IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2302.05806.html
   My bibliography  Save this paper

Random Utility, Repeated Choice, and Consumption Dependence

Author

Listed:
  • Christopher Turansick

Abstract

We study consumption dependence in the context of random utility and repeated choice. We show that, in the presence of consumption dependence, the random utility model is a misspecified model of repeated rational choice. This misspecification leads to biased estimators and failures of standard random utility axioms. We characterize exactly when and by how much the random utility model is misspecified when utilities are consumption dependent. As one possible solution to this problem, we consider time disaggregated data. We offer a characterization of consumption dependent random utility when we observe time disaggregated data. Using this characterization, we develop a hypothesis test for consumption dependent random utility that offers computational improvements over the natural extension of Kitamura and Stoye (2018) to our setting.

Suggested Citation

  • Christopher Turansick, 2023. "Random Utility, Repeated Choice, and Consumption Dependence," Papers 2302.05806, arXiv.org, revised Oct 2023.
  • Handle: RePEc:arx:papers:2302.05806
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2302.05806
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jetlir Duraj, 2018. "Dynamic Random Subjective Expected Utility," Papers 1808.00296, arXiv.org.
    2. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, July.
    3. Morris, Stephen, 1994. "Trade with Heterogeneous Prior Beliefs and Asymmetric Information," Econometrica, Econometric Society, vol. 62(6), pages 1327-1347, November.
    4. Marina Agranov & Pietro Ortoleva, 2017. "Stochastic Choice and Preferences for Randomization," Journal of Political Economy, University of Chicago Press, vol. 125(1), pages 40-68.
    5. Machina, Mark J, 1985. "Stochastic Choice Functions Generated from Deterministic Preferences over Lotteries," Economic Journal, Royal Economic Society, vol. 95(379), pages 575-594, September.
    6. Ariel Pakes & Jack R. Porter & Mark Shepard & Sophie Calder-Wang, 2021. "Unobserved Heterogeneity, State Dependence, and Health Plan Choices," NBER Working Papers 29025, National Bureau of Economic Research, Inc.
    7. M. Keith Chen, 2008. "Rationalization and Cognitive Dissonance: Do Choices Affect or Reflect Preferences?," Levine's Working Paper Archive 122247000000002336, David K. Levine.
    8. Samet, Dov, 1998. "Common Priors and Separation of Convex Sets," Games and Economic Behavior, Elsevier, vol. 24(1-2), pages 172-174, July.
    9. Deb, Rahul & Renou, Ludovic, 2021. "Dynamic Choice and Common Learning," CEPR Discussion Papers 16160, C.E.P.R. Discussion Papers.
    10. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    11. Nail Kashaev & Victor H. Aguiar, 2022. "Nonparametric Analysis of Dynamic Random Utility Models," Papers 2204.07220, arXiv.org.
    12. H.D. Block & Jacob Marschak, 1959. "Random Orderings and Stochastic Theories of Response," Cowles Foundation Discussion Papers 66, Cowles Foundation for Research in Economics, Yale University.
    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. Fedor Sandomirskiy & Omer Tamuz, 2023. "Decomposable Stochastic Choice," Papers 2312.04827, arXiv.org, revised May 2024.
    2. Chambers, Christopher P. & Masatlioglu, Yusufcan & Turansick, Christopher, 2024. "Correlated choice," Theoretical Economics, Econometric Society, vol. 19(3), July.
      • Christopher P. Chambers & Yusufcan Masatlioglu & Christopher Turansick, 2021. "Correlated Choice," Papers 2103.05084, arXiv.org, revised Mar 2023.
    3. Mira Frick & Ryota Iijima & Tomasz Strzalecki, 2019. "Dynamic Random Utility," Econometrica, Econometric Society, vol. 87(6), pages 1941-2002, November.
    4. Hellman, Ziv, 2011. "Iterated expectations, compact spaces, and common priors," Games and Economic Behavior, Elsevier, vol. 72(1), pages 163-171, May.
    5. 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.
    6. , & ,, 2011. "Agreeing to agree," Theoretical Economics, Econometric Society, vol. 6(2), May.
    7. Jie Bai, 2016. "Melons as Lemons: Asymmetric Information, Consumer Learning and Seller Reputation," Natural Field Experiments 00540, The Field Experiments Website.
    8. Khwaja, Ahmed & Sloan, Frank & Chung, Sukyung, 2006. "Learning about individual risk and the decision to smoke," International Journal of Industrial Organization, Elsevier, vol. 24(4), pages 683-699, July.
    9. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    10. Ziv Hellman & Miklós Pintér, 2022. "Charges and bets: a general characterisation of common priors," International Journal of Game Theory, Springer;Game Theory Society, vol. 51(3), pages 567-587, November.
    11. José Alvaro Rodrigues-Neto, 2012. "Cycles of length two in monotonic models," ANU Working Papers in Economics and Econometrics 2012-587, Australian National University, College of Business and Economics, School of Economics.
    12. Dirk Bergemann & Stephen Morris, 2012. "Robust Virtual Implementation," World Scientific Book Chapters, in: Robust Mechanism Design The Role of Private Information and Higher Order Beliefs, chapter 8, pages 263-317, World Scientific Publishing Co. Pte. Ltd..
    13. David Granlund, 2021. "A New Approach to Estimating State Dependence in Consumers’ Brand Choices Applied to 762 Pharmaceutical Markets," Journal of Industrial Economics, Wiley Blackwell, vol. 69(2), pages 443-483, June.
    14. Ching, Andrew T. & Erdem, Tülin & Keane, Michael P., 2014. "A simple method to estimate the roles of learning, inventories and category consideration in consumer choice," Journal of choice modelling, Elsevier, vol. 13(C), pages 60-72.
    15. Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
    16. Mingyu Joo & Dinesh K. Gauri & Kenneth C. Wilbur, 2020. "Temporal Distance and Price Responsiveness: Empirical Investigation of the Cruise Industry," Management Science, INFORMS, vol. 66(11), pages 5362-5388, November.
    17. Czajkowski, Mikolaj & Hanley, Nicholas & LaRiviere, Jacob, 2012. "The Effects of Experience on Preference Uncertainty: Theory and Empirics for Public and Quasi-Public Goods," Stirling Economics Discussion Papers 2012-17, University of Stirling, Division of Economics.
    18. Guofang Huang & Matthew Shum & Wei Tan, 2019. "Is pharmaceutical detailing informative? Evidence from contraindicated drug prescriptions," Quantitative Marketing and Economics (QME), Springer, vol. 17(2), pages 135-160, June.
    19. Hu, Yingyao & Kayaba, Yutaka & Shum, Matthew, 2013. "Nonparametric learning rules from bandit experiments: The eyes have it!," Games and Economic Behavior, Elsevier, vol. 81(C), pages 215-231.
    20. Yan Huang & Param Vir Singh & Kannan Srinivasan, 2014. "Crowdsourcing New Product Ideas Under Consumer Learning," Management Science, INFORMS, vol. 60(9), pages 2138-2159, September.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2302.05806. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.