IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v117y2012i3p862-865.html
   My bibliography  Save this article

A representative consumer theorem for discrete choice models in networked markets

Author

Listed:
  • Melo, Emerson

Abstract

We provide an alternative way to model sequential decision processes, which is consistent with the random utility maximization hypothesis and the existence of a representative agent. Our result is stated on terms of a direct utility representation, and it does not depend on parametric assumptions.

Suggested Citation

  • Melo, Emerson, 2012. "A representative consumer theorem for discrete choice models in networked markets," Economics Letters, Elsevier, vol. 117(3), pages 862-865.
  • Handle: RePEc:eee:ecolet:v:117:y:2012:i:3:p:862-865
    DOI: 10.1016/j.econlet.2012.09.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512005137
    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. Nicholas Economides, 1997. "The Economics of Networks," Brazilian Electronic Journal of Economics, Department of Economics, Universidade Federal de Pernambuco, vol. 1(0), December.
    2. Herriges, Joseph A. & Kling, Catherine L., 1996. "Testing the consistency of nested logit models with utility maximization," Economics Letters, Elsevier, vol. 50(1), pages 33-39, January.
    3. Ruud H. Koning & Geert Ridder, 2003. "Discrete choice and stochastic utility maximization," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 1-27, June.
    4. Gil-Molto, Maria Jose & Hole, Arne Risa, 2004. "Tests for the consistency of three-level nested logit models with utility maximization," Economics Letters, Elsevier, vol. 85(1), pages 133-137, October.
    5. Borsch-Supan, Axel, 1990. "On the compatibility of nested logit models with utility maximization," Journal of Econometrics, Elsevier, vol. 43(3), pages 373-388, March.
    6. Verboven, Frank, 1996. "The nested logit model and representative consumer theory," Economics Letters, Elsevier, vol. 50(1), pages 57-63, January.
    7. Daly, Andrew & Bierlaire, Michel, 2006. "A general and operational representation of Generalised Extreme Value models," Transportation Research Part B: Methodological, Elsevier, vol. 40(4), pages 285-305, May.
    8. Anderson, Simon Peter & de Palma, Andre & Thisse, Jacques-Francois, 1988. "A Representative Consumer Theory of the Logit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(3), pages 461-466, August.
    9. Simon P. Anderson & André Palma, 2006. "MARKET PERFORMANCE WITH MULTIPRODUCT FIRMS -super-," Journal of Industrial Economics, Wiley Blackwell, vol. 54(1), pages 95-124, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Mogens Fosgerau & André De Palma, 2016. "Generalized entropy models," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01291347, HAL.
    2. Fosgerau, Mogens & Frejinger, Emma & Karlstrom, Anders, 2013. "A link based network route choice model with unrestricted choice set," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 70-80.
    3. Mogens Fosgerau & André De Palma, 2016. "Generalized entropy models," Working Papers hal-01291347, HAL.

    More about this item

    Keywords

    Discrete choice models; Networked markets; Dynamic programming;

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    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:ecolet:v:117:y:2012:i:3:p:862-865. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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 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.

    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.