Learning in reverse causal strategic environments with ramifications on two sided markets

Seamus Somerstep, Yuekai Sun, Yaacov Ritov

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Keywords: Strategic Classification, Performative Prediction, Labor Market

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TL;DR: We develop and study an example of performative prediction that is applicable to economic models of labor markets.

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 consider employers that seek to anticipate the strategic response of a labor force when developing a hiring policy. We show theoretically that employers with performatively optimal hiring policies improve employer reward, labor force skill level, and labor force equity (compared to employers that do not anticipate the strategic labor force response) in the classic Coate-Loury labor market model. Empirically, we show that these desirable properties of performative hiring policies do generalize to our own formulation of a general equilibrium labor market. On the other hand, we also observe that the benefits of performatively optimal hiring policies are brittle in some aspects. We demonstrate that in our formulation a performative employer both harms workers by reducing their aggregate welfare and fails to prevent discrimination when more sophisticated wage and cost structures are introduced.

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Primary Area: societal considerations including fairness, safety, privacy

Submission Number: 2693