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As the use of sustainability metrics in sovereign fixed income becomes more widespread, there is still a lack of common understanding on how to appropriately apply them to assess countries’ Environmental, Social and Governance (ESG) performance. Recently, attention has been especially drawn to the income bias that is ingrained in sovereign ESG scores.
A key World Bank Study, Demystifying Sovereign ESG, sheds light on how ESG assessment criteria often assess Advanced Economies (AEs) more favourably than Emerging Markets and Developing Economies (EMDEs). This results in sovereign ESG scores and countries’ level of development being highly correlated – and potentially disadvantaging EMDEs access to finance.
Figure 1 below indeed shows two sets of ESG scores sorted by level of development: initial ESG scores which empirically illustrate the income bias; as well as income adjusted ESG scores.
Since income bias can directly impact the real economy and bring unintended consequences (i.e., lower scores can result in higher expected yields – increasing the overall debt burden – or in restricting access to some potential lenders), we first need to observe the current state of play and how countries perform in terms of ESG depending on their level of development. We can distinguish four different groups from initial ESG scores on Figure 1:
Within these brackets, sovereign ESG scores are quite concentrated, meaning that outliers are not very common, and the differentiation of countries is not that obvious.
Using an ex-post approach and our proprietary Sovereign Risk Monitor (SRM) methodology, we estimate a log-linear relationship between the income level of economies and their respective E, S and G performance assessment. Residuals are then normalized and used as income-adjusted sovereign E, S and G scores, representing the portion of initial E, S, and G scores unexplained by the income level.
What about income-adjusted ESG scores?
Once the income bias is corrected, we can differentiate between ESG performance of sovereigns at similar income levels much more clearly. Indeed, the dispersion around the average is more than twice as large after correcting for income bias. For example, Sweden, Singapore and Qatar – with comparable per capita income levels – appear broadly close for the initial scores (e.g., from 47.5 for Singapore E score to 97.7 for Sweden G score in 2020), but have very mixed income-adjusted E, S and G scores (e.g., from 2.0 for Qatar income-adjusted E score to 93.9 for Sweden income-adjusted E score).
As for the emerging countries of Latin America with comparable per capita income levels, the correction of the income bias highlights a relatively good performance of the E scores (e.g., Colombia, Ecuador and Paraguay gain about 30 points after correcting for income bias to get very high E scores) while the endemic weakness of the G scores seems exacerbated (e.g., these same three countries lose around 10 points to fall to levels between 25 and 40 after the correction). Income-adjusted S scores appear more balanced.
We expand on this in our recent research paper Dealing with income bias in sovereign ESG scores – Sovereign ESG revisited, showing that:
- The income bias is most pronounced for G scores, becoming weaker for S and particularly E scores;
- The existing differences in ESG performance between high-income OECD and non-OECD countries are amplified after adjusting for income bias;
- After removing income bias, low-income economies do score significantly in the E, S and G pillars.
The latter point, in particular, suggests that, despite lower income levels, some of these economies can establish strong adjusted ESG performance, in particular in the S and G pillars, which in turn are important drivers of future economic prosperity for EMDEs.
Please see our paper for more details on applying ESG to government bond indexes. Subscribe to our blog for more insight.
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Originally Posted September 30, 2022 – Does income bias in sovereign ESG disadvantage poor countries?
Disclosure: FTSE Russell
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