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Testing Impact Measures in Spatial Autoregressive Models

Author

Listed:
  • Giuseppe Arbia
  • Anil K. Bera
  • Osman DoÄŸan
  • Süleyman TaÅŸpınar

Abstract

Researchers often make use of linear regression models in order to assess the impact of policies on target outcomes. In a correctly specified linear regression model, the marginal impact is simply measured by the linear regression coefficient. However, when dealing with both synchronic and diachronic spatial data, the interpretation of the parameters is more complex because the effects of policies extend to the neighboring locations. Summary measures have been suggested in the literature for the cross-sectional spatial linear regression models and spatial panel data models. In this article, we compare three procedures for testing the significance of impact measures in the spatial linear regression models. These procedures include (i) the estimating equation approach, (ii) the classical delta method, and (iii) the simulation method. In a Monte Carlo study, we compare the finite sample properties of these procedures.

Suggested Citation

  • Giuseppe Arbia & Anil K. Bera & Osman DoÄŸan & Süleyman TaÅŸpınar, 2020. "Testing Impact Measures in Spatial Autoregressive Models," International Regional Science Review, , vol. 43(1-2), pages 40-75, January.
    • Handle: RePEc:sae:inrsre:v:43:y:2020:i:1-2:p:40-75
    DOI: 10.1177/0160017619826264
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    References listed on IDEAS

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    3. Deng, Mingyu & Wang, Mingxi, 2022. "Artificial regression test diagnostics for impact measures in spatial models," Economics Letters, Elsevier, vol. 217(C).
    4. Benjamin Montmartin & Marcos Herrera-Gomez, 2022. "Imitative Pricing: The Importance of Neighborhood Effects in Physicians' Consultation Prices," GREDEG Working Papers 2022-02, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    5. Ye Yang & Osman Dogan & Suleyman Taspinar & Fei Jin, 2023. "A Review of Cross-Sectional Matrix Exponential Spatial Models," Papers 2311.14813, arXiv.org.
    6. Montmartin, Benjamin & Herrera-Gómez, Marcos, 2023. "Spatial dependence in physicians’ prices and additional fees: Evidence from France," Journal of Health Economics, Elsevier, vol. 88(C).
    7. J. Paul Elhorst, 2022. "The dynamic general nesting spatial econometric model for spatial panels with common factors: Further raising the bar," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 42(3), pages 249-267, December.

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