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Model selection strategies in a spatial setting: Some additional results

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  • Mur, Jesús
  • Angulo, Ana

Abstract

This paper continues from the discussion of Florax et al. (Florax, R., H. Folmer and S. Rey, 2003. Specification searches in spatial econometrics: the relevance of Hendry's methodology. Regional Science and Urban Economics, 33, 557-579.), regarding the properties of various specification strategies for spatial econometric models. Habitual practise has popularised a technique based on the well-known Lagrange Multipliers, characterized as a Specific-to-General approach, and which seems to give good results. In our work, we contemplate other alternatives, some of which may be seen as slight variations of this proposal, including the selection tests of Vuong (Vuong, Q., 1989. Likelihood ratio-tests for model selection and non-nested hypotheses. Econometrica, 57, 307-333.) and of Clarke (Clarke, K., 2003. Nonparametric model discrimination in international relations. Journal of Conflict Resolutions, 47, 72-93.). We also examine an approach of the General-to-Specific type, as clearly opposite to the others. The comparison of the two strategies is carried out through a Monte Carlo experiment, the results of which are quite diffuse, in the sense that we do not find conclusive evidence in favour of either of these two approaches. However, it should be recognized that the General-to-Specific strategy seems to be more robust to the existence of anomalies in the Data Generating Process.

Suggested Citation

  • Mur, Jesús & Angulo, Ana, 2009. "Model selection strategies in a spatial setting: Some additional results," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 200-213, March.
    • Handle: RePEc:eee:regeco:v:39:y:2009:i:2:p:200-213
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    1. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    2. Florax, Raymond J. G. M. & Folmer, Hendrik & Rey, Sergio J., 2003. "Specification searches in spatial econometrics: the relevance of Hendry's methodology," Regional Science and Urban Economics, Elsevier, vol. 33(5), pages 557-579, September.
    3. Luc Anselin & Raymond J. G. M. Florax, 1995. "Small Sample Properties of Tests for Spatial Dependence in Regression Models: Some Further Results," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 2, pages 21-74, Springer.
    4. Zellner, Arnold, 1978. "Jeffreys-Bayes posterior odds ratio and the Akaike information criterion for discriminating between models," Economics Letters, Elsevier, vol. 1(4), pages 337-342.
    5. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    6. David F. Hendry & Hans-Martin Krolzig, 2005. "The Properties of Automatic "GETS" Modelling," Economic Journal, Royal Economic Society, vol. 115(502), pages 32-61, March.
    7. 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.
    8. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
    9. James P. LeSage, 2004. "A Family of Geographically Weighted Regression Models," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 11, pages 241-264, Springer.
    10. James P. Lesage, 1997. "Bayesian Estimation of Spatial Autoregressive Models," International Regional Science Review, , vol. 20(1-2), pages 113-129, April.
    11. Fisher, Gordon & McAleer, Michael, 1979. "On the interpretation of the cox test in econometrics," Economics Letters, Elsevier, vol. 4(2), pages 145-150.
    12. L W Hepple, 1995. "Bayesian Techniques in Spatial and Network Econometrics: 2. Computational Methods and Algorithms," Environment and Planning A, , vol. 27(4), pages 615-644, April.
    13. Raymond J. G. M. Florax & Thomas Graaff, 2004. "The Performance of Diagnostic Tests for Spatial Dependence in Linear Regression Models: A Meta-Analysis of Simulation Studies," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 2, pages 29-65, Springer.
    14. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    15. Hausman,Daniel M., 1992. "The Inexact and Separate Science of Economics," Cambridge Books, Cambridge University Press, number 9780521425230, December.
    16. Sawa, Takamitsu, 1978. "Information Criteria for Discriminating among Alternative Regression Models," Econometrica, Econometric Society, vol. 46(6), pages 1273-1291, November.
    17. Kevin D. Hoover & Stephen J. Perez, 2004. "Truth and Robustness in Cross‐country Growth Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 765-798, December.
    18. Maxwell L. King & Michael McAleer, 1987. "Further Results on Testing AR (1) Against MA (1) Disturbances in the Linear Regression Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 54(4), pages 649-663.
    19. Blommestein, Hans J., 1983. "Specification and estimation of spatial econometric models : A discussion of alternative strategies for spatial economic modelling," Regional Science and Urban Economics, Elsevier, vol. 13(2), pages 251-270, May.
    20. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    21. Florax, Raymond J.G.M. & Folmer, Hendrik & Rey, Sergio J., 2006. "A comment on specification searches in spatial econometrics: The relevance of Hendry's methodology: A reply," Regional Science and Urban Economics, Elsevier, vol. 36(2), pages 300-308, March.
    22. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    23. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124.
    24. Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey, 2004. "Econometrics for Spatial Models: Recent Advances," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax & Sergio J. Rey (ed.), Advances in Spatial Econometrics, chapter 1, pages 1-25, Springer.
    25. Dastoor, Naorayex K. & McAleer, Michael, 1989. "Some Power Comparisons of Joint and Paired Tests for Nonnested Models under Local Hypotheses," Econometric Theory, Cambridge University Press, vol. 5(1), pages 83-94, April.
    26. Badi Baltagi & Dong Li, 2001. "Double Length Artificial Regressions For Testing Spatial Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 20(1), pages 31-40.
    27. P Burridge, 1981. "Testing for a Common Factor in a Spatial Autoregression Model," Environment and Planning A, , vol. 13(7), pages 795-800, July.
    28. Hausman,Daniel M., 1992. "The Inexact and Separate Science of Economics," Cambridge Books, Cambridge University Press, number 9780521415019, December.
    29. Lutkepohl, Helmut, 2007. "General-to-specific or specific-to-general modelling? An opinion on current econometric terminology," Journal of Econometrics, Elsevier, vol. 136(1), pages 319-324, January.
    30. Douglas Rivers & Quang Vuong, 2002. "Model selection tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 1-39, June.
    31. Danilov, Dmitry & Magnus, J.R.Jan R., 2004. "On the harm that ignoring pretesting can cause," Journal of Econometrics, Elsevier, vol. 122(1), pages 27-46, September.
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