Bayesian Spatial Bivariate Panel Probit Estimation

Badi Baltagi, Peter Egger and Michaela Kesina ()
Additional contact information
Michaela Kesina: ETH Zürich, KOF Konjunkturforschungsstelle

No 187, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: 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.

Keywords: Spatial Econometric; Panel Probit; Multivariate Probit (search for similar items in EconPapers)
JEL-codes: C11 C31 C35 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2016-01
New Economics Papers: this item is included in nep-ecm and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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https://surface.syr.edu/cpr/220/ (application/pdf)

Related works:
Chapter: Bayesian Spatial Bivariate Panel Probit Estimation (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:187

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