Wards Finance Seminar Series. Green Silence: Double machine learning carbon emissions under sample selection bias
Published: 8 December 2025
21 January Wards Finance Seminar Series with Professor Olivier Scaillet. University of Geneva and Swiss Finance Institute
Professor Olivier Scaillet, University of Geneva and Swiss Finance Institute. "Green Silence: Double machine learning Carbon emissions under sample selection bias"
Wednesday 21 January 2026. 15:00-16:30 Room 587 The Adam Smith Business School Building
Abstract
Voluntary carbon disclosure collapses into a paradox of green silence: firms choose to disclose emissions based on strategic incentives (e.g., correcting vendor overestimates), while high emit-ters may exploit vendor estimation bias. Mirroring Heckman sample selection bias, this self censorship skews disclosed emissions into non-random samples, distorting climate risk pricing
and policy. We bridge economic problem and machine learning, proposing a Heckman inspired three step framework in high dimensional settings to correct for strategic non-disclosure and ensure variable selection consistency in the presence of sample selection bias. By integrating kernel group lasso (KG-lasso) and double machine learning (DML) from neighbouring firms, i.e., using information from carbon next door, we unveil systematic underestimation: empirical analysis of 3444 unique US firms (2010-2023) rejects the null of no selection bias. Our findings indicate that voluntary disclosure induces adverse selection, where green silence rewards polluters and undermines decarbonization. Underestimation translates to a $2.6 billion shortfall in tax revenues and up to $525 billion hidden social cost of carbon. Our high-dimensional imputations also imply a substantially larger carbon premium.
Bio
Olivier Scaillet, Belgo-Swiss is professor of finance and statistics at the Geneva Finance Research Institute of the University of Geneva, and has a senior chair at the Swiss Finance Institute. He holds a Ph.D. from University Paris IX Dauphine in applied mathematics. Professor Scaillet's research expertise is in the area of derivatives pricing, econometric theory and econometrics applied to finance and insurance. He has published several papers in top journals in econometrics and finance, and co-authored a book on financial econometrics. He has been one of the winners of the bi-annual award for the best paper published in the Journal of Empirical Finance on the topic of quantitative risk management and of the Banque Privée Espirito Santo award prize on the topic of mutual fund performance. He is an elected fellow of SoFiE, IAAE, and IMS, fellow of JoE, and elected member of ISI. He is an associate editor of several leading academic journals in econometrics, statistics, banking and finance. He is an advisor for research teams in the finance and banking industry.
For further information, please contact business-school-research@glasgow.ac.uk
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First published: 8 December 2025