Spatial- and Spatiotemporal-Autoregressive Probit Models of Interdependent Binary Outcomes Academic Article uri icon


  • Spatial/spatiotemporal interdependencethat is, that outcomes, actions or choices of some unit-times depend on those of other unit-timesis 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 nave 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.

published proceedings


altmetric score

  • 1

author list (cited authors)

  • Franzese, R., Hays, J. C., & Cook, S. J.

citation count

  • 19

complete list of authors

  • Franzese, Robert J Jr||Hays, Jude C||Cook, Scott J

publication date

  • January 1, 2016 11:11 AM