logitSimu: Choice Data Simulation Following the Logit Attention Rule

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

Choice Data Simulation Following the Logit Attention Rule

Description

logitSimu simulates choice data according to the logit attention rule considered by Brady and Rehbeck (2016). To be specific, for a choice problem S and its subset T, the attention that T attracts is assumed to be proportional to its size: |T|^a, where a is a parameter that one can specify. It will be assumed that the first alternative is the most preferred, and that the last alternative is the least preferred.

This function is useful for replicating the simulation results in Cattaneo, Ma, Masatlioglu, and Suleymanov (2020), and Cattaneo, Cheung, Ma, and Masatlioglu (2022).

Usage

logitSimu(n, uSize, mSize, a)

Arguments

n	Positive integer, the effective sample size for each choice problem.
uSize	Positive integer, total number of alternatives.
mSize	Positive integer, size of the choice problem.
a	Numeric, the parameter of the logit attention rule.

Value

menu	The choice problems.
choice	The simulated choices.

Author(s)

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

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

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

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

Elchin Suleymanov, Purdue University. [e-mail]

References

R. L. Brady and J. Rehbeck (2016). Menu-Dependent Stochastic Feasibility. Econometrica 84(3): 1203-1223. doi: 10.3982/ECTA12694

M. D. Cattaneo, X. Ma, Y. Masatlioglu, and E. Suleymanov (2020). A Random Attention Model. Journal of Political Economy 128(7): 2796-2836. doi: 10.1086/706861

M. D. Cattaneo, P. Cheung, X. Ma, and Y. Masatlioglu (2022). Attention Overload. Working paper.

Examples

set.seed(42)
logitSimu(n = 5, uSize = 6, mSize = 5, a = 2)

ramchoice documentation built on May 24, 2022, 1:06 a.m.