As FundForum Global ESG & Impact is now in full swing, many discussions are exploring the complexities surrounding the very definition of ESG and in particular, the understanding and implementation of the data within each of the three dimensions. Tom Steffen, Ph. D., Environmental Research, Osmosis Investment Management provides his insight on the environmental element below.
A recent study by academics from MIT and the University of Zurich shows that, with a value of 0.13, the average pairwise correlation between the measurements of corporate greenhouse gas (GHG) emissions by rating agencies is close to zero.¹ Meanwhile, a separate study from Harvard Business School, reports that in general rating disagreement among ESG (environment, social, governance) data providers increases with the quantity of publicly available information.²
So, why do rating scores diverge so considerably on the most quantifiable dimension of ESG? Quantitative environmental researcher Tom Steffen from Osmosis Investment Management explains some of the complexities involved in measuring the environmental – E – dimension of ESG.
Insights from academic studies suggest that considerable differences in environmental disclosure practices, as well as a lack of reporting standards, and thus comparability are the primary impediments to the clear interpretation of environmental data.
The absence of international reporting standards and varying degrees of disclosure quality call for expert knowledge to make sense of the reported environmental data – just as complex balance sheet data requires skilled financial analysts to separate material from superfluous information.
Generally, the vast number of indicators used to assess the environmental dimension leads to redundancies among the many attributes used to assess corporate environmental performance, explaining the disagreement between aggregate data provider E scores.
Yet, as demonstrated in the MIT-UZH study, with an average of 0.33, the ratings correlations on a very granular level such as corporate water consumption indicate an even lower level of agreement. The same study finds that pairwise correlations on waste assessment do not exceed 0.38 and hazardous waste and non-GHG emissions are often not covered at all.
The remarkably low levels of agreement between ESG agencies contradict the prior opinion that one might have held about the supposedly straightforward assessment of quantitative environmental data.
How do we disentangle the signal from the noise?
Decades of academic research has demonstrated that environmental performance can be economically meaningful and linked to financial performance.¹
However, corporate environmental impacts will only be properly reflected in stock prices if we can distill the signal from the noise; a process which requires significant knowledge and expertise. The intricate link between the draw on natural resources and the economic value generation process is highly complex.
"The remarkably low levels of agreement between ESG agencies contradict the prior opinion that one might have held about the supposedly straightforward assessment of quantitative environmental data."
We believe the identification of alpha lies in the techniques and methods we use to dig through this noise to enable a proper and thorough assessment of the E element. Only then can we truly compare one company to another.
Measuring action over intent
To cut through the complexity of the data it is necessary to develop a precise definition and narrow scope of what is to be assessed.
Are we trying to measure a company’s commitment at reducing its environmental footprint by assessing the quality of its policies, systems, and processes in place to achieve a targeted future improvement?
Alternatively, is the goal to measure a company’s action today in using the least amount of resources possible while generating economic value? The latter approach, favoured by Osmosis, puts emphasis on measuring the here and now instead of the company’s targets or intentions. When it comes to linking resource use to direct economic implications, todays actions count for more.
Strip out the subjectivity
For an accurate assessment of a company’s environmental performance we also need to strip out any subjectivity.
"To cut through the complexity of the data it is necessary to develop a precise definition and narrow scope of what is to be assessed."
Quantifiable metrics with a strong economic rationale and materiality such as carbon emissions, water usage, and waste disposal provide an objective way of benchmarking companies against each other, taking into account the nature of the industry that they operate in.
Building future reporting standards
Investor preferences have shifted dramatically from merely focusing on the financial health of companies to also taking into consideration their impact on the ecosystem.
For a long time, the financial industry has combed through publicly-disclosed balance sheet data to identify companies that have a potential to outperform in the future. When trying to link sustainability to financial performance, we believe the approach should be no different. Publicly-disclosed environmental data from integrated annual and sustainability reports should form the basis for any thorough assessment.
Data availability and thus reporting remains at the forefront of the challenges that the ESG community is facing. Our proprietary research team, which has specialised in the standardisation of environmental data since 2009, continues to work with the Carbon Disclosure Project and the Global Reporting Initiative to encourage a more consistent framework for environmental reporting standards.
Corporate environmental impacts, however, will only be properly reflected in stock prices by further distilling the signal from the noise. Cutting through the complexity of the intricate link between the draw on natural resources and the economic value generation process requires a lot of knowledge and expertise. Osmosis' proprietary model of resource efficiency is exploiting this complex relationship to identify sustainable investment opportunities.
 Dixon-Fowler, H.R., Slater, D.J., Johnson, J.L., Ellstrand, A.E. and Romi, A.M., 2013. Beyond “does it pay to be green?” A meta-analysis of moderators of the CEP–CFP relationship. Journal of Business Ethics, 112(2), pp.353-366.
 Berg, F., Kölbel, J.F. and Rigobon, R., 2019. Aggregate Confusion: The Divergence of ESG Ratings.
 Kotsantonis, S. and Serafeim, G., 2019. Four Things No One Will Tell You About ESG Data. Journal of Applied Corporate Finance, 31(2), pp.50-58.