IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

W-based versus latent variables spatial autoregressive models: evidence from Monte Carlo simulations

  • An Liu


  • Henk Folmer


  • Johan Oud


No abstract is available for this item.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Springer in its journal The Annals of Regional Science.

Volume (Year): 47 (2011)
Issue (Month): 3 (December)
Pages: 619-639

in new window

Handle: RePEc:spr:anresc:v:47:y:2011:i:3:p:619-639
Contact details of provider: Web page:

More information through EDIRC

Order Information: Web:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Michael Tiefelsdorf & Daniel A Griffith, 2007. "Semiparametric filtering of spatial autocorrelation: the eigenvector approach," Environment and Planning A, Pion Ltd, London, vol. 39(5), pages 1193-1221, May.
  2. Florax, Raymond & Folmer, Henk, 1992. "Specification and estimation of spatial linear regression models : Monte Carlo evaluation of pre-test estimators," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 405-432, September.
  3. Arnab Bhattacharjee & Chris Jensen-Butler, 2005. "Estimation of Spatial Weights Matrix in a Spatial Error Model, with an Application to Diffusion in Housing Demand," CRIEFF Discussion Papers 0519, Centre for Research into Industry, Enterprise, Finance and the Firm.
  4. 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.
  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. Raymond J.G.M. Florax & Hendrik Folmer & Sergio J. Rey, 2002. "Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology," Urban/Regional 0202001, EconWPA.
  7. 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.
  8. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 1. Model Comparison and Posterior Odds," Environment and Planning A, , vol. 27(3), pages 447-469, March.
  9. 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.
  10. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:spr:anresc:v:47:y:2011:i:3:p:619-639. 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: (Sonal Shukla)

or (Christopher F Baum)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.