IDEAS home Printed from https://ideas.repec.org/a/ris/invreg/0031.html
   My bibliography  Save this article

Updating weighting matrices by Cross-Entropy

Author

Listed:
  • Fernández Vázquez, Esteban

    () (Department of Applied Economics-University of Oviedo)

Abstract

The classical approach to estimate spatial models lays on the choiceof a spatial weights matrix that reflects the interactions among locations. The ruleused to define this matrix is supposed to be the most similar to the «true» spatialrelationships, but for the researcher is difficult to elucidate when the choice of thismatrix is right and when is wrong. This key step in the process of estimating spatialmodels is a somewhat arbitrary choice, as Anselin (2002) pointed out, and itcan be seen as one of their main methodological problems. This note proposes notimposing the elements of the spatial matrix but estimating them by cross entropy(CE) econometrics. Since the spatial weight matrices are often row-standardized,each one of their rows can be approached as probability distributions. EntropyEconometrics (EE) techniques are a useful tool for recovering unknown probabilitydistributions and its application allows the estimation of the elements of thespatial weights matrix instead of the imposition by researcher. Hence, the spatiallag matrix is not a matter of choice for researcher but of empirical estimation byCE. We compare classical with CE estimators by means of Monte Carlo simulationsin several scenarios on the true spatial effect. The results show that CrossEntropy estimates outperform the classical estimates, especially when the specificationof the weights matrix is not similar to the true one. This result points to CEas a helpful technique to reduce the degree of arbitrariness imposed in the estimationof spatial models.

Suggested Citation

  • 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.
  • Handle: RePEc:ris:invreg:0031
    as

    Download full text from publisher

    File URL: http://www.aecr.org/images/ImatgesArticles/2012/3/05_ESTEBAN.pdf
    File Function: Full text
    Download Restriction: no

    References listed on IDEAS

    as
    1. Enrique López-Bazo & Esther Vayá & Manuel Artís, 2004. "Regional Externalities And Growth: Evidence From European Regions," Journal of Regional Science, Wiley Blackwell, vol. 44(1), pages 43-73.
    2. 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.
    3. Douglas Holtz-Eakin & Amy Schwartz, 1995. "Spatial productivity spillovers from public infrastructure: Evidence from state highways," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 2(3), pages 459-468, October.
    4. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 531-542.
    5. 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.
    6. Pedro Cantos & Mercedes Gumbau‐Albert & Joaquín Maudos, 2003. "Transport infrastructures, spillover effects and regional growth: evidence of the Spanish case," Transport Reviews, Taylor & Francis Journals, vol. 25(1), pages 25-50, December.
    7. Case, Anne C. & Rosen, Harvey S. & Hines, James Jr., 1993. "Budget spillovers and fiscal policy interdependence : Evidence from the states," Journal of Public Economics, Elsevier, vol. 52(3), pages 285-307, October.
    8. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    9. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    10. Iain Fraser, 2000. "An application of maximum entropy estimation: the demand for meat in the United Kingdom," Applied Economics, Taylor & Francis Journals, vol. 32(1), pages 45-59.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Spatial econometrics; cross entropy econometrics; spatial models specifications; Monte Carlo simulations;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:invreg:0031. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Julieta Llungo-Ortíz). General contact details of provider: http://edirc.repec.org/data/aecrrea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.