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Model uncertainty in cross-country growth regressions

  • Carmen Fernandez

    (School of Mathematics and Statistics, University of Saint Andrews, UK)

  • Eduardo Ley

    (IMF Institute, International Monetary Fund, Washington, DC, USA)

  • Mark F. J. Steel

    (Institute of Mathematics and Statistics, University of Kent at Canterbury, UK)

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is spread widely among many models, suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast to 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. Copyright © 2001 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 16 (2001)
Issue (Month): 5 ()
Pages: 563-576

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Handle: RePEc:jae:japmet:v:16:y:2001:i:5:p:563-576
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  1. Durlauf,S.N. & Quah,D.T., 1998. "The new empirics of economic growth," Working papers 3, Wisconsin Madison - Social Systems.
  2. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  3. Robert J. Barro, 1989. "Economic Growth in a Cross Section of Countries," NBER Working Papers 3120, National Bureau of Economic Research, Inc.
  4. J. Bradford De Long & Lawrence H. Summers, . "Equipment Investment and Economic Growth," J. Bradford De Long's Working Papers _122, University of California at Berkeley, Economics Department.
  5. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
  6. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  7. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
  8. William A. Brock & Steven N.Durlauf, 2000. "Growth Economics and Reality," NBER Working Papers 8041, National Bureau of Economic Research, Inc.
  9. 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.
  10. Xavier X. Sala-i-Martin, 1997. "I Just Ran Four Million Regressions," NBER Working Papers 6252, National Bureau of Economic Research, Inc.
  11. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
  12. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  13. Carmen Fernandez & E Ley & Mark F J Steel, 2004. "Benchmark priors for Bayesian models averaging," ESE Discussion Papers 66, Edinburgh School of Economics, University of Edinburgh.
  14. 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.
  15. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
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