Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 11/03.
Length: 51 pages
Date of creation: 01 Jan 2011
Date of revision:
Contact details of provider:
Postal: Private Bag 4800, Christchurch, New Zealand
Phone: 64 3 369 3123 (Administrator)
Fax: 64 3 364 2635
Web page: http://www.econ.canterbury.ac.nz
More information through EDIRC
Model selection algorithms; Information Criteria; General-to-Specific modeling; Bayesian Model Averaging; Portfolio Models; AIC; SIC; AICc; SICc; Monte Carlo Analysis; Autometrics;
Other versions of this item:
- Jennifer L. Castle & Xiaochuan Qin & W. Robert Reed, 2013. "Using Model Selection Algorithms To Obtain Reliable Coefficient Estimates," Journal of Economic Surveys, Wiley Blackwell, vol. 27(2), pages 269-296, 04.
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
This paper has been announced in the following NEP Reports:
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.:
- Leeb, Hannes & P tscher, Benedikt M., 2003.
"The Finite-Sample Distribution Of Post-Model-Selection Estimators And Uniform Versus Nonuniform Approximations,"
Cambridge University Press, vol. 19(01), pages 100-142, February.
- Hannes Leeb & Benedikt M. Poetscher, 2000. "The Finite-Sample Distribution of Post-Model-Selection Estimators, and Uniform Versus Non-Uniform Approximations," Econometrics 0004001, EconWPA.
- 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.
- 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).
- McAleer, Michael & Pagan, Adrian R & Volker, Paul A, 1985.
"What Will Take the Con out of Econometrics?,"
American Economic Review,
American Economic Association, vol. 75(3), pages 293-307, June.
- Jennifer Castle & David Hendry & Jurgen A. Doornik, 2010.
"Evaluating Automatic Model Selection,"
Economics Series Working Papers
474, University of Oxford, Department of Economics.
- Peter C.B. Phillips, 2004.
"Automated Discovery in Econometrics,"
Cowles Foundation Discussion Papers
1469, Cowles Foundation for Research in Economics, Yale University.
- Durevall, Dick & Loening, Josef L. & Ayalew Birru, Yohannes, 2013. "Inflation dynamics and food prices in Ethiopia," Journal of Development Economics, Elsevier, vol. 104(C), pages 89-106.
- Durevall, Dick & Loening, Josef L. & Birru, Yohannes A., 2010. "Inflation Dynamics and Food Prices in Ethiopia," Working Papers in Economics 478, University of Gothenburg, Department of Economics, revised 03 Jun 2013.
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.