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Peer Effects in Consideration and Preferences

Nail Kashaev, Natalia Lazzati, Ruli Xiao

TL;DR

This paper develops a general discrete-choice model where peers influence both the consideration sets and preferences of agents, formalized through two edge types in a fixed network. Using a continuous-time Markov revision process and a system of conditional choice probabilities, the authors prove equilibrium existence and nonparametric identification of the network, consideration mechanisms, and preference rules from long-run choice data. They provide a constructive identification strategy that leverages changes in peers choices to recover who influences whom and whether influence acts on consideration or on preferences, without relying on exogenous covariates. The empirical application to expansion decisions of Nayuki and Heytea in China shows substantial limited consideration that evolves with network growth, and counterfactuals demonstrate that ignoring limited attention can severely misstate market profitability and competition dynamics, underlining the practical importance of considering bounded rationality in firm entry decisions.

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.

Peer Effects in Consideration and Preferences

TL;DR

This paper develops a general discrete-choice model where peers influence both the consideration sets and preferences of agents, formalized through two edge types in a fixed network. Using a continuous-time Markov revision process and a system of conditional choice probabilities, the authors prove equilibrium existence and nonparametric identification of the network, consideration mechanisms, and preference rules from long-run choice data. They provide a constructive identification strategy that leverages changes in peers choices to recover who influences whom and whether influence acts on consideration or on preferences, without relying on exogenous covariates. The empirical application to expansion decisions of Nayuki and Heytea in China shows substantial limited consideration that evolves with network growth, and counterfactuals demonstrate that ignoring limited attention can severely misstate market profitability and competition dynamics, underlining the practical importance of considering bounded rationality in firm entry decisions.

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.
Paper Structure (18 sections, 10 theorems, 48 equations, 4 figures)

This paper contains 18 sections, 10 theorems, 48 equations, 4 figures.

Table of Contents

  1. Introduction
  2. The Model
  3. Network, Consideration Sets, and Preferences
  4. Main Assumptions
  5. Equilibrium Behavior
  6. Empirical Content of the Model
  7. Identification of the Model From the Conditional Choice Probabilities
  8. Identification of the Conditional Choice Probabilities
  9. Extensions
  10. History Dependence and Own Past Choices
  11. Nonobservable Default
  12. Application
  13. Empirical Model
  14. Estimation
  15. Estimation Results
  16. ...and 3 more sections

Key Result

Proposition 2.1

If Assumptions ass: MM, ass: A1(i), and ass: A2(i) hold, then there exists a unique equilibrium $\mu$ with full support.

Figures (4)

  • Figure 1: Normalized histogram of consideration probabilities for both firms at the data's beginning and end.
  • Figure 2: Limited consideration vs. full consideration expansion probabilities.
  • Figure 3: Counterfactual Scenario 1. Fraction of monopolistic, duopolistic, and markets that are not served over time.
  • Figure 4: Counterfactual Scenario 2. Fraction of monopolistic, duopolistic, and markets that are not served over time.

Theorems & Definitions (28)

  • Example 1
  • Example 1: continued
  • Example 1: continued
  • Remark 1
  • Remark 2
  • Remark 3
  • Example 1: continued
  • Example 1: continued
  • Example 1: continued
  • Proposition 2.1
  • ...and 18 more