Measuring sovereign credit risk in emerging economies, Big Ideas Ep 76

Notes

What a sovereign credit rating measures

A credit rating is a way of compressing a single quantity into a grade. That quantity is the default probability, and the grade is an alphanumerical scale that runs from triple A at the top down through D. At the high end sits investment grade; at the low end sits speculative grade, or what the market calls junk. The grade is not decorative. It maps directly onto the price of money.

Luitel describes the link between the rating and the cost of borrowing:

"Once your rating increases, your cost of borrowing decreases. And when the rating decreases, your cost of borrowing increases. That's a direct link. That's what the investor looks into: the cost of borrowing. For the investor, it will be yield. It's just a mirror image, from two sides of the mirror."

A sovereign credit rating applies this same logic to the national government. The government issues bonds, and the rating captures the default probability attached to it as the issuer. Default, in Luitel's plain framing, is a question of whether the government can pay its principal and coupon on time. The rating is the estimate of how likely it is to fail that test.

Credit risk runs in a loop between the sovereign and its firms

Because the sovereign is the reference point for everything issued inside its borders, its rating shapes the ratings of the firms and banks around it. Luitel invokes the "sovereign ceiling," an idea the rating agencies formally reject but which he says holds in practice for emerging markets. To make it concrete, he offers an image:

The sovereign ceiling means, if you look at the ceiling of your room, that's the highest level. So that will be the credit rating of the sovereign, the government. And the rating of the corporate sectors, which are domiciled inside that country, will have a lower rating.

"The sovereign therefore carries the lowest credit risk in the country, and corporates sit above it. A sovereign rating matters for corporate ratings and for financial market development more broadly. But Luitel's central move is to resist treating this as a one-way street. The corporate sector also acts on the sovereign, and distress there, especially among big firms, can travel upward."

He contrasts this with the conventional academic view:

"Traditionally, what we see, and also in academia, is that the spillover goes from the sovereign credit risk to the banking sectors and to the corporate sectors. But we can also say, hold on, there's distress in the corporate sector, especially the big firms, then it can move up. So the sovereign is not only the transmitter; the corporate can also be a transmitter back to the sovereign."

This circular framing, where risk can flow in both directions, is the idea behind his paper "A Circular Model for Credit Risk Contagion."

Corporate data can flag sovereign distress before macro data

The loop is not just conceptually interesting; it has a practical payoff in timing. Macroeconomic data such as GDP or the fiscal deficit arrives slowly, typically on a quarterly basis. Corporate data, by contrast, is available at much higher frequency. Luitel argues this makes firm-level signals useful for anticipating where the sovereign is headed.

He frames the mechanism as a lead-lag relationship between markets:

"Imagine if a corporate CDS moves today; what will be the movement of the sovereign CDS in the future, or tomorrow? That's the idea. Corporate data is more frequent, so it is useful to understand any incremental information that comes from it to explain the variation of this sovereign credit."

Asked how to spot early signs of sovereign distress, Luitel points first to the banking sector and to large firms, while cautioning against leaning on ratings for this purpose. The signals worth watching are on balance sheets: the liquidity position of corporates and the capital buffer of banks. Because big firms have an outsized effect on the economy, their stress is informative about whether the sovereign is functioning smoothly or moving toward distress. He stresses that this reading should come through internal models and stress tests rather than credit ratings on their own.

Rating agencies are gatekeepers, but over-reliance carries a cost

The agencies that assign these grades occupy a powerful position. Luitel is clear that they act as gatekeepers, and that their basic role, to provide ratings and to monitor the market so investors can make informed decisions, is legitimate. The problem is concentration and dependence. Three agencies, Moody's, Standard & Poor's, and Fitch, hold close to 90% of the market, and their opinions have been embedded deeply in regulation.

He warns against building the regulatory framework too heavily on their output, citing 2008 as the cautionary case. Ratings, in his view, should be one input among several, cross-checked with internal modeling and stress tests run by banks, regulators, and firms working together. Rating is a "check and balance," not the whole answer.

Luitel is careful to distribute responsibility when over-reliance ends badly:

"If things go well, everyone is happy, but the moment things go south, the blame will be mostly on the rating agencies, that they were not able to provide information in advance. But there is a blame on the investor also, which they should take responsibility for, because they relied too much only on the rating itself."

Separating objective from subjective, and measuring risk where instruments are thin

On fairness for emerging markets, Luitel notes that agencies claim objectivity while studies point to bias. His response is to decompose a rating into two parts. The objective part comes from hard data: macroeconomic figures, financial market data, and corporate sector data. The subjective part is less quantified and works through what he calls a soft information channel. For a given grade, one can ask how much of, say, a double A comes from each.

The two parts behave differently in the market. Luitel observes that pricing tracks the objective component:

"In the market, when you look at the pricing, the market prices mostly on the objective part. The subjective part is not priced; we can say it is not priced at all."

The subjective component still has value, but of a particular kind. Its soft information is useful mainly as a short-term signal of whether a default is coming, rather than a long-term one.

The conversation closes on measurement in emerging markets, where credit default swaps and similar instruments are new or lacking even though the interest in measuring risk is high. Luitel weighs three options. Ratings carry a lot of information but are sluggish, updated on a yearly calendar unless a big event forces a change, with the outlook (positive, negative, or stable) offering a quicker preview. Bond yields are also infrequently traded. The credit default swap, being frequently traded and more liquid, gives the fastest reading:

"This is very frequently traded, so it's more liquid in the market. That means the pricing is done very frequently, on market demand and supply. And this already gives you a signal about what the economy looks like."

All three, he says, are equally valid; the question is simply which delivers the information first.

Supplementary Resources

• Pernicious Effects: How the Credit Rating Agencies Disadvantage Emerging Markets by Prabesh Luitel, Rosanne Vanpée and Lieven De Moor (Journal article)
• Subjectivity in Sovereign Credit Ratings by Lieven De Moor, Prabesh Luitel, Piet Sercu and Rosanne Vanpée (Journal article)
• Sovereign Credit Rating Provision and Financial Development by Oskar Kowalewski, Prabesh Luitel and Rosanne Vanpée (Journal article)

The complete transcript file is available to download below.