IDEAS home Printed from
   My bibliography  Save this paper

Demand-Led Growth In A Multi-Commodity Model With Learning: Some Preliminary Results


  • White, Graham


The paper represents a preliminary attempt to shed light on the following question: in the context of demand-led growth, how does learning by agents about the economic system's structure and the determinants of long-run growth affect the long-run dynamics of the economy? Analysis is conducted in terms of an extension of the simplified two-sector model with autonomous demands in White (2008). The focus of the analysis is on the impact of learning about two mechanisms in particular: about how the growth of autonomous demand influences growth of the economy as a whole; and about how expectations about growth affect the dynamics of growth. The mechanics of learning are twofold: first, a simple gradient-descent rule, whereby key coefficients in the investment function relating producers expectations about growth to past growth in their own sector and in the economy are modified in a way which aims to minimize forecast errors; and, second, a more ambitious mechanism whereby producers attempt to uncover aspects of the true relation between past growth rates and expected growth rates. Analysis of the system's dynamics is primarily by means of computer simulation.

Suggested Citation

  • White, Graham, 2010. "Demand-Led Growth In A Multi-Commodity Model With Learning: Some Preliminary Results," Working Papers 2010-03, University of Sydney, School of Economics.
  • Handle: RePEc:syd:wpaper:2123/7069

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:syd:wpaper:2123/7069. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vanessa Holcombe). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.