Strategic Attribute Learning
Theoretical Economics
2025-11-27 v2
Abstract
A researcher allocates a budget of informative tests across multiple unknown attributes to influence a decision-maker. We derive the researcher's equilibrium learning strategy by solving an auxiliary single-player problem. The attribute weights in this problem depend on how much the researcher and the decision-maker disagree. If the researcher expects an excessive response to new information, she forgoes learning altogether. In an organizational context, we show that a manager favors more diverse analysts as the hierarchical distance grows. In another application, we show how an appropriately opposed advisor can constrain a discriminatory politician, and identify the welfare-inequality Pareto frontier of researchers.
Cite
@article{arxiv.2412.10024,
title = {Strategic Attribute Learning},
author = {Jean-Michel Benkert and Ludmila Matyskova and Egor Starkov},
journal= {arXiv preprint arXiv:2412.10024},
year = {2025}
}