Standard & Poor’s rating of Kenya is conjecture

Unless you are a keen observer of Kenya’s public finance, it may have escaped you that Standard & Poor’s (S&P) — one of the three globally renowned rating agencies — has recently had some news for you.

It affirmed Kenya’s short- and long-term foreign and local currency sovereign credit ratings at “B+/B” with a stable outlook. 

What S&P was telling us is that, in Jazz musician Bobby McFerrin-speak, “don’t worry be happy”. The reason we are being soothed is that “the ratings on Kenya are supported by its monetary flexibility, liquid domestic financial markets and per capita GDP growth as well as an increasingly diversified economic base”.

Meanwhile, S&P is telling South Africans that they need to be worried. Why? Jacob Zuma, their flamboyant president, sacked his well-regarded Finance minister and his deputy.

The new finance minister has new ideas, seeking a “radical transformation of the economy” that will entail taking the Treasury from “orthodox economists and international investors”.

It took S&P to call Mr Zuma’s bluff, downgrading South African’s credit rating to junk status. In other words the economy’s debt rating moved from relatively low risk of default to high risk. One more move by the other two big ratings agencies – Moody’s and Fitch – and the economy’s bonds will get off the main international indices.   

The question is whether the contrasting verdict on Kenya and South Africa is a reflection of the differences in the underlying fundamentals with regard to the state of each country’s public debt on the one hand and economic performance on the other.

The answer, I would argue, lies in the hypothesis that sometimes rating decisions are simply conjectures coated by a model. To test the hypothesis, one must recognise that the interpretation of public debt and how it relates to output growth — and therefore ability to meet debt obligations — can sometimes be slippery. Consider one example to illustrate this point.

In May 2010 two American economists, Carmen Reinhart and Kenneth Rogoff, published a paper in the prestigious American Economic Review titled “Growth in a Time of Debt”. As respected scholars — both are economics professors at Harvard University, and Rogoff has previously served as IMF’s chief economist — one could expect their pronouncements on the subject to be taken serious.

But that wasn’t the case. Their assertion that when the US’s debt crosses the 90 per cent of GDP it starts to have a negative effect on growth got swift intellectual pushback on account of two main factors.

One reason was on the logic — what economists call the direction of causality.

Being a ratio, debt/GDP can increase if the economy is doing badly or if the debt rises at a faster rate than the economy is growing.

The other reason was more embarrassing. The eminent economists had made a coding error in their modelling; therefore their numbers were not reliable. By the time the error was detected, the political class had seized this piece of work to further their prejudiced case on public debt.

It is therefore possible that conclusions may be arrived at hurriedly. And that may not be for want of sophistication by either scholars or rating agencies. Take the latter’s case. Ratings are generated by highly sophisticated statistical models.

Underpinning such models is the implicit assumption that sophistication implies quality.

There lies a trap. As economics Nobel Laureate Paul Krugman often argues, beauty can sometimes be mistaken for truth.

The truth is, however, that financial modelling changes the statistical laws governing the financial system in real-time. This is because market participants react to measurements and therefore change the underlying statistical process, implying therefore that modellers are always playing catch-up. 

By no means am I suggesting that the models employed by the rating agencies are without merit. However, to the extent that these models — sophisticated as they are — implicitly assume away the characteristic of the dynamic nature of the financial systems’ statistical laws, their outputs have been subject to criticism. 

Notably, ratings are blamed for being reactions rather than anticipations. In other words ratings are lagging, as opposed to leading, indicators.

They reflect the agencies’ estimates of the probability of default over a given period, ignoring the possibility that the market for a given rated security may be illiquid. They equally ignore the likely recovery rate if the security defaults.

I don’t expect S&P or any other member of the trio to project political action such as Mr Zuma’s. That is why prior to the political tantrum, there seemed to be no urgency to review either the rating or outlook.

At the very least though, they should attempt to build some reasonable assumptions into their models regarding general political behaviour and political leaders’ comportment that feed into political actions.

But even if I were to assume comparative advantage in the financial science in their models over the ability to read the minds of the political class, rating decisions are sometimes hinged on gut feeling.

That is why, for instance, the last thing one would expect to underpin the affirmation of Kenya’s rating and outlook is monetary flexibility.

There is glaring evidence that Kenya’s monetary flexibility is constrained, and S&P needn’t work very hard to find it.

The Central Bank of Kenya’s monetary policy committee said as much in its statement of March 28, 2017 — the constraint arising from the capping of interest rates. 

There is more. The central bank has no scope for an accommodative monetary policy stance to forestall the plummeting rate of credit growth to the private sector.