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Peer Effects in Consideration and Preferences

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  • 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 only preferences, only 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 the preferences and the consideration mechanisms of each agent. 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 coffee chains and find evidence of limited consideration. We simulate counterfactual predictions and show how limited consideration slows down competition.

Suggested Citation

  • Nail Kashaev & Natalia Lazzati & Ruli Xiao, 2023. "Peer Effects in Consideration and Preferences," Papers 2310.12272, arXiv.org, revised Jan 2024.
    • Handle: RePEc:arx:papers:2310.12272
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Pietro Bonaldi & Ali Hortaçsu & Jakub Kastl, 2015. "An Empirical Analysis of Funding Costs Spillovers in the EURO-zone with Application to Systemic Risk," NBER Working Papers 21462, National Bureau of Economic Research, Inc.
    4. Kashaev, Nail & Aguiar, Victor H., 2022. "A random attention and utility model," Journal of Economic Theory, Elsevier, vol. 204(C).
    5. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    6. 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.
    7. 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.
    8. 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.
    9. 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).
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    Cited by:

    1. Roy Allen, 2024. "Exogenous Consideration and Extended Random Utility," Papers 2405.13945, arXiv.org.

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