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Abstract

In spatial econometrics, it is customary to specify a weighting matrix, the so-called W matrix,by choosing one matrix from a finite set of matrices. The decision is extremely important because,if the W matrix is misspecified, the estimates are likely to be biased and inconsistent. However,the procedure to select W is not well defined and, usually, it reflects the judgments of the user.In this paper, we revise the literature looking for criteria to help with this problem. Also, a newnonparametric procedure is introduced. Our proposal is based on a measure of the information,conditional entropy. We compare these alternatives by means of a Monte Carlo experiment.



Item Type: MPRA Paper -

Original Title: Selecting the W Matrix: Parametric vs. Non Parametric Approaches-

Language: English-

Keywords: Spatial weighting matrix; selection models; parametric methods; non parametric methods-

Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C15 - Statistical Simulation Methods: GeneralC - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C31 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions ; Social Interaction ModelsC - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C50 - General-





Autor: Mur Lacambra, Jesús

Fuente: https://mpra.ub.uni-muenchen.de/71181/



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