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Growth Regressions, Principal Components and Frequentist Model Averaging

  • Wagner, Martin

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

  • Hlouskova, Jaroslava

    (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria)

This paper offers two innovations for empirical growth research. First, the paper discusses principal components augmented regressions to take into account all available information in well-behaved regressions. Second, the paper proposes a frequentist model averaging framework as an alternative to Bayesian model averaging approaches. The proposed methodology is applied to three data sets, including the Sala-i-Martin et al. (2004) and Fernandez et al. (2001) data as well as a data set of the European Union member states' regions. Key economic variables are found to be significantly related to economic growth. The findings highlight the relevance of the proposed methodology for empirical economic growth research.

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File URL: http://www.ihs.ac.at/publications/eco/es-236.pdf
File Function: First version, 2009
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Paper provided by Institute for Advanced Studies in its series Economics Series with number 236.

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Length: 38 pages
Date of creation: Mar 2009
Date of revision:
Handle: RePEc:ihs:ihsesp:236
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Order Information: Postal: Institute for Advanced Studies - Library, Stumpergasse 56, A-1060 Vienna, Austria

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  1. Kevin D. Hoover & Stephen J. Perez, . "Truth and Robustness in Cross-country Growth Regressions," Department of Economics 01-01, California Davis - Department of Economics.
  2. Gernot Doppelhofer & Ronald I. Miller & Xavier Sala-i-Martin, 2000. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," NBER Working Papers 7750, National Bureau of Economic Research, Inc.
  3. Johnson, Paul & Durlauf, Steven N & Temple, Johnathan R. W., 2004. "Growth Econometrics," Vassar College Department of Economics Working Paper Series 61, Vassar College Department of Economics.
    • Durlauf, Steven N. & Johnson, Paul A. & Temple, Jonathan R.W., 2005. "Growth Econometrics," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 1, chapter 8, pages 555-677 Elsevier.
  4. Ulrike Schneider & Martin Wagner, 2009. "Catching Growth Determinants with the Adaptive Lasso," wiiw Working Papers 55, The Vienna Institute for International Economic Studies, wiiw.
  5. repec:cup:cbooks:9780521852258 is not listed on IDEAS
  6. Xavier X. Sala-i-Martin, 1997. "I Just Ran Four Million Regressions," NBER Working Papers 6252, National Bureau of Economic Research, Inc.
  7. Carmen Fernandez & Eduardo Ley & Mark Steel, 1999. "Model uncertainty in cross-country growth regressions," Econometrics 9903003, EconWPA, revised 06 Oct 2001.
  8. David Hendry & Hans-Martin Krolzig, 2004. "We Ran One Regression," Economics Series Working Papers 2004-W17, University of Oxford, Department of Economics.
  9. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-13, June.
  10. Bruce E. Hansen, 2007. "Least Squares Model Averaging," Econometrica, Econometric Society, vol. 75(4), pages 1175-1189, 07.
  11. Schott, James R., 2006. "A high-dimensional test for the equality of the smallest eigenvalues of a covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 827-843, April.
  12. Hjort N.L. & Claeskens G., 2003. "Frequentist Model Average Estimators," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 879-899, January.
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