IDEAS home Printed from
   My bibliography  Save this article

Aprendizaje con información incompleta en modelos de consumo con múltiples atributos


  • José Carlos Ramírez

    (Departamento de Economía, CIDE. México, D.F. Mexico)

  • John Goddard

    (Universidad de Oxford)


This paper deals with an intertemporal model of optimization, which is based on multiple attribute utility functions (MUAT). The model assumes that consumers do not know a priori the optimal mixture of attributes which would maximize their utility from consumption. By using a MUAT lineal model, we state that the resulting consumption paths for four “extreme cases” are associated with several learning processes. In particular, we show that optimal equilibria in consumption of goods can be reached before the consumer exhausts her/his budget, a kind of equilibrium situation not analyzed in traditional utility functions.

Suggested Citation

  • José Carlos Ramírez & John Goddard, 2001. "Aprendizaje con información incompleta en modelos de consumo con múltiples atributos," Economía Mexicana NUEVA ÉPOCA, , vol. 0(1), pages 121-158, January-J.
  • Handle: RePEc:emc:ecomex:v:10:y:2001:i:1:p:121-158

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    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:emc:ecomex:v:10:y:2001:i:1:p:121-158. 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: (Ricardo Tiscareño). 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.