Compensation greenwashing illustration by Wasabikon from Pixabay
Compensation greenwashing: 13x new research on climate facts, green (fintech) nudges, greentech, ESG data, ESG risks, ESG ratings, sustainable investors, climate news effects, fiduciary climate duty, forestation effects and FinAI (# shows SSRN full paper downloads as of Nov. 7th, 2024)
Social and ecological research
Climate fact checking AI: Automated Fact-Checking of Climate Change Claims with Large Language Models by Markus Leippold and many more as of March 8th, 2024 (#126): „This paper presents Climinator, a novel AI-based tool designed to automate the fact-checking of climate change claims. Utilizing an array of Large Language Models (LLMs) informed by authoritative sources like the IPCC reports and peer-reviewed scientific literature … Our model demonstrates remarkable accuracy when testing claims collected from Climate Feedback and Skeptical Science. Notably, when integrating an advocate with a climate science denial perspective in our framework, Climinator’s iterative debate process reliably converges towards scientific consensus, underscoring its adeptness at reconciling diverse viewpoints into science-based, factual conclusions” (abstract).
Green nudges? Creating pro-environmental behavior change: Economic incentives or norm-nudges? by Mathias Ekström, Hallgeir Sjåstad and Kjetil Bjorvatn as of Sept. 26th, 2024 (#27): “… we present causal evidence from a two-year field experiment, comparing how a small price incentive and a social norm-nudge affect the recycling behavior of more than 2,000 households. The results show a large, immediate, and persistent positive effect of incentives on both the quantity and quality of recycling, but no effect of the norm-nudge. However, the price incentive reduced customer satisfaction, unless it was combined with the norm-nudge …“ (abstract).
Fintech climate nudging: Fighting Climate Change with FinTech by Antonio Gargano and Alberto G. Rossi as of Oct. 23rd, 2024 (#25): “We study the environmental sustainability of individuals’ consumption choices using unique data from a FinTech App that tracks users’ spending and emissions at the transaction level. … we show that individuals are likely to purchase carbon calculator services that provide them with detailed transaction-level information about their emissions. However, such a tool does not cause significant changes in their consumption and emissions. On the other hand, services that offset individuals’ emissions by planting trees are less likely to be adopted but prove effective in reducing users’ net emissions. … the lack of effectiveness likely stems from users not viewing climate change as more important than other socio-economic problems to alter their habits. The lack of adoption of carbon offsetting is instead driven by limited attention and users’ desire to directly benefit from the externality associated with having trees planted in their country of origin“ (abstract).
ESG investing research (in: Compensation greenwashing)
Greentech-rewards: Technological greenness and long-run performance by Stefano Battiston, Irene Monasterolo and Maurizio Montone as of Oct. 25th, 2024 (#339): “Using a science-based technological measure of greenness, we find that adopting sustainable technologies leads to a long-run improvement in fundamentals that is only partially reflected in stock prices. Correspondingly, firms with greener technologies achieve higher returns over a multi-year period and are better positioned for the transition to a low-carbon economy. These effects are especially pronounced in financially developed countries and among firms with better climate-related disclosure”. My comment: This is encouraging since I invest in green technologies through my mutual fund.
Missing ESG data: ESG Data Imputation and Greenwashing by Giulia Crippa as of Nov. 4th, 2024 (#87): “This paper provides a simple and comprehensive tool to tackle the issue of missing ESG data. Firstly, it allows to shed light on the failure of ESG ratings due to data sparsity. Exploiting machine learning techniques, we find that the most significant metrics are promises, targets and incentives, rather than realized variables. Then, data incompleteness is addressed, which affects about 50% of the overall dataset. Via a new methodology, imputation accuracy is improved with respect to traditional median-driven techniques. Lastly, exploiting the newly imputed data, a quantitative dimension of greenwashing is introduced. We show that when rating agencies do not efficiently impute missing metrics, ESG scores carry a quantitative bias that should be accounted by market players“ (abstract). My comment: My ESG data provider Clarity.ai extensively uses AI (also to handle missing data) and recently switched to more focus on “realized” data.
Imbalanced ESG risk: Imbalanced ESG investing? by Maria-Eleni K. Agoraki, Georgios P. Kouretas, Haoran Wu, and Binru Zhao as of Nov. 2nd, 2024 (#49): “Our findings reveal a pronounced focus on environmental risks, particularly among funds with higher sustainability ratings, suggesting that E risks receive more strategic attention than S and G risks. Our analysis also demonstrates that ESG imbalances can adversely impact fund flows, particularly for funds with high sustainability ratings, as investors appear to favor a more balanced approach to ESG integration. However, we observe that this negative effect is moderated by growing public concern over climate change, which may influence investor tolerance for certain imbalances in favor of environmental priorities. … we find an association between ESG imbalance and higher risk profiles, including volatility, downside risk, and fund concentration, suggesting that prioritizing one ESG dimension, especially environmental factors, could compromise portfolio diversification, increasing the overall risk borne by investors“ (p. 26/27). My comment: Since many years I select stocks with high Best-in-universe-scores for E, S and G separately. The volatility of my fund with only 30 stocks from a relatively small number of market segments and countries is low with <13%.
Green prospectus beats rating: What attracts Sustainable Fund Flows? Prospectus vs. Ratings by Kevin Birk, Stefan Jacob, Marco Wilkens as of June 4th, 2024 (#45): “We investigate the effect of sustainability information in fund prospectuses on fund flows and find that it strongly affects investor decisions. The economic relevance of prospectus information outweighs that of external sustainability ratings by far. … We posit that investors may use ratings to verify a fund’s self-proclaimed sustainability. … We find that sustainability cues in fund names attract more investors, likely because they make such funds easier to find or identify. … while retail investors prefer thematic funds with trendy investment approaches (e.g., climate change), institutional investors opt for funds combining exclusions and ESG criteria“ (p. 17/18). My comment: The results surprise me somewhat: Fund names often do not explain much and the fund prospectus typically only documents minimum sustainability requirements whereas sustainability ratings are based on much more and more recent information.
Negative climate news and positive returns: Climate Risk Perception and Mutual Fund Flows: Implications for Performance by Viktoriya Lantushenko and Gulnara R. Zaynutdinova as of June 7th, 2024 (#27): “… We propose a measure of a fund’s flow sensitivity to negative climate news, namely climate-risk-flow sensitivity, and investigate its effect on fund alpha. Our findings reveal that mutual funds experiencing increased inflows in response to negative climate news outperform other funds in the sample. This performance differential is economically meaningful: a one-standard-deviation rise in climate-risk-flow sensitivity corresponds to a 0.48% increase in annualized risk-adjusted returns. The results are pronounced only for mutual funds that experience inflows when more negative climate-related news are published. … we find that our results are driven by more actively managed funds. Our findings reveal that mutual funds with stronger stock-selection abilities are better positioned to capitalize on the influx of new capital as climate concerns strengthen“ (p. 23).
SDG investment research
Sustainable investor identification: A First Step Towards a Standardized Framework for Identifying Sustainable Investors: A Comparison of Common Measures by David Shkel as of Nov. 1st, 2024 (#10): “… there is no consensus on a standard set of control variables to identify sustainable investors. This study compares measures from three categories: (i) financial literacy/sustainable finance literacy, (ii) sustainability literacy, and (iii) human-nature interaction. … We recommend a concise set of measures: the financial literacy measure by Lusardi and Mitchell (2008), a question assessing the „warm glow“ effect, and the environmental literacy measure by Anderson and Robinson (2022)” (abstract).
Fiduciary climate duty: Sustainable Fiduciary Duties – The time has come for financial fiduciaries to adapt to the new climate reality by Andreas Wildner and Maurits Dolmans as of Oct. 31st, 2024 (#17): “Preserving and maximizing financial returns on investment means actively pursuing climate mitigation, and ensuring that investee companies and public authorities do so, too. The key points in this paper are two: the importance of market failure as a cause of the climate change and nature loss crises; and the recognition of the role existing principles of fiduciary duties can play to help solve this market failure, by avoiding the associated prisoners’ dilemma” (abstract). My comment: I hope that more and more investors (and advisors) will recognize this fiduciary duty.
Effective forests? Serious errors impair an assessment of forest carbon projects: A rebuttal of West et al. (2023) by Edward T. A. Mitchard et al. as of Dec. 20th, 2023 (#1519): “West et al. conclude that “only a minority of projects achieved statistically significant reductions in comparison with ex post counterfactuals”, but we have shown that this result is highly uncertain given the lack of sensitivity of their approach given their input satellite data, use of inappropriate synthetic controls resulting in poor synergies between control and project sites and sensitivity of their results to small changes in methodology, and calculation errors …“ (p. 9).
ESG compensation greenwashing? All Hat and No Cattle? ESG Incentives in Executive Compensation by Matthias Efing, Patrick Kampkötter, Stefanie Ehmann, and Raphael Moritz as of Oct. 2nd, 2024 (#253): “… this study reveals significant heterogeneity in the role of ESG metrics in executive compensation across industries, firms, and executive positions. While ESG metrics are increasingly prevalent, their integration into executive pay often lacks material weight and incentive power. Discretionary ESG metrics dominate in financial firms and large, visible companies, raising concerns of greenwashing rather than genuine incentive alignment. In contrast, firms in energy-intensive and high-polluting industries, as well as those with highly volatile stock prices, tend to adopt binding ESG metrics with more substantial weights” (p.35/36). My comment: Many shareholder engagement (and voting) activities focus on ESG compensation. I focus on other points e.g. employee and customer (ESG) satisfaction, see Shareholder engagement: 21 science based theses and an action plan – including low CEO pay ratios (see Wrong ESG bonus math? Content-Post #188).
Other investment research (in: Compensation greenwashing)
FinAI bets GenAI: Re(Visiting) Large Language Models in Finance by Eghbal Rahimikia and Felix Drinkall as of October 13, 2024: “This study introduces a novel suite of historical large language models (LLMs) pre-trained specifically for accounting and finance ….. Empirical analysis reveals that, in trading, these specialised models outperform much larger models, including the state-of-the-art LLaMA 1, 2, and 3, which are approximately 50 times their size” (abstract).
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Werbung (in: Compensation greenwashing)
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