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New econometrics paper details fairness-accuracy frontier inference

This paper introduces a method for identifying and inferring the fairness-accuracy frontier, a concept crucial in econometrics. The proposed techniques allow for hypothesis testing and the construction of confidence sets for this frontier, particularly when outcome data is only available for a subset of individuals. The research provides a characterization of the identification region for the FA-frontier under specific selection processes and loss measurements, with extensions to broader loss functions currently in progress. AI

RANK_REASON The cluster contains a single academic paper published on arXiv, detailing new theoretical results in econometrics. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.LG →

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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yiqi Liu, Francesca Molinari, Amilcar Velez ·

    Identification and Inference for Algorithmic Frontiers with Selective Labels

    arXiv:2606.14977v1 Announce Type: cross Abstract: This paper provides identification results to characterize a fairness-accuracy (FA) frontier, and statistical inference tools to test hypotheses and build a confidence set for the FA-frontier, when outcomes are observed only for s…