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A nonparametric spatial regression model using partitioning estimators

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  • Olmo, Jose
  • Sanso-Navarro, Marcos

Abstract

Conventional spatial regression models are extended by modelling the spatial effects of the exogenous regressor model (SLX) as a functional coefficient. This coefficient is estimated by partitioning the domain of the spatial variable into a set of disjoint intervals and approximating the function using local Taylor expansions. The asymptotic properties of the proposed partitioning estimator are derived, and pointwise and uniform tests for the presence of spatial effects are developed. An empirical application of this work is used to study environmental Engel curves and provides strong evidence of neighbouring effects in the relationship between households’ income and the amount of pollution embodied in the goods and services they consume.

Suggested Citation

  • Olmo, Jose & Sanso-Navarro, Marcos, 2026. "A nonparametric spatial regression model using partitioning estimators," Econometrics and Statistics, Elsevier, vol. 37(C), pages 126-153.
    • Handle: RePEc:eee:ecosta:v:37:y:2026:i:c:p:126-153
    DOI: 10.1016/j.ecosta.2023.02.003
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