IDEAS home Printed from https://ideas.repec.org/p/ags/aaea09/49491.html
   My bibliography  Save this paper

Information Theoretic Estimators of the First-Order Spatial Autoregressive Model

Author

Listed:
  • Perevodchikov, Evgeniy V.

Abstract

Information theoretic estimators for the first-order autoregressive model are considered. Extensive Monte Carlo experiments are used to compare finite sample performance of traditional and three information theoretic estimators including maximum empirical likelihood, maximum empirical exponential likelihood, and maximum log Euclidean likelihood. It is found that information theoretic estimators are robust to specification of spatial autocorrelation and dominate traditional estimators in finite samples. Finally, the proposed estimators are applied to an illustrative example of hedonic housing pricing.

Suggested Citation

  • Perevodchikov, Evgeniy V., 2009. "Information Theoretic Estimators of the First-Order Spatial Autoregressive Model," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49491, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea09:49491
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/49491
    Download Restriction: no

    More about this item

    Keywords

    information theoretic estimators; the first-order spatial autoregressive model; Research Methods/ Statistical Methods;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aaea09:49491. 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: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaeaaea.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.

    We have no references for this item. You can help adding them by using 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.