IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.12272.html

Peer Effects in Consideration and Preferences

Author

Listed:
  • Nail Kashaev
  • Natalia Lazzati
  • Ruli Xiao

Abstract

We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behavior and establish conditions under which all parts of the model can be recovered from a sequence of choices. We allow peers to affect preferences, consideration, or both. We show that these peer-effect mechanisms have different behavioral implications in the data. This allows us to recover the set and the type of connections between the agents in the network. We then use this information to recover each agent's preferences and consideration mechanisms. These nonparametric identification results allow for general forms of heterogeneity across agents and do not rely on the variation of either exogenous covariates or the set of available options (menus). We apply our results to model expansion decisions by tea chains and find evidence of limited consideration. We simulate counterfactual predictions and show how limited consideration slows market penetration and competition.

Suggested Citation

  • Nail Kashaev & Natalia Lazzati & Ruli Xiao, 2023. "Peer Effects in Consideration and Preferences," Papers 2310.12272, arXiv.org, revised Feb 2026.
    • Handle: RePEc:arx:papers:2310.12272
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.12272
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kashaev, Nail & Aguiar, Victor H., 2022. "A random attention and utility model," Journal of Economic Theory, Elsevier, vol. 204(C).
    2. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    3. Áureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: identification, simulations and an application," CeMMAP working papers CWP58/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Jeremy T. Fox & Natalia Lazzati, 2017. "A note on identification of discrete choice models for bundles and binary games," Quantitative Economics, Econometric Society, vol. 8(3), pages 1021-1036, November.
    5. 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.
    6. Jason Abaluck & Abi Adams-Prassl, 2021. "What do Consumers Consider Before They Choose? Identification from Asymmetric Demand Responses," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(3), pages 1611-1663.
    7. Áureo de Paula & Imran Rasul & Pedro C L Souza, 2025. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 92(4), pages 2691-2729.
    8. Agranov, Marina & Elliott, Matt & Ortoleva, Pietro, 2021. "The importance of Social Norms against Strategic Effects: The case of Covid-19 vaccine uptake," Economics Letters, Elsevier, vol. 206(C).
    9. Fabian Dunker & Stefan Hoderlein & Hiroaki Kaido, 2017. "Nonparametric identification of random coefficients in endogenous and heterogeneous aggregate demand models," CeMMAP working papers 11/17, Institute for Fiscal Studies.
    10. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "Empirical Analysis of Funding Cost Spillovers in the EURO Zone with Application to Systemic Risk," Working Papers 2015-5, Princeton University. Economics Department..
    11. Bet Caeyers, 2014. "Peer effects in development programme awareness of vulnerable groups in rural Tanzania," CSAE Working Paper Series 2014-11, Centre for the Study of African Economies, University of Oxford.
    12. Blevins, Jason R., 2017. "Identifying Restrictions For Finite Parameter Continuous Time Models With Discrete Time Data," Econometric Theory, Cambridge University Press, vol. 33(3), pages 739-754, June.
    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. Hui Liu & Yao Luo, 2025. "Demand Analysis under Price Rigidity and Endogenous Assortment: An Application to China's Tobacco Industry," Papers 2501.17251, arXiv.org.
    2. Roy Allen, 2024. "Exogenous Consideration and Extended Random Utility," Papers 2405.13945, arXiv.org.

    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. Nail Kashaev & Natalia Lazzati, 2019. "Peer Effects in Random Consideration Sets," Papers 1904.06742, arXiv.org, revised May 2021.
    2. Roy Allen, 2024. "Exogenous Consideration and Extended Random Utility," Papers 2405.13945, arXiv.org.
    3. Marco Battaglini & Eleonora Patacchini & Edoardo Rainone, 2019. "Endogenous Social Connections in Legislatures," NBER Working Papers 25988, National Bureau of Economic Research, Inc.
    4. Zhou, Xianbo & Wu, Yingming & Sun, Yucheng, 2025. "Consumption peer effects among migrants in China," International Review of Economics & Finance, Elsevier, vol. 103(C).
    5. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    6. Roy Allen & John Rehbeck, 2020. "Identification of Random Coefficient Latent Utility Models," Papers 2003.00276, arXiv.org.
    7. Siddhartha Chib & Kenichi Shimizu, 2023. "Scalable Estimation of Multinomial Response Models with Random Consideration Sets," Papers 2308.12470, arXiv.org, revised Sep 2025.
    8. Wang, Ao, 2023. "Sieve BLP: A semi-nonparametric model of demand for differentiated products," Journal of Econometrics, Elsevier, vol. 235(2), pages 325-351.
    9. Zhou, Wenyu, 2019. "A network social interaction model with heterogeneous links," Economics Letters, Elsevier, vol. 180(C), pages 50-53.
    10. Kovach, Matthew & Suleymanov, Elchin, 2023. "Reference dependence and random attention," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 421-441.
    11. Takeshi Fukasawa, 2024. "The Biases in Applying Static Demand Models Under Dynamic Demand," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 65(2), pages 561-594, September.
    12. Hossein Alidaee & Eric Auerbach & Michael P. Leung, 2020. "Recovering Network Structure from Aggregated Relational Data using Penalized Regression," Papers 2001.06052, arXiv.org.
    13. Wang, Ao, 2020. "Identifying the Distribution of Random Coefficients in BLP Demand Models Using One Single Variation in Product Characteristics," The Warwick Economics Research Paper Series (TWERPS) 1304, University of Warwick, Department of Economics.
    14. Promit K. Chaudhuri & Matthew O. Jackson & Sudipta Sarangi & Hector Tzavellas, 2023. "Games Under Network Uncertainty," Papers 2305.03124, arXiv.org, revised Dec 2024.
    15. Candelaria, Luis E. & Ura, Takuya, 2020. "Identification and Inference of Network Formation Games with Misclassified Links," The Warwick Economics Research Paper Series (TWERPS) 1258, University of Warwick, Department of Economics.
    16. Ayden Higgins & Federico Martellosio, 2019. "Shrinkage Estimation of Network Spillovers with Factor Structured Errors," Papers 1909.02823, arXiv.org, revised Nov 2021.
    17. Kaushil Patel, 2025. "Price-Based Attention and Welfare," Papers 2511.03813, arXiv.org.
    18. Sentana, Enrique, 2025. "Reprint of: Finite underidentification," Journal of Econometrics, Elsevier, vol. 248(C).
    19. Wang, Ao, 2021. "A BLP Demand Model of Product-Level Market Shares with Complementarity," The Warwick Economics Research Paper Series (TWERPS) 1351, University of Warwick, Department of Economics.
    20. Hsieh, Chih-Sheng & Hsu, Yu-Chin & Ko, Stanley I.M. & Kovářík, Jaromír & Logan, Trevon D., 2024. "Non-representative sampled networks: Estimation of network structural properties by weighting," Journal of Econometrics, Elsevier, vol. 240(1).

    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:2310.12272. 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.