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Challenges to Inference in the Study of Crisis Bargaining*

Published online by Cambridge University Press:  16 March 2015

Philip Arena  and
Kyle A. Joyce
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Abstract

The possibility that actors strategically condition their behavior on partially unobservable factors poses a grave challenge to causal inference, particularly if only some of the actors whose behavior we analyze are at risk of experiencing the outcome of interest. We present a crisis bargaining model that indicates that targets can generally prevent war by arming. We then create a simulated data set where the model is assumed to perfectly describe interactions for those states engaged in crisis bargaining, which we assume most pairs of states are not. We further assume researchers cannot observe which states are engaged in crisis bargaining, although observable variables might serve as proxies. We demonstrate that a naïve design would falsely (and unsurprisingly) indicate a positive relationship between arming and war. More importantly, we then evaluate the performance of matching, instrumental variables, and statistical backwards induction. The latter two show some promise, but matching fares poorly.

Type
Original Articles
Information
Political Science Research and Methods , Volume 3 , Issue 3 , September 2015 , pp. 569 - 587
Copyright
© The European Political Science Association 2015 

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Footnotes

*

Philip Arena, Visiting Assistant Professor of Political Science, Department of Political Science, University of Rochester, Harkness Hall, Rochester, NY 14627 ([email protected]). Kyle A. Joyce, Assistant Professor of Political Science, Department of Political Science, University of California, Davis One Shields Ave., 469 Kerr Hall, Davis, CA 95616 ([email protected]). The authors thank Amber Boydstun, Daina Chiba, Sean Gailmard, Heather McKibben, Randy Siverson, Zeev Maoz, Jamie Monogan III, Bill Reed, Toby Rider, Jas Sekhon, and Curt Signorino for valuable comments. The authors also thank Matt Buttice for research assistance. This article also benefited from comments provided by the participants at EITM (2010) and attendees of the Annual Meeting of the Society for Political Methodology (2010). To view supplementary material for this article, please visit http://dx.doi.org/10.1017/psrm.2014.42

References

The Age . 2012. ‘India’s Dam Plans Anger Pakistan, Symbolise Global Water Woes’. The Age, 19 May.Google Scholar
Angrist, Joshua, and Pischke, Jörn-Steffen. 2009. Mostly Harmless Econometrics: An Empiricist’s Companion . Princeton, NJ: Princeton University Press.Google Scholar
Bas, Muhammet Ali, Signorino, Curtis S., and Walker, Robert. 2008. ‘Statistical Backwards Induction: A Simple Method for Estimating Recursive Strategic Models’. Political Analysis 16(1):21–40.Google Scholar
Bennett, D. Scott, and Stam, Allan C.. 2004. The Behavioral Origins of War. Ann Arbor, MI: University of Michigan Press.Google Scholar
Bound, John, Jaeger, David, and Baker, Regina. 1995. ‘Problems with Instrumental Variable Estimation When the Correlation Between Instruments and the Endogenous Explanatory Variable is Weak’. Journal of the American Statistical Association 90(430):443–450.Google Scholar
Clarke, Kevin. 2009. ‘Return of the Phantom Menace: Omitted Variable Bias in Political Research’. Conflict Management and Peace Science 26(1):46–66.Google Scholar
Freedman, David, and Sekhon, Jasjeet. 2010. ‘Endogeneity in Probit Response Models’. Political Analysis 18(2):138–150.Google Scholar
Gibler, Douglas, Rider, Toby J., and Hutchison, Marc. 2005. ‘Taking Arms Against a Sea of Troubles: Conventional Arms Races During Periods of Rivalry’. Journal of Peace Research 42(2):131–147.Google Scholar
Imai, Kosuke, King, Gary, and Lau, Olivia. 2008. ‘Toward a Common Framework for Statistical Analysis and Development’. Journal of Computational and Graphical Statistics 17(4):892–913.Google Scholar
Jones, Daniel, Bremer, Stuart, and Singer, J. David. 1996. ‘Militarized Interstate Disputes, 1816-1992: Rationale, Coding Rules, and Empirical Patterns’. Conflict Management and Peace Science 15(2):163–213.Google Scholar
Lemke, Douglas, and Reed, William. 2001. ‘The Relevance of Politically Relevant Dyads’. Journal of Conflict Resolution 45(1):126–144.Google Scholar
Lewis, Jeffrey, and Schultz, Kenneth. 2003. ‘Revealing Preferences: Empirical Estimation of a Crisis Bargaining Game with Incomplete Information’. Political Analysis 11(4):345–367.Google Scholar
Reuters . 2012. ‘Thirsty South Asia’s River Rifts Threaten “Water Wars”’. Reuters, 25 July.Google Scholar
Rider, Toby J., Findley, Michael G., and Diehl, Paul F.. 2011. ‘Just Part of the Game? Arms Races, Rivalry, and War’. Journal of Peace Research 48(1):85–100.Google Scholar
Sekhon, Jasjeet S. 2008. ‘The Neyman-Rubin Model of Causal Inference and Estimation via Matching Methods’. In Janet M. Box-Steffensmeier, Henry E. Brady and David Collier (eds), The Oxford Handbook of Political Methodology. 271–299. New York, NY: Oxford University Press.Google Scholar
Sekhon, Jasjeet S.. 2009. ‘Opiates for the Matches: Matching Methods for Causal Inference’. Annual Review of Political Science 12:487–508.Google Scholar
Sekhon, Jasjeet S.. 2011. ‘Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching Package for R’. Journal of Statistical Software 42(7):1–52.Google Scholar
Signorino, Curtis S. 1999. ‘Strategic Interaction and the Statistical Analysis of International Conflict’. American Political Science Review 93(2):279–298.Google Scholar
Signorino, Curtis S.. 2003. ‘Structure and Uncertainty in Discrete Choice Models’. Political Analysis 11(4):316–344.Google Scholar
Signorino, Curtis S., and Yilmaz, Kuzey. 2003. ‘Strategic Misspecification in Regression Models’. American Journal of Political Science 47(3):551–566.Google Scholar
Slantchev, Branislav. 2011. Military Threats: The Costs of Coercion and the Price of Peace. New York, NY: Cambridge University Press.Google Scholar
Sovey, Allison J., and Green, Donald P.. 2011. ‘Instrumental Variables Estimation in Political Science: A Reader’s Guide’. American Journal of Political Science 55(1):188–200.Google Scholar
Voice of America . 2014. ‘China to Start Regular Patrols From Disputed South China Sea Island’. Voice of America, 21 January.Google Scholar
Wand, Jonathan. 2006. ‘Comparing Models of Strategic Choice: The Role of Uncertainty and Signaling’. Political Analysis 14(1):101–120.Google Scholar
Whang, Taehee. 2010. ‘Empirical Implications of Signaling Models: Estimation of Belief Updating in International Crisis Bargaining’. Political Analysis 18(3):381–402.Google Scholar
Xiang, Jun. 2010. ‘Relevance as a Latent Variable in Dyadic Analysis of Conflict’. Journal of Politics 72(2):484–498.Google Scholar
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