A new paper from Timothy Christensen proposes a coupled-label bootstrap method to address biases in OLS estimators that arise when using AI/ML-generated labels as covariates in economic regressions. The research highlights that standard fixed-label bootstrap methods are often invalid unless specific independence conditions are met. The proposed coupled-label bootstrap jointly resamples true and imputed labels, offering a more robust solution without these stringent conditions, and includes finite-sample adjustments for improved accuracy. This work is illustrated with simulations and applied to analyze the relationship between wages and remote work status. AI
影响 Provides a statistical method to improve the reliability of economic analyses that incorporate AI-generated data labels.
排序理由 Academic paper on a statistical method for using AI-generated labels in economic regressions.
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