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Growth Regressions, Principal Components and Frequentist Model Averaging

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Wagner, Martin & Hlouskova, Jaroslava, 2009. "Growth Regressions, Principal Components and Frequentist Model Averaging," Economics Series 236, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:236
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    File URL: http://www.ihs.ac.at/publications/eco/es-236.pdf
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    References listed on IDEAS

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    1. Kevin D. Hoover & Stephen J. Perez, 2004. "Truth and Robustness in Cross‐country Growth Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 765-798, December.
    2. 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.
    3. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    4. Ulrike Schneider & Martin Wagner, 2012. "Catching Growth Determinants with the Adaptive Lasso," German Economic Review, Verein für Socialpolitik, vol. 13(1), pages 71-85, February.
    5. David F. Hendry & Hans‐Martin Krolzig, 2004. "We Ran One Regression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 799-810, December.
    6. Xavier X. Sala-i-Martin, 1997. "I Just Ran Four Million Regressions," NBER Working Papers 6252, National Bureau of Economic Research, Inc.
    7. 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.
    8. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    9. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    10. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258, January.
    11. Leamer, Edward E, 1985. "Sensitivity Analyses Would Help," American Economic Review, American Economic Association, vol. 75(3), pages 308-313, June.
    12. 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.
    13. Bruce E. Hansen, 2007. "Least Squares Model Averaging," Econometrica, Econometric Society, vol. 75(4), pages 1175-1189, July.
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    Cited by:

    1. Ulrike Schneider & Martin Wagner, 2012. "Catching Growth Determinants with the Adaptive Lasso," German Economic Review, Verein für Socialpolitik, vol. 13(1), pages 71-85, February.
    2. Vanina Forget, 2012. "Doing well and doing good: a multi-dimensional puzzle," Working Papers hal-00672037, HAL.
    3. Martin Wagner & Achim Zeileis, 2012. "Heterogeneity of Regional Growth in the European Union," Working Papers 2012-20, Faculty of Economics and Statistics, University of Innsbruck.
    4. Enrique Moral-Benito, 2010. "Model Averaging in Economics," Working Papers wp2010_1008, CEMFI.
    5. Jaroslava Hlouskova & Martin Wagner, 2013. "The Determinants of Long-Run Economic Growth: A Conceptually and Computationally Simple Approach," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 445-492, December.
    6. Enrique Moral-Benito, 2015. "Model Averaging In Economics: An Overview," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 46-75, February.

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    More about this item

    Keywords

    Frequentist model averaging; Growth regressions; Principal components;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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