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Dynamic Spatial Panels: Models, Methods and Inferences

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Spatial Econometrics

Part of the book series: SpringerBriefs in Regional Science ((BRIEFSREGION))

Abstract

This chapter provides a survey of the existing literature on the specification and estimation of dynamic spatial panel data models, a collection of models for spatial panels extended to include one or more of the following variables and/or error terms: a dependent variable lagged in time, a dependent variable lagged in space, a dependent variable lagged in both space and time, independent variables lagged in time, independent variables lagged in space, serial error autocorrelation, spatial error autocorrelation, spatial-specific and time-period specific effects. The well-known Baltagi and Li (2004) panel dataset, explaining cigarette demand for 46 US states over the period 1963 to 1992, is used to investigate whether the extension of a non-dynamic to a dynamic spatial panel data specification increases the explanatory power of the model.

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Notes

  1. 1.

    If W has more than just one eigenvalue that is equal to 1, say p, the number N−1 must be adjusted to N−p.

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Authors and Affiliations

  1. Faculty of Economics and Business, University of Groningen, Nettelbosje 2, 9747 AE, Groningen, The Netherlands

    J. Paul Elhorst

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  1. J. Paul Elhorst
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Elhorst, J.P. (2014). Dynamic Spatial Panels: Models, Methods and Inferences. In: Spatial Econometrics. SpringerBriefs in Regional Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40340-8_4

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  • DOI: https://doi.org/10.1007/978-3-642-40340-8_4

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