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LEARNING IN REVERSE CAUSAL STRATEGIC ENVIRONMENTS WITH RAMIFICATIONS ON TWO SIDED MARKETS

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

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.

Original languageEnglish
StatePublished - 2024
Externally publishedYes
Event12th International Conference on Learning Representations, ICLR 2024 - Hybrid, Vienna, Austria
Duration: 7 May 202411 May 2024

Conference

Conference12th International Conference on Learning Representations, ICLR 2024
Country/TerritoryAustria
CityHybrid, Vienna
Period7/05/2411/05/24

Bibliographical note

Publisher Copyright:
© 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

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