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Model Selection Using Information Criteria and Genetic Algorithms

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Listed author(s):
  • Kelvin Balcombe

    ()

Abstract

Automated model searches using information criteria are used for the estimation of linear single equation models. Genetic algorithms are described and used for this purpose. These algorithms are shown to be a practical method for model selection when the number of sub-models are very large. Several examples are presented including tests for bivariate Granger causality and seasonal unit roots. Automated selection of an autoregressive distributed lag model for the consumption function in the US is also undertaken. Copyright Springer Science + Business Media, Inc. 2005

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File URL: http://hdl.handle.net/10.1007/s10614-005-2209-8
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Article provided by Springer & Society for Computational Economics in its journal Computational Economics.

Volume (Year): 25 (2005)
Issue (Month): 3 (June)
Pages: 207-228

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Handle: RePEc:kap:compec:v:25:y:2005:i:3:p:207-228
DOI: 10.1007/s10614-005-2209-8
Contact details of provider: Web page: http://www.springer.com

Web page: http://www.comp-econ.org/

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Order Information: Web: http://www.springer.com/economics/economic+theory/journal/10614/PS2

Keywords: algorithms; autoregressive; distributed lags; genetic; information criteria; model selection;

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  1. Hylleberg, S. & Engle, R. F. & Granger, C. W. J. & Yoo, B. S., 1990. "Seasonal integration and cointegration," Journal of Econometrics, Elsevier, vol. 44(1-2), pages 215-238.
  2. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
  3. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
  4. de Crombrugghe, Denis & Palm, Franz C & Urbain, Jean-Pierre, 1997. "Statistical Demand Functions for Food in the USA and the Netherlands," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 615-637, Sept.-Oct.
  5. Magnus, Jan R & Morgan, Mary S, 1997. "Design of the Experiment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 459-465, Sept.-Oct.
  6. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
  7. Kelvin Balcombe & Alastair Bailey & Iain Fraser, 2005. "Measuring the impact of R&D on Productivity from a Econometric Time Series Perspective," Journal of Productivity Analysis, Springer, vol. 24(1), pages 49-72, 09.
  8. Phillips, Peter C. B., 1995. "Bayesian model selection and prediction with empirical applications," Journal of Econometrics, Elsevier, vol. 69(1), pages 289-331, September.
  9. Magnus, J.R. & Morgan, M.S., 1997. "The data : A brief description," Other publications TiSEM 4bdd1a8c-adbb-4786-9fc1-b, Tilburg University, School of Economics and Management.
  10. Chao, John C. & Phillips, Peter C. B., 1999. "Model selection in partially nonstationary vector autoregressive processes with reduced rank structure," Journal of Econometrics, Elsevier, vol. 91(2), pages 227-271, August.
  11. Werner Ploberger & Peter C. B. Phillips, 2003. "Empirical Limits for Time Series Econometric Models," Econometrica, Econometric Society, vol. 71(2), pages 627-673, March.
  12. Phillips, Peter C. B., 1995. "Bayesian prediction a response," Journal of Econometrics, Elsevier, vol. 69(1), pages 351-365, September.
  13. Werner Ploberger & Peter C.B. Phillips, 1998. "Rissanen's Theorem and Econometric Time Series," Cowles Foundation Discussion Papers 1197, Cowles Foundation for Research in Economics, Yale University.
  14. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  15. Magnus, Jan R & Morgan, Mary S, 1997. "The Data: A Brief Description," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 651-661, Sept.-Oct.
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Cited by:

  1. Massimiliano Kaucic, 2009. "Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 173-193, September.

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