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Model uncertainty in cross-country growth regressions

Author

Listed:
  • Carmen Fernandez

    (University of Saint Andrews)

  • Eduardo Ley

    (IMF Institute)

  • Mark Steel

    (University of Kent at Canterbury)

Abstract

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast with Levine and Renelt (1992), our results broadly support the more "optimistic'' conclusion of Sala-i-Martin (1997b), namely that some variables are important regressors for explaining cross-country growth patterns. However, care should be taken in the methodology employed. The approach proposed here is firmly grounded in statistical theory and immediately leads to posterior and predictive inference.

Suggested Citation

  • Carmen Fernandez & Eduardo Ley & Mark Steel, 1999. "Model uncertainty in cross-country growth regressions," Econometrics 9903003, University Library of Munich, Germany, revised 06 Oct 2001.
  • Handle: RePEc:wpa:wuwpem:9903003
    Note: Type of Document - Tex; prepared on MacOS, TeXtures; to print on any printer; figures: included. Forthcoming in the Journal of Applied Econometrics. Replaces the paper entitled: "We have just averaged over two trillion cross-country growth regressions" with ewp-em/0110002.
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    References listed on IDEAS

    as
    1. Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001. "Benchmark priors for Bayesian model averaging," Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
    2. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, Oxford University Press, vol. 106(2), pages 407-443.
    3. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(3), pages 409-431, August.
    4. Durlauf, Steven N. & Quah, Danny T., 1999. "The new empirics of economic growth," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 4, pages 235-308, Elsevier.
    5. William A. Brock & Steven N.Durlauf, 2000. "Growth Economics and Reality," NBER Working Papers 8041, National Bureau of Economic Research, Inc.
    6. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
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    9. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
    10. Kormendi, Roger C. & Meguire, Philip G., 1985. "Macroeconomic determinants of growth: Cross-country evidence," Journal of Monetary Economics, Elsevier, vol. 16(2), pages 141-163, September.
    11. Xavier X. Sala-i-Martin, 1997. "I Just Ran Four Million Regressions," NBER Working Papers 6252, National Bureau of Economic Research, Inc.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Bayesian Model Averaging; Choice of Regressors; Economic Growth; Markov chain Monte Carlo; Prediction;
    All these keywords.

    JEL classification:

    • O49 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Other
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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