Researchers at the University of Pretoria warn that a ratings downgrade of South Africa to junk status may serve as a “self-fulfilling prophecy”, which places the country’s economy at risk and could create the exact economic decline that it aims to predict.
South Africa is currently at risk of being downgraded to non-investment grade ratings levels – also known as junk status – by several ratings agencies such as Fitch and Standard & Poor’s.
In March Moody’s Investors Service has placed South Africa’s Baa2 bond and issuer ratings on review for downgrade, which would put another agency with South Africa just above junk status.
This situation puts South Africa in the very likely situation where it will be downgraded to junk status, where the country’s bonds will be perceived as riskier.
As a result, investors typically require higher yields, or “interest” for a given bond. This has a trickle-down effect to the entire economy, making access to capital more difficult and expensive, and discouraging investment and business enterprise.
According to the University of Pretoria researchers, the methodologies used by rating agencies to make ratings decisions are “black boxes” that are not open to independent evaluation and validation.
Dr. Conrad Beyers, spokesperson for the group of researchers, extended an invitation to credit rating agencies to “open the black box” and make their models available to him and his colleagues for scrutiny.
According to Beyers, any downgrade of South African government bonds without detailed information on how the decision was arrived at, is irresponsible.
“A ratings downgrade, especially in a highly publicised, controversial and politically loaded case such as South Africa, may result in a self-fulfilling prophecy effect,” said Beyers.
He explained that a hypothetical country with strong economic fundamentals may be plunged into a negative spiral after a prominent and controversial ratings downgrade.
The researchers argue that the potential downgrade might already have had a negative impact on the South African economy.
“Markets are forward looking and tend to react to what they think might happen in the future. Since the potential downgrade has been widely publicised, markets already started to reflect a possible downgrade,” said Beyers.
As a result, any attempt to assess the true impact of a downgrade should consider movements from the initial signal of a possible downgrade, until well after the downgrade.
According to Beyers, a ratings downgrade reflects the view of a particular ratings agency, and is based on their preferred model, subjective assumptions and decisions.
“These assumptions and decisions should be clearly disclosed to an extent where it can be critically examined, at least, by South African and other academics,” said Beyers.
The researchers suggested specific questions that should be asked about credit rating models and related decision:
- How specifically are global methodologies tailored to the South African environment?
- On what basis are essentially non-quantitative elements such as the South African government’s policy and strategy, or policymakers’ commitment to financial restraint evaluated and quantified?
- What are the assumptions and modelling decisions (e.g. weightings) that are used in the models and how are they determined?
- What are the assumptions and model specifications according to which longer term economic performance for South Africa is evaluated?
Beyers said that in general, ratings agencies expect the public to simply accept their outlook on the South African economy, based on some unknown assumptions and models.
“Credit rating decisions affects every single household and business in South Africa. It would be negligent if such decisions are not properly scrutinised to better understand how this decision was arrived at,” said Beyers.
The research titled “Downgrade of SA credit rating can be self-fulfilling prophecy” was conducted by Dr. Conrad Beyers from the Department of Actuarial Science, Dr. Pieter de Villiers from the Department of Electrical, Electronic and Computer Engineering, and Dr. Reyno Seymore from the Department of Economics.