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Spatial Growth Regressions: Model Specification, Estimation and Interpretation

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  • James Lesage
  • Manfred Fischer

Abstract

Abstract We attempt to clarify a number of points regarding use of spatial regression models for regional growth analysis. We show that as in the case of non-spatial growth regressions, the effect of initial regional income levels wears off over time. Unlike the non-spatial case, long-run regional income levels depend on: own region as well as neighbouring region characteristics, the spatial connectivity structure of the regions, and the strength of spatial dependence. Given this, the search for regional characteristics that exert important influences on income levels or growth rates should take place using spatial econometric methods that account for spatial dependence as well as own and neighbouring region characteristics, the type of spatial regression model specification, and weight matrix. The framework adopted here illustrates a unified approach for dealing with these issues.

Suggested Citation

  • James Lesage & Manfred Fischer, 2008. "Spatial Growth Regressions: Model Specification, Estimation and Interpretation," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(3), pages 275-304.
    • Handle: RePEc:taf:specan:v:3:y:2008:i:3:p:275-304
    DOI: 10.1080/17421770802353758
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    References listed on IDEAS

    as
    1. James P. LeSage & R. Kelley Pace, 2008. "Spatial Econometric Modeling Of Origin‐Destination Flows," Journal of Regional Science, Wiley Blackwell, vol. 48(5), pages 941-967, December.
    2. James P. Lesage, 2008. "An Introduction to Spatial Econometrics," Revue d'économie industrielle, De Boeck Université, vol. 0(3), pages 19-44.
    3. Maria Abreu & Henri L.F. de Groot & Raymond J.G.M. Florax, 2004. "Space and Growth," Tinbergen Institute Discussion Papers 04-129/3, Tinbergen Institute.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Model uncertainty; Bayesian model averaging; Markov chain Monte Carlo model composition; spatial weight structures; C11; C21; 047; 052; R11;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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