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TFP growth and its determinants: nonparametrics and model averaging

Author

Listed:
  • Michael Danquah

    (Swansea University)

  • Enrique Moral-Benito

    (Bank Of Spain)

  • Bazoumana Ouattara

    (Swansea University)

Abstract

Total Factor Productivity (TFP) accounts for a sizeable proportion of the income and growth differences across countries. Two challenges remain to researchers aiming to explain these differences: on the one hand, TFP growth is hard to measure; on the other hand, model uncertainty hampers consensus on its key determinants. This paper combines a non-parametric measure of TFP growth with model averaging techniques to addess both issues. The empirical findings suggest that the most robust TFP growth determinants are unobserved heterogeneity, initial GDP, consumption share, and trade openness. We also investigate the main determinants of the TFP components: efficiency change (i.e. catching up) and technological progress (i.e. innovation).

Suggested Citation

  • Michael Danquah & Enrique Moral-Benito & Bazoumana Ouattara, 2011. "TFP growth and its determinants: nonparametrics and model averaging," Working Papers 1104, Banco de España.
    • Handle: RePEc:bde:wpaper:1104
    as

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    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/11/Fich/dt1104e.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Enrique Moral-Benito, 2012. "Determinants of Economic Growth: A Bayesian Panel Data Approach," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 566-579, May.
    3. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Serguei Kaniovski & Thomas Url & Helmut Hofer & Viola Garstenauer, 2021. "A Long-run Macroeconomic Model of the Austrian Economy (A-LMM 2.0). New Results (2021)," WIFO Studies, WIFO, number 67377.
    2. Ravindra H. Dholakia, 2020. "A Theory of Growth and Threshold Inflation with Estimates," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 471-493, September.
    3. Nonnis, Alberto & Bounfour, Ahmed & Kim, Keungoui, 2023. "Knowledge spillovers and intangible complementarities: Empirical case of European countries," Research Policy, Elsevier, vol. 52(1).
    4. Sánchez Serrano, Antonio, 2022. "Loan renegotiation and the long-term impact on total factor productivity," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(4).
    5. Edinaldo Tebaldi, 2016. "The Dynamics of Total Factor Productivity and Institutions," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 41(4), pages 1-25, December.

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    More about this item

    Keywords

    Productivity; Bayesian Model Averaging; Nonparametric methods;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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