IDEAS home Printed from https://ideas.repec.org/p/cvs/starer/91-01.html

Optimal Growth with Unobservable Resources and Learning

Author

Listed:
  • Nyarko, Yaw
  • Olson, Lars J.

Abstract

No abstract is available for this item.

Suggested Citation

  • Nyarko, Yaw & Olson, Lars J., 1991. "Optimal Growth with Unobservable Resources and Learning," Working Papers 91-01, C.V. Starr Center for Applied Economics, New York University.
    • Handle: RePEc:cvs:starer:91-01
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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. Rustichini, Aldo & Wolinsky, Asher, 1995. "Learning about variable demand in the long run," Journal of Economic Dynamics and Control, Elsevier, vol. 19(5-7), pages 1283-1292.
    2. Moxnes, Erling, 2003. "Uncertain measurements of renewable resources: approximations, harvesting policies and value of accuracy," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 85-108, January.
    3. Kling, David M. & Sanchirico, James N. & Fackler, Paul L., 2017. "Optimal monitoring and control under state uncertainty: Application to lionfish management," Journal of Environmental Economics and Management, Elsevier, vol. 84(C), pages 223-245.
    4. Fu, Wentao & Le Riche, Antoine, 2021. "Endogenous growth model with Bayesian learning and technology selection," Mathematical Social Sciences, Elsevier, vol. 114(C), pages 58-71.
    5. Santanu Roy & Itzhak Zilcha, 2012. "Stochastic growth with short-run prediction of shocks," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(3), pages 539-580, November.
    6. Lars J. Olson & Santanu Roy, 2006. "Theory of Stochastic Optimal Economic Growth," Springer Books, in: Rose-Anne Dana & Cuong Le Van & Tapan Mitra & Kazuo Nishimura (ed.), Handbook on Optimal Growth 1, chapter 11, pages 297-335, Springer.
    7. Klumpp, Tilman, 2006. "Linear learning in changing environments," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2577-2611, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:cvs:starer:91-01. 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: Anne Stubing The email address of this maintainer does not seem to be valid anymore. Please ask Anne Stubing to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/aenyuus.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.