IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v20y1998i5-6p495-512.html
   My bibliography  Save this article

Technological change and the timing of mitigation measures

Author

Listed:
  • Grubler, Arnulf
  • Messner, Sabine

Abstract

No abstract is available for this item.

Suggested Citation

  • Grubler, Arnulf & Messner, Sabine, 1998. "Technological change and the timing of mitigation measures," Energy Economics, Elsevier, vol. 20(5-6), pages 495-512, December.
    • Handle: RePEc:eee:eneeco:v:20:y:1998:i:5-6:p:495-512
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(98)00010-3
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Messner, S. & Golodnikov, A. & Gritsevskii, A., 1996. "A stochastic version of the dynamic linear programming model MESSAGE III," Energy, Elsevier, vol. 21(9), pages 775-784.
    2. Watanabe, Chihiro, 1995. "Identification of the role of renewable energy," Renewable Energy, Elsevier, vol. 6(3), pages 237-274.
    3. Alan Manne & Richard Richels, 1995. "The Greenhouse Debate: Economic Efficiency, Burden Sharing and Hedging Strategies," The Energy Journal, , vol. 16(4), pages 1-37, October.
    4. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    5. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    6. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    Full references (including those not matched with items on IDEAS)

    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. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    2. Gregory F. Nemet, 2006. "How well does Learning-by-doing Explain Cost Reductions in a Carbon-free Energy Technology?," Working Papers 2006.143, Fondazione Eni Enrico Mattei.
    3. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    4. Berglund, Christer & Soderholm, Patrik, 2006. "Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in bottom-up energy models," Energy Policy, Elsevier, vol. 34(12), pages 1344-1356, August.
    5. Martinsen, Thomas, 2011. "Technology learning in a small open economy--The systems, modelling and exploiting the learning effect," Energy Policy, Elsevier, vol. 39(5), pages 2361-2372, May.
    6. Junginger, Martin & de Visser, Erika & Hjort-Gregersen, Kurt & Koornneef, Joris & Raven, Rob & Faaij, Andre & Turkenburg, Wim, 2006. "Technological learning in bioenergy systems," Energy Policy, Elsevier, vol. 34(18), pages 4024-4041, December.
    7. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    8. Mathias Mier & Jacqueline Adelowo & Valeriya Azarova, 2022. "Endogenous Technological Change in Power Markets," ifo Working Paper Series 373, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    9. Karali, Nihan & Park, Won Young & McNeil, Michael, 2017. "Modeling technological change and its impact on energy savings in the U.S. iron and steel sector," Applied Energy, Elsevier, vol. 202(C), pages 447-458.
    10. Elke Moser & Dieter Grass & Gernot Tragler, 2016. "A non-autonomous optimal control model of renewable energy production under the aspect of fluctuating supply and learning by doing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 545-575, July.
    11. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    12. Takanobu Kosugi, 2010. "Assessments of ‘Greenhouse Insurance’: A Methodological Review," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 17(4), pages 345-363, December.
    13. Chen, Huayi & Zhou, P., 2019. "Modeling systematic technology adoption: Can one calibrated representative agent represent heterogeneous agents?," Omega, Elsevier, vol. 89(C), pages 257-270.
    14. Guido Fioretti, 2007. "A connectionist model of the organizational learning curve," Computational and Mathematical Organization Theory, Springer, vol. 13(1), pages 1-16, March.
    15. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    16. Tat Y. Chan & Jia Li & Lamar Pierce, 2014. "Learning from Peers: Knowledge Transfer and Sales Force Productivity Growth," Marketing Science, INFORMS, vol. 33(4), pages 463-484, July.
    17. Rasmussen, Tobias N., 2001. "CO2 abatement policy with learning-by-doing in renewable energy," Resource and Energy Economics, Elsevier, vol. 23(4), pages 297-325, October.
    18. Chakravorty, Ujjayant & Leach, Andrew & Moreaux, Michel, 2009. ""Twin Peaks" in Energy Prices: A Hotelling Model with Pollution Learning," Working Papers 2009-10, University of Alberta, Department of Economics.
    19. Strupeit, Lars & Neij, Lena, 2017. "Cost dynamics in the deployment of photovoltaics: Insights from the German market for building-sited systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 948-960.
    20. Lee, Shun-Chung & Shih, Li-Hsing, 2010. "Renewable energy policy evaluation using real option model -- The case of Taiwan," Energy Economics, Elsevier, vol. 32(Supplemen), pages 67-78, September.

    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:eee:eneeco:v:20:y:1998:i:5-6:p:495-512. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.