Jointness in Bayesian Variable Selection with Applications to Growth Regression

The authors present a measure of jointness to explore dependence among regressors in the context of Bayesian model selection. The jointness measure they propose equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. They show its application in cross-country growth regressions using two data-sets from the model-averaging growth literature

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Year of publication:	2012
Authors:	Ley, Eduardo ; Steel, Mark F. J.
Publisher:	[Erscheinungsort nicht ermittelbar]
Subject:	Regressionsanalyse \| Regression analysis \| Bayes-Statistik \| Bayesian inference \| Theorie \| Theory \| Wirtschaftswachstum \| Economic growth

Extent:	Online-Ressource
Series:	Policy Research Working Paper ; 4063
Type of publication:	Book / Working Paper
Language:	English
Notes:	English en_US
Other identifiers:	hdl:10986/8865 [Handle]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012553881