Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates
This review surveys a number of common Model Selection Algorithms (MSAs), discusses how they relate to each other, and identifies factors that explain their relative performances. At the heart of MSA performance is the trade-off between Type I and Type II errors. Some relevant variables will be mistakenly excluded, and some irrelevant variables will be retained by chance. A successful MSA will find the optimal trade-off between the two types of errors for a given data environment. Whether a given MSA will be successful in a given environment depends on the relative costs of these two types of errors. We use Monte Carlo experimentation to illustrate these issues. We confirm that no MSA does best in all circumstances. Even the worst MSA in terms of overall performance – the strategy of including all candidate variables – sometimes performs best (viz., when all candidate variables are relevant). We also show how (i) the ratio of relevant to total candidate variables and (ii) DGP noise affect relative MSA performance. Finally, we discuss a number of issues complicating the task of MSAs in producing reliable coefficient estimates.
|Date of creation:||01 Jan 2011|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: 64 3 369 3123 (Administrator)
Fax: 64 3 364 2635
Web page: http://www.econ.canterbury.ac.nz
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.:
- Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011.
"Evaluating Automatic Model Selection,"
Journal of Time Series Econometrics,
De Gruyter, vol. 3(1), pages 1-33, February.
- McAleer, Michael & Pagan, Adrian, 1985.
"What Will Take the Con Out of Econometrics?,"
CEPR Discussion Papers
39, C.E.P.R. Discussion Papers.
- 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.
- Peter C.B. Phillips, 2004.
"Automated Discovery in Econometrics,"
Cowles Foundation Discussion Papers
1469, Cowles Foundation for Research in Economics, Yale University.
- Jacobson, Tor & Karlsson, Sune, 2002.
"Finding Good Predictors for Inflation: A Bayesian Model Averaging Approach,"
Working Paper Series
138, Sveriges Riksbank (Central Bank of Sweden).
- Sune Karlsson & Tor Jacobson, 2004. "Finding good predictors for inflation: a Bayesian model averaging approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(7), pages 479-496.
When requesting a correction, please mention this item's handle: RePEc:cbt:econwp:11/03. 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: (Albert Yee)
If references are entirely missing, you can add them using this form.