In times of elevated uncertainties and risks associated with an extended period of high real interest rates, economic hard landings, ripple effects from China’s economic challenges, and geopolitical tensions threatening market and business confidence, greater prominence has been assigned to the outlooks and assessments from the Credit Rating Agencies (CRAs), primarily the big three agencies (Fitch, Standard & Poor’s, and Moody’s). Sovereign ratings assigned by the agencies are taken to be an accurate and credible metric of the default and credit risks associated with a rated sovereign, which in turn determines the cost of funds borrowed by a country.

Yet, several issues emerge while looking into the rating methodologies utilised by the CRAs.

First, the methodologies utilised by credit rating agencies are opaque and appear to disadvantage developing economies in certain ways. Reading through the methodology documents of the big three agencies, one would find that the descriptions and justifications for several parameters included in the methodology are not obvious.

Vague criteria

For instance, the Fitch document mentions that the rating agency “takes comfort from high levels of foreign ownership” in the banking sector and that “public-owned banks have historically been subject to political interference.” Such an assessment tends to discriminate against developing countries, where the banking sector is primarily run by the public sector.

It also ignores the welfare and development functions that public sector banks tend to play in a developing country, where government-owned banks have played an important role in promoting financial inclusion. In contrast, the expansion of foreign owned banks in a developing country seems to target the already-banked middle class and does not appear to serve the unbanked low-income households.

Second, the experts generally consulted for the rating assessments are selected in a non-transparent manner, adding another layer of opaqueness to an already difficult-to-interpret methodology.

Lastly, the rating agencies do not convey clearly the assigned weights for each parameter considered. While Fitch does lay out some numerical weights for each parameter, they do go on to state that the weights are for illustrative purposes only. Thus, it is left to the reader to make educated guesses on what the assigned weights could be for the qualitative and the quantitative factors.

Discriminatory intent

Opaqueness and non-transparency in rating methodologies are fertile grounds for sowing suspicion about the discriminatory intent of CRAs, particularly when rating downgrades are mostly in respect to economically weaker nations. For instance, between 2020 and 2022, over 56 per cent of the African countries that are rated by at least one of the big three CRAs were downgraded.

The downgrades experienced by European nations stood at only 9 per cent. Further, the negative warning announcements by the CRAs (in the form of reviews, watches, and outlooks) have been linked to increases in the cost of borrowing for developing countries. There is a strong feeling among the developing countries that subjective assessments tilt, most often, in favour of the advanced economies, as developing countries have borne the brunt of over 95 per cent of all credit rating downgrades despite experiencing economic contractions which were milder than their advanced economy counterparts.

Credit downgrades for developing countries have made it difficult for them to access cheaper long-term funding from international capital markets.

Over-reliance on non-transparent qualitative factors, including perceptions, value judgments, views of a limited number of experts, and surveys with loose methodologies in sovereign rating, results in unacceptable outcomes from a global point of view.

It makes the rating of developing countries almost invariant with respect to even sizeable movements in relevant macroeconomic fundamentals. This happens because the base rating, estimated through quantitative scoring of macro-fundamentals, is overridden by qualitative considerations while finalising the published ratings. The set of loose qualitative information fed into the quantitative scoring of countries and the final qualitative overlay, based purely on the agency’s subjective assessment of the countries’ ability and willingness to pay, become heavily loaded against the developing countries. The composite result of this is exemplified by India’s recent rating history.

The rating of India remained static at BBB- during the last 15 years, despite it climbing the ladders from the 12th largest economy in the world in 2008 to the 5th largest in 2023, with the second highest growth rate recorded during the period among all the comparator economies. Thereby, any improvement in macro-economic parameters may virtually mean nothing for a credit rating if qualitative parameters are judged to be in need of improvement. This has serious implications for developing sovereigns’ access to capital markets and ability to borrow at affordable rates.

The question whether the dependence on less-than-optimal qualitative information is unavoidable also comes to the fore. The answer is a clear NO. On a zero base, there cannot be any better-revealed preference for willingness and determination to pay back a country’s debt obligations than its repayment history itself. Thus, a nation that has not defaulted throughout its external debt history and through the vicissitudes of its socio-economic development should be taken as fool-proof in its ‘willingness to pay’ back.

This, if made the benchmark, can form the basis for the treatment of different combinations of debt defaults and the reasons therein on the one hand and the assessment of the willingness to pay on the other. This involves painstakingly building up country-wise baseline information on debt history, instances of restructuring, defaults, and the circumstances leading to such events. However, this will do enormous good to the credibility of credit rating by enabling the CRAs to dispense with mechanical application of unconvincing qualitative information and judgments.

Even if governance indicators are to be relied upon, they must be based on clear, well-defined, measurable principles than subjective judgments by CRAs. Like all subjective qualifications, these judgments also suffer from heuristic and cognitive biases such as echo chambers, bandwagon effects, and difficult-to-change commitment and confirmation biases.

While CRAs expect sovereigns to make improvements in the quality of their governance, reduce market risks, and improve the regulatory environment, the agencies themselves offer no insights or guidance on exactly what factors are part of their considerations and suggestions.

This opaqueness makes it difficult for any country to fully understand what reforms are needed to earn a credit rating upgrade.

Excerpts from the chapter on credit rating methodologies from ‘Re-examining Narratives: A collection of essays’, brought out by the Office of the Chief Economic Adviser, Ministry of Finance

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