Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates

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dc.contributor.authorCastle, J.L.
dc.contributor.authorQin, X.
dc.contributor.authorReed, W.R.
dc.date.accessioned2011-08-23T21:48:03Z
dc.date.available2011-08-23T21:48:03Z
dc.date.issued2011en
dc.descriptionRePEc Working Paper Series: No. 03/2011en
dc.description.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.en
dc.identifier.citationCastle, J.L., Qin, X., Reed, W.R. (2011) Using Model Selection Algorthims to Obtain Reliable Coefficient Estimates. Department of Economics and Finance. 51pp..en
dc.identifier.urihttp://hdl.handle.net/10092/5359
dc.language.isoen
dc.publisherCollege of Business and Economicsen
dc.publisherUniversity of Canterbury. Department of Economics and Financeen
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subjectmodel selection algorithmsen
dc.subjectinformation criteriaen
dc.subjectgeneral-to-specific modelingen
dc.subjectBayesian model averagingen
dc.subjectportfolio modelsen
dc.subjectAICen
dc.subjectSICen
dc.subjectAICcen
dc.subjectSICcen
dc.subjectMonte Carlo analysisen
dc.subjectautometricsen
dc.subject.anzsrcFields of Research::38 - Economics::3802 - Econometrics::380203 - Economic models and forecastingen
dc.subject.anzsrcFields of Research::49 - Mathematical sciences::4903 - Numerical and computational mathematics::490302 - Numerical analysisen
dc.titleUsing Model Selection Algorthims to Obtain Reliable Coefficient Estimatesen
dc.typeDiscussion / Working Papers
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