Model Selection Using Information Criteria and Genetic Algorithms
AbstractAutomated 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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Bibliographic InfoArticle provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 25 (2005)
Issue (Month): 3 (June)
algorithms; autoregressive; distributed lags; genetic; information criteria; model selection;
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- Magnus, Jan R & Morgan, Mary S, 1997. "The Data: A Brief Description," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 651-61, Sept.-Oct.
- 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.
- Smith, Michael & Kohn, Robert, 1996.
"Nonparametric regression using Bayesian variable selection,"
Journal of Econometrics,
Elsevier, vol. 75(2), pages 317-343, December.
- Smith, M. & Kohn, R., . "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
- J. Joseph Beaulieu & Jeffrey A. Miron, 1992.
"Seasonal Unit Roots in Aggregate U.S. Data,"
NBER Technical Working Papers
0126, National Bureau of Economic Research, Inc.
- John C. Chao & Peter C.B. Phillips, 1997.
"Model Selection in Partially Nonstationary Vector Autoregressive Processes with Reduced Rank Structure,"
Cowles Foundation Discussion Papers
1155, Cowles Foundation for Research in Economics, Yale University.
- 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.
- Hylleberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988.
"Seasonal, Integration And Cointegration,"
6-88-2, Pennsylvania State - Department of Economics.
- Carmen Fernández & Eduardo Ley & Mark F. J. Steel, .
"Benchmark priors for Bayesian Model averaging,"
- Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, EconWPA, revised 31 Jul 1999.
- Carmen Fernandez & E Ley & Mark F J Steel, 2004. "Benchmark priors for Bayesian models averaging," ESE Discussion Papers 66, Edinburgh School of Economics, University of Edinburgh.
- 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 615-37, Sept.-Oct.
- Phillips, Peter C. B., 1995.
"Bayesian model selection and prediction with empirical applications,"
Journal of Econometrics,
Elsevier, vol. 69(1), pages 289-331, September.
- Peter C.B. Phillips, 1992. "Bayesian Model Selection and Prediction with Empirical Applications," Cowles Foundation Discussion Papers 1023, Cowles Foundation for Research in Economics, Yale University.
- Phillips, Peter C. B., 1995. "Bayesian prediction a response," Journal of Econometrics, Elsevier, vol. 69(1), pages 351-365, September.
- Magnus, J.R. & Morgan, M.S., 1997. "The data: A brief description," Open Access publications from Tilburg University urn:nbn:nl:ui:12-74211, Tilburg University.
- 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.
- Werner Ploberger & Peter C. B. Phillips, 2003.
"Empirical Limits for Time Series Econometric Models,"
Econometric Society, vol. 71(2), pages 627-673, March.
- Peter C.B. Phillips & Werner Ploberger, 1999. "Empirical Limits for Time Series Econometric Models," Cowles Foundation Discussion Papers 1220, Cowles Foundation for Research in Economics, Yale University.
- Magnus, Jan R & Morgan, Mary S, 1997. "Design of the Experiment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 459-65, Sept.-Oct.
- Massimiliano Kaucic, 2009. "Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm," Computational Economics, Society for Computational Economics, vol. 34(2), pages 173-193, September.
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