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The Impact of Data Revisions on the Robustness of Growth Determinants - A Note on 'Determinants of Economic Growth. Will Data Tell?'

Author

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  • Feldkircher, Martin

    (Oesterreichische Nationalbank)

  • Zeugner, Stefan

    (Université Libre de Bruxelles)

Abstract

Ciccone and Jarocinski (2010) show that inference in Bayesian model averaging (BMA) can be highly sensitive to small changes in the dependent variable. In particular they demonstrate that the importance of growth determinants in explaining growth varies tremendously over different revisions of Penn World Table (PWT) income data. They conclude that ’agnostic’ priors appear too sensible for this strand of growth empirics. In response, we show that the instability found owes much to a specific BMA set-up: the variation in results can be considerably reduced by applying an evenly ’agnostic’, but flexible prior.

Suggested Citation

  • Feldkircher, Martin & Zeugner, Stefan, 2010. "The Impact of Data Revisions on the Robustness of Growth Determinants - A Note on 'Determinants of Economic Growth. Will Data Tell?'," Working Papers in Economics 2010-12, University of Salzburg.
    • Handle: RePEc:ris:sbgwpe:2010_012
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    References listed on IDEAS

    as
    1. Jesus Crespo Cuaresma, 2011. "How different is Africa? A comment on Masanjala and Papageorgiou," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1041-1047, September.
    2. 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.
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    More about this item

    Keywords

    Bayesian model averaging; Growth determinants; Zellner’s g prior; Model uncertainty;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • 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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