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Dynamic spatial panels: models, methods, and inferences

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  • J. Elhorst

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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  • J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
    • Handle: RePEc:kap:jgeosy:v:14:y:2012:i:1:p:5-28
    DOI: 10.1007/s10109-011-0158-4
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    More about this item

    Keywords

    Dynamic effects; Spatial spillover effects; Identification; Estimation methods; Stationarity conditions; C21; C23; C51;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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