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On the Effect of Prior Assumptions in Bayesian Model Averaging with Applications to Growth Regression

This paper examines the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations...

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Bibliographic Details
Main Authors: Ley, Eduardo, Steel, Mark F. J.
Language:English
Published: World Bank, Washington, DC 2012
Subjects:
AREA
BAYES FACTOR
BINOMIAL DISTRIBUTION
CLASSIFICATION
COVARIANCE
FORECASTS
INTEGER
LATIN AMERICAN
LINEAR MODELS
LINEAR REGRESSION
MATRIX
PRECISION
PREDICTION
PREDICTIONS
PROBABILITIES
PROBABILITY
PROBABILITY MODELS
REASONING
RESEARCH WORKING PAPERS
SAMPLE SIZE
SCENARIO
SIMULATION
STANDARD DEVIATION
Online Access:http://documents.worldbank.org/curated/en/2007/06/7712856/effect-prior-assumptions-bayesian-model-averaging-applications-growth-regression
http://hdl.handle.net/10986/7401

Internet

http://documents.worldbank.org/curated/en/2007/06/7712856/effect-prior-assumptions-bayesian-model-averaging-applications-growth-regression
http://hdl.handle.net/10986/7401

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