Enthusiasm for ‘greening the financial system’ is welcome, but does the explosion of ‘green’ finance indicators reflect the science? Using artificial intelligence to construct the world’s first ‘climate smart’ sovereign credit rating, economists warn that as many as 63 sovereigns could suffer climate-induced downgrades by 2030
Climate change is “the biggest market failure the world has seen”, with wide-ranging implications for stability – financial, economic, political, social, and environmental. As estimates of the economic consequences of climate change continue to grow, financial markets and business leaders face increasing pressure to factor climate risks into decision making. Climate change will hit markets from all directions. In boardrooms and at AGMs, what were once token whispers of eco-marketing have become serious discussions of extreme weather events, reputational risks, activist movements (shareholder and consumer), regulatory and transition risks, asset stranding, and environmental litigation. In response, investors and regulators are calling for climate risk disclosures and a clear demonstration that portfolios and business models are consistent with the Paris Climate Agreement. Central bankers, finance ministers, the International Monetary Fund and United Nations are in on the action.
Such enthusiasm for ‘greening the financial system’ is welcome, but a fundamental challenge remains: financial decision makers lack the necessary information. It is not enough to know that climate change is bad. Markets need credible, digestible information on how climate change translates into material risks. Instead, an explosion of ESG (environmental, societal, and governance) ratings and voluntary, ad hoc, unregulated climate disclosures has created a confusing world of unfamiliar, incomparable, and conflicting metrics.
A chief concern is the lack of scientific foundations in risk disclosures. Climate models operate at global scales, projecting impacts over decades and centuries. Financial models do not. How should a high-frequency trading algorithm (operating in nanoseconds) adjust to the possibility that climate may reduce global output in 2100 by 10%? How should corporate disclosures address issues largely beyond their control, such as the carbon intensity of the national electricity grid, or the direction of government flood strategies? Most disclosures present companies as if they are independent of their physical (geographical) and macroeconomic surroundings. But climate change does not just affect firms individually, it affects countries and economies systemically. No corporate climate risk assessment is complete without also considering the effect of climate on sovereign bonds. Without scientific credibility, economic evidence, and decision-ready metrics, the field of green finance is open to charges of greenwash.
This is what motivated us to bridge the gap between climate science and real-world financial indicators. We focused on a metric that is eminently familiar to financial decision makers: the sovereign credit rating. By linking climate science with economic models and real-world best practice in sovereign ratings, we simulate the effect of climate change on sovereign credit ratings for 108 countries under three different warming scenarios (see Figure 1).
We were guided by a single overarching principle: to remain as close as possible to climate science, economics, and real-world practice in the field of sovereign credit ratings. We are the first to simulate the effect of climate on future sovereign ratings under multiple warming scenarios. We also provide initial estimates of the effects of climate-induced sovereign downgrades on the cost of public and corporate debt around the world.
Bridging the gap between climate science and financial indicators
Sovereign ratings are reported using a 20-notch scale, where AAA is ‘prime high grade’ and anything below BBB- is considered ‘speculative’ (or informally, ‘junk’). We convert this into a numerical scale and use a machine learning model to predict creditworthiness, training it on ratings issued by S&P (one of the largest credit ratings agencies) from 2015-2020. Next, we combine climate economic models and S&P’s own natural disaster risk assessments to develop a set of climate-adjusted data. We use these to simulate the effect of climate change on sovereign ratings. Finally, we calculate the additional cost of corporate and sovereign debt due to climate-induced sovereign downgrades (Figure 1, purple).
We focus on sovereign ratings because they are already used in a range of financial decision-making contexts (e.g. under Basel II rules, ratings directly affect the capital requirements of banks and insurance companies). They cover over US$ 66 trillion in sovereign debt, acting as ‘gatekeepers’ to global financial markets. Sovereign downgrades increase the cost of both public and corporate debt, influencing overall economic performance and significantly affecting fiscal sustainability.
We document three key empirical findings. First, in contrast to much of the climate-economics literature, we find material impacts of climate change as early as 2030. In one realistic scenario, we find that 63 sovereigns suffer climate-induced downgrades of approximately 1.02 notches by 2030, rising to 80 sovereigns facing an average downgrade of 2.48 notches by 2100. Figure 2 depicts the magnitude and geographical distribution of sovereign ratings changes, showing that the most affected nations include Chile, China, Slovakia, Malaysia, Mexico, India, Peru and Canada. More importantly, our results show that virtually all countries, whether rich or poor, hot or cold, will suffer downgrades if the current trajectory of carbon emissions is maintained.
Global climate-induced sovereign ratings changes (2100, RCP 8.5)
Second, our data strongly suggests that stringent climate policy consistent with the Paris Climate Agreement will result in minimal impacts of climate on ratings – with an average downgrade of just 0.65 notches by 2100.
Third, we calculate the additional costs to sovereign debt – best interpreted as increases in annual interest payments due to climate-induced sovereign downgrades – in our sample to be between US$ 22–33 billion under a low emissions scenario known as RCP2.6, rising to US$ 137–205 billion under RCP 8.5. These translate to additional annual costs of servicing corporate debt ranging from US$ 7.2–12.6 billion to US$ 35.8–62.6 billion in each case.
There are caveats. There are no scientifically credible quantitative estimates of how climate change will impact social and political factors, so these are excluded from our model. Thus, our findings should be considered as conservative. Moreover, our results should be understood as scenario-based simulations rather than predictions. We do not comment on the relative probabilities of any given warming scenario playing out in practice.
The key take-home message is that existing climate science and economics are capable of supporting credible, decision-ready green finance indicators. Governments issue ever-longer dated bonds, of which life insurance companies and pension funds are eager buyers, thus enabling them to match their own long-term liabilities. Therefore, investors should consider the long-term creditworthiness of sovereign issuers. Currently there is no reliable yardstick for assessing sovereign creditworthiness beyond the current decade and this research fills this gap. Based on the methodology applied here future research could focus on developing ultra-long ratings not only for sovereigns but also for other issuers including corporates.
This article was originally published by the Bennett Institute for Public Policy and can be read here
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