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A Bayesian Approach to Model Uncertainty


  • Charalambos G Tsangarides


This paper develops the theoretical background for the Limited Information Bayesian Model Averaging (LIBMA). The proposed approach accounts for model uncertainty by averaging over all possible combinations of predictors when making inferences about the variables of interest, and it simultaneously addresses the biases associated with endogenous and omitted variables by incorporating a panel data systems Generalized Method of Moments estimator. Practical applications of the developed methodology are discussed, including testing for the robustness of explanatory variables in the analyses of the determinants of economic growth and poverty.

Suggested Citation

  • Charalambos G Tsangarides, 2004. "A Bayesian Approach to Model Uncertainty," IMF Working Papers 04/68, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:04/68

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    References listed on IDEAS

    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    3. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    4. Kim, Jae-Young, 2002. "Limited information likelihood and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 175-193, March.
    5. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    6. Carlos A Leite & Charalambos G Tsangarides & Dhaneshwar Ghura, 2002. "Is Growth Enough? Macroeconomic Policy and Poverty Reduction," IMF Working Papers 02/118, International Monetary Fund.
    7. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
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    Cited by:

    1. Steel, Mark F. J., 2017. "Model Averaging and its Use in Economics," MPRA Paper 81568, University Library of Munich, Germany.
    2. Theo S. Eicher & Alex Lenkoski & Adrian Raftery, 2009. "Bayesian Model Averaging and Endogeneity Under Model Uncertainty: An Application to Development Determinants," Working Papers UWEC-2009-19-FC, University of Washington, Department of Economics.
    3. Eicher, Theo S. & Helfman, Lindy & Lenkoski, Alex, 2012. "Robust FDI determinants: Bayesian Model Averaging in the presence of selection bias," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 637-651.
    4. Alin T Mirestean & Charalambos G Tsangarides & Huigang Chen, 2009. "Limited Information Bayesian Model Averaging for Dynamic Panels with Short Time Periods," IMF Working Papers 09/74, International Monetary Fund.
    5. Coulibaly, Issiaka & Gnimassoun, Blaise, 2013. "Optimality of a monetary union: New evidence from exchange rate misalignments in West Africa," Economic Modelling, Elsevier, vol. 32(C), pages 463-482.
    6. Enrique Moral-Benito, 2012. "Determinants of Economic Growth: A Bayesian Panel Data Approach," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 566-579, May.
    7. Huigang Chen & Alin T Mirestean & Charalambos G Tsangarides, 2011. "Limited Information Bayesian Model Averaging for Dynamic Panels with An Application to a Trade Gravity Model," IMF Working Papers 11/230, International Monetary Fund.

    More about this item


    Economic models; Forecasting models; Dynamic Panel Estimation; Bayesian Model Averaging; probability; probabilities; hypothesis testing; bayes factors; equation;

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