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...

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Bibliographic Details
Main Authors:	Ley, Eduardo, Steel, Mark F. J.
Format:	Policy Research Working Paper
Language:	English en_US
Published:	2012
Subjects:	BENCHMARK BLACK MARKET BLACK MARKET PREMIUM CALIBRATION CIVIL LIBERTIES CLASSIFICATION COUNTING COVARIANCE COVARIANCE MATRIX DATA SETS DENSITY FUNCTION DEPENDENT VARIABLE ECONOMETRICS EXCHANGE RATE EXPLANATORY VARIABLES EXPORTS GDP GROWTH DETERMINANTS GROWTH LITERATURE GROWTH MODELS GROWTH REGRESSION GROWTH REGRESSIONS LABOR FORCE LATIN AMERICAN LINEAR REGRESSION LOGARITHMS MALARIA MATRIX NORMAL DISTRIBUTION OPEN ECONOMY POLICY RESEARCH PRECISION PROBABILITIES PROBABILITY PROBABILITY MODELS PUBLIC INVESTMENT REAL EXCHANGE RATE SCALE EFFECT STANDARD DEVIATION STANDARD DEVIATIONS
Online Access:	http://documents.worldbank.org/curated/en/2006/11/7186414/jointness-bayesian-variable-selection-applications-growth-regression http://hdl.handle.net/10986/8865

Internet

http://documents.worldbank.org/curated/en/2006/11/7186414/jointness-bayesian-variable-selection-applications-growth-regression
http://hdl.handle.net/10986/8865

Jointness in Bayesian Variable Selection with Applications to Growth Regression

Internet

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