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On the Spatial Correlation of International Conflict Initiation and Other Binary and Dyadic Dependent Variables

We examine spatially correlated interregional flows measured as binary choice outcomes. Since the dependent variable is not only binary and dyadic, but also spatially correlated, we propose a spatial origin-destination probit model and a Bayesian estimation methodology that avoids inconsistent maximum likelihood estimates. We apply the model to militarized interstate dispute initiations, observations of which are clearly binary and dyadic and which may be spatially correlated due to their geographic distribution. Using a cross-section of 26 European countries drawn from the period leading up to WWII, we find empirical evidence for target-based spatial correlation and sizable network effects resulting from the correlation. In particular, we find that the effect of national military capability of the potential aggressor, which is a significant determinant of conflict in either case, is overstated in a benchmark model that ignores spatial correlation. This effect is further differentiated by the geographic location of a country.

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Paper provided by Department of Economics, University of Missouri in its series Working Papers with number 1306.

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Length: 41 pgs.
Date of creation: 24 May 2013
Date of revision:
Publication status: Published in Regional Science and Urban Economics 2014
Handle: RePEc:umc:wpaper:1306
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  1. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
  2. James P. LeSage & Christine Thomas-Agnan, 2015. "Interpreting Spatial Econometric Origin-Destination Flow Models," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 188-208, 03.
  3. Vassilis A. Hajivassiliou & Daniel L. McFadden, 1998. "The Method of Simulated Scores for the Estimation of LDV Models," Econometrica, Econometric Society, vol. 66(4), pages 863-896, July.
  4. Hess, Gregory D. & Orphanides, Athanasios, 2001. "Economic conditions, elections, and the magnitude of foreign conflicts," Journal of Public Economics, Elsevier, vol. 80(1), pages 121-140, April.
  5. Manfred M. Fischer & Thomas Scherngell & Eva Jansenberger, 2005. "The Geography of Knowledge Spillovers between High-Technology Firms in Europe - Evidence from a Spatial Interaction Modelling Perspective," ERSA conference papers ersa05p5, European Regional Science Association.
  6. Stuart A. Bremer, 1992. "Dangerous Dyads," Journal of Conflict Resolution, Peace Science Society (International), vol. 36(2), pages 309-341, June.
  7. Corinne Autant-Bernard & James Lesage, 2009. "Quantifying knowledge spillovers using spatial econometric models," Post-Print hal-00430618, HAL.
  8. James P. LeSage & Manfred M. Fischer & Thomas Scherngell, 2007. "Knowledge spillovers across Europe: Evidence from a Poisson spatial interaction model with spatial effects," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 393-421, 08.
  9. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
  10. Smirnov, Oleg A., 2010. "Modeling spatial discrete choice," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 292-298, September.
  11. Philippe Robert-Demontrond & R. Ringoot, 2004. "Introduction," Post-Print halshs-00081823, HAL.
  12. Seung-Whan Choi, 2010. "Legislative Constraints: A Path to Peace?," Journal of Conflict Resolution, Peace Science Society (International), vol. 54(3), pages 438-470, June.
  13. D. Scott Bennett & Allan C. Stam, 2000. "Research Design and Estimator Choices in the Analysis of Interstate Dyads," Journal of Conflict Resolution, Peace Science Society (International), vol. 44(5), pages 653-685, October.
  14. Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
  15. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin-Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967.
  16. HÃ¥vard Hegre & John R Oneal & Bruce Russett, 2010. "Trade does promote peace: New simultaneous estimates of the reciprocal effects of trade and conflict," Journal of Peace Research, Peace Research Institute Oslo, vol. 47(6), pages 763-774, November.
  17. L. Randall Wray & Stephanie Bell, 2004. "Introduction," Chapters, in: Credit and State Theories of Money, chapter 1 Edward Elgar.
  18. King, Gary, 2001. "Proper Nouns and Methodological Propriety: Pooling Dyads in International Relations Data," International Organization, Cambridge University Press, vol. 55(02), pages 497-507, March.
  19. Daniel M. Jones & Stuart A. Bremer & J. David Singer, 1996. "Militarized Interstate Disputes, 1816–1992: Rationale, Coding Rules, and Empirical Patterns," Conflict Management and Peace Science, Peace Science Society (International), vol. 15(2), pages 163-213, September.
  20. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
  21. Anselin, Luc, 2002. "Under the hood Issues in the specification and interpretation of spatial regression models," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 27(3), November.
  22. J. Barkley Rosser, 2009. "Introduction," Chapters, in: Handbook of Research on Complexity, chapter 1 Edward Elgar.
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