IDEAS home Printed from https://ideas.repec.org/p/bde/wpaper/1104.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: http://www.bde.es/f/webbde/SES/Secciones/Publicaciones/PublicacionesSeriadas/DocumentosTrabajo/11/Fich/dt1104e.pdf
    File Function: First version, April 2011
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Moral-Benito, Enrique, 2010. "Model averaging in economics," MPRA Paper 26047, University Library of Munich, Germany.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. Nonnis, Alberto & Bounfour, Ahmed & Kim, Keungoui, 2023. "Knowledge spillovers and intangible complementarities: Empirical case of European countries," Research Policy, Elsevier, vol. 52(1).
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Enrique Moral-Benito, 2010. "Panel Growth Regressions with General Predetermined Variables: Likelihood-Based Estimation and Bayesian Averaging," Working Papers wp2010_1006, CEMFI.
    2. León-González, Roberto & Montolio, Daniel, 2015. "Endogeneity and panel data in growth regressions: A Bayesian model averaging approach," Journal of Macroeconomics, Elsevier, vol. 46(C), pages 23-39.
    3. Aiyar, Shekhar & Duval, Romain & Puy, Damien & Wu, Yiqun & Zhang, Longmei, 2018. "Growth slowdowns and the middle-income trap," Japan and the World Economy, Elsevier, vol. 48(C), pages 22-37.
    4. Ulaşan, Bülent, 2012. "Cross-country growth empirics and model uncertainty: An overview," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-69.
    5. Próchniak, Mariusz & Witkowski, Bartosz, 2013. "Time stability of the beta convergence among EU countries: Bayesian model averaging perspective," Economic Modelling, Elsevier, vol. 30(C), pages 322-333.
    6. Michael Danquah & Enrique Moral-Benito & Bazoumana Ouattara, 2014. "TFP growth and its determinants: a model averaging approach," Empirical Economics, Springer, vol. 47(1), pages 227-251, August.
    7. Aart Kraay & Norikazu Tawara, 2013. "Can specific policy indicators identify reform priorities?," Journal of Economic Growth, Springer, vol. 18(3), pages 253-283, September.
    8. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    9. 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.
    10. repec:zbw:bofrdp:urn:nbn:fi:bof-201508211364 is not listed on IDEAS
    11. Rockey, James & Temple, Jonathan, 2016. "Growth econometrics for agnostics and true believers," European Economic Review, Elsevier, vol. 81(C), pages 86-102.
    12. Laura Recuero Virto & Denis Couvet & Frédéric Ducarme, 2018. "The determinants of economic growth in countries with high marine biodiversity," Working Papers 2018.03, FAERE - French Association of Environmental and Resource Economists.
    13. repec:rnp:ecopol:ep1345 is not listed on IDEAS
    14. Carl Grekou, 2019. "From nominal devaluations to real depreciations," International Economics, CEPII research center, issue 157, pages 68-81.
    15. Błażejowski, Marcin & Kwiatkowski, Jacek, 2015. "Bayesian Model Averaging and Jointness Measures for gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i05).
    16. Jesus regstdpo-Cuaresma & Neil Foster & Robert Stehrer, 2011. "Determinants of Regional Economic Growth by Quantile," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 809-826.
    17. Iftekhar Hasan & Roman Horvath & Jan Mares, 2018. "What Type of Finance Matters for Growth? Bayesian Model Averaging Evidence," The World Bank Economic Review, World Bank Group, vol. 32(2), pages 383-409.
    18. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    19. Leon-Gonzalez, Roberto & Vinayagathasan, Thanabalasingam, 2015. "Robust determinants of growth in Asian developing economies: A Bayesian panel data model averaging approach," Journal of Asian Economics, Elsevier, vol. 36(C), pages 34-46.
    20. Aiyar, Shekhar & Ebeke, Christian, 2020. "Inequality of opportunity, inequality of income and economic growth," World Development, Elsevier, vol. 136(C).
    21. Kebede, Jeleta & Naranpanawa, Athula & Selvanathan, Saroja, 2023. "Financial inclusion and income inequality nexus: A case of Africa," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 539-557.
    22. In Do Hwang, 2017. "Which Type of Trust Matters?:Interpersonal vs. Institutional vs. Political Trust," Working Papers 2017-15, Economic Research Institute, Bank of Korea.

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bde:wpaper:1104. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ángel Rodríguez. Electronic Dissemination of Information Unit. Research Department. Banco de España (email available below). General contact details of provider: https://edirc.repec.org/data/bdegves.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.