Evaluating Automatic Model Selection
We evaluate automatically selecting the relevant variables in an econometric model from a large candidate set.� General-to-specific selection is outlined for a constant model in orthogonal variables, where only one decision is required to select, irrespective of the number of regressors (N < T) where T is the sample size, then evaluated in simulation experiments for N = 1000.� Comparisons with 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, and evaluate Autometrics'�capability in dynamic models by its cost of search versus costs of inference.
|Date of creation:||01 Jan 2010|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.economics.ox.ac.uk/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Jerzy Mycielski & Michal Kurcewicz, 2004. "A Specification Search Algorithm for Cointegrated Systems," Computing in Economics and Finance 2004 321, Society for Computational Economics.
- repec:cup:cbooks:9780521634809 is not listed on IDEAS
- Lovell, Michael C, 1983. "Data Mining," The Review of Economics and Statistics, MIT Press, vol. 65(1), pages 1-12, February.
- Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2009. "How To Pick The Best Regression Equation: A Review And Comparison Of Model Selection Algorithms," Working Papers in Economics 09/13, University of Canterbury, Department of Economics and Finance.
- Hannes Leeb & Benedikt M. Poetscher, 2000.
"The Finite-Sample Distribution of Post-Model-Selection Estimators, and Uniform Versus Non-Uniform Approximations,"
- Leeb, Hannes & P tscher, Benedikt M., 2003. "The Finite-Sample Distribution Of Post-Model-Selection Estimators And Uniform Versus Nonuniform Approximations," Econometric Theory, Cambridge University Press, vol. 19(01), pages 100-142, February.
- Jennifer Castle & David Hendry, 2010. "Automatic Selection for Non-linear Models," Economics Series Working Papers 473, University of Oxford, Department of Economics.
- Carlos Santos & David Hendry & Soren Johansen, 2008.
"Automatic selection of indicators in a fully saturated regression,"
Springer, vol. 23(2), pages 317-335, April.
- David Hendry & Søren Johansen & Carlos Santos, 2008. "Automatic selection of indicators in a fully saturated regression," Computational Statistics, Springer, vol. 23(2), pages 337-339, April.
- repec:cup:cbooks:9780521632423 is not listed on IDEAS
- Castle, Jennifer L. & Doornik, Jurgen A. & Hendry, David F., 2012.
"Model selection when there are multiple breaks,"
Journal of Econometrics,
Elsevier, vol. 169(2), pages 239-246.
When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:474. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Monica Birds)
If references are entirely missing, you can add them using this form.