Advanced Search
MyIDEAS: Login to save this paper or follow this series

How To Pick The Best Regression Equation: A Review And Comparison Of Model Selection Algorithms

Contents:

Author Info

  • Jennifer L. Castle
  • Xiaochuan Qin
  • W. Robert Reed

    ()
    (University of Canterbury)

Abstract

This paper reviews and compares twenty-one different model selection algorithms (MSAs) representing a diversity of approaches, including (i) information criteria such as AIC and SIC; (ii) selection of a “portfolio” or best subset of models; (iii) general-to-specific algorithms, (iv) forward-stepwise regression approaches; (v) Bayesian Model Averaging; and (vi) inclusion of all variables. We use coefficient unconditional mean-squared error (UMSE) as the basis for our measure of MSA performance. Our main goal is to identify the factors that determine MSA performance. Towards this end, we conduct Monte Carlo experiments across a variety of data environments. Our experiments show that MSAs differ substantially with respect to their performance on relevant and irrelevant variables. We relate this to their associated penalty functions, and a bias-variance tradeoff in coefficient estimates. It follows that no MSA will dominate under all conditions. However, when we restrict our analysis to conditions where automatic variable selection is likely to be of greatest value, we find that two general-to-specific MSAs, Autometrics, do as well or better than all others in over 90% of the experiments.

Download Info

If 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.
File URL: http://www.econ.canterbury.ac.nz/RePEc/cbt/econwp/0913.pdf
Download Restriction: no

Bibliographic Info

Paper provided by University of Canterbury, Department of Economics and Finance in its series Working Papers in Economics with number 09/13.

as in new window
Length: 55 pages
Date of creation: 01 Oct 2009
Date of revision:
Handle: RePEc:cbt:econwp:09/13

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

Related research

Keywords: Model selection algorithms; Information Criteria; General-to-Specific modeling; Bayesian Model Averaging; Portfolio Models; AIC; SIC; AICc; SICc; Monte Carlo Analysis; Autometrics;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Castle Jennifer L. & Doornik Jurgen A & Hendry David F., 2011. "Evaluating Automatic Model Selection," Journal of Time Series Econometrics, De Gruyter, De Gruyter, vol. 3(1), pages 1-33, February.
  2. Steven L. Scott & Hal R. Varian, 2013. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Working Papers 19567, National Bureau of Economic Research, Inc.
  3. Graham Bird & Alex Mandilaras & Helen Popper, 2012. "Explaining Shifts in Exchange Rate Regimes," School of Economics Discussion Papers, School of Economics, University of Surrey 1312, School of Economics, University of Surrey.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:cbt:econwp:09/13. 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 you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.