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Generalizing impact computations for the autoregressive spatial interaction model

Author

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  • Thomas-Agnan, Christine
  • Margaretic, Paula
  • Laurent, Thibault

Abstract

We extend the impact decomposition proposed by LeSage and Thomas-Agnan (2015) in the spatial interaction model to a more general framework, where the sets of origins and destinations can be different, and where the relevant attributes characterizing the origins do not coincide with those of the destinations. These extensions result in three flow data configurations which we study extensively: the square, the rectangular, and the non-cartesian cases. We propose numerical simplifications to compute the impacts, avoiding the inversion of a large filter matrix. These simplifications considerably reduce computation time; they can also be useful for prediction. Furthermore, we define local measures for the intra, origin, destination and network effects. Interestingly, these local measures can be aggregated at different levels of analysis. Finally, we illustrate our methodology in a case study using remittance flows all over the world.

Suggested Citation

  • Thomas-Agnan, Christine & Margaretic, Paula & Laurent, Thibault, 2022. "Generalizing impact computations for the autoregressive spatial interaction model," TSE Working Papers 22-1357, Toulouse School of Economics (TSE), revised Feb 2023.
    • Handle: RePEc:tse:wpaper:127301
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    References listed on IDEAS

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    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. Michel Goulard & Thibault Laurent & Christine Thomas-Agnan, 2017. "About predictions in spatial autoregressive models: optimal and almost optimal strategies," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(2-3), pages 304-325, July.
    3. James P. LeSage & Manfred M. Fischer, 2016. "Spatial Regression-Based Model Specifications for Exogenous and Endogenous Spatial Interaction," Advances in Spatial Science, in: Roberto Patuelli & Giuseppe Arbia (ed.), Spatial Econometric Interaction Modelling, chapter 0, pages 15-36, Springer.
    4. James P. LeSage & Christine Thomas-Agnan, 2015. "Interpreting Spatial Econometric Origin-Destination Flow Models," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 188-208, March.
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    Cited by:

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    More about this item

    Keywords

    Impact decomposition ; local effects; spatial interaction autoregressive models; non-cartesian flow data;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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