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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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Paper provided by EconWPA in its series Econometrics with number 9903003.

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Date of creation: 27 Mar 1999
Date of revision: 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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  1. 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.
  2. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
  3. S Durlauf & Danny Quah, 1998. "The New Empirics of Economic Growth," CEP Discussion Papers dp0384, Centre for Economic Performance, LSE.
  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. Smith, M. & Kohn, R., . "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
  6. 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.
  7. Xavier Sala-i-Martin, 1997. "I just ran four million regressions," Economics Working Papers 201, Department of Economics and Business, Universitat Pompeu Fabra.
  8. Siddhartha Chib & Edward Greenberg, 1994. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometrics 9408001, EconWPA, revised 24 Oct 1994.
  9. Brock,W.A. & Durlauf,S.N., 2000. "Growth economics and reality," Working papers 24, Wisconsin Madison - Social Systems.
  10. Edward E. Leamer, 1982. "Let's Take the Con Out of Econometrics," UCLA Economics Working Papers 239, UCLA Department of Economics.
  11. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  12. Levine, Ross & Renelt, David, 1991. "A sensitivity analysis of cross-country growth regressions," Policy Research Working Paper Series 609, The World Bank.
  13. Jonathan Temple, 1999. "The New Growth Evidence," Journal of Economic Literature, American Economic Association, vol. 37(1), pages 112-156, March.
  14. Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998. "Benchmark priors for Bayesian model averaging," ESE Discussion Papers 66, Edinburgh School of Economics, University of Edinburgh.
  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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