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Spatial- and Spatiotemporal-Autoregressive Probit Models of Interdependent Binary Outcomes*

Published online by Cambridge University Press:  07 September 2015

Robert J. Franzese Jr. ,
Jude C. Hays  and
Scott J. Cook
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Abstract

Spatial/spatiotemporal interdependence—that is, that outcomes, actions or choices of some unit-times depend on those of other unit-times—is substantively important and empirically ubiquitous in binary outcomes of interest across the social sciences. Estimating and interpreting binary-outcome models that incorporate such spatial/spatiotemporal dynamics directly is difficult and rarely attempted, however. This article explains the inferential challenges posed by spatiotemporal interdependence in binary-outcome models and recent advances in their estimation. Monte Carlo simulations compare the performance of one of these consistent and asymptotically efficient methods (maximum simulated likelihood, using recursive importance sampling) to estimation strategies naïve about (inter-) dependence. Finally, it shows how to calculate, in terms of probabilities of outcomes, the estimated spatial/spatiotemporal effects of (and response paths to) hypotheticals of substantive interest. It illustrates with an application to civil war in Sub-Saharan Africa.

Type
Original Articles
Information
Political Science Research and Methods , Volume 4 , Issue 1 , January 2016 , pp. 151 - 173
Copyright
© The European Political Science Association 2015 

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Footnotes

*

Robert J. Franzese, Jr. is a Professor of Political Science, University of Michigan, Ann Arbor, MI 48109 ([email protected]). Jude C. Hays is an Associate Professor of Political Science, University of Pittsburgh, Pittsburgh, PA 15260 ([email protected]). Scott J. Cook is an Assistant Professor of Political Science, Texas A&M University, College Station, TX 77840 ([email protected]). Though many more provided helpful feedback at various stages of this project, we are particularly indebted to Patrick Brandt, Scott McClurg, Eric Neumayer, Thomas Plümper, Lena Schaffer, Curt Signorino, Vera Troeger and the participants of the 2013 Spatial Models of Politics conference at Texas A&M. Thanks are also in order to the reviewers and editor for their useful comments and suggestions. All remaining errors are our own. To view supplementary material for this article, please visit http://dx.doi.org/10.1017/psrm.2015.14.

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