Jointness in Bayesian variable selection with applications to growth regression

Eduardo Ley and Mark Steel ()

No 4063, Policy Research Working Paper Series from The World Bank

Abstract: 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.

Keywords: Statistical&Mathematical Sciences; Climate Change; Educational Technology and Distance Education; Economic Theory&Research; Achieving Shared Growth (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dev and nep-ecm
Date: 2006-11-01
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Journal Article: Jointness in Bayesian variable selection with applications to growth regression (2007)
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