ramdata

choice

The file contains a standard choice data of 9,000 observations.
 There are five alternatives in the grand set.
See <code>revealPref</code> for revealed preference analysis, and <code>revealAtte</code>
 for revealed attention. <code>sumData</code> is a low-level function that computes summary
 statistics, and <code>genMat</code> generates constraint matrices subject to given preferences.

It is widely documented in psychology, economics and other disciplines that socio-economic agent may not pay full attention to all available alternatives, rendering standard revealed preference theory invalid. This package implements the estimation and inference procedures of Cattaneo, Ma, Masatlioglu and Suleymanov (2020) <arXiv:1712.03448> and Cattaneo, Cheung, Ma, and Masatlioglu (2022) <arXiv:2110.10650>, which utilizes standard choice data to partially identify and estimate a decision maker's preference and attention. For inference, several simulation-based critical values are provided.

Xinwei Ma

ramchoice

Revealed Preference and Attention Analysis in Random Limited
Attention Models

ramdata function

<dl>
 <dt>menu</dt>
<dd>Numeric matrix of 0s and 1s, choice problems (1 indicates an alternative in the choice problem and 0 otherwise).</dd> <dt>choice</dt>
<dd>Numeric matrix of 0s and 1s, choices (1 indicates an alternative being chosen).</dd>
</dl>

Format

ramdata: Simulated Choice Data — ramdata

<dl>
 <dt>menu</dt>
<dd>Numeric matrix of 0s and 1s, choice problems (1 indicates an alternative in the choice problem and 0 otherwise).</dd>

 <dt>choice</dt>
<dd>Numeric matrix of 0s and 1s, choices (1 indicates an alternative being chosen).</dd>


</dl>

ramdata: ramdata: Simulated Choice Data

Description

Arguments

Format