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Robust Growth Determinants

Author

Listed:
  • Doppelhofer, Gernot

    (Dept. of Economics, Norwegian School of Economics and Business Administration)

  • Weeks, Melvyn

    (University of Cambridge)

Abstract
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth by Sala-i-Martin et al. (2004) are sensitive to deviations from benchmark model averaging. For example, the GDP shares of mining or government consumption, are no longer robust or economically significant once deviations from the normal benchmark assumptions are allowed. The paper identifies outlying observations { most notably Botswana { in explaining economic growth in a cross-section of countries.

Suggested Citation

  • Doppelhofer, Gernot & Weeks, Melvyn, 2011. "Robust Growth Determinants," Discussion Paper Series in Economics 3/2011, Norwegian School of Economics, Department of Economics.
    • Handle: RePEc:hhs:nhheco:2011_003
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    References listed on IDEAS

    as
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    Cited by:

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    2. Havranek, Tomas & Horvath, Roman & Irsova, Zuzana & Rusnak, Marek, 2015. "Cross-country heterogeneity in intertemporal substitution," Journal of International Economics, Elsevier, vol. 96(1), pages 100-118.
    3. Doris A. Oberdabernig & Stefan Humer & Jesus Crespo Cuaresma, 2018. "Democracy, Geography and Model Uncertainty," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(2), pages 154-185, May.
    4. Mark F. J. Steel, 2020. "Model Averaging and Its Use in Economics," Journal of Economic Literature, American Economic Association, vol. 58(3), pages 644-719, September.
    5. Piotr Wójcik & Bartłomiej Wieczorek, 2020. "We have just explained real convergence factors using machine learning," Working Papers 2020-38, Faculty of Economic Sciences, University of Warsaw.
    6. Kuo-Jung Lee & Yi-Chi Chen, 2018. "Of needles and haystacks: revisiting growth determinants by robust Bayesian variable selection," Empirical Economics, Springer, vol. 54(4), pages 1517-1547, June.
    7. Ertefaie Ashkan & Asgharian Masoud & Stephens David A., 2018. "Variable Selection in Causal Inference using a Simultaneous Penalization Method," Journal of Causal Inference, De Gruyter, vol. 6(1), pages 1-16, March.

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    More about this item

    Keywords

    Determinants of Economic Growth; Robust Model Averaging; Heteroscedasticity; Outliers; Mixture models.;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O50 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - General

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