Supplemental Appendix for “Dyadic Trade, Exit Costs, and Conflict”

Timothy M. Peterson [email protected] Oklahoma State University Department of Political Science

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This appendix provides additional information regarding the construction and interpretation of dyad-year level exit cost measures. It also provides robustness check models examining MID initiation rather than event counts, as are examined in the main text.

Exit Cost Measures Differences from Crescenzi's (2003, 2005) operationalization I model the importer's (exporter's) exit costs for the flow of a given commodity using the price elasticities for that commodity and the share of each state's imports (exports) of that commodity from its dyadic partner. This modeling decision diverges from Marquez (1990), whose measures Crescenzi (2003, 3005) employs, in that I do not estimate trade elasticities by the dyad, instead calculating the import and export elasticity for each commodity, by trading state.1 I contend that a state's supply of or demand for a given commodity is independent of the states with which it trades.2 To this effect, I estimate elasticities with a series of fixed effects regressions by commodity, for each state – both as an importer and an exporter. Specifically, for each state, the models estimate the response of trade volumes imported and exported (the DVs) to price (the primary IV) across all trade partners, between 1984 and 2000. Crescenzi, utilizing Marquez's elasticity estimates, has only one elasticity and trade interaction value per directed dyad, and, as such, is able to include both of these variables as well as the interaction thereof (the latter of which is equivalent to the exit cost measure provided in this study). This operationalization is useful to examine how the influence of trade interaction varies at different levels of elasticity and vice-versa. However, as my interaction and elasticity 1 In accordance with Marquez (1990), these elasticities are constant over the time period studied. 2 There are certainly political variables that affect supply and demand (for example, distance and dyadic history of conflict); however, fixed effects account for these issues; and I control for these factors in my conflict models.

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measures vary at the commodity level, I cannot use such an operationalization in tests of conflict at the dyadic level. Furthermore, Crescenzi's model does not specify conditional measures of exit costs (i.e., an interaction of State A's exit costs with State B and B's exit costs with A), instead specifying only country-level exit cost measures. Although I could construct a weighted elasticity for each state, 3 and then include it with the state-level trade share or trade/GDP measure, interacting the two, I would then have to create a second interaction of each state's exit cost interaction term. The interpretation of this specification would be cumbersome.

MID initiation Models As a robustness check, I code two dependent variables for MID initiation; specifically, I code the initiation of any MID and fatal MIDs in order to capture the impact of exit costs on commonly used measures of conflict. I use rare events logit models to address the effect of exit costs on these dependent variables, excluding directed dyad years in which a MID is ongoing (Bennett and Stam 2000).4 MID initiation is similar to Crescenzi's (2003, 2005) “high level conflict” coding of events data, and also useful to facilitate comparison of my results with other research, given its common use in studies of trade and conflict. Other than the DV and statistical model used, these models are specified identically to Models 1 through 6. 5 Table A-1 contains Models 13 through 18, presenting rare events logit coefficients examining the impact of exit costs on MID initiation. The results of Table A-1, which utilizes the 3 However, with regard to trade share, this weighted elasticity would not account for the number of commodities traded, unlike my current specifications. I contend that the measure I present in the text is superior as, if a given state imports a large share of a given commodity from its dyadic partner, it may not matter that these imports compose only a small part of dyadic trade – particularly if the commodity holds strategic value. 4 Use of rare events logit models are justified because MID initiation is an exceedingly rare event (King and Zeng 1999), with a baseline probability equal to 0.0015. 5 Zero inflation is not modeled in my rare events logit models; however, rare events logits produce coefficients that are adjusted for the preponderance of zeros in the dependent variable (King and Zeng 1999).

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share-based exit cost measure, look generally like the results presented in the main text. However, they are distinct enough to merit further discussion. Overall, exit costs for the potential initiator generally behave as they do in count models examining high and low-level conflict events. Specifically, A's exit costs, given zero exit costs for B, are associated with increased likelihood that A initiates a MID or a fatal MID against state B in all models, generally supporting hypothesis 2. The coefficient for B's exit costs does not reach statistical significance in any model, however, suggesting that support for the causal mechanism linking the potential initiator's exit costs to dyadic MID initiation is more robust than that for the potential target's exit costs, ceteris paribus. These results, therefore, do not support hypothesis 1, contrary to the event count models.6 The exit cost interaction is negative and significant in all models, however, providing support for hypothesis 3 (further confirmed by an examination of marginal effects). Overall, Models 13 through 18 look quite similar to Models 1 through 6. Notably, the interaction effects for Models 15 and 16, examining exit costs for trade in strategic goods, follow the same pattern as those from Models 3 and 4 (as well as Models 9 and 10); the marginal effect of A's exit costs is positive when B's equal zero, but decline as B's increase, becoming negative and significant at high levels of B's exit costs. Again, these results suggest that trade in strategic commodities may sharply aggravate or pacify dyadic relationships, depending on the relative extent of exit costs. [Table A-1 about here]

6 The models presented in the text suggest a similar conclusion given that unilaterally high exit costs for the initiator lead to a higher expected count of high-conflict events in the primary models. Again, the case of World War II in the pacific supports this finding, given that it was the more vulnerable state that initiated militarized conflict.

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References Bennett, S., and A. Stam. 2000. Design and Estimator Choices in the Analysis of Interstate Dyads: When Decisions Matter.” Journal of Conflict Resolution 44(5): 653-685. Crescenzi, Mark J. C. 2003 “Economic Exit, Interdependence, and Conflict.” Journal of Politics 65(3): 809-832. Crescenzi, Mark J. C. 2005. Economic Interdependence and Conflict in World Politics. Lanham: Lexington Books. King, Gary, and Langche Zeng. 1999. “Logistic Regression in Rare Events Data.” Department of Government, Harvard University, available from http://GKing.Harvard.Edu.

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Table A-1: Exit costs and MID initiation 1985-2001; share-based measure of exit costs All commodities Strategic commodities 13: Any MID 14: Fatal 15: Any MID 16: Fatal MID MID A's exit costs 0.510*** 0.935** 0.500*** 0.907* (0.133) (0.286) (0.150) (0.390) B's exit costs 0.101 0.489 0.103 0.337 (0.132) (0.299) (0.140) (0.298) A's exit costs X B's exit costs -0.106** -0.191* -0.175* -0.521* (0.0383) (0.0885) (0.0785) (0.206) ln trade flow 0.129 -0.340** 0.0440 -0.0746 (0.0697) (0.106) (0.0317) (0.0388) Minimum GDP 0.220*** 0.260 0.296*** 0.206 (0.0654) (0.142) (0.0675) (0.137) ln Distance -0.264*** -0.314*** -0.284*** -0.360*** (0.0353) (0.0629) (0.0345) (0.0612) Capability ratio 1.825*** 1.564* 1.642*** 1.500* (0.300) (0.699) (0.264) (0.688) Polity2 in A 0.00354 0.0103 -0.00317 0.0107 (0.0202) (0.0324) (0.0214) (0.0323) Polity2 in B 0.0171 -0.0172 0.0181 -0.0149 (0.0243) (0.0402) (0.0247) (0.0392) Polity2 A X Polity2 B -0.00412** -0.00398 -0.00365* -0.00384 (0.00147) (0.00291) (0.00154) (0.00280) Alliance similarity -0.880** -1.182 -0.999** -0.864 (0.332) (0.729) (0.325) (0.690) Peace years -0.163*** -0.509*** -0.159*** -0.501*** (0.0261) (0.0699) (0.0262) (0.0703) Peace years2 0.00237*** 0.0129*** 0.00231*** 0.0126*** (0.000670) (0.00237) (0.000669) (0.00242) Peace years3 -9.32e-06* -8.58e-05*** -9.10e-06* -8.40e-05*** (3.90e-06) (2.22e-05) (3.88e-06) (2.29e-05) Constant -8.682*** -4.809 -8.336*** -5.888* (1.157) (2.549) (1.171) (2.611) Observations 164,722 164,722 Prob χ2 ≤0.0001 ≤0.0001 *** p<0.001, ** p<0.01, * p<0.05; two-tailed tests Robust standard errors in parentheses

164,722 ≤0.0001

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164,722 ≤0.0001

Non-strategic commodities 17: Any MID 18: Fatal MID 0.661*** 0.816** (0.134) (0.286) 0.245 0.303 (0.142) (0.279) -0.131** -0.182* (0.0410) (0.0913) 0.00309 -0.160* (0.0768) (0.0660) 0.283*** 0.161 (0.0687) (0.129) -0.254*** -0.312*** (0.0357) (0.0628) 1.811*** 1.637* (0.291) (0.696) 0.00587 0.0107 (0.0200) (0.0327) 0.0207 -0.0194 (0.0239) (0.0394) -0.00420** -0.00402 (0.00149) (0.00288) -0.974** -0.959 (0.333) (0.730) -0.162*** -0.505*** (0.0262) (0.0685) 0.00236*** 0.0127*** (0.000672) (0.00235) -9.28e-06* -8.43e-05*** (3.91e-06) (2.22e-05) -8.729*** -4.803 (1.142) (2.560) 164,722 ≤0.0001

164,722 ≤0.0001

Supplemental Appendix for

compose only a small part of dyadic trade – particularly if the commodity holds strategic value. 4 Use of rare events logit models are justified because MID ...

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