ramchoice-package: ramchoice: Revealed Preference and Attention Analysis in...

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

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

Description

Preferences and attention are important for understanding decision making, conducting welfare analysis, and providing robust policy recommendations. Decision makers may not pay full attention to all available alternatives, however, which can invalidate standard revealed preference analysis.

This package implements identification, estimation, inference, and specification procedures for the Random Attention Model of Cattaneo, Ma, Masatlioglu, and Suleymanov (2020; \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1086/706861")}) and the Attention Overload Model of Cattaneo, Cheung, Ma, and Masatlioglu (2026).

The principal RAM and homogeneous-AOM interfaces are revealPref, ramTest, revealAtte, revealPrefModel, aomModel, aomTest, and aomIdentify. The heterogeneous list-based AOM interfaces are hlaoModel, hlaoTest, hlaoNoPITest, hlaoEvent, and hlaoRankings. Data preparation and simulation utilities include sumData, genMat, logitAtte, and logitSimu. The legacy rAtte interface and simulated ramdata dataset are retained for compatibility and illustration.

Author(s)

Matias D. Cattaneo (maintainer), Princeton University. [e-mail].

Paul Cheung, University of Maryland. [e-mail]

Xinwei Ma, University of California San Diego. [e-mail]

Yusufcan Masatlioglu, University of Maryland. [e-mail]

Elchin Suleymanov, Purdue University. [e-mail]

References

M. D. Cattaneo, X. Ma, Y. Masatlioglu, and E. Suleymanov (2020). A Random Attention Model. Journal of Political Economy 128(7): 2796–2836. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1086/706861")}

M. D. Cattaneo, P. H. Y. Cheung, X. Ma, and Y. Masatlioglu (2026). Attention Overload. Working paper.

See Also

Useful links:

• https://github.com/mdcattaneo/ramchoice

• https://arxiv.org/abs/2110.10650

• Report bugs at https://github.com/mdcattaneo/ramchoice/issues

ramchoice documentation built on Sept. 4, 2026, 9:07 a.m.