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Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets

Machine Learning 2024-04-23 v1 Computer Science and Game Theory Machine Learning

Abstract

Motivated by equilibrium models of labor markets, we develop a formulation of causal strategic classification in which strategic agents can directly manipulate their outcomes. As an application, we compare employers that anticipate the strategic response of a labor force with employers that do not. We show through a combination of theory and experiment that employers with performatively optimal hiring policies improve employer reward, labor force skill level, and in some cases labor force equity. On the other hand, we demonstrate that performative employers harm labor force utility and fail to prevent discrimination in other cases.

Keywords

Cite

@article{arxiv.2404.13240,
  title  = {Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets},
  author = {Seamus Somerstep and Yuekai Sun and Ya'acov Ritov},
  journal= {arXiv preprint arXiv:2404.13240},
  year   = {2024}
}

Comments

22 pages, 5 figures

R2 v1 2026-06-28T16:00:29.519Z