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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.
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
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Internet

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

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