Building on recent work on how to measure deviations of actual GDP from potential GDP, known as an output gap, I’m pleased to reveal a world map of results for 2023. Remember that an output gap is positive when actual GDP is above potential – or trend – and negative when it is below. In the map below, countries in blue have positive output gaps in 2023, while those in orange and red are negative.
While most countries are exhibiting above-trend GDP growth, there are some noteworthy pockets of below-trend output. Chief among these is a large negative output gap in Ukraine, clearly related to the ongoing war with Russia, and which also appears to have infected several of its neighbors in north-eastern and north-central Europe.
Other countries with active conflicts or security-related concerns also seem to be well below potential: Sudan, Myanmar, Haiti, and Iraq.
There are also some clusters of negative gaps in various regions: Latin America (Peru, Bolivia, Paraguay, and Chile), South/Southeast Asia (Pakistan, Nepal, Bhutan, Myanmar, Thailand, Laos), and West-Central Africa (Ghana, Burkina Faso, Gabon).
As for the positive output gaps around the world, these are mostly in the range of 0-2.5% of potential GDP. Much of southern Europe is above this level: Portugal, Spain, Italy, Croatia, Montenegro, Albania, Greece. Farther east, Georgia, Armenia, Iran, and Tajikistan have also recorded above-trend output beyond 2.5%. Brazil and some parts of Africa (Libya, Republic of Congo, Democratic Republic of Congo, Botswana, Benin, and Liberia).
The countries with the largest positive output gaps are in darkest blue: Guyana, Yemen, and Libya. The latter two have of course experienced significant conflicts over the past decade, suggesting that actual GDP is now well above trend as a result of those previous shocks. High positive output gaps can also be a symptom of economic overheating.
Note that data for 2023 is absent for some countries in the map because the IMF did not provide actual GDP estimates for this year in its October 2023 World Economic Outlook. These include Sri Lanka, Afghanistan, Syria, Venezuela, and Cuba. Given high economic uncertainty and/or the absence of reliable data from these countries, fair enough.
Trend GDP: a visual primer
So far in my writing about output gaps I haven’t made any visual presentations of what real and potential GDP look like. As explained previously, measuring potential GDP is complicated and data-intensive, so economists often use a shortcut: deriving a moving average of actual GDP readings as a proxy for potential GDP. The approach I have taken is known as Hodrick-Prescott filtering.
As a result of the previously-noted pitfalls of using moving averages to measure potential GDP, I refer to the term of “trend” rather than “potential” GDP. As for “actual” GDP, this is data in national currency units using constant prices, meaning that it is real – and not nominal – GDP.
The charts below provide examples actual and trend GDP. I’ve selected these countries because they are ongoing sovereign debt restructuring cases of interest, even if I only present them here for demonstrating how actual / real and trend / potential GDP relate to each other and output gaps:
Output Gap = (Real GDP - Potential GDP) / Potential GDP * 100
Sri Lanka is perhaps the most interesting case, even if the data is only through 2022: a sizable positive output gap – indicating potential overheating in the economy – preceded a sharp drop in GDP, leading to a negative output gap. Also currently in negative territory, Ghana’s GDP exhibits some of the same behavior, albeit with less volatility.
Zambia sustained a positive output gap throughout most of the 2010s, until an economic contraction in 2020 led it into negative territory, though the gap turned positive again in 2023. Once one of the world’s fastest growing economies, Ethiopia’s economic growth has also been remarkably stable, despite the recent Tigray conflict. This makes for a more “boring” chart but is a credit to the country’s economy, with the output gap in marginally positive territory.
Angola, Pakistan, Egypt, Jordan, Argentina, El Salvador, Ecuador, and Belize are among the market-access countries most at risk of sovereign stress, according to the model presented below.Unsurprisingly, several advanced economies appear least at risk, including Norway, Ireland, Denmark, Singapore, the Netherlands, Luxembourg, Hong Kong, and Switzerland.
Earlier this year I published the high-level initial results of a sovereign debt stress tracker, based on a model developed by the International Monetary Fund for countries that it classifies as having access to international markets. The IMF presented this model as part of its update to its Debt Sustainability Framework for Market-Access Countries in 2021, claiming at the time that it had performed significant robustness checks to ensure forecast salience. Time will tell how useful this tool is in predicting sovereign debt strains, and, in any case, it should only be used in conjunction with other analytical approaches.
Heatmaps
Using the latest available data for 2023, the heatmaps below rank order countries by the probability of experiencing sovereign stress, as represented by the column farthest to the right. Neither the probabilities for the dependent variable nor any of the raw data readings for any of the independent variables is shown below. Instead, readers can see the percentile rank compared to the maximum value in each variable column, which is beneficial for visually detecting relative heat for each indicator.
Lighter colors represent more risk, while darker colors represent less risk. Independent variables with negative coefficients, i.e. are negative predictors of sovereign stress, have been reversed in order to ensure color scheme coherence. These include institutional quality, the current account, and international reserves.
The first heatmap below suggests that Angola, Pakistan, Egypt, Jordan, Argentina, El Salvador, Ecuador, and Belize are most at risk of experiencing sovereign debt strains. Looking across the independent variables for this group of countries:
They generally suffer from high external public debt burdens and from relatively poor institutional quality, though Argentina and Jordan fare better on those measures, respectively.
El Salvador is penalized relatively less on stress history, though this assumes spread widening in recent years remained under the IMF’s stress definition threshold (see “Model” section below).
One-year changes in general government debt in Angola, Egypt, and Argentina point to potential risks.
El Salvador, Jordan, and, to a lesser extent, Pakistan, appear to need some replenishing of their international reserve buffers.
Angola and – to a lesser extent – Argentina are marked down for surging REERs.
Pakistan and Egypt display relatively concerning public debt/revenue ratios.
Jordan stands out for poor current account performance.
Egypt, Jordan, and Ecuador exhibit high credit-to-GDP gaps, though several other countries fare worse on this measure.
Each value is divided by the maximal value in that column, resulting in its own empirical percentile. Each value shown is the percent of observations with that value or below it. Sources: IMF, WGI, WB, Bruegel, BIS, author’s calculations.
The second heatmap uses foreign currency general government debt to replace the external PPG debt indicator featured in the first heatmap (see explanation in “Data” section below). Neither of these indicators is ideal, as in both cases coverage for many countries is either lacking or data points are equal to zero. This is obvious in both heatmaps from the absence of dark-colored cells in the relevant column, meaning that many countries are zero. Overall country coverage on this variable is better in the first heatmap, but the second one provides value for countries where data is missing in the first one (e.g. Israel, Korea, Sweden).
The eight countries most at risk of sovereign stress in this second heatmap are the same as in the first one, albeit in a slightly different order and except for Mexico replacing Belize. On this latter point, FX general government debt data – sourced from the BIS (see “Data” section below) – is missing for Belize, conferring on it an unfair advantage over Mexico and other countries where data are present for this indicator. In the first heatmap, external debt data is present for both Mexico and Belize, with the latter appearing more at risk than the former.
Each value is divided by the maximal value in that column, resulting in its own empirical percentile. Each value shown is the percent of observations with that value or below it. Sources: IMF, WGI, WB, Bruegel, BIS, author’s calculations.
Interpretation
Focusing on a country case helps illustrate ways to interpret the data in this model. Take Angola, as it appears most at-risk. Using heatmap (1), the brightest and thus most concerning data points are in the institutional quality, REER 3-year change, general government debt 1-year change, and external public and publicly-guaranteed debt columns. This suggests that the government and public sector more broadly are borrowing heavily, while prices and the exchange rate have also combined to rise quickly. Moreover, the institutions to set a good policy framework appear to be lacking. This is already a dangerous mix.
On the other hand, Angola scores well on its current account balance and international reserves variables. This is easily explained by the fact that the country is an oil exporter, thereby keeping its current account balance high and accumulating foreign reserves from the proceeds of these oil sales to buyers abroad.
While these oil exports provide Luanda with ample benefits, heavy reliance on a commodity-based export sector is also a double-edged sword. The result is often an appreciation of the exchange rate, making the economy less competitive for developing other industries: a classic case of Dutch Disease.
More concerning still is the presence of high inflation. The country’s surging REER variable already suggests that prices are probably rising, as the overall increase is unlikely to be due to nominal exchange rate dynamics alone. Increases in government debt suggest potential fiscal profligacy, which can lead to undesirably-high inflation, the presence of which is confirmed by a glance at recent Angolan statistics. The credit-to-GDP gap, which measures the deviation from trend of credit to the non-financial private sector as a share of GDP, is not particularly alarming in Angola, but may be high enough to also be contributing to the rising price level.
Angola also exhibits a high public debt-to-revenue ratio, which is worrying, given all the oil revenues that the country is seemingly raking in, suggesting that less borrowing and more fiscal discipline are likely needed. Recent sovereign stress is also a concern, indicating that, for all its natural resources, the government is unable or unwilling to pursue policies required to maintain macroeconomic stability.
Model
To recap, the model’s dependent variable is the probability of sovereign stress, which the IMF has detailed criteria for defining – running the gamut from outright default to a mere spread widening beyond a certain threshold. Regarding the independent variables:
The first two represent how recently a country has experienced sovereign stress, and its government effectiveness and regulatory quality.
Other explanatory variables are macroeconomic in nature, including current account balances, real effective exchange rates – which also capture price changes, credit gaps to the private sector, and international reserves.
More specifically fiscal indicators include those on general government debt, foreign currency public debt, and public debt-to-revenue ratios.
With the exception of REERs and debt-to-revenue, these macro-fiscal indicators are all expressed as a share of GDP.
A global variable also features in the model, the VIX Index, which measures stock market volatility in the US, but is not presented in the heatmaps above, given its constance across countries.
Data
In the first iteration of the tracker, 2023 data was captured for 43 market-access countries, including both emerging markets-developing economies and advanced economies. Thanks to more available data for this year and refinements in data capture, coverage has been expanded to 82 MACs in these heatmaps.
Two similar heatmaps are presented in this article, with a difference in one of the independent variables and, as a result, slight changes to the overall results in the dependent variable. One of the IMF’s indicators is foreign currency public debt. In the first instance, the World Bank indicator for external public and publicly-guaranteed debt is used as the best available proxy for the IMF’s variable. While using this data from the World Bank remains the best possible option at this stage, there are some glaring omissions in coverage. For instance, the World Bank source suggests that Israel’s external PPG debt is equal to zero, which is clearly incorrect.
As a remedy to the World Bank’s data deficiencies, a second heatmap applies data from the Bank of International Settlements on foreign currency general government debt, as a proxy for this indicator in the same overall model. The BIS data does fill in some of the World Bank gaps – e.g. Israel – but in fact covers fewer countries than the first source. As such, the first heatmap is still preferable.
It is also worth noting that both the World Bank and BIS indicators differ from the IMF variable of foreign currency public debt. In the former case, external public debt differs somewhat from foreign currency public debt, even if virtually all external debt is in foreign currency. In the latter case, foreign currency general government debt excludes some types of debt that is covered under foreign currency public debt.
The World Bank Group-International Monetary Fund Annual Meetings drew to a close in Marrakech this past weekend, the first time these events have been held in Africa since the 1973 edition in Nairobi. While the Bank-Fund leadership expressed their usual endorsement of international cooperation and optimism for the future, this year’s agenda also explicitly aimed to address geopolitical fragmentation and fully acknowledged heightened threats to the goals of eradicating poverty; bolstering sustainable, inclusive growth; and preserving macroeconomic stability.
The main problem at this year’s annuals wasn’t a new one and goes by many names: geopolitical competition, fragmentation, deglobalization, trade frictions, or decoupling. A whole host of challenges to multilateral financing efforts stem from the political obstacles to international cooperation that have emerged over the past decade, with the 2007-2009 Global Financial Crisis marking the end of America’s “unipolar moment” and ushering in a new, more competitive era. The prospects for a new capital increase for multilateral development banks, innovative hybrid financing solutions to boost World Bank lending, and sovereign debt restructuring processes are all suffering from the fractured backdrop.
IMF Global Policy Agenda
The IMF’s policy priorities are a response to the main macroeconomic challenges in today’s global economy:
tame inflation
ensure financial stability
restore fiscal room
boost medium-term growth
Indeed, inflation has not yet reverted to central bank targets in many countries, while the rapid rise in interest rates in the past few years have strained parts of the US banking system. At the same time, expansionary fiscal policies have pushed up yields on government debt in various countries, with the return of bond vigilantes evident in the US in 2023. The prospect of higher fiscal deficits can also sometimes undermine financial stability, as exemplified by the UK mini-budget straining pension schemes in September 2022. Tighter fiscal policy will be necessary in many countries to guard against future shocks, while appropriate reforms are also widely-needed to revive the dimmed outlook of medium-term growth.
In parallel with the macroeconomic policy priorities, the Fund is pursuing complementary objectives. The IMF launched, with the government of Morocco, the Marrakech Principles for Global Cooperation, which include reinvigorating inclusive and sustainable growth; building resilience; supporting transformational reforms; and strengthening and modernizing global cooperation. These principles are a welcome attempt to stem the tide of global divergences, even if they are unlikely to meet with much success in the short term. In a similar vein, the IMF has attracted more funding for the interest-free Poverty Reduction and Growth Trust and for the climate change-focused Resilience and Sustainability Trust.
Of note, the IMFC Chair committed to concluding the 16th General Review of quotas by December 2023, in light of agreement on a significant increase of quotas this year. Crucially, there seems to be support for quota realignment by June 2025 to reflect current economic realities, including through an updated quota formula. The IMFC has also called for the creation of a third chair on the IMF Executive Board for Sub-Saharan Africa, in order to improve the continent’s representation.
Yet the IMF has not been able to deliver more in the way of impactful policy successes. One potentially high-impact policy area would be finding a solution for re-allocating SDR usage from the wealthy countries that don’t need them to the poorer countries that do. A further work-stream with outsized effects would be to do more to strengthen the Global Financial Safety Net, which includes the IMF’s toolkit, bilateral swap arrangements, regional financial arrangements, and international reserves – a tall order in the current environment.
Global Sovereign Debt Roundtable
The official sector has achieved a modicum of progress on improving the sovereign debt restructuring architecture in recent months. Probably of most importance to private creditors is improved information-sharing during restructurings, with new possibilities for private lenders to access debt sustainability analyses and related elements at the same time as official creditors, under certain conditions. The Fund has highlighted the increasing speed from staff-level approval to Board approval, from 11 months in Chad in 2022, to 9 in Zambia, 6 in Sri Lanka, and 5 in Ghana most recently, while recognizing that this is still above the 2-3 month average in the past.
The IMF maintains that external public debt strains are not currently as high as they were in the 1990s, even considering the existence of larger local debt markets, which has led to some observers wondering if there is a sense of complacency about pending risks in low-income countries. The IMFC welcomed progress in Zambia, Sri Lanka, and Suriname but called for more results in Ghana, Ethiopia, and Malawi, while also calling for stronger creditor coordination for sovereign debt restructurings occurring outside the Common Framework.
One of the main pieces of news to come out of the meetings was that Zambia’s finance ministry and its official creditor committee signed a memorandum of understanding, thus formalizing the agreement reached in June, and paving the way for Zambia to seek comparable treatment from its commercial creditors. It was also revealed that Kenya may be seeking exceptional access to IMF support ahead of a $2 billion bond maturing in June 2024.
There are some other minor new features in the sovereign restructuring framework, regarding cutoff dates (no later than staff-level agreement), state-contingent debt instruments (which shouldn’t be the norm), and the appropriate approaches to domestic debt (case-by-case) and SOE debt. Other areas remain contentious among the various creditor categories, such as appropriate discount rates to be used for NPV calculations for comparability of treatment. There is also no consensus on the treatment of arrears and on debt service suspensions during negotiations.
Show me the money: capital increases for MDBs?
Despite the ongoing efforts of senior staff to convince donor countries to provide more resources for development, the World Bank Group’s ambitions will continue to lack requisite firepower. The cause is an absence of political will in most of the G7 countries to make sufficient financial commitments to development, as evidenced by a succession of broken Western promises. To be sure, some efforts are under way, such as Japan’s pledge to significantly raise its contribution to the IMF’s zero-interest loan tool, the Poverty Reduction and Growth Trust. For its part, the US may transfer $2 billion in additional funding to the World Bank Group this year, though this is a far cry from the scale that is needed.
Additional annual financing required to meet the United Nations’ Sustainable Development Goals stands at around $3 trillion. The G20’s Capital Adequacy Review framework suggests that a general capital increase for the multilateral bank system, including the IBRD, could unlock $200 billion in annual lending, with a further $80 billion annually from balance sheet optimization (e.g. callable and hybrid capital). The Center of Global Development suggests that the international development finance system should boost its annual financing by $500 billion by 2030, with multilateral development banks providing $260 billion and national development finance institutions delivering the remainder. Private capital ought to match that half-trillion increase, for a combined public-private total of $1 trillion.
Yet these figures still fall well short of the additional $3 trillion needed annually. By the CGD’s calculations, each dollar of new equity in MDBs can be leveraged for $15 of external sustainable investment financing, of which $7 in direct MDB lending and $8 in private capital. Assuming that private finance can be crowded in to such a degree is likely overly optimistic, as the CGD’s own figures indicate that MDBs currently mobilize only 60 cents for each dollar lent. Even so, public and private stakeholders will have to come up with financing solutions to achieve the SDGs, and this should be possible with enough political will: just look at the over $100 billion raised for Ukraine.
The World Bank’s Evolution Roadmap
The World Bank Group’s recently-appointed president, Ajay Banga, has laid out a roadmap to enhance the organization’s effectiveness. More efficient balance sheet management should unleash $157 billion in additional lending over 10 years, while preserving the Bank’s AAA rating. These measures include increasing the loan to equity ratio, launching a hybrid capital instrument, and creating a portfolio guarantee mechanism. Similarly, management is also exploring solutions using callable capital and SDRs. An elegant approach to channeling some of 2021’s SDR 650 billion windfall could be to have the Bank issue SDR bonds, to be purchased by national central banks.
A number of other changes are in the works under Banga. These include setting up a Global Public Goods Fund to grow concessional resources by attracting funding from governments and philanthropies, exploring maturities of up to 40 years for social and human capital investments, and exploring energy transition solutions. More importantly, efficiency gains are at the heart of the new strategy. There is an objective to slash project review and approval times by a third by simplifying procedures, while partnerships with other MDBs are already being pursued more actively so as to amplify impact. Similarly, Banga’s team plans on scaling knowledge-sharing in order to more easily share impactful solutions, and a private sector investment lab has already been set up to galvanize private financing.
Banga’s plans to streamline processes seem like a requisite pre-condition for convincing donor countries to increase the Bank’s share capital, though even if his team can deliver, any new equity is far from guaranteed. Early signs of the new president’s first few months in the role have demonstrated his dynamism and communication skills, and future success in reforming the institution’s bureaucracy, while likely challenging to achieve, could yield significant development benefits. However, his team is reportedly difficult to approach internally, which could potentially delay progress.
As part of tracking the probability of credit stress among 112 sovereign issuers, one of the variables of interest in the IMF’s model is the credit-to-GDP gap. This indicator matters not only because of its predictive power for sovereign credit events but for many other reasons as well, including monetary policy transmission and government borrowing. When analyzed in conjunction with other data, credit gaps are useful barometers for detecting the presence of credit bubbles, economic over- or under-heating, and policy distortions such as financial repression and fiscal dominance.
Credit gaps are derived from observations of credit extended to the private sector as a percentage of GDP, and then a statistical technique, usually Hodrick-Prescott filtering, is used to smooth out the data points in the time series as a way to measure an underlying trend. While there are some shortcomings to this approach, including the arbitrary nature of the smoothing parameters used to identify the trend, it helps ascertain whether the cyclical component of lending is above or below long-term expected processes.
A credit-to-GDP gap is thus an actual observation at time t minus the trend in the same time period. As such, a positive credit gap is one in which lending is above trend, whereas a negative one is below. The credit gap coefficient in the IMF model is positive, as is the case in other models in the financial crisis academic literature, meaning that higher values are associated with an increased likelihood of sovereign debt strains. Looking at quarterly data through end-202212023 data will be presented in future posts on credit gaps. from the Bank of International Settlements on 43 countries plus the Euro Area, this first set of charts presents the actual credit-to-GDP ratios in blue, the smoothed trend in yellow, and the credit-to-GDP gaps in green.
SLIDE DOWN: actual data vs trend; SLIDE UP: the cyclical gap between the two; XM = Euro Area
In the chart above, credit gaps in this mix of developed (DMs) and major emerging market economies (EMs) are currently mostly negative. This makes sense given the tighter monetary policy stances around the world to combat inflation, with EM central banks having begun their rate-raising cycles2Some EM central banks are so far ahead of DM that they have already begun cutting rates in 2023. before their DM peers. A spike in credit gaps can also be observed in 2020 as policymakers worldwide lowered interest rates and facilitated the extension of credit as part of emergency measures to mitigate economic scarring at the height of the pandemic.
The BIS credit gap data is extremely useful for this set of countries, which, after all, comprise the world’s largest economies, and all the more so because it is available on a quarterly basis. The BIS describes its credit-to-GDP ratio as capturing total borrowing from all domestic and foreign sources by the private non-financial sector.3https://www.bis.org/statistics/about_credit_stats.htm However, other sources are needed for measuring credit to the private sector in other countries, and, thankfully, the World Bank has a similar indicator: domestic credit to the private sector by banks.4 https://databank.worldbank.org/metadataglossary/jobs/series/FS.AST.PRVT.GD.ZS The World Bank data series has far broader country coverage than the BIS data, thus opening vast additional swathes of the world to analytical coverage.
In contrast to the BIS data with its inclusion of both domestic and foreign credit to the non-financial private sector, the World Bank indicator appears to only include domestic sources of financing. Moreover, the BIS data appears to include sources of non-bank financing, unlike the World Bank data. Taken together, these two differences likely explain much of the discrepancy between these two datasets. Further, the World Bank data appears to only be available at a yearly frequency, thus requiring the BIS quarterly data to be transformed to yearly averages for the purposes of comparison.
The charts below present BIS data in blue and World Bank data in yellow, in yearly form through end-2022 in both cases. As seen above, the BIS provides credit gap and trend data alongside its credit ratios and uses a one-sided Hodrick-Prescott filter with the smoothing parameter λ set to 400,000 for this quarterly data. The World Bank only provides its credit ratios on a standalone basis, meaning that the trend and credit gap need to be estimated independently. This is simple enough for one country, and thankfully panel statistical techniques enable scalability for quick estimation across a large number of countries and years. As such, trends and credit gaps are derived from the World Bank’s credit ratios using a two-sided HP filter with λ = 100, the recommended setting for annual data.
SLIDE DOWN: actual data; SLIDE UP: trend data, smoothed with HP filters
Consistent with the inclusion of foreign sources of credit, the BIS credit ratios are usually higher than those from the World Bank, especially in many European countries, e.g. Luxembourg and Belgium. Elsewhere, the figures track more closely, as is the case with Japan, Malaysia, and the UK. The US and China also fell into this category, but the datasets have diverged in recent decades for those countries. Surprisingly, there are also a few countries where the World Bank ratio exceeds the BIS reading, despite the former excluding foreign credit sources, with South Africa and the US standing out most prominently from this perspective.
The point of comparing the two datasets is to use the BIS as a benchmark to get a sense if the World Bank data is at least somewhat aligned with the former and it is any good for predictive purposes. Certainly, the similar characteristics of the actual and trend data above are a positive sign. As for the credit gaps themselves, the BIS and World Bank figures are presented below. While there are large differences in most countries, there are also similar processes at work in many countries, e.g. the United Kingdom, Malaysia. The BIS credit gaps appear to be more volatile than those of the World Bank, which could be explained by the former’s inclusion of foreign lending: capital flows of the portfolio variety, which includes debt, are prone to sudden stops and starts.
To simplify further, the difference in the BIS and World Bank credit gaps, where the former is subtracted from the latter (difference = WB – BIS), features in the chart above. Ideally, the data readings would all be horizontal lines at zero or at least resemble a stationary process hovering above and below zero. While some countries do have these features – Sweden, the UK, the US, and Switzerland, among others, a large cohort exhibits some sort of bias. A statistical test of this difference in credit gaps across this panel of countries over these years would likely reject the notion that the difference is equal to zero. Nevertheless, the World Bank domestic credit to private sector by banks indicator seems fit for purpose, particularly given the large role that domestic banks play in credit provision in most economies.
Future posts will expand further on the importance of credit gaps and present broad country coverage of World Bank credit gap data.
1
2023 data will be presented in future posts on credit gaps.
2
Some EM central banks are so far ahead of DM that they have already begun cutting rates in 2023.
The recent wave of coups in Africa has increased scrutiny of France’s role on the continent. Looking at France’s net stocks of foreign direct investment in its former colonies reveals some surprises for those not closely monitoring these trends, and helps provide some sense of where Paris’s relations are with this group of countries. A snapshot of Franco-African economic relations helps debunk the oft-exaggerated importance of French influence in Africa, despite it being too early for a Françafrique post-mortem. Using foreign direct investment as a proxy delivers useful context for observers wondering where the next coup might strike, not as a causal factor, but as an illustration of heterogeneity.
As a percentage of all FDI in Sub-Saharan Africa by country, France is best represented in Senegal, Côte d’Ivoire, Burkina Faso, Togo, the Republic of Congo, Cameroon, and Angola. Of these countries, only Burkina Faso has experienced a coup d’Etat in recent years. French FDI as a percentage of GDP is highest in Senegal, the Congo, the Central African Republic, and Angola, and was also significant in Niger in the mid-2010s. The point is that the French factor, especially in the economic sphere, fails to shed much light on why any of the coups in Gabon, Niger, Chad, Burkina Faso, Mali, and Guinea occurred, each of which has its own idiosyncratic explanations.
Coup’s next?
As for the prospects of further military takeovers in Africa’s Sub-Saharan francosphere, Senegal and Congo appear the least likely candidates. In Senegal, President Macky Sall is not seeking an unconstitutional third term in the 2024 election, in keeping with the country’s history of political stability. In Congo, President Denis Sassou-Nguesso’s apparently ironclad grip on the country has shown no signs of wavering. In Cameroon, President Paul Biya’s late August military reshuffle could offer him some temporary protection, though the ongoing conflict with separatist rebels in its anglophone region is a source of risk.
Côte d’Ivoire’s 2025 presidential election is an upcoming flashpoint in an ethnic powder-keg, with President Alassane Ouattara already having changed the constitution to enable a third term from 2020. Since the International Criminal Court in the Hague acquitted former president Laurent Gbagbo of all charges in 2019, it’s a politically-explosive resurrection given the context of ongoing ethnic favoritism in Ivorian politics. To complicate matters further, the largest of the country’s three main ethnicities – Ouattara and Gbagbo hailing from the other two – hasn’t held the presidency since 1999, setting the stage for further grievances.
With all eyes on Libreville following Gabon’s August coup, facile narratives of France’s relevance are overblown, historical, linguistic, and security ties notwithstanding. France’s FDI involvement in GDP terms was higher in Gabon than in any other Central African country at one point in the mid-2000s, though Congo has had more French investment stock as a share of its economy for most of this century. In dollars, however, Angola has attracted the largest quantity of French investment.
Use vertical slider to compare USD vs % GDP figures.
Gabon’s main economic drivers are the oil, manganese, and wood sectors, with a French presence in each of these and well beyond. The French oil major Total has ongoing but diminished activities, following its sale of some of its Gabonese assets to the Anglo-French oil company Perenco in 2021. The Euronext-listed metallurgical and mining company Eramet continues to operate the country’s chief manganese concessions, while the Rougier group is a significant wood processor and exporter.
Yet Gabon’s economic partnerships have been tilting away from France for over a decade. Singapore has been a major player in the country since the agri-business company Olam entered into a joint venture with the government in 2010 to create a Special Economic Zone. The Paris-listed oil junior Maurel & Prom continues to operate in Gabon but has been majority-controlled by the Indonesian state oil company Pertamina since 2017. In 2022, Gabon joined the Commonwealth, alongside Togo, another former French colony, even as Libreville’s trading relationships shifted away from France and towards Asian partners.
France is a leading foreign investor in Angola, accounting for 60 subsidiaries and 45 local companies that employ around 10,000 people – trailing only Portugal and China on this metric. France has benefited from President João Lourenço’s efforts to rebalance economic ties away from Chinese, Russian, and Turkish interests in favor of Western partners. The French presence is concentrated in the oil and oil services sectors, with Total, Maurel & Prom, and Technip among the major players. Total alone accounts for 40% of Angola’s national oil production and is one of the country’s largest employers, alongside the French brewer Castel.
Total’s presence accounts for a large share of France’s FDI footprint in the Republic of Congo, where most French companies operate in the oil services and construction sectors. French firms currently employ around 15,000 people, though this is down from over 25,000 in 2015. Italy, the US, and China are the other main foreign investors in the country.
West Africa
Côte d’Ivoire accounts for France’s highest stock of FDI in francophone West Africa, followed closely by Senegal. The latter being the smaller economy of the two, France’s presence in Senegal is heavier in GDP terms. There was also a strong French economic presence in Niger in the mid-2010s, according to the data from the Banque de France below, though this has fallen off sharply in recent years.
Use vertical slider to compare USD vs % GDP figures.
France is the largest foreign investor in Côte d’Ivoire, with around 240 subsidiaries and some 1,000 companies owned by French citizens. These investments are spread across numerous economic sectors, reflecting the highly-diversified nature of the Ivorian economy.
France also has the highest proportion of foreign investment in Senegal, though its share has declined markedly since the mid-2010s. This involvement is also spread broadly across economic sectors, including banking, retail, telecoms, and industrials.
I spent most of 2012 working in Gabon, a gem of a country well-endowed with some of the lushest rainforest on the planet, abundant natural resources – oil, manganese, wood – and a small population. Like many observers, I was aware of the concerns leading up to the August 2023 presidential elections as President Ali Bongo sought a third consecutive term, especially given the post-electoral violence in 2016.
Yet the military coup of August 30th still comes as a surprise because, in recent years, the military takeovers in Africa had largely been confined to the Sahel region: Niger, Mali, Burkina Faso, Chad, and Sudan. There were two other recent putsches, one in Guinea, on the Sahel’s doorstep, and another one in Zimbabwe.
These countries have much lower income/capita and larger populations. Unlike Gabon, most of them are landlocked and have arid climates.1Guinea is neither landlocked, nor does it have an arid climate. Zimbabwe is also not as arid as the Sahel. So what do these countries have in common with Gabon? Plenty, whether their colonial pasts under France2With the exceptions of Sudan and Zimbabwe. or the nitroglycerin-like combination of weak institutions and ethnic divisions.
My analytical fallacy was to think about the coups in the Sahel as some sort of wave with common drivers, which would have a bearing in other parts of Africa and beyond. Not so, or at least not beyond the Sahel where several weak, poor states having trouble coping with terrorist insurgents is a commonality. Rather than a wave of African coups with a shared set of narrowly-defined underlying causes, a version of the Anna Karenina principle applies: “Each unhappy country is unhappy in its own way.”
Moreover, it is good discipline to keep ethnicity front of mind when analyzing African politics, as this helps reveal some of the political forces at play that make each country unique. Even though ethnic factors are often of secondary importance, as in the case of Gabon, considering ethno-linguistic and cultural differences also provides contextual granularity that is often absent from English-language coverage of francophone Africa.
Below, I also provide charts on France’s net FDI to each of the francophone countries as a simple gauge of its ongoing involvement in each economy. This simple measure does not explain the coups in each country, nor does it encompass the complexity of the bilateral economic, political, and security relationships, but it provides relevant context as observers ponder Paris’s links to the continent.
Omar Bongo had long relied on French support, while his son Ali had made some concessions to the larger Fang ethnicity (33% of the population) and others at various points during his terms.
In Africa, only the Seychelles and Mauritius have higher GNI/capita than Gabon, where 1/3 of the population lives below the poverty line.
Clearly, any wealth redistribution from the rapacious Bongo clan was insufficient for the population to allow him to continue pilfering the country indefinitely amid suspicions of electoral fraud in the current and previous elections.
Enfeebled by a stroke in October 2018, Ali Bongo – and his reportedly dissolute family members – provided a complacent atmosphere at the presidential palace, thus combining with popular discontent to set the ideal conditions for Nguema and his co-conspirators.
Of note, France’s net foreign direct investment stock in Gabon has been on a downward trend since the mid-2010s (see charts below), declining from around €1.8bn in 2013 to under €500mn in 2022. This is despite the global net FDI stock in Gabon rising over the same period, pointing to France’s diminished stature in the Gabonese economy. More detailed information on this topic will be available in future posts.
🇳🇪 Niger
July 2023: Junta leaders oust President Mohamed Bazoum, who is of Arab ethnicity ( < 0.5% of the population), purportedly for leniency towards islamist insurgents. This underscores the political importance of the security situation, as in several other countries throughout the Sahel.
Bazoum succeeded Mahamadou Issoufou (Hausa, 55% of the population), who completed two terms as president without trying to run for a third term, instead nominating Bazoum as his preferred successor.
Issoufou had himself come to power through elections a few years after a military coup ousted a previous president – Mamadou Tandja – who had attempted to stay on as president for longer than two terms, much like Ali Bongo in Gabon today.
As in Gabon, France’s net FDI stock in Niger has been on the wane since the mid-2010s, declining from over €1bn to under €500mn as of last year. The entirety of French exposure to the country appears to in the form of debt and other instruments, including in all likelihood intra-company debt.
Despite limited French net FDI exposure to Chad, even here France’s presence is declining, from nearly €200mn in the early 2000s to around €100mn today.
In constrast to Gabon, Niger, and Chad, France’s net FDI stock in Burkina Faso has been rising steadily for the past decade, driven mainly by reinvested earnings into increasing shareholder equity. Overall exposure has jumped from ~€100mn in 2012 to ~€400mn in 2022.
April 2019 & October 2021: General Abdel Fattah al-Burhan seized power in 2021, placing Prime Minister Abdalla Hamdok under house arrest. The Sudanese Armed Forces ousted the long-reigning Omar al-Bashir in 2019 under the leadership of Ahmad Awad Ibn Auf.
France’s net FDI exposure to Guinea has been rising steadily since the mid-2010s, albeit from a low base, partly reflecting Conakry’s historically relatively cool relations with Paris. Up from €100mn in 2015, French FDI stock stood at ~€175mn in 2022.
🇲🇱 Mali
August 2020: A colonel in Mali’s special forces, Assimi Goïta (Minianka, ~7%, b. 1983) has been the country’s de facto leader since a successful coup ousting IBK in August 2020.
Introducing a sovereignstress tracker covering 100+ countries, based on the IMF’s Debt Sustainability Framework for Market-Access Countries.The model used in this analysis suggests that sovereign debt strains are lower in 2023 than they were in either 2022 or 2020 for this group of countries. MACs comprise all economies that are lower-middle income and above, including many emerging economies and all advanced economies.
Market-Access Countries
In 2021, the IMF released its new Debt Sustainability Analysis framework for Market-Access Countries, in line with its differentiation between MACs and low-income countries. The reasons given for distinguishing between these two groups is that MACs generally have significant access to international capital markets, whereas LICs rely on concessional resources to fulfill their external financing needs.
As such, the Fund has a separate approach to debt sustainability analysis for LICs, which is beyond the scope of this tracker. The strict definition is that countries eligible for the IMF’s Poverty Reduction and Growth Trust, which is an interest-free concessional financing tool, are treated as LICs, whereas the rest are considered MACs.
Geographic coverage
Overall, 140+ countries and territories were included in this analysis, but results were only obtained for 112,1Angola, Albania, United Arab Emirates, Argentina, Armenia, Antigua & Barbuda, Australia, Austria, Azerbaijan, Belgium, Bulgaria, Bahrain, Bahamas, Bosnia & Herzegovina, Belarus, Belize, Bolivia, Brazil, Barbados, Brunei, Botswana, Canada, Switzerland, Chile, China, Colombia, Costa Rica, Cyprus, Czechia, Germany, Denmark, Dominican Republic, Algeria, Ecuador, Egypt, Spain, Estonia, Finland, Fiji, France, Gabon, United Kingdom, Georgia, Equatorial Guinea, Greece, Guatemala, Hong Kong SAR, China, Croatia, Hungary, Indonesia, India, Ireland, Iran, Iraq, Iceland, Israel, Italy, Jamaica, Jordan, Japan, Kazakhstan, St. Kitts & Nevis, South Korea, Kuwait, Lebanon, Sri Lanka, Lithuania, Luxembourg, Latvia, Morocco, Mexico, North Macedonia, Malta, Mongolia, Mauritius, Malaysia, Namibia, Nigeria, Netherlands, Norway, New Zealand, Oman, Pakistan, Panama, Peru, Philippines, Poland, Portugal, Paraguay, Qatar, Romania, Russia, Saudi Arabia, Singapore, El Salvador, Suriname, Slovakia, Slovenia, Sweden, Eswatini, Seychelles, Syria, Thailand, Trinidad & Tobago, Tunisia, Turkey, Ukraine, Uruguay, United States, Venezuela, Vietnam, South Africa given insufficient data availability in around 30 cases. The analysis is based on a multivariate model, meaning that a missing data point for a single variable across all years makes it impossible to derive a final measurement for the country in question, resulting in exclusion.
The calculated probabilities of sovereign stress for the 112 countries do not cover all years, unfortunately. For instance, there are only results for 43 countries in 2023, given less availability of annual data and/or forecasts for the current year. Data coverage will be improved in future iterations of the tracker.
All countries included are either high, upper middle, or lower middle income countries, with few exceptions, such as Syria, which the World Bank reclassified as a LIC in 2018. There is also some debate as to whether Venezuela constitutes an UMIC or a LMIC, though it is treated as a LMIC here.
Model
The IMF claims that extensive testing demonstrates that its new MAC DSF is much better at accurately predicting sovereign debt distress. Predictive analysis is based on a multivariate logit model developed by Fund staff. Passing the required data into the model provides a probability that a sovereign borrower experiences debt stress:
Multivariate logit model specification
Regressor
Coefficient
Institutional quality
-1.073 ***
Stress History
0.514 ***
Current account balance/GDP
-0.024 **
REER (3-year change)
0.013 **
Credit/GDP gap (t -1)
0.086 ***
Δ Public debt/GDP
0.052 ***
Public debt/revenue
0.002 ***
FX public debt/GDP
0.024 ***
International reserves/GDP
-0.034 ***
ΔVIX
0.015 ***
*** / ** indicate statistical significance at the 1 percent / 5 percent levels
Results
In addition to the dotplot chart above, a further way to view the broad results from this analysis of 112 countries is as a boxplot, presented below. I fully acknowledge that this data is unbalanced, given the limited number of data points in 2023 and also in the early 2000s – as can be seen in the first chart above – compared to better country representation in the middle years of the sample. More charts are presented in the next section below in order to address this issue.
As can be seen in the data, in 2023 there appears to be less systemic sovereign stress among MACs as compared to previous years, particularly 2022 and 2020. Future posts will provide granular details and heatmaps at the country level.
The first web application as part of Sovereign Vibe’s DataHub disaggregates the World Bank’s International Debt Statistics’ outstanding debt stock data for 68 low-income countries by creditors type: multilateral, bilateral, and private. Further decompositions are provided for the concessional and non-concessional components of multilateral and bilateral lending, and also for private credit by bondholders, banks, and other private lenders.
This first update to the “External Sovereign Debt: DSSI Countries” dashboard adds some helpful new features for users seeking to quickly view and analyze external public and publicly-guaranteed debt stock data. To begin with, the updated app now covers data extending back to 1970, the earliest year available in the WB database. The pilot version only extended coverage back to 2000, given the heavier data burden and the uncertainties around this initial attempt.
Secondly, this new version of the dashboard allows users to view the IDS debt stock data in US dollars, as previously, but now also includes an option to view the readings as a percentage of GDP.
Third, a new category has been created to aggregate all borrowing countries. When opening the application, the “Sovereign borrower(s)” category defaults to “All DSSI,” while the “Creditor(s)” menu defaults to “World” so that users can get a high-level view of all lending (i.e. from the entire world) for all these countries (i.e. all DSSI) at once. This view is presented in the previous post, “Cure worse than the disease,” but was previously unavailable through the dashboard.
Finally, the update enables users to select multiple creditors when viewing a country’s external debt stock. Over two hundred creditor locations and types are specified in the creditor menu, so, for example, a user could choose to look at how much China, France, bondholders, and the World Bank-IBRD have lent to Zambia up until the latest data reading.
Further updates to this dashboard could include allowing users to select multiple borrowers at once. While in practice providing this is currently possible for viewing the debt stock data in US dollars, some back-end work is needed to make aggregating borrowers usable in percentage of GDP. Next steps will include:
Enabling users to select multiple borrowers at once
Expanding coverage to the broader emerging markets universe
Moving beyond external debt stocks and towards associated external sovereign debt flows
Progressing from descriptive data towards analytical outputs
What are your thoughts on this basic dashboard? How do you think it could be improved, and what features would you like to see? Feel free to submit comments in the section below or via the website’s Contact page.
All suggestions for avenues of further research are welcome as Sovereign Vibe progresses from its current pilot phase towards deeper analysis of challenges facing the sovereign debt landscape and the emerging markets complex.
A high-level snapshot of the structure of outstanding external sovereign debt burdens for low-income countries and reflections on the G20’s pandemic-era DSSI policy and its successor, the Common Framework for Debt Treatments beyond the DSSI.
LIC debt burdens
During last month’s IMF-World Bank Spring Meetings, I listened to a discussion on debt crisis resolution between civil society activists and IMF staff. The vastly different frames of reference, language, and motivations on low-income country (LIC) debt playing out were captivating. It is precisely this clash of worlds that the sovereign debt space needs more of as stakeholders search for the best policies to foster inclusive growth and eradicate poverty.
Civil society organizations (CSOs) have a long-standing and well-known position on LIC external sovereign debt: in a nutshell, just cancel it. Indeed, rising external debt burdens in LICs in recent years have fueled more calls for debt forgiveness. Looking at the DSSI-eligible LICs, the rapid increase in external sovereign debt in the 2010s does give pause for concern. While the overall external public and publicly-guaranteed (PPG) debt load hovered around $200 billion throughout the 1990s and 2000s, it surpassed the $600 billion mark in 2021.
Contrast the CSO perspective with IMF staff assertions that external sovereign debt strains in LICs are less severe today than in the past. Needless to say, the CSO representatives were essentially unanimous in taking issue with this position, labeling it as provocative. IMF staff presented a chart resembling the one below, highlighting how external public debt-to-GDP was much heavier previously. In fact, the most acute strains occurred in the mid-1990s. These declined until the late 2000s, partly thanks to the Heavily-Indebted Poor Countries initiative (HIPC) from 1996 and the Multilateral Debt Relief Initiative (MDRI) from 2005.
While today’s external PPG debt ratios are less alarming, the growth of domestic capital markets in many LICs suggests that overall (i.e. domestic plus external) sovereign debt-to-GDP could be too high. Moreover, LIC sovereigns have borrowed more on non-concessional terms over the past decade, pointing to greater interest payment pressures.
The new data above will augment the DSSI dashboard in the Sovereign Vibe DataHub, where users can filter data by borrower and creditor.
