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Selecting the Most Adequate Spatial Weighting Matrix:A Study on Criteria

Author

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  • Herrera Gómez, Marcos
  • Mur Lacambra, Jesús
  • Ruiz Marín, Manuel

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 new nonparametric 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.

Suggested Citation

  • Herrera Gómez, Marcos & Mur Lacambra, Jesús & Ruiz Marín, Manuel, 2012. "Selecting the Most Adequate Spatial Weighting Matrix:A Study on Criteria," MPRA Paper 73700, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:73700
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    File URL: https://mpra.ub.uni-muenchen.de/73700/1/MPRA_paper_73700.pdf
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    References listed on IDEAS

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    1. Esteban Fernández-Vázquez & Matías Mayor-Fernández & Jorge Rodríguez-Vález, 2009. "Estimating Spatial Autoregressive Models by GME-GCE Techniques," International Regional Science Review, , vol. 32(2), pages 148-172, April.
    2. L W Hepple, 1995. "Bayesian techniques in spatial and network econometrics: 2. Computational methods and algorithms," Environment and Planning A, Pion Ltd, London, vol. 27(4), pages 615-644, April.
    3. P Bodson & D Peeters, 1975. "Estimation of the Coefficients of a Linear Regression in the Presence of Spatial Autocorrelation. An Application to a Belgian Labour-Demand Function," Environment and Planning A, , vol. 7(4), pages 455-472, June.
    4. Henk Folmer & Johan Oud, 2008. "How to get rid of W: a latent variables approach to modelling spatially lagged variables," Environment and Planning A, Pion Ltd, London, vol. 40(10), pages 2526-2538, October.
    5. Conley, Timothy G. & Molinari, Francesca, 2007. "Spatial correlation robust inference with errors in location or distance," Journal of Econometrics, Elsevier, vol. 140(1), pages 76-96, September.
    6. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    7. Olivier Parent & James Lesage, 2005. "Bayesian Model Averaging for Spatial Econometric Models," Post-Print hal-00375489, HAL.
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    9. Raffaele Paci & Stefano Usai, 2009. "Knowledge flows across European regions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 669-690, September.
    10. repec:taf:specan:v:7:y:2011:i:1:p:75-107 is not listed on IDEAS
    11. López, Fernando & Matilla-García, Mariano & Mur, Jesús & Marín, Manuel Ruiz, 2010. "A non-parametric spatial independence test using symbolic entropy," Regional Science and Urban Economics, Elsevier, vol. 40(2-3), pages 106-115, May.
    12. Anselin, Luc, 2002. "Under the hood Issues in the specification and interpretation of spatial regression models," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 27(3), November.
    13. S Openshaw, 1977. "Optimal Zoning Systems for Spatial Interaction Models," Environment and Planning A, , vol. 9(2), pages 169-184, February.
    14. L W Hepple, 1995. "Bayesian techniques in spatial and network econometrics: 1. Model comparison and posterior odds," Environment and Planning A, Pion Ltd, London, vol. 27(3), pages 447-469, March.
    15. Peter Burridge & Bernard Fingleton, 2010. "Bootstrap Inference in Spatial Econometrics: the J-test," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 93-119.
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    17. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
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    Citations

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    Cited by:

    1. Aliaga, Javier & Herrera, Marcos & Leguía, Daniel & Mur, Jesús & Ruiz, Manuel & Villegas, Horacio, 2011. "Spatial Causality. An application to the Deforestation Process in Bolivia," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 183-198.
    2. Jesùs Mur, 2013. "Causality, Uncertainty and Identification: Three Issues on the Spatial Econometrics Agenda," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2013(1), pages 5-27.

    More about this item

    Keywords

    Spatial weighting matrix; Nonparametric procedure; Conditional entropy;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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