- We update our external liquidity scorecard for 43 emerging and frontier markets as an early signal for distress
- The most vulnerable countries are Sri Lanka, Ethiopia, Tunisia, Laos, Kenya, Bahrain, Bolivia and Turkey
- The least vulnerable are Russia, Brazil, Peru, Uruguay, Vietnam, Iraq, Kazakhstan and Malaysia
After updating our Debt Sustainability Index a fortnight ago, we update our External Liquidity Scorecard initially released in January. The External Liquidity Scorecard is based on higher frequency data than the Debt Sustainability Index, so all 11 of the variables are refreshed. We also add an additional variable – total reserves as a percentage of the IMF’s ARA metric (see appendix for further detail) – and three additional countries (Azerbaijan, Tajikistan, and Uzbekistan) that were absent from the initial scorecard.
Aside from the additions, we also undertake a methodological update. Rather than expressing variables in ordinal terms, we express them in terms of standard deviations from the sample median and average across variables to arrive at a composite score. This brings the methodology in line with that of the debt sustainability index and allows for more granular analysis.
The methodological changes make it difficult to compare how country scores have evolved since the initial external liquidity scorecard in January, but makes for a more accurate and complete scorecard, in our view. Each indicator is detailed in the appendix under “Data explanations and sources”.
The first table shows the data in raw form, and the second scores each variable in terms of standard deviations better (worse) than the sample median and takes the simple average across variables to arrive at a composite external liquidity score (with lower/more negative numbers corresponding to greater vulnerability):
The resulting output is a quick and dirty way to quantify the relative risk of an external debt or balance of payments crisis across in-sample countries, or vulnerability to a sudden stop in capital flows. We find that the most vulnerable countries are Sri Lanka, Ethiopia, Tunisia, Laos, Kenya, Bahrain, Bolivia and Turkey. On the other hand, the least vulnerable countries are Russia, Brazil, Peru, Uruguay, Vietnam, Iraq, Kazakhstan and Malaysia.
The “Bottom 8” constituents are unchanged relative to the January scorecard, except for Bolivia and Turkey, which replace Jamaica and Costa Rica. The “Top 8” are also largely unchanged, aside from Uruguay, Iraq and Kazakhstan replacing South Africa, Argentina and Mexico. That said, methodological changes make it difficult to draw any concrete conclusions from the changes in index ranking.
Moreover, a simple scatter plot shows that there is a negative relationship between the overall external liquidity score and the country risk premium (measured by the EMBI), as we should expect. A linear line of best fit is statistically significant at the 99% confidence level with an R2 = 25.9%, and the R2 rises to 28.5% if Sri Lanka and Argentina are excluded as outliers.
We can use this model to make broad inferences about bond valuations, with large residuals pointing to under/overvaluation. On that basis, Tajikistan, Ecuador, Iraq, Angola, El Salvador, Ghana and Nigeria all stand out as notably undervalued (excluding Sri Lanka and Argentina), while Croatia, Serbia, Mongolia, Vietnam, Jamaica, Malaysia and Azerbaijan appear to be notably overvalued.
While we appreciate our model is highly stylised, the simplified and transparent approach is part of its appeal and we find it mostly offers intuitive results (and where it does not, this can be a signal for further investigation). Of course, we urge our readers to take this data and its conclusions with a pinch of salt, and caution that it should be used in conjunction with traditional country risk analysis.
We also recognise some drawbacks of this approach. It fails to account for potential nonlinearities and threshold effects within variables, while equal weighting may ignore potential differences in importance. In addition, more timely and thorough data can be found for many countries using official sources, providing a more complete snapshot (but making cross-country comparison more difficult).
Nor have we backtested the model, and any model is likely to give false signals (Type 1 and Type 2 errors). While we were able to backtest our debt sustainability index after its first update, methodological changes to our external liquidity scorecard have made this impossible and we will thus have to wait until the next iteration to assess its predictive power.
The primary methodological change has been a switch from ordinally ranking the variables to stating them in terms of standard deviations from the sample median. While the update maintains the relative nature of the index, it allows a more granular comparison. We have also added an additional variable – total reserves as a percentage of the IMF’s Assessing Reserve Adequacy metric (see the appendix for further detail).
Data availability and the vintage of the available data is another challenge, though most of our indicators were deliberately chosen for their forward-looking or high-frequency nature. The longer the lag, and less contemporaneous the data is, the less useful it is as an early warning indicator.
We also omit other indicators which might be a cause or signal of distress, including political and institutional factors. However, we have chosen a more general approach to allow for cross-country comparison, and think our scorecard serves as a useful warning light for external stress.
We welcome feedback from our readers on methodology and coverage, and remain available to answer any questions.
Appendix: Data explanations and sources
Gross FX reserves (months of import)
Common international reserve benchmark, calculated in this instance by dividing gross foreign exchange reserve holdings by the trailing 12-month average of monthly imports (rather than the forward-looking 12-month estimate of goods and services imports, which is more complete but for which data was lacking). Net reserves or total reserves (gross FX + gold) are possible alternative reserve indicators, subject to data availability.
Source: IMF International Financial Statistics (via Bloomberg) for reserves and IMF Direction of Trade Statistics (via Bloomberg) for imports. Frequency: Monthly (ranges from September 2020 to March 2021 for reserves and January 2021 for imports).
Total reserves (% of ARA metric)
Total reserves (FX reserves + gold) as a percentage of the IMF’s Assessing Reserve Adequacy metric (see here for details). IMF benchmark is 100-150% of ARA metric.
Source: IMF Assessing Reserve Adequacy DataMapper. Frequency: Annual (2020) for ARA metric and monthly (ranges from September 2020 to March 2021) for total reserves (via Bloomberg)
Short-term external debt / reserves
Short-term external debt on remaining maturity basis in 2021 relative to reserves (see above).
Source: IMF Assessing Reserve Adequacy DataMapper (via Bloomberg). Frequency: Annual (2021)
Eurobond debt service / reserves
Remaining Eurobond principal and interest payments due from May to December 2021, according to Bloomberg’s DDIS function.
Source: Bloomberg DDIS. Frequency: Annual (2021)
External debt service / exports
Total external debt service (principal + interest) relative to 12-month trailing exports of goods. Exports of goods and services (and remittances) may be a more useful denominator, subject to availability.
Source: World Bank International Debt Statistics for external debt service and IMF Direction of Trade Statistics (via Bloomberg) for goods exports. Frequency: Annual (2021) for external debt service and monthly (January 2021) for exports
External debt service / revenue
Total external debt service (principal + interest) relative to projected government revenue.
EMBI spread (basis points)
Proxy for refinancing risk. Spreads above 1,000bps imply limited market access and potential difficulties refinancing external obligations.
Source: JP Morgan (via Haver). Frequency: Daily (3 May 2021)
Real effective exchange rate (vs 10-year average)
Source: Bruegel (via Haver). Frequency: Monthly (February 2021). Note: Based on CPI differential with 38 largest trading partners
Current account balance / GDP (2021)
Projected external funding needs (sources) arising from the current account deficit (surplus) as % of GDP.
Source: IMF April 2021 WEO. Frequency: Annual (2021)
Current account gap / GDP (2021-25)
Difference between “cyclically adjusted CA” (proxied by the projected 2021-25 average, without cyclical adjustment) and the “CA norm” (proxied by 2010-19 average). Large deviations between the cyclically adjusted CA and CA norm point to external imbalances that must be resolved through BoP consolidation or exchange rate devaluation (see here and here for detailed methodology and estimates).
Source: IMF April 2021 WEO. Frequency: Annual (2021-25)
GEFR / reserves
Projected gross external financing requirement for 2021 derived by adding (subtracting) the current account deficit (surplus) to (from) estimated amortizations of medium and long-term (MLT) external debt. Some sources exclude short-term external debt in their GEFR calculation, but we exclude due to data limitations.
NIIP / reserves
Net international investment position (foreign assets less foreign liabilities). Proxy for risk of capital flight. We prefer non-resident holdings of domestic government debt or portfolio investment liabilities, but use this as a proxy due to data limitations.
Source: IMF International Investment Position. Frequency: Annually and quarterly (mixed)
Debt sustainability index, 28 April 2021
Taper tantrum scorecard, 20 February 2021
External liquidity scorecard, 11 January 2021
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