[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/bge/wpaper/1018.html
   My bibliography  Save this paper

Separating Predicted Randomness from Noise

Author

Listed:
  • Jose Apesteguia
  • Miguel Ángel Ballester
Abstract
Given observed stochastic choice data and a model of stochastic choice, we offer a methodology that enables separation of the data representing the model's inherent randomness from residual noise, and thus quantify the maximal fraction of the data that are consistent with the model. We show how to apply our approach to any model of stochastic choice. We then study the case of four well-known models, each capturing a different notion of randomness. We conclude by illustrating our results with an experimental dataset.

Suggested Citation

  • Jose Apesteguia & Miguel Ángel Ballester, 2018. "Separating Predicted Randomness from Noise," Working Papers 1018, Barcelona School of Economics.
    • Handle: RePEc:bge:wpaper:1018
    as

    Download full text from publisher

    File URL: https://www.barcelonagse.eu/sites/default/files/working_paper_pdfs/1018.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Drew Fudenberg & Tomasz Strzalecki, 2015. "Dynamic Logit With Choice Aversion," Econometrica, Econometric Society, vol. 83, pages 651-691, March.
    2. Drew Fudenberg & Ryota Iijima & Tomasz Strzalecki, 2015. "Stochastic Choice and Revealed Perturbed Utility," Econometrica, Econometric Society, vol. 83, pages 2371-2409, November.
    3. Faruk Gul & Wolfgang Pesendorfer, 2006. "Random Expected Utility," Econometrica, Econometric Society, vol. 74(1), pages 121-146, January.
    4. David S. Ahn & Todd Sarver, 2013. "Preference for Flexibility and Random Choice," Econometrica, Econometric Society, vol. 81(1), pages 341-361, January.
    5. Paulo Natenzon, 2019. "Random Choice and Learning," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 419-457.
    6. Afriat, S N, 1973. "On a System of Inequalities in Demand Analysis: An Extension of the Classical Method," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 460-472, June.
    7. Faruk Gul & Paulo Natenzon & Wolfgang Pesendorfer, 2014. "Random Choice as Behavioral Optimization," Econometrica, Econometric Society, vol. 82, pages 1873-1912, September.
    8. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    9. Frederick Mosteller & Philip Nogee, 1951. "An Experimental Measurement of Utility," Journal of Political Economy, University of Chicago Press, vol. 59(5), pages 371-371.
    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. Victor H. Aguiar & Maria Jose Boccardi & Nail Kashaev & Jeongbin Kim, 2023. "Random utility and limited consideration," Quantitative Economics, Econometric Society, vol. 14(1), pages 71-116, January.

    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. Duffy, Sean & Gussman, Steven & Smith, John, 2021. "Visual judgments of length in the economics laboratory: Are there brains in stochastic choice?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    2. Duffy, Sean & Smith, John, 2020. "An economist and a psychologist form a line: What can imperfect perception of length tell us about stochastic choice?," MPRA Paper 99417, University Library of Munich, Germany.
    3. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2019. "Dynamic Random Utility," Econometrica, Econometric Society, vol. 87(6), pages 1941-2002, November.
    4. Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2019. "Deliberately Stochastic," American Economic Review, American Economic Association, vol. 109(7), pages 2425-2445, July.
      • Simone Cerreia-Vioglio & David Dillenberger & Pietro Ortoleva & Gil Riella, 2012. "Deliberately Stochastic," PIER Working Paper Archive 17-013, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 25 May 2017.
    5. Jose Apesteguia & Miguel A. Ballester, 2016. "Stochastic representatitve agent," Economics Working Papers 1536, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Liu Shi & Jianying Qiu & Jiangyan Li & Frank Bohn, 2024. "Consciously stochastic in preference reversals," Journal of Risk and Uncertainty, Springer, vol. 68(3), pages 255-297, June.
    7. Efe A. Ok & Gerelt Tserenjigmid, 2023. "Measuring Stochastic Rationality," Papers 2303.08202, arXiv.org, revised Dec 2023.
    8. Jose Apesteguia & Miguel A. Ballester & Jay Lu, 2017. "Single‐Crossing Random Utility Models," Econometrica, Econometric Society, vol. 85, pages 661-674, March.
    9. Yosuke Hashidate, 2018. "Preferences for Randomization and Anticipated Utility," CIRJE F-Series CIRJE-F-1083, CIRJE, Faculty of Economics, University of Tokyo.
    10. Chew, Soo Hong & Miao, Bin & Shen, Qiang & Zhong, Songfa, 2022. "Multiple-switching behavior in choice-list elicitation of risk preference," Journal of Economic Theory, Elsevier, vol. 204(C).
    11. Francesco Cerigioni & Simone Galperti, 2021. "Listing specs: The effect of framing attributes on choice," Economics Working Papers 1775, Department of Economics and Business, Universitat Pompeu Fabra.
    12. S. Cerreia-Vioglio & F. Maccheroni & M. Marinacci & A. Rustichini, 2017. "Multinomial logit processes and preference discovery: inside and outside the black box," Working Papers 615, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. Allen, Roy & Dziewulski, Paweł & Rehbeck, John, 2022. "Making sense of monkey business: Re-examining tests of animal rationality," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 220-228.
    14. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2020. "Multinomial logit processes and preference discovery: outside and inside the black box," Working Papers 663, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    15. Roy Allen & John Rehbeck, 2023. "Revealed stochastic choice with attributes," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 75(1), pages 91-112, January.
    16. Andrew J. Keith & Darryl K. Ahner, 2021. "A survey of decision making and optimization under uncertainty," Annals of Operations Research, Springer, vol. 300(2), pages 319-353, May.
    17. Matthew Kovach & Gerelt Tserenjigmid, 2022. "Behavioral Foundations of Nested Stochastic Choice and Nested Logit," Journal of Political Economy, University of Chicago Press, vol. 130(9), pages 2411-2461.
    18. Heydari, Pedram, 2024. "Regret, responsibility, and randomization: A theory of stochastic choice," Journal of Economic Theory, Elsevier, vol. 217(C).
    19. Pennesi, Daniele, 2021. "Intertemporal discrete choice," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 690-706.
    20. Victor H. Aguiar & Maria Jose Boccardi & Nail Kashaev & Jeongbin Kim, 2023. "Random utility and limited consideration," Quantitative Economics, Econometric Society, vol. 14(1), pages 71-116, January.

    More about this item

    Keywords

    stochastic choice; randomness; noise;
    All these keywords.

    JEL classification:

    • D00 - Microeconomics - - General - - - General

    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:bge:wpaper:1018. 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: Bruno Guallar (email available below). General contact details of provider: https://edirc.repec.org/data/bargses.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.