IDEAS home Printed from https://ideas.repec.org/p/udc/wpaper/wp216.html
   My bibliography  Save this paper

Incentivos Reputacionales para la Autorregulación: Un Análisis Experimental

Author

Listed:
  • Javier Nuñez
  • Jose Luis Lima

Abstract

Las industrias de bienes de confianza generalmente se encuentran organizadas como Organizaciones Autorregluadas (OA). Sin embargo, la autorregulación implica una situación de captura regulatoria por lo cual los incentivos de la OA para controlar la calidad provista en el mercado y denunciar evidencia de provisión de mala calidad no están garantizadas. En este trabajo analizamos, utilizando técnicas experimentales, si crear una reputación de buena calidad entre los consumidores es suficiente para que la OA tengan los incentivos para hacer su trabajo. Nuestros resultados ofrecen un sólido soporte a la posibilidad de que la OA realice su trabajo por motivos reputacionales en el caso en que es teóricamente factible. También encontramos evidencia de que los consumidores pueden aprender la estructura del mercado y ajustar su comportamiento hacia los equilibrios teóricos, y de esta manera suplir su falta de experimentación directa de la mala calidad y control.

Suggested Citation

  • Javier Nuñez & Jose Luis Lima, 2005. "Incentivos Reputacionales para la Autorregulación: Un Análisis Experimental," Working Papers wp216, University of Chile, Department of Economics.
  • Handle: RePEc:udc:wpaper:wp216
    as

    Download full text from publisher

    File URL: http://www.econ.uchile.cl/uploads/publicacion/61f57e85-5657-4551-b53b-59a24c79baed.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Winand Emons, 1997. "Credence Goods and Fraudelent Experts," RAND Journal of Economics, The RAND Corporation, vol. 28(1), pages 107-119, Spring.
    3. David J. Cooper & Susan Garvin & John H. Kagel, 1997. "Signalling and Adaptive Learning in an Entry Limit Pricing Game," RAND Journal of Economics, The RAND Corporation, vol. 28(4), pages 662-683, Winter.
    4. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, April.
    5. Cooper, David J & Garvin, Susan & Kagel, John H, 1997. "Adaptive Learning vs. Equilibrium Refinements in an Entry Limit Pricing Game," Economic Journal, Royal Economic Society, vol. 107(442), pages 553-575, May.
    6. F. Berkhout, 1999. "Essay," Energy & Environment, , vol. 10(2), pages 209-212, March.
    7. David J. Cooper, 1999. "Gaming against Managers in Incentive Systems: Experimental Results with Chinese Students and Chinese Managers," American Economic Review, American Economic Association, vol. 89(4), pages 781-804, September.
    8. Nunez, Javier, 2001. "A model of self-regulation," Economics Letters, Elsevier, vol. 74(1), pages 91-97, December.
    9. Carolyn Pitchik & Andrew Schotter, 1994. "Norms And Competition In Markets With Asymmetric Information: An Experimental Study Of The Development Of Industry Ethics," Metroeconomica, Wiley Blackwell, vol. 45(2), pages 188-207, June.
    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. Hopkins, Ed, 2007. "Adaptive learning models of consumer behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 64(3-4), pages 348-368.
    2. Colin Camerer & Teck H Ho & Juin-Kuan Chong & Keith Weigelt, 2003. "Strategic teaching and equilibrium models of repeated trust and entry games," Levine's Bibliography 506439000000000506, UCLA Department of Economics.
    3. Ilya R. P. Cuypers & Youtha Cuypers & Xavier Martin, 2017. "When the target may know better: Effects of experience and information asymmetries on value from mergers and acquisitions," Strategic Management Journal, Wiley Blackwell, vol. 38(3), pages 609-625, March.
    4. David Cooper & John Kagel, 2008. "Learning and transfer in signaling games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 34(3), pages 415-439, March.
    5. Jacob K. Goeree & Charles A. Holt, 2001. "Ten Little Treasures of Game Theory and Ten Intuitive Contradictions," American Economic Review, American Economic Association, vol. 91(5), pages 1402-1422, December.
    6. Cuypers, I.R.P., 2009. "Essays on equity joint ventures, uncertainty and experience," Other publications TiSEM 8dc79e86-c625-467f-a450-8, Tilburg University, School of Economics and Management.
    7. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November.
    8. Cooper, David J. & Kagel, John H., 2003. "The impact of meaningful context on strategic play in signaling games," Journal of Economic Behavior & Organization, Elsevier, vol. 50(3), pages 311-337, March.
    9. José Luis Lima R. & Javier Nuñez E., 2004. "Experimental Analysis of the Reputational Incentives in a Self Regulated Organization," Econometric Society 2004 Latin American Meetings 194, Econometric Society.
    10. Andrzej Baranski & David J. Cooper & Guillaume Fréchette, 2024. "Introduction to the special issue in honor of John H. Kagel," Experimental Economics, Springer;Economic Science Association, vol. 27(1), pages 1-8, March.
    11. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
    12. Drouvelis, Michalis & Müller, Wieland & Possajennikov, Alex, 2012. "Signaling without a common prior: Results on experimental equilibrium selection," Games and Economic Behavior, Elsevier, vol. 74(1), pages 102-119.
    13. Ido Erev & Alvin Roth & Robert Slonim & Greg Barron, 2007. "Learning and equilibrium as useful approximations: Accuracy of prediction on randomly selected constant sum games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(1), pages 29-51, October.
    14. Kets, W., 2008. "Networks and learning in game theory," Other publications TiSEM 7713fce1-3131-498c-8c6f-3, Tilburg University, School of Economics and Management.
    15. Galbiati, Marco & Soramäki, Kimmo, 2011. "An agent-based model of payment systems," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 859-875, June.
    16. Schipper, Burkhard C., 2021. "Discovery and equilibrium in games with unawareness," Journal of Economic Theory, Elsevier, vol. 198(C).
    17. Mathieu Faure & Gregory Roth, 2010. "Stochastic Approximations of Set-Valued Dynamical Systems: Convergence with Positive Probability to an Attractor," Mathematics of Operations Research, INFORMS, vol. 35(3), pages 624-640, August.
    18. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    19. ,, 2011. "Manipulative auction design," Theoretical Economics, Econometric Society, vol. 6(2), May.
    20. Christian Ewerhart, 2020. "Ordinal potentials in smooth games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(4), pages 1069-1100, November.

    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L84 - Industrial Organization - - Industry Studies: Services - - - Personal, Professional, and Business Services

    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:udc:wpaper:wp216. 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: Mohit Karnani (email available below). General contact details of provider: https://edirc.repec.org/data/deuclcl.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.