IDEAS home Printed from https://ideas.repec.org/p/pit/wpaper/7145.html
   My bibliography  Save this paper

Identification of Incomplete Preferences

Author

Listed:
  • Arie Beresteanu

Abstract

We provide a sharp identification region for discrete choice models in which consumers' preferences are not necessarily complete and only aggregate choice data is available to the analysts. Behavior with non complete preferences is modeled using an upper and a lower utility for each alternative so that non-comparability can arise. The identification region places intuitive bounds on the probability distribution of upper and lower utilities. We show that the existence of an instrumental variable can be used to reject the hypothesis that all consumers' preferences are complete, while attention sets can be used to rule out the hypothesis that all individuals cannot compare any two alternatives. We apply our methods to data from the 2018 mid-term elections in Ohio.

Suggested Citation

  • Arie Beresteanu, 2021. "Identification of Incomplete Preferences," Working Paper 7145, Department of Economics, University of Pittsburgh.
    • Handle: RePEc:pit:wpaper:7145
    as

    Download full text from publisher

    File URL: https://www.econ.pitt.edu/sites/default/files/working_papers/Identification_Incomplete_Preferences-Beresteanu_Rigotti_0.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Yuichi Kitamura & Jörg Stoye, 2018. "Nonparametric Analysis of Random Utility Models," Econometrica, Econometric Society, vol. 86(6), pages 1883-1909, November.
    2. Paola Manzini & Marco Mariotti, 2014. "Stochastic Choice and Consideration Sets," Econometrica, Econometric Society, vol. 82(3), pages 1153-1176, May.
    3. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    4. Hoderlein, Stefan, 2011. "How many consumers are rational?," Journal of Econometrics, Elsevier, vol. 164(2), pages 294-309, October.
    5. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
    6. Oben K. Bayrak & John D. Hey, 2020. "Understanding Preference Imprecision," Journal of Economic Surveys, Wiley Blackwell, vol. 34(1), pages 154-174, February.
    7. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    8. Juan Dubra & Fabio Maccheroni & Efe A. Ok, 2004. "Expected Utility Without the Completeness Axiom," Yale School of Management Working Papers ysm404, Yale School of Management.
    9. Yusufcan Masatlioglu & Daisuke Nakajima & Erkut Y. Ozbay, 2012. "Revealed Attention," American Economic Review, American Economic Association, vol. 102(5), pages 2183-2205, August.
    10. Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2011. "Sharp Identification Regions in Models With Convex Moment Predictions," Econometrica, Econometric Society, vol. 79(6), pages 1785-1821, November.
    11. Pawel Dziewulski, 2021. "A comprehensive revealed preference approach to approximate utility maximisation," Working Paper Series 0621, Department of Economics, University of Sussex Business School.
    12. Feddersen, Timothy J. & Pesendorfer, Wolfgang, 1999. "Abstention in Elections with Asymmetric Information and Diverse Preferences," American Political Science Review, Cambridge University Press, vol. 93(2), pages 381-398, June.
    13. Charles F. Manski & Elie Tamer, 2002. "Inference on Regressions with Interval Data on a Regressor or Outcome," Econometrica, Econometric Society, vol. 70(2), pages 519-546, March.
    14. Dubra, Juan & Maccheroni, Fabio & Ok, Efe A., 2004. "Expected utility theory without the completeness axiom," Journal of Economic Theory, Elsevier, vol. 115(1), pages 118-133, March.
    15. Kfir Eliaz & Ran Spiegler, 2011. "Consideration Sets and Competitive Marketing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 235-262.
    16. Melinda Gann Hall & Chris W. Bonneau, 2008. "Mobilizing Interest: The Effects of Money on Citizen Participation in State Supreme Court Elections," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 457-470, July.
    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. Gorno, Leandro & Rivello, Alessandro T., 2023. "A maximum theorem for incomplete preferences," Journal of Mathematical Economics, Elsevier, vol. 106(C).
    2. Arlegi, Ritxar & Bourgeois-Gironde, Sacha & Hualde, Mikel, 2022. "Attitudes toward choice with incomplete preferences: An experimental study," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 663-679.
    3. Horan, Sean & Manzini, Paola & Mariotti, Marco, 2022. "When is coarseness not a curse? Comparative statics of the coarse random utility model," Journal of Economic Theory, Elsevier, vol. 202(C).

    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. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers CWP55/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Eddie Dekel & Barton L. Lipman, 2010. "How (Not) to Do Decision Theory," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 257-282, September.
    5. Magnac, Thierry, 2013. "Identification partielle : méthodes et conséquences pour les applications empiriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 89(4), pages 233-258, Décembre.
    6. Ellis, Andrew, 2018. "Foundations for optimal inattention," Journal of Economic Theory, Elsevier, vol. 173(C), pages 56-94.
    7. Lu, Zhentong, 2022. "Estimating multinomial choice models with unobserved choice sets," Journal of Econometrics, Elsevier, vol. 226(2), pages 368-398.
    8. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers 55/13, Institute for Fiscal Studies.
    9. Christian Bontemps & Thierry Magnac & Eric Maurin, 2012. "Set Identified Linear Models," Econometrica, Econometric Society, vol. 80(3), pages 1129-1155, May.
    10. Roy Allen & John Rehbeck, 2020. "Identification of Random Coefficient Latent Utility Models," Papers 2003.00276, arXiv.org.
    11. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    12. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    13. Aguiar, Victor H. & Boccardi, Maria Jose & Dean, Mark, 2016. "Satisficing and stochastic choice," Journal of Economic Theory, Elsevier, vol. 166(C), pages 445-482.
    14. Helmers, Christian & Krishnan, Pramila & Patnam, Manasa, 2019. "Attention and saliency on the internet: Evidence from an online recommendation system," Journal of Economic Behavior & Organization, Elsevier, vol. 161(C), pages 216-242.
    15. Carlo Baldassi & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Marco Pirazzini, 2020. "A Behavioral Characterization of the Drift Diffusion Model and Its Multialternative Extension for Choice Under Time Pressure," Management Science, INFORMS, vol. 66(11), pages 5075-5093, November.
    16. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    17. Levon Barseghyan & Maura Coughlin & Francesca Molinari & Joshua C. Teitelbaum, 2021. "Heterogeneous Choice Sets and Preferences," Econometrica, Econometric Society, vol. 89(5), pages 2015-2048, September.
    18. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Demirkan, Yusufcan & Kimya, Mert, 2020. "Hazard rate, stochastic choice and consideration sets," Journal of Mathematical Economics, Elsevier, vol. 87(C), pages 142-150.
    20. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2023. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," Econometrica, Econometric Society, vol. 91(1), pages 107-146, January.

    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:pit:wpaper:7145. 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: Department of Economics, University of Pittsburgh (email available below). General contact details of provider: https://edirc.repec.org/data/depghus.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.