We use BERT, an AI-based algorithm for language understanding, to quantify regulatory climate risk disclosures and analyze their impact on the term structure in the credit default swap (CDS) market. Risk disclosures can either increase or decrease CDS spreads, depending on whether the disclosure reveals new risks or reduces uncertainty. Training BERT to differentiate between transition and physical climate risks, we find that disclosing transition risks increases CDS spreads after the Paris Climate Agreement of 2015, while disclosing physical risks decreases the spreads. In addition, we also find that the election of Trump had a negative impact on CDS spreads for firms exposed to transition risk. These impacts are consistent with theoretical predictions and economically and statistically significant. 

We assess how investors' willingness-to-pay (WTP) for sustainable investments responds to the social impact of those investments, using a framed field experiment. While investors have a substantial WTP for sustainable investments, they do not pay significantly more for more impact. This also holds for dedicated impact investors. When investors compare several sustainable investments, their WTP responds to relative but not to absolute levels of impact. Regardless of investments' impact, investors experience positive emotions when choosing sustainable investments. Our findings suggest that the WTP for sustainable investments is primarily driven by an emotional rather than a calculative valuation of impact. 

This paper investigates the divergence of environmental, social, and governance (ESG) ratings based on data from six prominent ESG rating agencies: Kinder, Lydenberg, and Domini (KLD), Sustainalytics, Moody’s ESG (Vigeo-Eiris), S&P Global (RobecoSAM), Refinitiv (Asset4), and MSCI. We document the rating divergence and map the different methodologies onto a common taxonomy of categories. Using this taxonomy, we decompose the divergence into contributions of scope, measurement, and weight. Measurement contributes 56% of the divergence, scope 38%, and weight 6%. Further analyzing the reasons for measurement divergence, we detect a rater effect where a rater’s overall view of a firm influences the measurement of specific categories. The results call for greater attention to how the data underlying ESG ratings are generated. 

Investors and regulators require reliable estimates of physical climate risks for decision-making. While assessing these risks is challenging, several commercial data providers and academics have started to develop firm-level physical risk scores. We compare six physical risk scores. We find a substantial divergence between these scores, also among those based on similar methodologies. We show how this divergence could cause problems when testing whether financial markets are pricing physical risks. Hence, financial markets may not adequately account for the physical risk exposure of corporations using available risk scores. Finally, we identify key sources of uncertainty for further investigation. 

This article asks how sustainable investing contributes to societal goals, conducting a literature review on investor impact—that is, the change investors trigger in companies’ environmental and social impact. We distinguish three impact mechanisms: shareholder engagement, capital allocation, and indirect impacts, concluding that the impact of shareholder engagement is well supported in the literature, the impact of capital allocation only partially, and indirect impacts lack empirical support. Our results suggest that investors who seek impact should pursue shareholder engagement throughout their portfolio, allocate capital to sustainable companies whose growth is limited by external financing conditions, and screen out companies based on the absence of specific environmental, social, and governance practices that can be adopted at reasonable costs. For rating agencies, we outline steps to develop investor impact metrics. For policy makers, we highlight that sustainable investing helps diffuse good business practices, but is unlikely to drive a deeper transformation without additional policy measures. 

This paper documents that ESG funds in the U.S. charge net expense ratios that are 8.8 to 12.8 basis points lower than those of conventional funds. This fee difference is driven by waivers, which are larger and more frequent for ESG funds. Based on a model of horizontal differentiation, we provide evidence consistent with three explanations: (1) ESG funds are in a highly competitive market segment, (2) ESG funds exhibit lower expected returns, and (3) fund providers use ESG funds with low fees to cross-sell higher-fee funds.

We report results from a pre-registered field experiment about the impact of index provider engagement on corporate climate policy. A randomly chosen group of 300 out of 1227 international companies received a letter from an index provider, encouraging the company to commit to setting a science-based climate target to remain included in its climate transition benchmark indices. After one year, we observed a significant effect: 21.0% of treated companies have committed, vs. 15.7% in the control group. This suggests that engagement by financial institutions can affect corporate policies when a feasible request is combined with a credible threat of exit. 

A fundamental concern about green investing is that it may crowd out political support for public policy addressing negative externalities. We examine this concern in a preregistered experiment shortly before a real referendum on a climate law with a representative sample of the Swiss population (N = 2,051). We find that the opportunity to invest in a climate friendly fund does not reduce individuals’ support for climate regulation, measured as political donations and voting intentions. The results hold for participants who actively choose green investing. We conclude that the effect of green investing on political behavior is limited. 

Existing measures of ESG (environmental, social, and governance) performance -- ESG ratings -- are noisy and, therefore, standard regression estimates of the effect of ESG performance on stock returns are biased. Addressing this as a classical errors-in-variables problem, we develop a noise-correction procedure in which we instrument ESG ratings with ratings of other ESG rating agencies. With this procedure, the median increase in the regression coefficients is a factor of 2.1. The results are similar when we use accounting profitability measures as outcome variables. In simulations, our noise-correction procedure outperforms alternative approaches such as simple averages or principal component analysis. 

We identify six recommendations to support harmonization while respecting the need for contextual relevance and the great efforts already underway in the ecosystem:

1. Converge on core metrics that are widely accepted and feasible.

2. Converge on key sector-specific material issues—agree on what to measure before how.

3. Coordinate new metric development to avoid duplication from the outset.

4. Map between existing measurement resources, particularly toward SDG targets.

5. Harmonize the structure of impact reporting to improve comparability and aggregation.

6. Leverage AI to interpret context and bridge standardization with flexibility.

Since August 2022, European banks have been required to record clients’ sustainability preferences under the MiFID II regulations. We present the results of a survey of banks to understand the practical consequences of this rule. We find that banks implement the regulation in different ways with no clear emergence of a common practice yet. Our main results indicate that, on average, only 5% of clients express a preference for sustainability. This figure is low compared to the fraction of clients who have invested in sustainable products, which is on average 40%. We explore possible reasons for this gap and offer suggestions for improving the measurement of sustainability preferences. 

This guide supports impact-driven investors in developing an investment strategy that accomplishes real-world change. Changing the world through investing is complex and has been studied by many academic researchers. We’ve reviewed existing research,1 examined the mechanisms researchers have identified, and synthesized the available evidence in order to offer these practical recommendations on how to maximize your impact as an investor with an evidence-based investment strategy.