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Jointness In Bayesian Variable Selection With Applications To Growth Regression / Ley, Eduardo

World Bank Open Knowledge Repository (formerly "World Bank E-Library Publications") Available online

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Format:
Book
Government document
Author/Creator:
Ley, Eduardo
Contributor:
Ley, Eduardo
Steel, Mark F. J.
Series:
Policy research working papers.
World Bank e-Library.
Language:
English
Subjects (All):
Arts and Music.
Calibration.
Climate Change.
Counting.
Covariance.
Culture & Development.
Data.
Econometrics.
Economic Theory and Research.
Educational Technology and Distance Learning.
Environment.
Evaluation.
Finance and Financial Sector Development.
Financial Literacy.
Indicators.
Information Security and Privacy.
Less.
Linear Regression.
Logarithms.
Macroeconomics and Economic Growth.
Matrix.
Poverty Reduction.
Precision.
Pro-Poor Growth.
Probabilities.
Probability.
Probability Models.
Science and Technology Development.
Sensitivity Analysis.
Standard Deviation.
Standard Deviations.
Statistical and Mathematical Sciences.
Statistics.
Variables.
Local Subjects:
Arts and Music.
Calibration.
Climate Change.
Counting.
Covariance.
Culture & Development.
Data.
Econometrics.
Economic Theory and Research.
Educational Technology and Distance Learning.
Environment.
Evaluation.
Finance and Financial Sector Development.
Financial Literacy.
Indicators.
Information Security and Privacy.
Less.
Linear Regression.
Logarithms.
Macroeconomics and Economic Growth.
Matrix.
Poverty Reduction.
Precision.
Pro-Poor Growth.
Probabilities.
Probability.
Probability Models.
Science and Technology Development.
Sensitivity Analysis.
Standard Deviation.
Standard Deviations.
Statistical and Mathematical Sciences.
Statistics.
Variables.
Physical Description:
1 online resource (17 pages)
Place of Publication:
Washington, D.C., The World Bank, 2006
System Details:
data file
Summary:
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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