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Model uncertainty in cross-country growth regressions

  • Carmen Fernandez

    (University of Saint Andrews)

  • Eduardo Ley

    (IMF Institute)

  • Mark Steel

    (University of Kent at Canterbury)

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.

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File URL: http://128.118.178.162/eps/em/papers/0110/0110002.pdf
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Paper provided by EconWPA in its series Econometrics with number 0110002.

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Date of creation: 06 Oct 2001
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Handle: RePEc:wpa:wuwpem:0110002
Note: Type of Document - Tex; prepared on MacOS, TeXtures; to print on any printer; figures: included. Forthcoming in the Journal of Applied Econometrics
Contact details of provider: Web page: http://128.118.178.162

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  1. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  2. Durlauf,S.N. & Quah,D.T., 1998. "The new empirics of economic growth," Working papers 3, Wisconsin Madison - Social Systems.
  3. Xavier Sala-i-Martin, 1997. "I just ran four million regressions," Economics Working Papers 201, Department of Economics and Business, Universitat Pompeu Fabra.
  4. Barro, R.J., 1989. "Economic Growth In A Cross Section Of Countries," RCER Working Papers 201, University of Rochester - Center for Economic Research (RCER).
  5. 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.
  6. J. Bradford De Long & Lawrence H. Summers, 1990. "Equipment Investment and Economic Growth," NBER Working Papers 3515, National Bureau of Economic Research, Inc.
  7. 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.
  8. William A. Brock & Steven N.Durlauf, 2000. "Growth Economics and Reality," NBER Working Papers 8041, National Bureau of Economic Research, Inc.
  9. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
  10. Temple, Jonathan, 2000. "Growth Regressions and What the Textbooks Don't Tell You," Bulletin of Economic Research, Wiley Blackwell, vol. 52(3), pages 181-205, July.
  11. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
  12. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
  13. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
  14. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  15. 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.
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