Most Downloaded Articles
- Consideration of Trends in Time Series by White, Halbert and Granger, Clive W.J.
- Bootstrap Point Optimal Unit Root Tests by Wang, Liqiong
- Asymptotic Theory for Regressions with Smoothly Changing Parameters by Hillebrand, Eric/ Medeiros, Marcelo C. and Xu, Junyue
- Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion by Skrobotov, Anton
Evaluating Automatic Model Selection
1University of Oxford
2University of Oxford
3University of Oxford
Citation Information: Journal of Time Series Econometrics. Volume 3, Issue 1, ISSN (Online) 1941-1928, DOI: 10.2202/1941-1928.1097, February 2011
- Published Online:
We outline a range of criteria for evaluating model selection approaches that have been used in the literature. Focusing on three key criteria, we evaluate automatically selecting the relevant variables in an econometric model from a large candidate set. General-to-specific selection is outlined for a regression model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors. Comparisons with an automated model selection algorithm, Autometrics (Doornik, 2009), show similar properties, but not restricted to orthogonal cases. Monte Carlo experiments examine the roles of post-selection bias corrections and diagnostic testing as well as evaluate selection in dynamic models by costs of search versus costs of inference.