This paper formulates and analyzes Bayesian model variants for the analysis of systems of spatial panel data with binary dependent variables. The paper focuses on cases where latent variables of cross-sectional units in an equation of the system contemporaneously depend on the values of the same and, eventually, other latent variables of other cross-sectional units. Moreover, the paper discusses cases where time-invariant effects are exogenous versus endogenous. Such models may have numerous applications in industrial economics, public economics, or international economics. The paper illustrates that the performance of Bayesian estimation methods for such models is supportive of their use with even relatively small panel data sets.

Document Type

Working Paper


Spring 1-2016


Spatial Econometrics, Panel Probit, Multivariate Probit, Bayesian Model




Working Papers Series


Econometrics | Economic Policy | Economics | Public Affairs, Public Policy and Public Administration



Additional Information

Working paper no. 187

The authors Badi Baltagi (Economics Department and Center for Policy Research); Peter H. Egger (ETH Zurich, CEPR, CESifo, GEP) and Michaela Kesina (ETH Zurich) would like to thank an anonymous reviewer, Cheng Hsiao, and Jaya Krishnakumar for numerous helpful comments on earlier versions of the manuscript. Moreover we are grateful to the participants of the Advances in Econometrics Conference 2015 at Baton Rouge and the 26th (EC)2 Conference on Theory and Practice of Spatial Econometrics.

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