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Talk of the title: “title”

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Short Biography: ...

Talk of the title: “title”

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Short Biography: Sophie Dabo-Niang is professor of Applied Mathematics (Statistics) at University of Lille and member of INRIA-MODAL team. She completed a 3-years PhD in Statistics from the University Paris 6 in 2002. She was chair of the axis MeQAME (Quantitauve methods in Management and Economics) of LEM and vice-chair of EMS-CDC (European Mathematical Society-Committee of Developing Counties; http://euro-math-soc.eu/committee/developing-countries). Dr. Sophie Dabo-Niang research program is focused on the study of non(semi)-parametric inference of functional and spatio-temporal data. From an applied perspective, she is interested in economics, medical, environmental and hydrological studies. She published more than forty statistical papers.

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Short Biography: Nazim Hussain is an Associate Professor of Sustainability Accounting at the University of Groningen, The Netherlands. His research focuses on corporate sustainability, corporate governance, the circular economy, and greenwashing. He has published extensively in top-tier academic journals, including the British Accounting Review, Journal of Business Ethics, British Journal of Management, and Journal of Product Innovation Management, among many others. 

Title of the talk:  "Corporate Environmental Sustainability"

Abstract: This study investigates whether and how greenwashing—the gap between a firm’s “green talk” and “green walk”—affects bond pricing. Using 3,810 public bonds issued by US firms, we find a positive relationship between greenwashing and the cost of bonds. We identify the causal relationship by using the Federal Trade Commission’s 2012 regulatory intervention to curb misleading environmental claims as an exogenous shock to greenwashing. We also find a more pronounced relationship between greenwashing and the cost of bonds for firms whose credit rating is adjacent to the investment–speculative borderline, firms operating in environmentally sensitive industries, and firms with opaque information environments. Moreover, our two-step channel analyses show that greenwashing is associated with higher environmental litigation costs and a higher chance of rating disagreements among credit rating agencies, thus identifying risk and information channels through which greenwashing increases the cost of bonds. Our results shed new light on the economic consequences of greenwashing through the lens of the bond market.

Short Biography: : Agronomic Engineer from Institut Agronomique et Vétérinaire Hassan II, Rabat (1981), and Ecole Supérieure du Bois, Paris France(1980). Master of Sciences (1988) in economics and PhD in Forestry (19992) from the University of Idaho, USA. Master of Sciences in ICT, University of Louis Pasteur, Strasbourg, France (virtual campus). Full Professor at Ecole Nationale Forestière d’Ingénieurs since 1994, and visiting professor to many universities.  Research Fellow in the Royal Institute of Strategic Studies (IRES), Morocco, and in the Institute for Labor Studies (IZA), Germany. His recent research interests deal with integrated natural resources management, environmental assessment, climate change adaptation, and rural development. Author of many publications (book chapters, scientific papers, expertise reports, outreaching documents, etc.), recipient of numerous research grants and consultant for international organizations (UNESCO, ISESCO, UNDP, UNEP, World Bank, FAO, GIZ, ..) and national public and private institutions. Fulbright Alumni, president of the Regional Science Association of Morocco. Lead author for the IPCC fifth report, chapter 5 (coastal zones and low lying areas).

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Short Biography: : A Dr Rachida Ouysse is a Senior Lecturer in Economics at the UNSW Business School, UNSW Sydney. She holds a PhD in Economics/Econometrics from Boston College and an MA in Econometrics from the Université de Montréal. She has published in leading A and A* econometrics, statistics, forecasting, and financial econometrics journals, including the Journal of Financial Econometrics, the International Journal of Forecasting, and the Journal of Multivariate Analysis. Her research lies at the intersection of econometric theory, financial econometrics, and big‑data modelling, with work on high‑dimensional factor models, Bayesian and bootstrap methods, and dense and sparse predictive models for economic and financial time series.

A central theme of her recent work is the measurement of environmental and sustainability risk in financial markets. She develops matrix‑factor and high‑dimensional methods for structured ESG disclosure data to quantify firms’ alignment with sector‑specific materiality standards and to detect potential greenwashing in corporate reporting, with the aim of supporting more transparent and reliable environmental and climate‑related disclosures.

Dr Ouysse is co‑leading an “AI‑Powered ESG Alignment & Greenwashing Risk Analytics Platform” funded by an AEA IGNITE grant, in collaboration with industry partners, to deliver scalable tools that can be used by financial institutions, investors, and regulators. Through her role in the UNSW Fintech AI Innovation Consortium and its regulatory roundtables, she works at the interface of econometrics, AI, and policy, contributing evidence‑based insights to debates on sustainable finance, AI governance, and the design of climate‑aligned financial regulation.

Title of the talk:  “Disclosure Architecture and Materiality Alignment: Estimation and Inference in High-Dimensional ESG Panels” 

Abstract: ThiExisting work on ESG disclosure largely measures disclosure intensity or aggregate scores, leaving the internal structure of disclosure across topics largely unexamined. That leaves open whether firms disclose the topics that are materially relevant for their industry or simply disclose more. The distinction matters for investors, lenders, regulators, and standard setters because materiality-based reporting is intended to support decision-useful information. This paper studies whether the cross-metric architecture of structured ESG disclosure aligns with sector-specific materiality benchmarks. We model firm-level disclosure matrices in a large-firm, large-metric, fixed-time setting and construct a rotation-invariant Materiality Architecture Score from the estimated metric-factor projection space. We establish consistency of the estimated metric-factor projection space, asymptotic normality of the induced architecture-level measures, and valid firm-cluster pairs-bootstrap inference under the unbalanced-panel design.

The empirical application uses Eurofidai structured ESG disclosures, with data obtained via EUROFIDAI, matched to SASB materiality maps for four sectors: Commercial Banks, Semiconductors, Software & IT Services, and Biotechnology & Pharmaceuticals. The data allow disclosure to be studied as a structured cross-metric object rather than collapsed into a scalar intensity measure, and the sectoral SASB mapping provides an external benchmark for testing whether disclosure architecture is materially aligned. The results show systematic cross-sector differences in alignment and support an architecture-level greenwashing measure that distinguishes disclosure volume from materiality alignment.

Short Biography: : short bio

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Short Biography: : short bio

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