Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 7 November 2018 / Approved: 8 November 2018 / Online: 8 November 2018 (04:42:15 CET)

How to cite: Herrera, M.; Mur, J.; Ruiz Marín, M. A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix. Preprints 2018, 2018110188 (doi: 10.20944/preprints201811.0188.v1). Herrera, M.; Mur, J.; Ruiz Marín, M. A Comparison Study on Criteria to Select the Most Adequate Weighting Matrix. Preprints 2018, 2018110188 (doi: 10.20944/preprints201811.0188.v1).

Abstract

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 $\mathbf{W}$ issue. Probably, the aprioristic approach is not the best solution although, nowadays, there few alternatives for the user. Our contribution focuses on the problem of selecting a $\mathbf{W}$ matrix from among a finite set of matrices, all of them considerer 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 Monte Carlo to calibrate the effectiveness of our approach compared to the others. A well-known case study is also included.

Subject Areas

weights matrix; model selection; entropy; monte carlo

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