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Estimating Spatial Autoregressive Models by GME-GCE Techniques

Author

Listed:
  • Esteban Fernández-Vázquez

    (University of Oviedo, Oviedo, Spain)

  • Matías Mayor-Fernández

    (University of Oviedo, Oviedo, Spain)

  • Jorge Rodríguez-Vález

    (BBVA Banking Group, Bilbao, Spain)

Abstract

The traditional approach to estimate spatial models bases on a preconceived spatial weights matrix to measure spatial interaction among locations. The a priori assumptions used to define this matrix are supposed to be in line with the ``true'' spatial relationships among the locations of the dataset. Another possibility consists of using some information present on the sample data to specify an empirical matrix of spatial weights. In this article we propose to estimate spatial autoregressive models by generalized maximum entropy (GME) and generalized cross entropy (GCE) econometrics. We compare some traditional methodologies with the proposed GME-GCE estimator by means of Monte Carlo simulations in several scenarios. The results show that the entropy-based estimation techniques can outperform traditional approaches under some circumstances. An empirical case is also studied to illustrate the implementation of the proposed techniques for a real-world example.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:inrsre:v:32:y:2009:i:2:p:148-172
    DOI: 10.1177/0160017608326600
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    Cited by:

    1. Jesus Mur & Marcos Herrera & Manuel Ruiz, 2011. "Selecting the W Matrix. Parametric vs Nonparametric Approaches," ERSA conference papers ersa11p1055, European Regional Science Association.
    2. Suárez Cano, Patricia & Mayor Fernández, Matías & Cueto Iglesias, Begoña, 2011. "How important is access to employment offices in Spain? An urban and non-urban perspective," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 119-140.
    3. Fernández Vázquez, Esteban, 2011. "Updating weighting matrices by Cross-Entropy," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 21, pages 53-69.
    4. Paelinck, Jean & Mur, Jesús & Trivez, F. Javier, 2015. "Modelos para datos espaciales con estructura transversal o de panel. Una revisión/Models for Spatial Data with Panel or Cross-Sectional Structure. A Review," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 7-30, Enero.
    5. Angulo, Ana & Burridge, Peter & Mur, Jesús, 2018. "Testing for breaks in the weighting matrix," Regional Science and Urban Economics, Elsevier, vol. 68(C), pages 115-129.
    6. Herrera Gómez, Marcos & Mur Lacambra, Jesús & Ruiz Marín, Manuel, 2011. "¿Cuál matriz de pesos espaciales?. Un enfoque sobre selección de modelos [Which spatial weighting matrix? An approach for model selection]," MPRA Paper 37585, University Library of Munich, Germany.
    7. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    8. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    9. Elżbieta Antczak, 2018. "Building W Matrices Using Selected Geostatistical Tools: Empirical Examination and Application," Stats, MDPI, vol. 1(1), pages 1-22, September.
    10. Jesús Mur & Jean Paelinck, 2011. "Deriving the W-matrix via p-median complete correlation analysis of residuals," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(2), pages 253-267, October.
    11. Herrera Gómez, Marcos & Cid, Juan Carlos & Paz, Jorge Augusto, 2012. "Introducción a la econometría espacial: Una aplicación al estudio de la fecundidad en la Argentina usando R [Introduction to Spatial Econometrics: An application to the study of fertility in Argent," MPRA Paper 41138, University Library of Munich, Germany.
    12. Jes?s Mur, 2013. "Causality, Uncertainty and Identification: Three Issues on the Spatial Econometrics Agenda," SCIENZE REGIONALI, FrancoAngeli Editore, vol. 2013(1), pages 5-27.
    13. Esteban Fernandez-Vazquez, 2011. "Estimating spatial weighting matrices in cross-regressive models by entropy techniques," ERSA conference papers ersa10p503, European Regional Science Association.
    14. Maté, María Luz. & Hernández, Ginés. & Sánchez, Javier. & Mínguez, Antonio., 2013. "¿Hay efectos de interacción regional en el comportamiento financiero de las PyME?," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(320), pages 841-867, octubre-d.
    15. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
    16. 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.
    17. Jesus Mur & Antonio Paez, 2011. "Local weighting or the necessity of flexibility," ERSA conference papers ersa11p942, European Regional Science Association.

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