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An efficient branch-and-bound strategy for subset vector autoregressive model selection

  • Gatu, Cristian
  • Kontoghiorghes, Erricos J.
  • Gilli, Manfred
  • Winker, Peter

A computationally efficient branch-and-bound strategy for finding the subsets of the most statistically significant variables of a vector autoregressive (VAR) model from a given search subspace is proposed. Specifically, the candidate submodels are obtained by deleting columns from the coefficient matrices of the full-specified VAR process. The strategy is based on a regression tree and derives the best-subset VAR models without computing the whole tree. The branch-and-bound cutting test is based on monotone statistical selection criteria which are functions of the determinant of the estimated residual covariance matrix. Experimental results confirm the computational efficiency of the proposed algorithm.

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Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 32 (2008)
Issue (Month): 6 (June)
Pages: 1949-1963

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Handle: RePEc:eee:dyncon:v:32:y:2008:i:6:p:1949-1963
Contact details of provider: Web page: http://www.elsevier.com/locate/jedc

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  1. Erricos J. Kontoghiorghes, . "Computing 3SLS Solutions of Simultaneous Equation Models with Possible Singular Variance-Covariance Matrix," Computing in Economics and Finance 1996 _032, Society for Computational Economics.
  2. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer, vol. 21(1), pages 243-247, December.
  3. Paolo Foschi & Erricos Kontoghiorghes, 2003. "Estimation of VAR Models Computational Aspects," Computational Economics, Society for Computational Economics, vol. 21(1), pages 3-22, February.
  4. Gatu, Cristian & Kontoghiorghes, Erricos J., 2006. "Estimating all possible SUR models with permuted exogenous data matrices derived from a VAR process," Journal of Economic Dynamics and Control, Elsevier, vol. 30(5), pages 721-739, May.
  5. Winker, Peter, 1994. "Identification of multivariate AR-models by threshold accepting," Discussion Papers, Series II 224, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
  6. Kontoghiorghes, E. J. & Clarke, M. R. B., 1995. "An alternative approach for the numerical solution of seemingly unrelated regression equations models," Computational Statistics & Data Analysis, Elsevier, vol. 19(4), pages 369-377, April.
  7. Dietmar Maringer & Peter Winker, 2004. "Optimal Lag Structure Selection in VEC-Models," Computing in Economics and Finance 2004 155, Society for Computational Economics.
  8. Gatu, Cristian & Yanev, Petko I. & Kontoghiorghes, Erricos J., 2007. "A graph approach to generate all possible regression submodels," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 799-815, October.
  9. Cristian Gatu & Erricos Kontoghiorghes, 2005. "Efficient strategies for deriving the subset VAR models," Computational Management Science, Springer, vol. 4(4), pages 253-278, November.
  10. Hofmann, Marc & Gatu, Cristian & Kontoghiorghes, Erricos John, 2007. "Efficient algorithms for computing the best subset regression models for large-scale problems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 16-29, September.
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