Accurate Estimation of Small Effects: Illustration Through Air Pollution and Health

Vincent Bagilet ()
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Vincent Bagilet: ENS de Lyon - École normale supérieure de Lyon - Université de Lyon

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Abstract: This paper identifies design parameters that can lead to inaccurate estimates of small effects. Low statistical power not only makes such effects difficult to detect but resulting significant estimates necessarily exaggerate true effect sizes on average. Through the literature on short-term health effects of air pollution, I explore this issue and its policy implications. Exaggeration can be substantial and power low even with large sample sizes. Real-data simulations highlight key additional drivers: the number of exogenous shocks, instrument strength, and outcome count. I propose a workflow to evaluate and mitigate exaggeration risk in non-experimental studies.

Keywords: Exaggeration; Statistical Power; Causal Inference; Acute Health Effects; Air Pollution; Simulations (search for similar items in EconPapers)
Date: 2026-05-18
Note: View the original document on HAL open archive server: https://hal.science/hal-05624839v1
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