Learning In Reverse Causal Strategic Environments With Ramifications on Two Sided Markets
This addresses equilibrium modeling in two-sided markets like labor, with incremental contributions to strategic classification.
The paper tackles the problem of causal strategic classification in labor markets, where employers anticipate workers' strategic behavior, and finds that performatively optimal hiring policies improve employer reward and labor force skill level, but harm labor force utility and fail to prevent discrimination in some cases.
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.