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ramchoice (version 2.2)

Revealed Preference and Attention Analysis in Random Limited Attention Models

Description

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) and Cattaneo, Cheung, Ma, and Masatlioglu (2022) , 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.

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Version

Install

install.packages('ramchoice')

Monthly Downloads

188

Version

2.2

License

GPL-2

Maintainer

Xinwei Ma

Last Published

January 22nd, 2024

Functions in ramchoice (2.2)

rAtte

Revealed Preference Analysis in Random Limited Attention Models
ramdata

ramdata: Simulated Choice Data
ramchoice-package

ramchoice: Revealed Preference and Attention Analysis in Random Limited Attention Models
print.ramchoiceRevealPref

Internal function.
logitSimu

Choice Data Simulation Following the Logit Attention Rule
revealAtte

Revealed Attention Analysis in Random Limited Attention Models
genMat

Generate Constraint Matrices
logitAtte

Compute Choice Probabilities and Attention Frequencies for the Logit Attention Rule
sumData

Generate Summary Statistics
revealPref

Revealed Preference Analysis in Random Limited Attention Models
print.ramchoiceRevealAtte

Internal function.
summary.ramchoiceRevealPrefModel

Internal function.
print.ramchoiceRevealPrefModel

Internal function.
summary.ramchoiceRevealPref

Internal function.
summary.ramchoiceRevealAtte

Internal function.
revealPrefModel

Model Falsification with Random Limited Attention