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Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows

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  • James Paul Lesage
  • Wolfgang Polasek

Abstract

Abstract We use a spatial econometric extension of the traditional regression-based gravity model to model commodity flows, focusing on a formal methodology for incorporating information regarding the highway network into the spatial connectivity structure of the spatial autoregressive econometric model. We show that our simple approach to incorporating this information in the model produces improved model fit and higher likelihood function values. Empirical estimates of the relative importance of the different types of origin–destination connectivity between regions indicates that the strongest spatial autoregressive effects arise when both origin and destination regions have neighbouring regions located on the highway network.

Suggested Citation

  • James Paul Lesage & Wolfgang Polasek, 2008. "Incorporating Transportation Network Structure in Spatial Econometric Models of Commodity Flows," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 225-245.
    • Handle: RePEc:taf:specan:v:3:y:2008:i:2:p:225-245
    DOI: 10.1080/17421770801996672
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    More about this item

    Keywords

    Commodity flows; spatial autoregression; corridor weights; C11; C13; C21; R11;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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