ramchoice (version 1.1)

ramchoice-package: ramchoice: Estimation and Inference in Random Attention Models

Description

Information about socio-economic agent's preference (consumer, firm, organization, voter, etc.) is important not only for understanding the decision making process, but also for conducting welfare analysis and providing robust policy recommendations. However, it is widely documented in psychology, economics and other disciplines that decision makers may not pay full attention to all available alternatives, rendering standard revealed preference theory invalid.

This package implements the estimation and inference procedure documented in Cattaneo, Ma, Masatlioglu and Suleymanov (2019), which utilizes standard choice data to partially identify decision maker's preference. For statistical inference, several simulation-based critical values are provided.

The following functions are provided: rAtte (the main function), sumData, genMat. A simulated dataset ramdata is also included for illustration purpose.

Arguments

References

M. D. Cattaneo, X. Ma, Y. Masatlioglu and E. Suleymanov (2019). A Random Attention Model. Journal of Political Economy, forthcoming.