Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology
AbstractThis paper brings together a number of new specification search strategies in spatial econometric modeling. In the literature, experimental results for several forward stepwise strategies aimed at remedying spatial dependence, have been reported. Essentially, these strategies boil down to the expansion of a spatial linear regression model with spatially lagged variables, conditional upon the results of misspecification tests. We investigate a Hendry-like specification strategy, starting from the spatial common factor model and subsequently reducing the number of spatially lagged variables on the basis of significance tests. The experimental simulations pertain to various small to large sample sizes, with spatial processes modeled on regular lattice surfaces. Our main conclusion is that the classical forward stepwise approach outperforms the Hendry strategy in terms of finding the true data generating process as well as in the observed accuracy of the estimators for spatial and non-spatial parameters. It also dominates concurrent forward stepwise strategies recently suggested in the literature.
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Bibliographic InfoPaper provided by EconWPA in its series Urban/Regional with number 0202001.
Length: 30 pages
Date of creation: 08 Feb 2002
Date of revision:
Note: Type of Document - Latex; prepared on Linux; to print on PostScript; pages: 30 ; figures: included
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Web page: http://22.214.171.124
spatial econometrics; autocorrelation; pre-testing; specification strategy;
Other versions of this item:
- 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.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-10 (All new papers)
- NEP-ECM-2002-02-22 (Econometrics)
- NEP-PKE-2002-02-15 (Post Keynesian Economics)
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.:
- Anselin, Luc & Hudak, Sheri, 1992. "Spatial econometrics in practice : A review of software options," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 509-536, September.
- Bera, Anil K. & Yoon, Mann J., 1993. "Specification Testing with Locally Misspecified Alternatives," Econometric Theory, Cambridge University Press, vol. 9(04), pages 649-658, August.
- 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.
- 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.
- 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.
- Thomas de Graaff & Raymond J.C.M. Florax & Peter Nijkamp & Aura Reggiani, 2001. "A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and Nonlinearity," Journal of Regional Science, Wiley Blackwell, vol. 41(2), pages 255-276.
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