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

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  • An Liu

    ()

  • Henk Folmer

    ()

  • Johan Oud

    ()

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Bibliographic Info

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

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

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Handle: RePEc:spr:anresc:v:47:y:2011:i:3:p:619-639

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Related research

Keywords: C13; C15; C52; R15;

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References

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  1. Raymond J.G.M. Florax & Hendrik Folmer & Sergio J. Rey, 2002. "Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology," Urban/Regional, EconWPA 0202001, EconWPA.
  2. 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.
  3. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, Blackwell, vol. 27(3), pages 247-267, November.
  4. 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.
  5. Florax, R. & Folmer, H., 1991. "Specification and Estimation of Spatial Linear Regression Models: Monte Carlo Evaluation of Pre-Test Estimator," Mansholt Working Papers 1991-4, Wageningen University, Mansholt Graduate School of Social Sciences.
  6. 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.
  7. 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.
  8. Anselin, Luc, 2002. "Under the hood Issues in the specification and interpretation of spatial regression models," Agricultural Economics: The Journal of the International Association of Agricultural Economists, International Association of Agricultural Economists, International Association of Agricultural Economists, vol. 27(3), November.
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