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Bayesian estimation of the spatial Durbin error model with an application to voter turnout in the 2004 presidential election

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Lacombe, D. J., Holloway, G. J. and Shaughnessy, T. M. (2014) Bayesian estimation of the spatial Durbin error model with an application to voter turnout in the 2004 presidential election. International Regional Science Review, 37 (3). pp. 294-323. ISSN 1552-6925

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To link to this article DOI: 10.1177/0160017612452133

Abstract/Summary

The potential for spatial dependence in models of voter turnout, although plausible from a theoretical perspective, has not been adequately addressed in the literature. Using recent advances in Bayesian computation, we formulate and estimate the previously unutilized spatial Durbin error model and apply this model to the question of whether spillovers and unobserved spatial dependence in voter turnout matters from an empirical perspective. Formal Bayesian model comparison techniques are employed to compare the normal linear model, the spatially lagged X model (SLX), the spatial Durbin model, and the spatial Durbin error model. The results overwhelmingly support the spatial Durbin error model as the appropriate empirical model.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
ID Code:28341
Uncontrolled Keywords:spatial econometrics, spatial Durbin Error model, Bayesian inference
Publisher:Sage

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