IDEAS home Printed from https://ideas.repec.org/p/tch/wpaper/cep010.html

The Growth Disease at 50 – Baumol after Oulton

Author

Listed:
  • Jochen Hartwig

    (Faculty of Economics and Business Administration, Chemnitz University of Technology, Germany)

  • Hagen Krämer

    (Faculty of Management Science and Engineering, Karlsruhe University of Applied Sciences, Germany)

Abstract

The year 2017 marks the 50th anniversary of William J. Baumol’s seminal model of ‘unbalanced growth’, which predicts the so-called ‘Growth Disease’, i.e., the tendency of aggregate productivity growth to slow down in the process of tertiarisation. In an important contribution published in 2001, however, Nicholas Oulton showed that the shift of resources to the service sector may raise rather than lower aggregate productivity growth if the service industries produce intermediate rather than final products. While Oulton’s reasoning is logically consistent, the question arises whether it is also valid from an empirical point of view. We use the 2011 release of EU KLEMS data to determine whether the shift of resources to services has raised or lowered aggregate productivity growth in the G7 countries.

Suggested Citation

  • Jochen Hartwig & Hagen Krämer, 2017. "The Growth Disease at 50 – Baumol after Oulton," Chemnitz Economic Papers 010, Department of Economics, Chemnitz University of Technology.
    • Handle: RePEc:tch:wpaper:cep010
    as

    Download full text from publisher

    File URL: https://www.tu-chemnitz.de/wirtschaft/vwl1/RePEc/download/tch/wpaper/CEP010_Baumol_after_Oulton_v4.pdf
    File Function: First version, 2017
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. Liu, Hongda & Zhao, Haifeng & Li, Shiyuan, 2023. "Future social change of manufacturing and service industries: Service-oriented manufacturing under the integration of innovation-flows drive," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    2. Theo Santini & Ricardo Azevedo Araujo, 2021. "Productivity growth and sectoral interactions under Domar aggregation: a study for the Brazilian economy from 2000 to 2014," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-30, December.
    3. Kritikos, Alexander S. & Schiersch, Alexander & Stiel, Caroline, 2021. "The Productivity Puzzle in Business Services," IZA Discussion Papers 14610, Institute of Labor Economics (IZA).
    4. Philip Flegler & Hagen Krämer, 2021. "Das Produktivitätsparadoxon der unternehmensbezogenen Dienstleistungen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 74(03), pages 38-45, March.
    5. Jochen Hartwig, 2019. "Further insights into 'Baumol's disease' in Japan," Economics Bulletin, AccessEcon, vol. 39(4), pages 2308-2316.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • O14 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Industrialization; Manufacturing and Service Industries; Choice of Technology
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

    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:tch:wpaper:cep010. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Christian Kulitza The email address of this maintainer does not seem to be valid anymore. Please ask Christian Kulitza to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/fwtucde.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.