IDEAS home Printed from https://ideas.repec.org/p/ulp/sbbeta/9912.html
   My bibliography  Save this paper

Estimation of Spatial Panel Data Models Using a Minimum Distance Estimator: Application

Author

Listed:
  • Théophile AZOMAHOU

Abstract

This paper is concerned with modelling and estimating panel data autoregressive spatial processes in the framework of minimum distance methods. A contiguity matrix based on distance between points relates observations spatially. The model is estimated in two stages. First, the cross-section parameters are consistently estimated by maximum likelihood, and a consistent asymptotic covariance matrix is computed for the second stage. Minimum distance estimators are derived under fixed slopes and all identical parameters restrictions. We used this specification to examine empirically spatial patterns of residential water demand for the French department of "Moselle", including electricity price effects.

Suggested Citation

  • Théophile AZOMAHOU, 1999. "Estimation of Spatial Panel Data Models Using a Minimum Distance Estimator: Application," Working Papers of BETA 9912, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    • Handle: RePEc:ulp:sbbeta:9912
    as

    Download full text from publisher

    File URL: http://beta.u-strasbg.fr/WP/1999/9912.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Lars Gårn Hansen, 1996. "Water and Energy Price Impacts on Residential Water Demand in Copenhagen," Land Economics, University of Wisconsin Press, vol. 72(1), pages 66-79.
    3. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
    4. James P. Ziliak & Beth A. Wilson & Joe A. Stone, 1999. "Spatial Dynamics And Heterogeneity In The Cyclicality Of Real Wages," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 227-236, May.
    5. Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
    6. Kodde, D A & Palm, Franz C & Pfann, G A, 1990. "Asymptotic Least-Squares Estimation Efficiency Considerations and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(3), pages 229-243, July-Sept.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Théophile Azomahou, 2008. "Minimum distance estimation of the spatial panel autoregressive model," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 2(1), pages 49-83, April.
    2. Théophile AZOMAHOU, 2001. "Efficient Estimation of Spatial Autoregressive Models," Working Papers of BETA 2001-05, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    3. Theophile Azomahou, 1999. "Estimation of Spatial Panel-Data Models Using a Minimum-Distance Estimator," Computing in Economics and Finance 1999 1322, Society for Computational Economics.
    4. Théophile Azomahou, 2001. "GMM Estimation of Lattice Models Using Panel Data: Application," Working Papers of BETA 2001-09, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    5. Jörg Breitung & Michael Lechner, 1996. "Estimation de modèles non linéaires sur données de panel par la méthode des moments généralisés," Économie et Prévision, Programme National Persée, vol. 126(5), pages 191-203.
    6. Crawford, Ian & Laisney, Francois & Preston, Ian, 2003. "Estimation of household demand systems with theoretically compatible Engel curves and unit value specifications," Journal of Econometrics, Elsevier, vol. 114(2), pages 221-241, June.
    7. Andi Syah Putra & Guangji Tong & Didit Okta Pribadi, 2020. "Spatial Analysis of Socio-Economic Driving Factors of Food Expenditure Variation between Provinces in Indonesia," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    8. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
    9. repec:esx:essedp:772 is not listed on IDEAS
    10. Kelejian, Harry H. & Piras, Gianfranco, 2014. "Estimation of spatial models with endogenous weighting matrices, and an application to a demand model for cigarettes," Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 140-149.
    11. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    12. Won Koh & Byoung Cheol Jung & Badi H. Baltagi & Seuck Heun Song, 2004. "Testing for Serial Correlation, Spatial Autocorrelation and Random Effects," Econometric Society 2004 Australasian Meetings 338, Econometric Society.
    13. 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.
    14. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    15. Antonio Diez de Los Rios, 2015. "A New Linear Estimator for Gaussian Dynamic Term Structure Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 282-295, April.
    16. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    17. Arnab Bhattacharjee & Sean Holly, 2013. "Understanding Interactions in Social Networks and Committees," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(1), pages 23-53, March.
    18. Lee, Lung-fei, 2007. "The method of elimination and substitution in the GMM estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 140(1), pages 155-189, September.
    19. Sadat Reza & Puneet Manchanda & Juin-Kuan Chong, 2021. "Identification and Estimation of Endogenous Peer Effects Using Partial Network Data from Multiple Reference Groups," Management Science, INFORMS, vol. 67(8), pages 5070-5105, August.
    20. Martellosio, Federico, 2008. "Some correlation properties of spatial autoregressions," MPRA Paper 13141, University Library of Munich, Germany.
    21. Gupta, Abhimanyu, 2019. "Estimation Of Spatial Autoregressions With Stochastic Weight Matrices," Econometric Theory, Cambridge University Press, vol. 35(2), pages 417-463, April.

    More about this item

    Keywords

    Minimum distance estimator; panel data; spatial dependence; water demand;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    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:ulp:sbbeta:9912. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bestrfr.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.