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Jointness in Bayesian variable selection with applications to growth regression

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Ley, Eduardo and Steel, Mark F. J. (2007) Jointness in Bayesian variable selection with applications to growth regression. Journal of Macroeconomics, Vol.29 (No.3). pp. 476-493. doi:10.1016/j.jmacro.2006.12.002

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Official URL: http://dx.doi.org/10.1016/j.jmacro.2006.12.002

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Abstract

We present a measure of jointness to explore dependence among regressors, in the context of Bayesian model selection. The jointness measure proposed here equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. We illustrate its application in cross-country growth regressions using two datasets from the model-averaging growth literature. (c) 2007 Elsevier Inc. All rights reserved.

Item Type: Journal Article
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HC Economic History and Conditions
Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Uncertainty -- Econometric models, Bayesian statistical decision theory, Gross domestic product -- Forecasting -- Econometric models, Regression analysis
Journal or Publication Title: Journal of Macroeconomics
Publisher: Elsevier BV * North-Holland
ISSN: 0164-0704
Official Date: September 2007
Dates:
DateEvent
September 2007Published
Volume: Vol.29
Number: No.3
Number of Pages: 18
Page Range: pp. 476-493
DOI: 10.1016/j.jmacro.2006.12.002
Status: Peer Reviewed
Publication Status: Published

Data sourced from Thomson Reuters' Web of Knowledge

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