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A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix

The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so-called [Formula: see text] issue. Probably, the aprioristic approach is not the best solution although, presently, there are few alternatives for the use...

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Detalles Bibliográficos
Autores principales: Herrera, Marcos, Mur, Jesus, Ruiz, Manuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514642/
https://www.ncbi.nlm.nih.gov/pubmed/33266875
http://dx.doi.org/10.3390/e21020160
Descripción
Sumario:The practice of spatial econometrics revolves around a weighting matrix, which is often supplied by the user on previous knowledge. This is the so-called [Formula: see text] issue. Probably, the aprioristic approach is not the best solution although, presently, there are few alternatives for the user. Our contribution focuses on the problem of selecting a [Formula: see text] matrix from among a finite set of matrices, all of them considered appropriate for the case. We develop a new and simple method based on the entropy corresponding to the distribution of probability estimated for the data. Other alternatives, which are common in current applied work, are also reviewed. The paper includes a large study of Monte Carlo to calibrate the effectiveness of our approach compared to others. A well-known case study is also included.