Finite-sample non-parametric bounds with an application to the causal effect of workforce gender diversity on firm performance

Grace Lordan and Kaveh Salehzadeh Nobari

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Classical Manski bounds identify average treatment effects under minimal assumptions but, in finite samples, assume that latent conditional expectations are bounded by the sample’s own extrema or that the population extrema are known a priori—often untrue in firm-level data with heavy tails. We develop a finite-sample, concentration-driven band (concATE) that replaces that assumption with a Dvoretzky–Kiefer–Wolfowitz tail bound, combines it with delta-method variance, and allocates size via Bonferroni. The band extends to a group-sequential design that controls the family-wise error when the first “significant” diversity threshold is data-chosen. Applied to 945 listed firms (2015 Q2–2022 Q1) concATE shows that senior-level gender diversity raises Tobin’s Q once representation exceeds ≈ 30% in growth sectors and ≈ 65% in cyclical sectors.

JEL-codes: C14 C21 J16 L25 M14 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2025-09-03
New Economics Papers: this item is included in nep-ecm and nep-lab
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