A Bayesian Approach to Model Uncertainty

IMF Working Papers, April 1, 2004

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A Bayesian Approach to Model Uncertainty

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Bibliographic details

• Authors: Charalambos G Tsangarides
• Published: April 1, 2004
• Series: IMF Working Papers
• DOI: https://doi.org/10.5089/9781451849028.001

Methodological contribution

• Develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA).
• Accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest.
• Simultaneously addresses biases associated with endogenous and omitted variables by incorporating a panel data systems Generalized Method of Moments estimator.
• Discusses practical implementation and testing procedures for the developed methodology.

Applications and empirical focus

• Practical applications include testing for the robustness of explanatory variables in analyses of the determinants of economic growth and poverty.
• Relevant subject areas listed: Agroindustries, Bayesian models, Estimation techniques.
• Keywords provided: least squares, WP.

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• A Bayesian Approach to Model Uncertainty by Charalambos G. Tsangarides
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