A Note on the Selection of Time Series Models
AbstractWe consider issues related to the order of an autoregression selected using information criteria. We study the sensitivity of the estimated order to i) whether the effective number of observations is held fixed when estimating models of different order, ii) whether the estimate of the variance is adjusted for degrees of freedom, and iii) how the penalty for overfitting is defined in relation to the total sample size. Simulations show that the lag length selected by both the Akaike and the Schwarz information criteria are sensitive to these parameters in finite samples. The methods that give the most precise estimates are those that hold the effective sample size fixed across models to be compared. Theoretical considerations reveal that this is indeed necessary for valid model comparisons. Guides to robust model selection are provided.
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Bibliographic InfoPaper provided by Boston College Department of Economics in its series Boston College Working Papers in Economics with number 500.
Length: 18 pages
Date of creation: 15 Jun 2001
Date of revision:
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Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA
Web page: http://fmwww.bc.edu/EC/
More information through EDIRC
Information Criteria; AIC; BIC; lag length selection;
Other versions of this item:
- F30 - International Economics - - International Finance - - - General
- F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
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