. 45); deaths and displacements, Licklider (fn. 32) and Doyle and Sambanis (fn. 45); income per capita, Collier (fn. 45); major power involvement, Singer and Small (fn. 32); foreign intervention, Regan (fn. 33); third-party and UN peace operations, Doyle and Sambanis (fn. 45); democracy, Collier, Elbadawi, and Sambanis (fn. 30) and Håvard Hegre et al., “Towards a Democratic Civil Peace? Opportunity, Grievance, and Civil War, 1816–1992” (Paper presented at the World Bank Conference on the Economics of Political and Criminal Violence, Washington, D.C., February 16–22, 1999). I also controlled for the number of land borders, the decade the war started, and the cold war. I could not include too many of these variables together, given my small data set and the collinearity of these variables.

66 The Russia-Chechnya case causes the negative sign, and partition is positively correlated with WAREND if I drop that observation. The nonsignificance of partition, however, does not change by deleting that observation. I also sequentially deleted several other cases (e.g., Cyprus 1963/67, Somalia, Tajikistan, India), and the substantive results did not change. The results are also robust to using TYPELICK and TYPESTF instead of WARTYPE to identify ethnic wars.

67 The opposite argument (without much empirical support) is made in Kaufmann, Chaim, “Intervention in Ethnic and Ideological Civil Wars: Why One Can Be Done and the Other Can't,” Security Studies 6 (Autumn 1997).Google Scholar

68 The sign of LOGCOST in models 1 and 2 is negative, indicating that the higher the human cost, the greater the probability of war recurrence. This may seem counterintuitive: why would more costly wars lead to new wars? Would not great human cost discourage war recurrence? That reasoning is correct and it is reflected in my findings on war duration (see below), which verify the war-weariness hypothesis. However, controlling for this finding, the probability of war recurrence should be expected to be greater as the human costs of the war increase. These costs measure war-generated hostility and create grievances that may manifest themselves in future conflict. Further, the greater the human and economic cost of the war, the lower should be a country's human capital and the lower the state's capacity to resume normal operations.

69 OUTCOME2 is a categorical variable denoting whether the war ended in a truce, rebel victory, government victory, or peace settlement. It is highly significant in both models 1 and 2, though interpreting its sign is not straightforward. By disaggregating OUTCOME2, I found some of its components highly correlated with partition. Thus, entering them independently in the regression would increase collinearities. These correlations also generate sufficient concern over the possible endogeneity of partition when both OUTCOME2 and partition are included in the model.

70 Mason and Fett (fn. 33). I thank Russ Leng for pointing this out to me.

71 By contrast, Mason and Fett (fn. 33) find a significant negative correlation.

72 This finding may be due to selection effects, as I mentioned earlier, but it may also confirm the revenue-seeking economic model of civil war in Collier (fn. 45); and Collier and Hoeffler (fn. 45); the model looks at GDP per capita as a proxy for “lootable” resources, which would increase the risk of war.

73 Fearon, James and Laitin, David, “Explaining Interethnic Cooperation,” American Political Science Review 90 (December 1996).CrossRefGoogle Scholar

74 See, e.g., Collier, Elbadawi, and Sambanis (fn. 30).

75 This could be due to missing observations. The ten-year model was estimated on fifty cases. The coefficient and robust standard error of partition were -1.137 and .627, respectively, yielding a z-statistic of -1.813 (P> ∥z∥ = 0.070) and a model log-likelihood = -23.460, with a Wald chi2(8) = 32.14 and a Pseudo R2 = 0.3199.

76 Maddala, G. S., Limited Dependent and Qualitative Variables in Econometrics (Cambridge: Cambridge University Press, 1983)CrossRefGoogle Scholar; Rivers, D. and Vuong, Q., “Limited Information Estimators and Exogeneity Tests for Simultaneous Probit Models,” Journal of Econometrics 39 (1988).CrossRefGoogle Scholar This method is almost identical to Bollen, Kenneth A., Guilkey, D. K., and Mroz, T. A., “Binary Outcomes and Endogenous Explanatory Variables: Tests and Solutions with an Application to the Demand for Contraceptive Use in Tunisia,” Demography 32 (February 1995).CrossRefGoogle ScholarPubMed The two-stage probit model produces inefficient standard errors, though the efficiency loss is small. Rivers and Vuong derive the formula that gives the correct variance-covariance matrix, but their procedure is designed for continuous endogenous right-hand-side variables. A methodological discussion and Monte Carlo simulation results reporting the properties of this estimator in small samples are found in Michael Alvarez and Jennifer Glascow, “Two-Stage Estimation of Non-Recursive Choice Models,” Political Analysis (forthcoming). For a political science application of this method, see Michael Alvarez and L. Butterfield, “The Resurgence of Nativism in California? The Case of Proposition 187 and Illegal Immigration,” Social Science Quarterly (forthcoming). A discussion of the two binary variable case can be found in Madalla (p. 246).

77 For the case of two binary variables, this can be estimated as a seemingly unrelated bivariate probit model with a selection effect. The exogeneity test in this model consists of a Wald test of rbo, the estimated coefficient of the correlation of the error terms in the structural and reduced-form (“first-stage”) equations.

78 Michael Tomz, Jason Wittenberg, and Gary King, “Clarify: Software for Interpreting and Presenting Statistical Results,” version 1.2.1 (June 1, 1999). See also idem, “Making the Most of Statistical Analyses: Improving Interpretations and Presentation” (Paper presented at the annual meeting of the American Political Science Association, Boston, 1999).

79 Note that these estimates may differ slightly in replications since I did not fix the number seed used to randomly select samples for the simulations.

80 This result complements Bates's (fn. 47) findings on the relationship between ethnicity and political violence in Africa. Bates studies the relationship between ethnicity and economic modernization—urbanization, education, and the rise of per capita income, as well as political participation. Focusing on forty-six African countries from 1970 to 1995, he tests the relationship between ethnicity and political violence at several levels (not just wars). He measures the size distribution of ethnic groups, linguistic diversity, and the presence of an ethnic minority at risk, based on the work of a number of other researchers, and shows that the relationship between ethnicity and violence is complicated. Bates finds that “controlling for the impact of other variables, [linguistic diversity] associates with higher levels of violence … the size of the largest ethnic group enters quadratically; when the coefficient for the linear term is significant, so too is the coefficient for the quadratic. But as the size of the largest ethnic group grows, the level of violence initially decreases, but then increases; by contrast, the level of protest initially increases, but then falls” (p. 25). In Bates's analysis, it is extreme polarization that is most associated with violence. My finding that greater heterogeneity and more sizable ethnic groups reduce violence in postwar states is therefore compatible with Bates's result and complements it. I should note however, that Bates's results may not be generally applicable to non-African countries, given that African countries have a generally higher mean level of ethnic heterogeneity and this implies a selection effect if the results are to be applied widely to non-African countries. In my data set, for example, the mean and standard deviation of the ethnic heterogeneity index for African countries is 68.82 and 34.58, respectively, whereas for non-African countries it is 50.5 and 31.73. The ethnic heterogeneity index used was created by Vanhanen, Tatu, “Domestic Ethnic Conflict and Ethnic Nepotism: A Comparative Analysis,” Journal of Peace Research 36, no. 1 (1999).Google Scholar

81 Ten years after the end of the war partition has a negative correlation with an end to low-grade violence, but this result may be an artifact of missing (right-censored) observations (only fifty-five observations are available for the ten-year period).

82 Thus, development levels and military strength are more relevant with respect to war recurrence than with respect to low-level violence.

83 Results are available from the author. Finding good instruments in this data set has proven notoriously difficult. I did not change the specification of model 4; rather I just added and dropped instruments and considered other variables as potentially endogenous (specifically, WARDUR, LOGCOST, TREATY, ENERCAP). The instruments I used in various combinations were GEO, BORDER, EH, GDP, URBST (urban population at the start of the conflict), GARM, INTERVEN (was there an external intervention?), MAJOR (was there a major power involved?). I found only one permutation that made partition significant, but when I estimated this model using a bivariate probit estimator, I found that the error terms of the structural and reduced-form first equation were perfectly correlated (rbo = 1), which indicates either that there was too much noise in the system or that the distribution is not a bivariate normal.

84 To cite Horowitz (fn. 2), 135: “Is there any reason to believe that the more pronounced the cultural differences that exist between groups, the greater the ethnic conflict? There has been no shortage of offhanded assertions that cultural differences engender ethnic conflict. But … systematic statements of the relationship are more difficult to find.”

85 See, e.g., Herbst, Jeffrey, “Responding to State Failure in Africa,” International Security 21 (Winter 1996–97).CrossRefGoogle Scholar

86 Collier, Elbadawi, and Sambanis (fn. 30).

87 Laitin and Fearon (fn. 73).

88 My findings need not agree entirely with Bates's (fn. 47), since our samples and research questions differ. I have not measured the size of the largest ethnic group, which is critical in his argument, but I do find that greater ethnic heterogeneity within the context of a larger population reduces the risk of war recurrence and residual violence. This is consistent with Bates.

89 Bates (fn. 47), 28. The dangers of the process of democratization, as opposed to the end goal of democracy, should not be underestimated. On the potential of regime transitions, including democratic transitions, to create civil war, see Hegre et al. (fn. 65).

90 This correlation between GDP and war recurrence may seem counterintuitive since we saw that higher GDP is correlated with higher democracy, which is negatively correlated with civil war. The impact of GDP is ambiguous because GDP can be a proxy both for the country's overall development level, which should be positively associated with peace, and for “loot,” inciting new wars; see Collier and Hoeffler (fn. 45).

91 Despite the fact that this study looks only at cases where war has already taken place, the results on the impact of ethnic heterogeneity are compatible with studies of initial war occurrence, in that ethnic heterogeneity seems to increase the risk of war at first, but as the degree of heterogeneity increases, that risk declines. In my analysis, however, this effect has not been statistically significant.

92 Such a strategy, however, might indirectly support political repression, so it must be carefully and selectively applied and militaries should integrate the rebel army if possible.

93 The choice of estimator depends on the number of observations, the degree of identification of the model, the number of potentially endogenous variables, and the goodness of fit of the first-stage equation. See Bollen, Guilkey, and Mroz (fn. 76).

94 Use of this method is strictly based on attaining an R2 no smaller than 10 percent in equation 1. In my case, the R2 was higher than 30 percent. Further, Bollen, Guilkey and Mroz (fn. 76) discuss evidence from Monte Carlo simulations that suggest that the models' identification must be less than 75 percent for the two-step probit estimator to be preferable to the simple probit (i.e., the overlapping variables in the two equations must be fewer than three-fourths of the total number of right-hand-side variables in the structural equation).

95 Amemiya, T., “The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model,” Econometrica 45 (1978).Google Scholar

96 See Bollen Guilkey, and Mroz (fn. 76); and Tauchen, G., “Diagnostic Testing and Evaluation of Maximum Likelihood Models,” Journal of Econometrics 30 (1985).CrossRefGoogle Scholar Formulas to compute efficient standard errors can be found in Maddala (fn. 76), and a method to estimate the asymptotically efficient covariance matrix when the model is overidentified has been developed by Amemiya (fn. 95). Alvarez and Butterfield (fn. 76) use bootstrapping to obtain estimates of the correct standard errors.

97 Bollen, Guilkey and Mroz (fn. 76) find this to be the best-performing exogeneity test.