Pitfalls of estimating the marginal likelihood using the modified harmonic mean

Chan, JCC; Grant, AL

Pitfalls of estimating the marginal likelihood using the modified harmonic mean

Chan, JCC

Grant, AL

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Publication Type:: Journal Article
Citation:: Economics Letters, 2015, 131 pp. 29 - 33
Issue Date:: 2015-06-01

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Field	Value	Language
dc.contributor.author	Chan, JCC https://orcid.org/0000-0003-3632-128X	en_US
dc.contributor.author	Grant, AL https://orcid.org/0000-0002-6167-6130	en_US
dc.date.issued	2015-06-01	en_US
dc.identifier.citation	Economics Letters, 2015, 131 pp. 29 - 33	en_US
dc.identifier.issn	0165-1765	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119169
dc.description.abstract	© 2015 Elsevier B.V. The modified harmonic mean is widely used for estimating the marginal likelihood. We investigate the empirical performance of two versions of this estimator: one based on the observed-data likelihood and the other on the complete-data likelihood. Through an empirical example using US and UK inflation, we show that the version based on the complete-data likelihood has a substantial bias and tends to select the wrong model, whereas the version based on the observed-data likelihood works well.	en_US
dc.relation.ispartof	Economics Letters	en_US
dc.relation.isbasedon	10.1016/j.econlet.2015.03.036	en_US
dc.subject.classification	Economics	en_US
dc.title	Pitfalls of estimating the marginal likelihood using the modified harmonic mean	en_US
dc.type	Journal Article
utslib.citation.volume	131	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	14 Economics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Economics Discipline
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	131	en_US

Abstract:

© 2015 Elsevier B.V. The modified harmonic mean is widely used for estimating the marginal likelihood. We investigate the empirical performance of two versions of this estimator: one based on the observed-data likelihood and the other on the complete-data likelihood. Through an empirical example using US and UK inflation, we show that the version based on the complete-data likelihood has a substantial bias and tends to select the wrong model, whereas the version based on the observed-data likelihood works well.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/119169