Showing Restraint, Signaling Resolve
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1 Showing Restraint, Signaling Resolve Coalitions, Cooperation, and Crisis Bargaining Scott Wolford Department of Government University of Texas at Austin 1 October 2013 Scott Wolford (UT Austin) Restraint & Resolve Rochester 1 / 28
2 Book Project Question (general). How does military cooperation (coalitions) affect patterns of war and peace? Costly cooperation requires costly compensation Side payments, spoils, bargaining strategies Choice of coalition partner affects Threats, signaling, and war - Today (model forthcoming at AJPS, empirics new) Conflict expansion - Forthcoming at ISQ (2014) Peace (or not) among victors - Last chapter of ms Scott Wolford (UT Austin) Restraint & Resolve Rochester 2 / 28
3 Book Project Question (general). How does military cooperation (coalitions) affect patterns of war and peace? Costly cooperation requires costly compensation Side payments, spoils, bargaining strategies Choice of coalition partner affects Threats, signaling, and war - Today (model forthcoming at AJPS, empirics new) Conflict expansion - Forthcoming at ISQ (2014) Peace (or not) among victors - Last chapter of ms Scott Wolford (UT Austin) Restraint & Resolve Rochester 2 / 28
4 Book Project Question (general). How does military cooperation (coalitions) affect patterns of war and peace? Costly cooperation requires costly compensation Side payments, spoils, bargaining strategies Choice of coalition partner affects Threats, signaling, and war - Today (model forthcoming at AJPS, empirics new) Conflict expansion - Forthcoming at ISQ (2014) Peace (or not) among victors - Last chapter of ms Scott Wolford (UT Austin) Restraint & Resolve Rochester 2 / 28
5 Research Question Question (specific). How do coalition partners affect the probability of war? (Possible) answer: Maybe they affect signaling. Skittish partners often blamed for weak signals... Fearon 1997, Russett 1963, Lake 2011 Christensen 2011, Byman & Waxman 2002 But not all weak threats are dangerous: Kosovo 1999 Berlin 1961 Scott Wolford (UT Austin) Restraint & Resolve Rochester 3 / 28
6 Research Question Question (specific). How do coalition partners affect the probability of war? (Possible) answer: Maybe they affect signaling. Skittish partners often blamed for weak signals... Fearon 1997, Russett 1963, Lake 2011 Christensen 2011, Byman & Waxman 2002 But not all weak threats are dangerous: Kosovo 1999 Berlin 1961 Scott Wolford (UT Austin) Restraint & Resolve Rochester 3 / 28
7 Defining Concepts What are military coalitions? 2 states that make a joint threat of war in a crisis Not necessarily (indeed rarely) formal allies Coding rules ICB triggering entity + military involvement + prior to war Subjective review can remove, not add Scott Wolford (UT Austin) Restraint & Resolve Rochester 4 / 28
8 Coalitions and crisis escalation, Escalates to war Coalition No Yes Total Pr(war) No Yes Total χ 2 (1) = , p = Scott Wolford (UT Austin) Restraint & Resolve Rochester 5 / 28
9 Decomposition Analysis Pr(War) = 1 Probit Decomposition Coalition (0.222) CINC (1.489) (0.033) CINC (1.529) (0.012) Relative Capabilities (0.328) (0.016) Significance levels: : 10%, : 5%, and : 1% Scott Wolford (UT Austin) Restraint & Resolve Rochester 6 / 28
10 What s missing? Divergent preferences: skittish partners Costs of war fall differently across coalition members Domestic politics Geography Valuation of stakes Divergent preferences over mobilization/escalation Partner s willingness to cooperate Costs leader pays to secure cooperation Scott Wolford (UT Austin) Restraint & Resolve Rochester 7 / 28
11 A Theory of Coalitions and Crisis Bargaining Threats (signals), bargaining, military cooperation Leader, (potential) Partner, Target T uncertain over L s resolve (valuation of stakes) Mobilization (high, low) affects military balance Costly up front for L Direct impact on P s costs for war Partner can refuse cooperation in event of war (endogenous coalition formation) Scott Wolford (UT Austin) Restraint & Resolve Rochester 8 / 28
12 Game Tree L φ v L m L m L m L T 1 x 0 L accept reject (xv L m L, (1 x)v T, xv P ) (u i (coalitional war)) cooperate P N defect (u i (bilateral war)) 1 φ v L L m L m L m L T 1 x 0 L accept reject (xv L m L, (1 x)v T, xv P ) (u i (coalitional war)) cooperate P defect (u i (bilateral war)) threat crisis bargaining cooperation Scott Wolford (UT Austin) Restraint & Resolve Rochester 9 / 28
13 Sets of Equilibria Mobilization levels (high, low) may signal resolve Three cases: Two players No partner available Committed (i.e. non-skittish) partner P cooperates for all mobilization levels Skittish partner P cooperates iff low mobilization Scott Wolford (UT Austin) Restraint & Resolve Rochester 10 / 28
14 Two Player & Committed Partner Equilibria Separating Resolute L mobilizes high, irresolute low Target does not risk war Semi-separating Irresolute may bluff (high) Target may risk war Scott Wolford (UT Austin) Restraint & Resolve Rochester 11 / 28
15 Skittish Partner Equilibria Separating Resolute L mobilizes high, irresolute low Target does not risk war Semi-separating Irresolute may bluff (high) Target may risk war Pooling Both types choose low mobilization Target risks war Scott Wolford (UT Austin) Restraint & Resolve Rochester 12 / 28
16 The Equilibrium Space v L m T Two Players & Three Players w/committed Partner v L m T Three Players w/skittish Partner ˆmT separating separating mt semi-separating m T semi-separating m T pooling (m L ) c L c L Scott Wolford (UT Austin) Restraint & Resolve Rochester 13 / 28
17 Equilibrium Summary When P is skittish... Coalitions form around moderated threats When target is strong (bluffing expensive), preserving cooperation is disincentive to bluff partner s presence reduces probability of war When target is weak (bluffing cheap), preserving cooperation is disincentive to separate partner s presence increases probability of war Scott Wolford (UT Austin) Restraint & Resolve Rochester 14 / 28
18 Empirical Implications Probability of war by partner presence and target strength PrHWarL No Coalition PrHWarL mt Coalition w Skittish Partner mt 0 (Simulation based on equilibrium constraints and mixing probabilities) Scott Wolford (UT Austin) Restraint & Resolve Rochester 15 / 28
19 Expectations Assuming skittish partner in the coalition: H.1 In bilateral crises, the probability of war decreases slightly (if at all) in target military capabilities. H.2 In coalitional crises, the probability war decreases sharply in target military capabilities. Scott Wolford (UT Austin) Restraint & Resolve Rochester 16 / 28
20 Empirical Model Sample: Directed crisis-side dyads (ICB), 1 v. 2 DV: Escalation to war IVs: Coalition 1, CINC T Controls: CINC 1, number 1, min distance 1, % allied 1, min polity 1, UNSC support 1, USA 1, Cold War Errors: SEs clustered by crisis Pr(War = 1) =Φ(α + β 1 Coalition 1 + β 2 CINC T + β 3 (Coalition 1 CINC T ) + βx i + ε i ) Scott Wolford (UT Austin) Restraint & Resolve Rochester 17 / 28
21 Empirical Results Pr(War = 1) Variable Model 1 Model 2 No Interaction With Interaction Coalition (0.32) 0.83 (0.33) CINC T -.57 (1.97) 0.40 (1.88) Coalition 1 CINC T (9.69) N χ 2 (d.f.) (10) (11) Significance levels: : 10%, : 5%, and : 1% Scott Wolford (UT Austin) Restraint & Resolve Rochester 18 / 28
22 Predicted Probabilities of War No Coalition Coalition Predicted Probability of War Predicted Probability of War Target Military Capabilities Target Military Capabilities Scott Wolford (UT Austin) Restraint & Resolve Rochester 19 / 28
23 Conclusion The tradeoff: signaling resolve, showing restraint Coalitional politics affect the probability of war Intra-coalitional politics target characteristics Clarifies (abundant) conjectures about third parties Neither always bad... nor always good Logic behind coalition formation Weak threats can tie hands against risky bluffing Scott Wolford (UT Austin) Restraint & Resolve Rochester 20 / 28
24 Conclusion Questions? Scott Wolford (UT Austin) Restraint & Resolve Rochester 21 / 28
25 Book Outline 1 Introduction 2 Why Coalitions? Coalitions are unique phenomena, and I ve got data! 3 Coalition Formation Prefer Ps w/similar prefs, less selective as Ps powerful 4 Coalitions, Signaling, and War Coalition partners war w/weak targets, w/strong targets 5 Coalitional Durability and Conflict Expansion Diversity balancing vs strong coalitions, vs weak ones 6 Conclusion Diversity hastens breakdown of victorious coalitions Scott Wolford (UT Austin) Restraint & Resolve Rochester 22 / 28
26 Payoffs: Coalitional War ( ml + m P EU L (coalitional war) = m L + m L + m P + m T ( ) ml + m P EU P (coalitional war) = v P c P m L m L + m P + m T ( m T EU T (coalitional war) = m L + m P + m T ) v T c T ) v L c L Scott Wolford (UT Austin) Restraint & Resolve Rochester 23 / 28
27 Payoffs: Bilateral War EU L (bilateral war) = m L + ( ml m L + m T ( ) ml EU P (bilateral war) = v P m L + m T ( ) mt EU T (bilateral war) = v T c T m L + m T ) v L c L Scott Wolford (UT Austin) Restraint & Resolve Rochester 24 / 28
28 Defining skittishness Cooperate if m L = m L, or ( ml + m P m L + m P + m T ) ( ) ml v P c P m L v P, m L + m T and defect if ml = m L, or ( ) ( ml ml + m P v P > m L + m T m L + m P + m T True when c l P c P < c h P. ) v P c P m L. Scott Wolford (UT Austin) Restraint & Resolve Rochester 25 / 28
29 Equilibrium probabilities of war Where v L = v L w/prob φ, h is prob that v L bluffs, and r is prob that T risks war given m L = m L, No coalition (or committed partner): Pr(war) = φhr when mt < ˆm T. Pr(war) = 0 when mt ˆm T. Coalition w/skittish partner: Pr(war) = φ when mt < m T. Pr(war) = φhr when m T m T < m T. Pr(war) = 0 when mt m T. Scott Wolford (UT Austin) Restraint & Resolve Rochester 26 / 28
30 Full Empirical Results CHAPTER 4. COALITIONS, CRISIS BARGAINING, AND WAR 79 Table 4.1: Probit models of crisis escalation, Pr(War = 1) Variable Model 1 Model 2 No Interaction With Interaction Theoretical variables Coalition (0.32) 0.83 (0.33) CINC T -.57 (1.97) 0.40 (1.88) Coalition 1 CINC T (9.69) Control variables CINC (1.98) 2.95 (2.05) Number (0.10) 0.17 (0.11) Minimum Distance (0.00) 0.00 (0.00) Percent Allied (0.62) (0.62) Low Democracy (0.02) (0.02) UNSC Support (0.34) 0.24 (0.33) United States (0.54) (0.52) Cold War 0.43 (0.29) 0.43 (0.29) Intercept (0.30) (0.31) Model Statistics N Log-likelihood (d.f.) (10) (11) Significance levels: : 10%, : 5%, and : 1% power on the probability that the crisis escalates to war. The coefficient on the interaction term Scott Wolford (UT Austin) Restraint & Resolve Rochester 27 / 28
31 Decomposition Analysis Pr(War) = 1 Probit Decomposition Coalition (0.222) CINC (1.489) (0.033) CINC (1.529) (0.012) Relative Capabilities (0.328) (0.016) Number (0.115) (0.016) Intercept (0.227) Pr(War No Coalition) Pr(War Coalition) Difference Total Explained Significance levels: : 10%, : 5%, and : 1% Scott Wolford (UT Austin) Restraint & Resolve Rochester 28 / 28
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