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New paper questions interpretation of instrumental variable estimators

By PulseAugur Editorial · [1 sources] ·

A new paper published on arXiv by Danielle Tsao explores the challenges of interpreting instrumental variable (IV) estimators when dealing with aggregate treatment variables. The research highlights that the causal effect of an aggregate treatment can be ambiguous, depending on how interventions are implemented at a component level. The paper introduces the aggregate-constrained component intervention distribution (ACID) to formalize this relationship and identifies specific conditions under which standard IV estimators can still provide valid interpretations. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing a new methodology and analysis in statistics. [lever_c_demoted from research: ic=1 ai=0.1]

Read on arXiv stat.ML →

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New paper questions interpretation of instrumental variable estimators

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The cluster contains a research paper published on arXiv detailing a new methodology and analysis in statistics. [lever_c_demoted from research: ic=1 ai=0.1]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Danielle Tsao, Krikamol Muandet, Frederick Eberhardt, Emilija Perkovi\'c ·

    Lost in Aggregation: The Causal Interpretation of the IV Estimand

    arXiv:2601.12120v2 Announce Type: replace-cross Abstract: Instrumental variable estimation has emerged as a standard approach to mitigating confounding bias in the social sciences and epidemiology, where conducting randomized experiments can be too costly or infeasible. However, …

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