ramchoice: Revealed Preference and Attention Analysis in Random Limited Attention Models

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 (2021) <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.

Version: 2.0
Depends: R (≥ 3.1.0)
Imports: MASS
Published: 2021-10-23
Author: Matias D. Cattaneo, Paul Cheung, Xinwei Ma, Yusufcan Masatlioglu, Elchin Suleymanov
Maintainer: Xinwei Ma <x1ma at ucsd.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: ramchoice results

Documentation:

Reference manual: ramchoice.pdf

Downloads:

Package source: ramchoice_2.0.tar.gz
Windows binaries: r-devel: ramchoice_2.0.zip, r-release: ramchoice_2.0.zip, r-oldrel: ramchoice_2.0.zip
macOS binaries: r-release (arm64): ramchoice_2.0.tgz, r-release (x86_64): ramchoice_2.0.tgz, r-oldrel: ramchoice_2.0.tgz
Old sources: ramchoice archive

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