IDEAS home Printed from https://ideas.repec.org/b/wfo/wstudy/38921.html
   My bibliography  Save this book

Technological Change and Learning Curves in the Context of the TranSust.Scan Modelling Network. TranSust.Scan Working Paper

Author

Listed:
  • Claudia Kettner
  • Angela Köppl
  • Stefan Schleicher

    (WIFO)

Abstract

The paper deals with the concept of learning curves against a broader background of modelling technological change. Based on a literature survey the paper addresses four approaches (endogenous growth theory, learning curves, innovation theory and diffusion theory) and attempts to highlight the links between them. The second part of the paper tackles the empirical implementation of technological change in TranSust.Scan models. Learning curves are the predominantly used approach in empirical modelling as they show two main benefits: they allow inclusion of different technologies for which specific learning rates are estimated. Furthermore, evidence from ex-post observations and ex-ante estimation match closely.

Suggested Citation

  • Claudia Kettner & Angela Köppl & Stefan Schleicher, 2008. "Technological Change and Learning Curves in the Context of the TranSust.Scan Modelling Network. TranSust.Scan Working Paper," WIFO Studies, WIFO, number 38921, February.
    • Handle: RePEc:wfo:wstudy:38921
    as

    Download full text from publisher

    File URL: https://www.wifo.ac.at/wwa/pubid/38921
    File Function: abstract
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Tobias Wiesnethal & Arnaud Mercier & Burkhard Schade & H. Petric & Lazlo Szabo, 2010. "Quantitative Assessment of the Impact of the Strategic Energy Technology Plan on the European Power Sector," JRC Research Reports JRC61065, Joint Research Centre.

    More about this item

    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:wfo:wstudy:38921. 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: Florian Mayr (email available below). General contact details of provider: https://edirc.repec.org/data/wifooat.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.