A Random Attention Model
Bibliographic Data
| ID | 10171196 |
|---|---|
| Authors | Matias D Cattaneo (0000-0003-0493-7506), Xinwei Ma (0000-0001-8827-9146, University of California San Diego), Yusufcan Masatlıoĝlu (0000-0002-9423-3272, University of Maryland, College Park), Yusufcan Masatlioglu, Elchin Suleymanov (0000-0003-4816-5886, Purdue University West Lafayette) |
| Year | 2019 |
| Volume | 128 |
| Issue | 7 |
| Pages | 2796-2836 |
| Publication date | 2019-10-14 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Political Economy (JOURNAL) |
| Journal identifiers | ISSN: 0022-3808 • E-ISSN: 1537-534X |
| Publisher | University of Chicago Press (PUBLISHER • US) |
| DOI | 10.1086/706861 |
| OpenAlex | W2772115145 |
| Language | EN |
| Citations received | 10 |
| References cited | 36 |
This paper illustrates how one can deduce preference from observed choices when attention is not only limited but also random. In contrast to earlier approaches, we introduce a Random Attention Model (RAM) where we abstain from any particular attention formation, and instead consider a large class of nonparametric random attention rules. Our model imposes one intuitive condition, termed Monotonic Attention, which captures the idea that each consideration set competes for the decision-maker's attention. We then develop revealed preference theory within RAM and obtain precise testable implications for observable choice probabilities. Based on these theoretical findings, we propose econometric methods for identification, estimation, and inference of the decision maker's preferences. To illustrate the applicability of our results and their concrete empirical content in specific settings, we also develop revealed preference theory and accompanying econometric methods under additional nonparametric assumptions on the consideration set for binary choice problems. Finally, we provide general purpose software implementation of our estimation and inference results, and showcase their performance using simulations
Class (philosophy · Discrete choice · Econometric model · Econometrics · Inference · Machine learning · Monotonic function · Nonparametric statistics · Observable · Preference · Revealed preference · Set (abstract data type · Statistics · Artificial Intelligence · Computer Science · Consumer Market Behavior and Pricing · Decision-Making and Behavioral Economics · Economic and Environmental Valuation · Mathematics
An economist and a psychologist form a line
Context-Dependent Heterogeneous Preferences
Risk Preference Types, Limited Consideration, and Welfare
Dual Decision Processes
Progressive Random Choice
Mixture Choice Data
Luce rule with limited consideration
Random consideration and choice
Category-dependent preferences and stochastic choice
Limited attention and models of choice
Elimination by aspects
Intransitivity of preferences.
Confidence Intervals for Partially Identified Parameters
The perception-adjusted Luce model
Random consideration and choice
Luce rule with limited consideration
Stochastic Choice and Preferences for Randomization
Revealed Preference and the Utility Function
A Behavioral Model of Rational Choice
An Evaluation Cost Model of Consideration Sets
Adding Asymmetrically Dominated Alternatives
| Unique citing works | 10 |
|---|---|
| Citations per year | 1,25 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |