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Abstract The paper discusses the standard approaches in constructing the spatial weights matrix, W, and the implications of using such approaches in terms of the potential mis-specification of W. We then look at more recent attempts to measure W in the literature, including: Bayesian (searching for ‘best fit’); non-parametric techniques; the use of spatial correlation to estimate W; other iteration techniques; and alternative approaches. Lastly, an illustration is provided based on estimating spatial lag models determining establishment level R des techniques non paramétriques; l'emploi d'une corrélation spatiale pour l’évaluation de W; des techniques d'itération diverses; et d'autres méthodes en alternative. Enfin, elle contient une illustration basée sur l'estimation de modèles à décalage spatial permettant de déterminer le niveau d’établissement de dépenses en R técnicas no paramétricas; el uso de correlación espacial para estimar W; otras técnicas de iteración; y planteamientos alternativos. Finalmente, se ofrece una ilustración basada en estimar modelos de retardo (lag) espacial que determinan el gasto en I+D a nivel de establecimiento en el Reino Unido; se descubre que matrices W construidas de forma diferente producen estimaciones diferentes de excedentes (spillovers) espaciales.
Harris et al. (Tue,) studied this question.
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