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Holly LaFon
Holly LaFon
Articles (10163)  | Author's Website |

GMO Commentary: Gaming Out Sovereign Default When China Is a Major Creditor

By Carl Ross

July 18, 2019 | About:

Since the inception of GMO’s Emerging Country Debt strategies in 1994, there have been many big structural shifts in the marketplace. One is the very emergence of the bond market itself, to which GMO has borne witness all along the way. In 1994, bonds accounted for about 15% of the external debt of emerging countries. In 2017, this figure was 44%. Over the ensuing years, bonds have essentially replaced bilateral (country-to-country) loans, while loans from multilateral organizations (such as the World Bank, IMF, and others) have remained at 20-25% of the total. A second big structural shift is the emergence of China as a creditor to other emerging countries, a process that has accelerated in recent years as a result of the Belt and Road Initiative. Opacity in the data prevents a fully accurate accounting, but by some estimates China (via its state policy banks and other entities) accounts for about 30% of the public sector external debt of Sub-Saharan Africa, for example. This is corroborated by the line in Exhibit 1 showing that China has been the source of about 40% of disbursements of external debt to Africa in the past 10 years.1 This level of exposure means that China will be an important “player” in some future debt restructurings. In this piece, we employ simple techniques from game theory to model how China might change, for better or worse, recovery outcomes for bondholders.

Thankfully, sovereign debt is an asset class with a relatively low observed incidence of default.2 When defaults occur, recovery values are essentially a function of two things:

  1. the sovereign’s ability to pay (as governed by the economic and public finance realities); and 2) the strategic interaction among the “players,” in this case sovereign debtors and their creditors, which takes into account relative attitudes toward debt relief, economic adjustment, and strategic goodwill. The primary determinant of recovery value is the former, but the latter can also influence the outcome, positively or negatively. Moreover, recovery values in sovereign restructurings show wide variation over historical periods, ranging from 30% of face value on the low end to 90% on the high end. We already have an in-house model for estimating recovery based on the economic fundamentals. By understanding the strategic interaction among players a little better, we might be able to narrow the range of uncertainty around these estimates.

The Set-up of the “Game”

So, how might we model this strategic interaction? This is where game theory techniques can be useful.3 Imagine a simple interaction between debtor and creditor in which the debtor can offer economic policy reforms (PR) that will benefit the creditor (because it reduces country risk over time), while the creditor can offer debt write-off (DW) that will benefit the debtor.


Assume that the debtor receives negative utility (disutility) from PR, because those are often politically difficult and can be painful in the short term, and we know that politicians have very myopic horizons. Assume that the debtor receives positive utility from DW because of the favorable fiscal space it opens. Finally, we can also consider a “goodwill” or “reputational” element by which the debtor receives negative utility if the restructuring deal is too overly tilted in its favor. It knows, for example, that if it forces terms that are too harsh relative to the effort it makes on economic reforms, it will suffer reputational damage and need to pay permanently higher spreads on future borrowing. (Ecuador is a current example of such a country.)

Conversely, the creditor receives positive utility from PR implemented by the country, disutility from DW, and disutility from a deal that is too tilted in its favor, given it is aware of, and sensitive to, the humanitarian costs of a country remaining in a debt trap (and, frankly, doesn’t want to be back at the negotiating table in a few years’ time).

Simple utility functions for the creditor (c) and debtor (d) can therefore be specified as a function of PR, DW, and goodwill or reputation (Z) as follows:4

U c = aPR – bDW + cZ

U d = – xPR + yDW + zZ

The preferences of creditors and debtors can be defined by the relative size of the coefficients a, b, and c, and x, y, and z. We constrain each utility function’s coefficients to sum to unity, again for simplicity. We specify high (3), medium (2), and low (1) to PR and DW, while Z can be expressed as a function of PR and DW, because it is meant to proxy the relative effort of creditor and debtor.

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About the author:

Holly LaFon
I'm a financial journalist with a Master of Science in journalism from Medill at Northwestern University.

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