The “emerging market” classification has been redundant for some time now
The key chart
Trends in market share (%) of global debt since June 2009 (Source: BIS; CMMP)
The key message
Whisper it softly; the “emerging market” (EM) classification has been redundant for some time now.
CMMP analysis has questioned the relevance and usefulness of the “emerging market” classification for some time. The latest BIS data release, merely supports this view, at least from a debt perspective.
EM’s share of global debt has increased from 18% in June 2009 (at the time of the GFC) to 40% in June 2023 – a remarkable structural shift (see key chart above).
Over this period the EM debt ratio has risen from 97% GDP to 156% GDP, and is now only 6ppt below the debt ratio of so-called “advanced” of “developed markets” (DM).
For reference, the DM debt ratio has fallen from 174% GDP at the beginning of this period and from its all-time high of 183% GDP in 4Q20.
These dynamics have supported a popular investment narrative called, “The EM-debt story”.
In my previous post, however, I noted that all sectors of the Chinese economy are increasing their levels of indebtedness and that all their debt ratios hit new highs in 2Q23 (see “Whisper it softly – Part III“).
The key point here is that if we strip out China, EM’s shares of global debt has only increased slightly since the GFC, from 10% to 13%.
What this means is that rather than witnessing an EM-debt story, we have, in fact, been witnessing “The China-debt story” since the GFC.
So what?
While the EM classification remains convenient, it is increasingly less relevant and/or helpful in terms of understanding the impact of global debt dynamics on macro policy, investment decisions and financial stability.
Please note that the summary comments and chart above are abstracts from more detailed analysis that is available separately.
Trends in total EA mortgages (EUR bn, LHS) and annual growth (% YoY, RHS) (Source: ECB; CMMP)
The key message
The answer to the question, “Is there such a thing as the EA mortgage market?” seems obvious. Of course there is.
We know its size (€5,228bn), its structure (biased towards fixed rate lending) and its importance to banks (40% of total lending). We also know the current cost of borrowing (3.44%) and the speed with which higher policy rates have passed through to this cost (147bp so far). We can monitor the rate of growth in mortgages (3.0% YoY in nominal terms, -3.7% in real terms) and in monthly flows (slowing sharply).
Not so fast…!
The complication here is that these aggregate data points mask very important variations at the national level. These include:
Size (€5,288bn): five national markets dominate (“the big five”). Germany and France account for 56% of total EA mortgages alone and for 85% together with the Netherlands, Spain and Italy.
Structure of new mortgages (over 75% fixed-rate): varies from over 90% variable-rate in Finland, Lithuania, Estonia and Latvia to over 90% fixed-rate in Slovenia, Slovakia, France, Belgium and Ireland. Among the big five, relatively high exposures to fixed rate lending in France, Germany and the Netherlands, relatively low exposures in Italy and Spain.
Exposure to mortgage lending (40% of total lending): ranges from 50% in Malta and Slovakia to 25% or less in Luxembourg and Greece. Among the big five, above average exposures in the Netherlands, Germany and Spain, below average exposures in France, and more noticeably in Italy.
Cost of borrowing (3.44%, April 2023): ranges from 5.32%, 5.27% and 4.99% in Latvia, Lithuania and Estonia respectively to 2.24% and 2.61% in Malta and France respectively. Among the big five above average costs in all markets with the exception of France. Note that French banks have (1) relatively high exposure to fixed rate mortgages and, (2) unlike most other EA lenders, are constrained by the Banque de France on the amount they can charge borrowers.
Transmission mechanism of higher policy rates (147bp, so far): most rapid in Lithuania, Latvia, Estonia, Portugal, and in Italy and Spain among big five – all markets with above average exposure to variable-rate mortgages. Weakest in Malta, Ireland, Greece, and among the big five in France, Germany and the Netherlands. With the exception of Malta, these markets all have relatively high exposures to fixed-rate lending.
Growth (slowed to 3.0% YoY in April 2023, the slowest rate since May 2018): Skewed heavily towards German and French growth dynamics (1.1ppt and 1.0ppt of total 3.0% respectively). Large variations in nominal growth rates from 9.8% and 9.5% in Lithuania and Estonia respectively to -4.0% in Greece and -1.9% in Spain and Ireland. Among the big five, above average growth in France, Germany and the Netherlands, but below average growth in Italy and Spain. In real terms, mortgage growth peaked at 5.0% YoY in December 2020, eight months before the peak in nominal growth. It turned negative in February 2022 and has been negative ever since (-3.7% YoY, April 2023). Only Belgium and Malta are experiencing positive mortgage growth in real terms.
What does this mean?
The EA mortgage market is as an aggregation of heterogeneous, national markets that differ greatly in terms of size, structure, importance, cost, transmission mechanism and growth rates.
The challenge for bankers, investors and analysts alike is to understand these differences and their implications. The far greater challenge for the ECB is to incorporate them all in the design of a “one-size-fits-all” monetary policy. The context, in part, for this week’s ECB press conference on Thursday 15 June 2023.
Is there such a thing as the EA mortgage market?
Market size
Trends in the outstanding stock of EA mortgages (EUR bn) (Source: ECB; CMMP)
The outstanding stock of mortgages across the EA was €5,228bn at the end of April 2023 (see chart above).
Five national markets (the “big five”) dominate in terms of size and account for 85% of the outstanding stock collectively (see chart below) – Germany (€1,574bn, 30% share), France (€1,333bn, 26% share), the Netherlands (€555bn, 11% share), Spain (€505bn, 10% share) and Italy (€426bn, 8% share).
National mortgage markets ranked by size (EUR bn, LHS) and cumulative market share (%, RHS) (Source: ECB; CMMP)
Mortgage types
Twenty year trends in share of variable rate loans in total new mortages (%) (Source: ECB; CMMP)
At the aggregate level, just over three quarters of new mortgages are fixed-rate mortgages, up from 13% in March 2022 (see chart above). The structure varies, however, from over 90% variable rate mortgages in Finland, Lithuania, Estonia and Latvia to less than 10% variable rate mortgages in Slovenia, Slovakia, France, Belgium and Ireland (see chart below).
National mortgage markets ranked by exposure to variable rate lending (% new loans) (Source: ECB; CMMP)
Among the big five markets, the share of variable rate mortgages in new loans ranges from 41% and 39% in Italy and Spain to 20% in the Netherlands, 16% in Germany and only 4% in France. Note also that, in aggregate, the exposure to variable rate mortgages in the EA is currently higher than in the UK (18%).
Exposure to mortgage lending
National mortgage markets ranked by exposure to mortgages (% total loans) (Source: ECB; CMMP)
Mortgages account for 40% of total lending to EA residents at the aggregate level. This exposure ranges from 50% of total loans in Malta and Slovakia to 23% and 25% in Luxembourg and Greece respectively. Among the big five, banks in the Netherlands (48%), Germany (43%) and Spain (41%) have above average exposures to mortgage lending, while banks in France (39%) and, more noticeably, Italy (28%) have lower-than-average exposures.
Composite cost of borrowing for house purchase
National mortgage markets ranked by cost of borrowing for house purchase (%) (Source: ECB; CMMP)
In nominal terms, the CCOB for house purchases ranges from 5.32%, 5.27% and 4.99% in Latvia, Lithuania and Estonia respectively to 2.24% and 2.61% in Malta and France respectively (see chart above). Among the big five markets, the CCOB is above average in Italy (4.15%), Germany (3.89%), the Netherlands (3.62%) and Spain and only below average in France (2.61%).
Note that French banks have (1) relatively high exposure to fixed-rate mortgages and (2), unlike most other EA lenders, are constrained by a limit, set by the Banque de France, on the amount that they can charge for mortgages. In short, they have a lower sensitivity to the positive benefits of rising interest rates.
Note also that the CCOB of borrowing for house purchases remains below the current rates of inflation (HICP) in all of the EA economies except Luxembourg, Cyprus and Belgium.
Pass through of higher policy rates
National mortgage markets ranked by pass through (bp) of higher ECB policy rates (Source: ECB; CMMP)
The composite cost (CCOB) for new loans to EA HHs for house purchase has increased by 147bp since June 2022 to 3.44% in April 2023.
The pass through from policy tightening has been greatest (in nominal terms) in Lithuania (315bp), Latvia (284bp), Estonia (274bp) and Portugal (251bp) and in Italy (197bp) and Spain (179bp) among the big five markets.
The pass though has been weakest in Malta (11bp), Ireland (74bp), Greece (84bp) and in France (126bp), Germany (132bp) and the Netherlands (141bp) among the big five markets.
Change in CCOB since tightening (bp) plotted against current CCOB (% April 2023) (Source: ECB; CMMP)
Growth in mortgage lending
Trend in annual growth rate (% YoY, nominal) of lending to the private sector (Source: ECB; CMMP)
The annual growth rate in EA mortgages slowed to 3.0% YoY in April 2023, down 2.8ppt from the August 2021 peak of 5.8%. Growth has slowed 2.4ppt since tightening began in 2022. April 2023’s growth rate is the slowest rate of growth recorded since May 2018.
Contribution (ppt) of big five and “others” to growth in EA mortgages (% YoY) (Source: ECB, CMMP)
Germany and France have been the main contributors to aggregate growth since 2015. In April 2023, Germany and France contributed 1.1ppt and 1.0ppt to the total YoY growth of 3.0% alone. Netherlands and Italy contributed 0.4ppt and 0.2ppt respectively. The most obvious contrast between the post-2015 recovery in EA mortgage demand and the pre-GFC period is the lack of contribution/negative contribution from Spain for large parts of post-GFC period, reflecting the bursting of the Spanish real estate bubble.
National mortgage markets ranked by nominal growth rate (% YoY) (Source: ECB; CMMP)
Large variations exists in the nominal YoY growth rates at the country level. In April 2023, these ranged from 9.8% and 9.5% in Lithuania and Estonia respectively to -4.0% in Greece and -1.9% in both Spain and Ireland. Among the big five markets, growth was above average in France (4.1%), Germany (3.8%), and the Netherlands (3.6%) but below average in Italy (2.7%) and Spain (-1.9%).
Trends in mortgage growth rates expressed in nominal and real terms (Source: ECB; CMMP)
Inflation also complicates the analysis of EA mortgage dynamic. In real terms, mortgage growth peaked at 5.0% YoY in December 2020, eight months before the peak in nominal growth. It turned negative in February 2022 and has been negative since then. In April 2023, mortgage lending fell -3.7% YoY in real terms.
National mortgage markets ranked by real growth rate (% YoY) (Source: ECB; CMMP)
Conclusion
The EA mortgage market is as an aggregation of heterogeneous, national markets that differ greatly in terms of size, structure, importance, cost, transmission mechanism and growth rates. The challenge for bankers, investors and analysts alike is to understand these differences and their implications. The far greater challenge for the ECB is to incorporate them all in the design of a “one-size-fits-all” monetary policy. The context, in part, for this week’s ECB press conference on Thursday 15 June 2023.
Please note that the summary comments and charts above are abstracts from more detailed analysis that is available separately.
Trends in EM private sector debt ($bn) and debt ratio (% GDP) since the GFC (Source: BIS; CMMP)
The key message
In this fifth post in my “Global Debt Dynamics” series, I consider the hypothesis that the “EM-debt” story has been replaced by the “China-debt” story.
At its simplest, the EM-debt story refers to the sharp increase in the EM share of global private sector credit (PSC) and the narrowing of the gap between the aggregate PSC debt ratios for advanced (DM) and emerging (EM) economies since the global financial crisis (GFC).
The EM share of global PSC has increased sharply from 16% in 2Q08 to 38% in 2Q21. Over the same period, the gap between the PS debt ratios has narrowed from 86ppt to only 8ppt. This represents a remarkable structural shift from DM to EM economies.
Strip out China, however, and the EM share of global PSC is largely unchanged since the GFC. China has accounted for 20ppt of the 22ppt increase in market share described above and currently accounts for almost 70% of total EM PSC alone. For added perspective, China’s outstanding stock of PSC ($37tr) is c.10x and c.14x the outstanding stock in Korea and India respectively, the second and third largest EM PSC markets. Viewed from the narrow perspective of relative size and growth, there is some support for the hypothesis that the China debt story has replaced the EM debt story, or at least overtaken it.
There are two problems with this conclusion however: (1) it relies on an overly narrow view of global debt dynamics; and (2) in truth, there is no such thing as an EM debt story in the first place.
The EM universe includes a group of over 20 economies with very heterogeneous debt dynamics in terms of the level of indebtedness, the rate of excess credit growth and affordability of debt:
For most EM economies, the “potential-growth” story remains in both the NFC and HH sectors
Some of the fastest rates of excess credit growth are occuring in EM economies that already exhibit relatively high levels of indebtedness
Elevated affordability risks in a number of EM economies is of concern given the expected future direction of global rates
While the EM classification remains convenient, it is increasingly less relevant in terms of understanding the impact of debt dynamics on macro policy, investment decisions and financial stability.
Replace the EM debt story with individual EM country debt stories not just the China version.
EM debt dynamics
At its simplest, the so-called, “EM-debt” story refers to the sharp increase in EM’s share of global PSC and the rapid narrowing in the gap between the average PSC debt ratios in advanced (DM) and EM economies since the Global Financial Crisis (GFC).
Trends in private sector debt ($tr) and debt ratio (% GDP) since the GFC (Source: BIS; CMMP)
The outstanding stock of EM PSC has grown from $14tr in 2Q08 to $54tr in 2Q21, a nominal CAGR of 11.5% (see graph above). Over the same period, the outstanding stock of DM PSC has risen from $71tr to $87tr, a nominal CAGR of only 1.5%.
Breakdown of global PSC (% total) since the GFC (Source: BIS; CMMP)
The EM share of global PSC has increased sharply from 16% in 2Q08 to 38% in 2Q21, while the DM share of global debt has fallen from 84% to 62% (see chart above). As discussed in “Global Debt Dynamics –II”, this structural shift from DM to EM is one of the two key structural changes that have taken place in the global PSC market since the GFC (the other being the shift away from HH to NFC debt).
Trends in PSC debt ratios (% GDP) since the GFC (Source: BIS; CMMP)
The gap between the average DM and EM PSC debt ratio (debt % GDP) has also narrowed sharply since the GFC. At the end of 2Q08 the respective PSC debt ratios were 172% GDP and 86% GDP, a gap of 86ppt. At the end of 2Q21, the respective PSC debt ratios were 175% GDP and 167% GDP, a gap of only 8ppt (see chart above).
Trends in share of global PSC since GFC (Source: BIS; CMMP)
Strip out China, however, and the EM share of global PSC is largely unchanged since the GFC (see green line in chart above). China has accounted for 20ppt of the 22ppt increase in the increase in market share described above. As result, China’ share of EM PSC has risen from 36% to 68% over the period (and from 6% to 26% of global PSC).
China’s share of EM debt by category of debt (Source: BIS; CMMP)
China accounts for 64%, 68%, 71% and 61% of total, PSC, NFC and HH debt in EM respectively (see chart above). China’s outstanding stock of PSC ($37tr) is c.10x and c.14x the outstanding stock in Korea and India respectively, the second and third largest EM PSC markets (see chart below).
Relative size of PSC in largest EM PSC markets (Source: BIS; CMMP)
So in terms of relative growth, outstanding stock and relative size there are grounds for accepting the hypothesis that the EM story has been replaced by the China debt story. However, a key theme of CMMP analysis is that debt dynamics are not simply about the size/level of outstanding debt. There are other “chapters” to EM debt story including the levels of indebtedness, the growth rate in debt and the affordability of debt, for example.
EM HH debt ratios plotted against NFC debt ratios (Source: BIS; CMMP)
For most EM economies (as classified by the BIS) the potential “EM-growth” story remains. NFC and HH debt ratios in 16 EM economies remains below the 90% GDP and 85% GDP maximum threshold levels identified by the BIS (see chart above), for example. In contrast, elevated debt levels exist in both sectors in Hong Kong and Korea and in the NFC sector in China, Singapore and Chile.
NFC RGF plotted against NFC debt ratio (Source: BIS; CMMP)
As in DM, some of the fastest rates of excess credit growth are occurring in EM economies that already exhibit relatively high levels of indebtedness (for an explanation of the methodology, see here). In the NFC sector, for example, relatively high levels of excess credit growth have occurred in Hong Kong, Singapore, Korea, Chile and Saudi Arabia (see chart above). Similarly, relative high levels of excess HH credit growth have occurred in relatively indebted HH sectors in Korea, Hong Kong, Thailand, Malaysia and China (see graph below).
HH RGF plotted against HH debt ratio (Source: BIS; CMMP)
Elevated affordability risks in a number of EM economies is of concern given the likely future direction of global rates. Private sector debt ratios are not only high in absolute terms, but they are also above respective LT averages in Hong Kong, Turkey, China, and Brazil. Note in contrast the relatively low levels of affordability risk in CEE, Russia and India (see chart below).
Global DSR (x-axis) and deviations from LT averages (y-axis) (Source: BIS; CMMP)
Conclusion
In truth, there is no such thing as an EM debt story. The EM universe includes a group of economies with very heterogeneous debt dynamics. My financial stability heatmap summarising the debt dynamics of the 10 EM economies that account for over 90% of total EM PSC illustrated this clearly (see below).
Financial stability heatmap – top 10 EM economies (Source: CMMP)
So while the EM classification remains convenient, it is increasingly less relevant in terms of understanding the impact of debt dynamics on macro policy, investment decisions and financial stability.
Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.
Trends in global house prices since the GFC (Source: BIS; CMMP)
The key message
Anyone looking for evidence of COVID-19 “herd immunity” need look no further than global housing markets!
House prices rose 4% globally in 2020 in real terms, the fastest rate of growth since the GFC. Prices rose 7% in advanced economies, compared with a more modest 2% in emerging economies. House price resilience during the pandemic reflects many factors: a recovery in HH incomes thanks to continued policy support; lower borrowing costs; reduced supply as construction activity slowed; temporary tax breaks; and perceptions that housing was/is a relatively safe investment.
The combination of rising prices and an uncertain macro backdrop has kept measures of overvaluation elevated. In the euro area, for example, above average increases in house prices occurred in Luxembourg, Slovakia, Estonia, Portugal, Denmark, Austria, the Netherlands and France. With the exception of Estonia, estimates suggested overvaluation in each of these countries before the start of 2020, notably in Luxembourg, Denmark and Austria. Similarly, the Bank of England indicated unease about the UK housing market recently (1 June 2021) after the Nationwide Building Society said that prices were growing at their fastest pace since 2014.
Current EA housing and lending dynamics reflect Minsky’s hypothesis that, over the course of a long financial cycle, there will be a shift towards riskier and more speculative sectors. The flow of funds towards property and financial asset markets (FIRE-based lending) is increasing at the expense of more productive flows to the real economy (COCO-based lending). FIRE-based lending in the EA hit a new high of €5,905bn in April 2021 and accounts for 52% of total lending with negative implications for leverage, growth, stability and income inequality.
Resilience and risks in global housing
Anyone looking for evidence of COVID-19 “herd immunity” need look no further than global housing markets! House prices rose 4% globally in 2020 (in real terms) according to latest BIS data release, the fastest rate of growth since the GFC. Prices are now 21% higher than their average after the GFC (see chart below).
Real price change in 2020 plotted against real price change since the GFC (Source: BIS; CMMP)
Prices rose 7% in “advanced economies” (especially New Zealand, Canada, Denmark, Portugal, Austria, Germany, US) compared with a more modest 2% in “emerging economies.” The resilience of housing markets reflects many factors: a recovery in HH incomes thanks to continued policy support; lower borrowing costs; reduce supply as construction activity slowed; temporary tax breaks; and the perceptions that housing was/is a relatively safe investment.
EA trends – 2020 price change ploted against valuation at end-2019 (Source: ECB; CMMP)
The key risk here is that the combination of rising prices and an uncertain macro backdrop have kept measures of overvaluation elevated.
In their latest Financial Stability Review, for example, the ECB notes that “house price growth during the pandemic has generally been higher for those countries that were already experiencing pronounced overvaluation prior to the pandemic (see chart above).”
The largest/above average increases in house prices during 2020 in the EA occurred in Luxembourg (17%), Slovakia (16%), Estonia (9%), Portugal (9%), Denmark (9%), Austria (7%), the Netherlands (7%) and France (6%). With the exception of Estonia, ECB estimates suggest that house prices were overvalued in each of these countries before the start of 2020, notably in Luxembourg (39% overvalued, not shown in graph above), Denmark (16% overvalued) and Austria (15% overvalued).
On the 7 June 2021, the BIS will release 4Q20 credit and affordability data which will provide further insights into the risks associated with housing trends in the EA and the rest-of-the-world.
The rise in FIRE-based lending in the euro area (Source: ECB; CMMP)
In recent posts, I have noted an adaptation of Hyman Minsky’s hypothesis that states that over the course of a long financial cycle, there will be a shift towards riskier and more speculative sectors.
Minsky’s theory can be applied to the house price trends described above and to HH lending trends described in previous posts. Minsky’s “shift” is reflected in the decline in bank credit to the real sector (COCO-based credit) and an increase in funds flowing towards property and financial asset markets (FIRE-based credit).
FIRE-based lending in the EA hit a new high of €5,905bn in April 2021 and accounts for 52% of total lending with negative implications for leverage, growth, stability and income inequality.
Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.
Are the risks associated with excess growth re-emerging? Excess credit growth versus penetration rates (Source: BIS; CMMP)
The key message
Risks associated with “excess credit growth”, which had been declining in the pre-Covid period, have re-emerged during the pandemic.
Some of the highest rates of excess credit growth are currently occurring in economies where debt levels exceed maximum threshold levels (Singapore, France, Hong Kong, South Korea, Japan, Canada).
Affordability risks are also increasing within and outside (Sweden, Switzerland, Norway) this sub-set despite the low interest rate environment.
Risks are more elevated in the corporate (NFC) sector than in the household (HH) sector but are not unique to either the developed market (DM) or emerging market (EM) worlds – one more reason to question the relevance of the current DM v EM distinction
Much of the debate relating to global debt focuses exclusively on the level of debt and, to a lesser extent, on the debt ratio (debt as a percentage of GDP). This analysis highlights how the addition of growth and affordability factors provides a more complete picture of the risks associated with current trends and their investment implications.
Introduction
As noted above, much of the recent debate about global debt has been restricted to its level in absolute terms or as a percentage of GDP. The addition of other factors – the rate of growth in debt, its affordability and, in the case of many EMs, its structure – provides a more complete picture, however.
In this post, I add condsideration of the rate of growth in global debt to my previous analysis in “D…E…B…T, Part II.” The approach is based on the simple relative growth factor (RGF) concept which I have used since the early 1990s as a first step in analysing the sustainability of debt dynamics. I also link both to the affordability of debt as measured by debt service ratios (DSRs).
In short, this approach compares the rate of “excess credit growth” with the level of debt penetration in a given economy. The three-year CAGR in debt is compared with the three-year CAGR in nominal GDP to derive a RGF. This is then compared with the level of debt expressed as a percentage of GDP (the debt ratio).
The concept is simple – one would expect relative high levels of excess credit growth in economies where the level of leverage is relatively low and vice versa. Conversely, red flags are raised when excess credit growth continues in economies that exhibit relatively high levels of leverage or when excess credit growth continues beyond previously observed levels.
The key trends
Rolling private sector RGF for all BIS reporting, developed and emerging economies (Source: BIS; CMMP)
In the pre-COVID period, the risks associated with excess credit growth had been declining in developed (DM) and emerging (EM) economies (see chart above illustrating rolling RGF trends). In response to the pandemic, however, credit demand has risen while nominal GDP has fallen sharply. As a result, the RGF (as at the end of 3Q20) for all economies, DM and EM have risen to 3%, 2% and 4% respectively. As can be seen, these levels are elevated but remain below those seen in previous cycles during the past 15 years.
Private sector credit snapshots
Excess PS credit growth versus PS debt ratios as at end 3Q20 (Source: BIS; CMMP)Top ten ranking of private sector RGF by country (Source: BIS; CMMP)
Importantly, out of the top-ten economies experiencing the highest rates of excess private sector credit, six have private sector debt ratios higher than the threshold levels above which debt is considered a constraint to future growth – Singapore, France, Hong Kong, South Korea, Japan and Canada. In the graph above, and in similar ones below, the orange bar indicates where debt ratios exceed the threshold level.
Excess PS credit growth versus PS debt ratios as at end 3Q20 in LATEMEA (Source: BIS; CMMP)
Argentina and Chile have the highest private sector RGFs among the sample of LATEMEA economies. The associated risks are higher in the case of Chile than in Argentina given the two economies debt ratios of 169% GDP and 24% GDP respectively. As highlighted below, the risks in Chile relate primarily to excess growth in the NFC sector.
DSR and deviations from 10-year averages (Source: BIS; CMMP)
Within this subset, the debt service ratios in absolute terms and in relation to respective 10-year averages are also relatively high in France, Hong Kong, South Korea, Japan and Canada despite the low interest rate environment. Outside this subset, affordability risks are relatively high in Sweden, Switzerland and Norway where DSR’s are relatively high in absolute terms and in relation to each economy’s history.
NFC credit snapshots
Excess NFC credit growth versus NFC debt ratios as at end 3Q20 (Source: BIS; CMMP)Top ten ranking of NFC RGF by country (Source: BIS; CMMP)
Similarly, out of the top-ten economies experiencing the highest rates of excess NFC credit, seven have NFC debt ratios above the threshold level (90% GDP) – Singapore, Chile, France, Canada, Japan, South Korea and Switzerland.
DSR and deviations from 10-year averages (Source: BIS; CMMP)
Within this second subset, the debt service ratios in absolute terms and in relation to respective 10-year averages are relatively high in France, Canada, Japan and South Korea. Despite lower rates of excess NFC credit growth affordability risks are also relatively high in Sweden, Norway and the US. (Note that the availability of sector DSRs is more restricted than overall private sector DSRs).
HH credit snapshots
Excess HH credit growth versus HH debt ratios as at end 3Q20 (Source: BIS; CMMP)Top ten ranking of HH RGF by country (Source: BIS; CMMP)
In contrast, out of the top-ten economies experiencing the highest rates of excess HH credit, only two have HH debt ratios above the threshold level – Hong Kong and Singapore. This is not surprising given that HH debt ratios are lower than NFC debt levels in general. Of the 42 BIS reporting countries, 11 have HH debt ratios above the 85% GDP HH threshold level whereas 20 have NFC debt ratios above the 90% GDP NFC threshold level.
Rolling HH RGFs for China and Russia (Source: BIS; CMMP)
That said, experience suggests that the current levels of excess HH credit growth in China and Russia indicate elevated risks, especially in the former economy. In “Too much, too soon?“, posted in November 2019, I highlighted the PBOC’s concerns over HH-sector debt risks – “the debt risks in the HH sector and some low income HHs in some regions are relatively prominent and should be paid attention to.” (PBOC, Financial Stability Report 2019). Excess credit growth remains a key feature nonetheless.
DSR and deviations from 10-year averages (Source: BIS; CMMP)
Within this third subset, the debt service ratio in absolute terms and in relation to respective 10-year averages is relatively high in South Korea. Again, despite lower rates of excess HH credit growth, affordability risks are also relatively high in Sweden and Norway.
Conclusion
This summary post extends the analysis of the level of global debt and debt ratios to include an assessment of the rate of growth in debt and its affordability. Together, these factors provide a more complete picture of the sustainability of current debt trends.
Risks associated with excess credit growth are re-emerging and will be a feature of the post-COVID environment going forward. The two key risks here are: (1) some of the highest rates of excess credit growth are currently occurring in economies where debt levels exceed threshold levels; and (2) affordability risks are increasing within (and outside) this sub-set despite the low interest rate environment.
To some extent, little of this is new news – I have been flagging the same risks in an Asia context for some time – and the implications are the same. Despite recent market moves, the secular support for rates remaining “lower-for-longer” remains, albeit with more elevated sustainability risks in the NFC sector.
Revisiting the level and structure of global debt six months on
The key chart
What are the implications of new highs in global debt and debt ratios? (Source: BIS; CMMP)
The key message
Global debt hit new highs in absolute terms ($211tr) and as a percentage of GDP (277%) at the end of 3Q20, driven largely by government ($79tr) and NFC debt ($81tr).
Public sector and NFC debt ratios both hit new highs above the maximum threshold level that the BIS considers detrimental to future growth.
These trends provide on-going support for the “lower-for-longer” narrative but also raise concerns about sustainability risks in the NFC sector.
The US and China account for nearly 50% of global debt alone and more than 75% with Japan, France, the UK, Germany, Canada and Italy – but only Japan and France are included in the top-ten most indebted global economies.
The post-GFC period of private sector deleveraging/debt stability in advanced economies has ended as the private sector debt ratio increased to 179% GDP.
China’s accumulation of debt has eclipsed the “EM catch-up story”. Chinese debt now accounts for just under 70% of EM debt and EM x China’s share of global debt has remained unchanged over the past decade.
The traditional distinction between advanced/developed markets and emerging markets is increasingly irrelevant/unhelpful, especially when analysing Asian debt dynamics.
New terms of reference are required for analysing global debt trends that distinguish between economies with excess HH and/or corporate debt and the rest of the world. From this more appropriate foundation, further analysis can be made of the growth and affordability of debt…
D…E…B…T, Part II
Breakdown of global debt and trend in debt ratio since 2008 (Source: BIS; CMMP)
Global debt hit new highs in absolute terms and as a percentage of GDP at the end of 3Q20, driven largely by public sector debt and NFC debt. According to the BIS, total debt rose from $193tr at the end of 1Q20 to a new high of $211tr. Within this:
Government, NFC and HH debt all hit new absolute highs of $79tr, $81tr and $51tr respectively
The global debt ratio increased from 246% GDP in 1Q20 to a new high of 278% GDP
The public sector debt ratio increased from 88% GDP to 104% GDP and the NFC debt ratio increased from 96% GDP to 107% GDP over the same period. In both cases, the debt ratio was a new high and above the maximum threshold level of 90% above which the BIS considers the level of debt to become a constraint on future growth
The HH debt ratio also increased from 61% GDP to 67% but remains below its historic peak of 69% (3Q09) and the respective BIS threshold level of 85% GDP.
These trends provide on-going support for the “lower-for-longer” narrative but also raise concerns about sustainability especially in the NFC sector.
3Q20 ranking of BIS reporting economies by total debt and cumulative market share (Source: BIS; CMMP)
The US and China account for nearly 50% of global debt, but neither is ranked in the top-15 most indebted economies. At the end of 3Q20, total debt reached $61tr (29% global debt) in the US and $42tr in China (20% global debt). In absolute terms, these two economies are followed by Japan $21tr, France $10tr, UK $8tr, Germany $8tr, Canada $6tr and Italy $tr. In other words, the US and China account for almost a half of global debt and together with the other six economies account for over three-quarters of global debt. Note, however, that only two of these eight economies rank among the top-ten most indebted global economies (% GDP).
3Q20 ranking of BIS reporting economies by total debt as % GDP (Source: BIS; CMMP)
The post-GFC period of private sector deleveraging/debt stability in advanced economies has ended as the private sector debt ratio rose to 179% GDP, close to its all-time-high. Following the GFC, the private sector debt ratio in advanced economies had fallen from a peak of 181% GDP in 3Q09 to 151% in 1Q15. It had then stabilised at around the 160% of GDP level.
Private sector debt in advanced economies in absolute terms and as % GDP (Source: BIS; CMMP)
As discussed in “Are we there yet?”, this had direct implications for the duration and amplitude of money, credit and business cycles, inflation, policy options and the level of global interest rates. In subsequent posts, I will examine the implications of these recent trends on the sustainability and affordability of private sector debt in advanced economies.
Trends in China’s private sector debt and share of EM private sector debt (Source: BIS; CMMP)
China’s accumulation of debt has eclipsed the “EM catch-up story”. Fifteen years ago, China’s debt was just under $3tr and accounted for 35% of total EM debt. At the end of 3Q20, China’s debt had increased to $33tr to account for 67% of total EM debt. The so-called EM catch-up story is in effect, the story of China’s debt accumulation. Excluding China, EM’s share of global debt in unchanged (12%) over the past decade.
China and EMx China’s share of global debt (Source: BIS; CMMP)
The traditional distinction between advanced/developed markets and emerging markets is increasingly irrelevant/unhelpful, especially when analysing Asian debt dynamics. The BIS classifies Asian reporting countries into two categories: three “advanced” economies (Japan, Australia and NZ) and eight emerging economies (China, Hong Kong, India, Indonesia, Korea, Malaysia, Singapore and Thailand).
Asian NFC and HH debt ratios (Source: BIS; CMMP)
The classification of Japan, Australia and New Zealand as advanced economies is logical but masks different exposures to NFC (Japan) and HH (Australian and New Zealand) debt dynamics.
The remaining grouping is more troublesome as it ignores the wide variations in market structure, growth opportunities, risks and secular challenges. I prefer to consider China, Korea, Hong Kong and Singapore as unique markets. China is unique in terms of the level, structure and drivers of debt and in terms of the PBOC’s policy responses. Korea and Hong Kong stand out for having NFC and HH debt ratios that exceed BIS maximum thresholds. Hong Kong and Singapore are distinguished by their roles as regional financial centres but have different HH debt dynamics. Malaysia and Thailand can be considered intermediate markets which leaves India and Indonesia as genuine emerging markets among Asian reporting countries (see “Sustainable debt dynamics – Asia private sector credit”).
Global NFC and HH debt ratios (Source: BIS; CMMP)
New terms of reference are required for analysing global debt trends that distinguish between economies with excess HH and/or corporate debt and the rest of the world. In this case, excess refers to levels that are above the BIS thresholds. Among the BIS reporting economies (and excluding Luxembourg) there are:
Eight economies with excess HH and NFC debt levels: Hong Kong, Sweden, the Netherlands, Norway, Denmark, Switzerland, Canada and South Korea
Eleven economies with excess NFC debt levels: Ireland, France, China, Belgium, Singapore, Chile, Finland, Japan, Spain, Portugal, and Austria
Three economies with excess HH debt levels: Australia, New Zealand, the UK
The RoW with HH and NFC debt levels below the BIS thresholds
These classifications provide a more appropriate foundation for further analysis of the other, key features of global debt – its rate of growth and its affordability. These will be addressed in subsequent posts.
Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.
Time for new terms of reference when analysing global debt levels (Source: BIS; CMMP analysis)
The key message
Last week’s data release from the BIS provides five important insights into the “macro-state-of play” at the end of 1Q20 – the point at which the Covid-19 pandemic intensified globally:
Insight #1: the pandemic coincided with a new peak in global debt ($192tr), with the global debt ratio coming within 0.2ppt of its previous 3Q16 and 1Q18 peaks. Up to this point, the split between private ($122tr) and public ($69tr) was broadly unchanged at 64% and 36% respectively (n.b. I have deal with the subsequent impact of global policy responses on public sector debt levels in previous posts).
Insight #2: the long-term trend of passive deleveraging by the private sector in advanced economies continues with direct implications for: the duration and amplitude of money, credit and business cycles; inflation; policy options; and the level of global interest rates.
Insight #3: China’s catch-up story has replaced the wider emerging market (EM) catch up story. EM debt accounts for 36% of global debt but with China accounting for 68% of EM debt now compared with only 30% twenty years ago – strip out China and EM debt is now a slightly smaller share of global debt than it was five years ago.
Insight #4: the traditional distinction between emerging and developed/advanced economies is less relevant and/or helpful, especially when analysing Asia debt dynamics.
Insight #5: it is more helpful to begin by distinguishing between economies with excess household and/or corporate debt and the RoW and then consider the rate of growth and affordability of debt in that context. More to follow on both…
In the meantime, the key message is the importance of distinguishing between the “event-driven” effects of the Covid pandemic and longer-term “structural-effects” associated with the level, growth and affordability of different types of debt.
Five key charts
Insight #1: The pandemic coincided with a new peak in global debt (Source: BIS; CMMP analysis)Insight #2: the LT trend of passive deleveraging by the private sector in advanced economies continues (Source: BIS; CMMP analysis)Insight #3: China increasingly dominates the “EM catch-up” story (Source: BIS; CMMP analysis)Insight #4: traditional distinctions between EM and advanced economies are less relevant, especially when analysing Asian debt dynamics (Source: BIS; CMMP analysis)Insight #5: the key chart repeated – new terms of reference are needed as the starting point for analysing global debt (Source: BIS; CMMP analysis)
Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.
In “August snippets – Part 1”, I highlighted the importance of disciplined investment frameworks. In this second snippet, I revisit the foundations of my CMMP Analysis framework. I start by describing how I combine three different time perspectives into a consistent investment thesis (“three pillars”). I then explain how the core banking services (payments, credit and savings) link different economic agents over time to form an important fourth pillar – financial sector balances. Finally, I present examples of how these four pillars combine to deliver deep insights into policy options and responses.
The central theme is my belief that the true value in analysing developments in the financial sector lies less in considering investments in banks but more in understanding the implications of the relationship between banks and the wider economy for corporate strategy, investment decisions and asset allocation.
Three perspectives – one strategy
As an investor, I combine three different time perspectives into a single investment strategy
My investment outlook at any point in time reflects the dynamic between them
My conviction reflects the extent to which they are aligned
Pillar 1: Long-term investment perspective
Example chart 1: growth trends in PSC illustrate how global finance is shifting East and towards emerging markets ($bn) (Source: BIS; CMMP analysis )
My LT investment perspective focuses on the key structural drivers that extend across multiple business cycles. Given my macro and monetary economic background, I begin by analysing the level, growth, affordability and structure of debt. These four features of global debt have direct implications for: economic growth; the supply and demand for credit; money, credit and business cycles; policy options; investment risks and asset allocation. My perspective here reflects my early professional career in Asia and experience of Japan’s balance sheet recession. The three central themes are (1) global finance continues to shift East and towards emerging markets, (2) high, “excess HH growth rates” in India and China remain a key sustainability risk, and (3) progress towards dealing with the debt overhang in Europe remains gradual and incomplete. The following four links provide examples of LT investment perspectives:
Example chart 2:China’s HH debt ratio continued to rise sharply in 1Q20 – too much, too soon? (Source: National Bureau of Statistics; CMMP analysis)
Pillar 2 – Medium-term investment perspective
Example chart 3: growth rates in M1 and private sector credit demonstrate robust relationships with the business cycle through time and have proved more reliable indicators of recessions risks than the shape of the yield curve (Source: ECB; CMMP analysis)
My MT investment perspective centres on: analysing money, credit and business cycles; the impact of bank behaviour on the wider economy; and the impact of macro and monetary dynamics on bank sector profitability. Growth rates in narrow money (M1) and private sector credit demonstrate robust relationships with the business cycle through time. My interest is in how these relationships can assist investment timing and asset allocation. My investment experience in Europe shapes my MT perspective, supported by detailed analysis provided by the ECB. A central MT theme here is the fact that monetary developments: (1) have proved a more reliable indicator of recession risks than the shape of the yield curve; and (2) provide important insights into the impact, drivers and timing of the Covid-19 pandemic on developed market economies. The following four links provide examples of my analysis of MT investment perspectives:
Example chart 4: headling figures mask a more nuanced message from monthly flow data (Source: ECB; CMMP analysis)
Pillar 3: Short-term investment perspective
Example chart 5: banks played catch up from May 2020, but what kind of rally was this and was it sustainable? (Source: FT; CMMP analysis)
My ST investment perspective focuses on trends in the key macro building blocks that affect industry value drivers, company earnings and profitability at different stages within specific cycles. This perspective is influences by my experience of running proprietary equity investments within a fixed-income environment at JP Morgan. This led me to reappraise the impact of different drivers of equity market returns. I was able to demonstrate the “proof of concept” of this approach when I returned to the sell-side in 2017 as Global Head of Banks Equity Research at HSBC, most notably when challenging the consensus investor positioning towards European banks in 3Q17. A central ST theme is the importance of macro-building blocks in determining sector profitability and investment returns. The following four links provide examples of ST investment perspectives:
Example chart 6: why it was correct to question the conviction behind the SX7E rally during 2Q20 (Source: FT, CMMP analysis)
Pillar 4 – Financial Sector Balances
Example chart 7: Financial sector balances (and MMT!) can be understood easily by starting with the core services provided by banks to HHs and NFCs (Source: Bank of England; CMMP analysis)
In January 2020, I presented a consistent, “balance sheet framework” for understanding the relationship between the financial sector and the wider economy and applied it to the UK. I chose the UK deliberately to reflect the relatively large size of the UK financial system and the relatively volatile nature of its relationship with the economy. I extended this analysis to the euro area later. I began by focusing on the core services provided by the financial system (payments, credit and savings), how these services produce a stock of financial balance sheets that link different economic agents over time, and how these balance sheets form the foundation of a highly quantitative, objective and logical analytical framework. Central themes here were the large and persistent sector imbalances in the UK, why the HH sector in the UK was poised to disappoint and why a major policy review was required in the euro area even before the full impact of the COVID-19 pandemic was felt. The following four links provide examples of FSB analysis:
Example chart 8: Pre-Covid, the UK faced large and persistent sector imbalances and was increaingly reliant on the RoW as a net lender (4Q sum, % GDP) (Source: ONS; CMMP analysis)
Policy analysis
Example chart 9: “Fuelling the FIRE” – split in EA lending over past twenty years between productive (COCO) and less productive (FIRE) based lending (% total loans) (Source: ECB; CMMP analysis)
These four pillars provide a solid foundation for analysing macroeconomic policy options and choices. Since September 2019, I have applied them to identifying the hidden risks in QE, to arguing why the EA was trapped by its debt overhang and out-dated policy rules, and to assessing the policy responses to the COVID-19 pandemic. Central themes have included: (1) the hidden risk that QE is fuelling the growth in FIRE-based lending with negative implications for leverage, growth, stability and income inequality; (2) why the gradual and incomplete progress towards dealing with Europe’s debt overhang matters; (3) why Madame Lagarde was correct to argue that the appropriate and required response to the current growth shock “should be fiscal, first and foremost”; and (4) how three myths from the past posed a threat to the future of the European project. The following four links provide examples of policy analysis:
Example chart 10: failing the “common sense test”. What was the point of running tight fiscal policies when the private sector was running persistent financial surpluses > 3% GDP (Source: ECB; CMMP analysis)
Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately
Appropriate and necessary responses cannot hide on-going vulnerabilities
The key chart
Government debt ratios are expected to increase to new highs and by more than in response to the GFC- breakdown by region in percentage points for 2020 Source: IMF; CMMP analysis
Policy makers have introduced extraordinary fiscal and monetary policy measure in response to the crisis that have, in many cases, exceeded the measures introduced in the aftermatch of the GFC. These measures have been appropriate and necessary but cannot hide on-going regional and country vulnerabilities. Despite relatively high debt levels, advanced economies are positioned better than emerging and LIDC economies thanks to their ability to borrow at historically low rates that are likely to remain even after Covid-shutdowns end.
The EA policy response has been impressive in scale but assymetric in delivery and risk. Government debt levels across the EA are forecast to increase by between 4ppt and 24ppt taking the aggregate government debt ratio above 100% GDP. A major complicating factor here, is that the countries with the weakest economies, which includes those that have been hit hardest by the virus, have limited fiscal headroom to do “whatever it takes” to stimulate their economies. The sustainability of government debt levels in these economies is at risk of a more severe and prolonged downturn. The enduring myth that this is “the hour of national economic policy” means that this risk cannot be fully discounted. While the balance of power is shifting towards a common-European solution, execution risks remain.
Investment returns, including the impact of country and sector effects, will be driven by how this debate concludes as will the future of the entire European project.
Responses and vulnerabilities
The level, growth, affordability and structure of debt are key drivers of LT global investment cycles with direct implications for: economic growth; the supply and demand for credit; money, credit and business cycles; policy options; investment risks and asset allocation.
Global debt levels and debt ratios were already at, or close to, all-time highs when Covid-19 hit Source: BIS; Haver; CMMP analysis
Global debt levels and debt ratios were at all time highs (levels), or very close to them (ratios), when the Covid-19 pandemic hit global economies. At the end of 2019, global debt totalled $191trillion of which $122trillion (64%) was private sector debt and $69trillion (36%) was public sector debt. Private sector debt included $57trillion (46%) of debt from advanced economies excluding the euro area (EA), $23trillion (18%) of EA debt, $15trillion (12%) of debt from emerging economies excluding China and $29trillion (24%) of Chinese debt.
“Global debt is shifting east” – trends and breakdown of private sector debt 1999-2019 ($billions) Source: BIS; Haver; CMMP analysis
The breakdown of global debt is largely unchanged since previous analysis. The total debt ratio (debt as a % of GDP) was 243% at the end of 2019, very close to its 3Q16 high of 245% GDP. Similarly, the global PSC debt ratio of 156% was also very close to its 3Q18 high of 159% of GDP. Total EM and Chinese debt ratios both hit new highs of 194% GDP and 259% of GDP respectively.
Trends in global and EA total debt and PSC debt ratios since 2004 – develeraging in the EA began later and has been more gradual than in other advanced economies Sourrce: BIS; Haver; CMMP analysis
The exception here was the euro area (EA) which remained, “trapped by its debt overhang and out-dated policy rules.” EA total debt and private sector debt ratios both peaked in 3Q15 at 281% and 172% respectively. At the end of 2019 these ratios had fallen to 262% and 165% respectively but remained above the respective global averages of 245% and 156%. As detailed in “Are we there yet?”, high debt levels help to explain why money, credit and business cycles in the EA are significantly weaker than in past cycles, why inflation remains well below target, and why rates have stayed lower for longer than many expected. In spite of this, the collective pre-crisis fiscal policy of the EA nations was (1) about as tight as any period in the past twenty years and (2) was so at a time when the private sector was running persistent net financial surpluses (largely above 3% GDP) since the GFC. A policy reboot in the EA was overdue even before the pandemic hit.
Covid-19 elevated the need for fiscal policy action to unprecedented levels (global budget deficit as a percentage of GDP, broken down by region) Source: IMF; CMMP analysis
Policy makers have introduced extraordinary fiscal and monetary policy measures in response to the crisis that have, in many cases, exceeded the measures introduced in the aftermath of the GFC. IMF forecasts suggest that the aggregate, global fiscal deficit will total -6.5% of GDP in 2020e versus -4.9% in 2009. The US will be the main driver (-2.37% GDP 2020e versus -1.63% 2009), followed by the EA (-1.01% GDP versus -0.85% GDP), China (-1.0% GDP versus –0.15%), emerging economies (-0.65% GDP versus -1.09% GDP) and the RoW (-1.17% GDP versus -1.20% GDP).
Global debt ratios expected to hit new highs (% GDP) in 2020e Source: IMF; CMMP analysis
As a result, government debt ratios are expected to reach new highs in 2020e of 96% of GDP a rise of 13ppt over 2019. Advanced economies’ government debt is expected to reach 122% GDP versus 105% in 2019 and 92% in 2009. Emerging markets’ government debt is expected to reach 62% GDP versus 53% in 2019 and 39% in 2009. LIDC government debt is expected to reach 47% GDP versus 43% in 2019 and 27% in 2009.
EM and LIDC debt levels remain relatively low in comparison with advanced economies, but are growing rapidly in contrast to more stable trends in advanced economies Source: IMF; CMMP analysis
While these responses have been necessary and appropriate, they have also exposed underlying vulnerabilities relating to the starting position of individual regions and countries with the advanced world being having greater reslience than emerging and LIDC economies (IMF classifications). The effectiveness of fiscal responses is a function of the level of debt, the cost of servicing that debt, economic growth and inflation. While debt levels in emerging and LIDC ecomomies remain relatively low in comparision with advanced economies they have continued to grow rapidly in contrast to the more stable trends in advanced economies (at least up until 2020).
LIDC borrowing costs have risen sharply and have become more volatile (interest expense to tax revenue) Source: IMF; CMMP analysis
Governments in advanced economies are able to borrow at historically low rates and these rates are forecast to remain low for a long period even after the Covid-induced shutdowns end (IMF, Global Financial Stability Review, April 2020). In contrast, for many frontier and emerging markets (and, at times, some advanced economies), borrowing costs have risen sharply and have become more volatile since the coronavirus began spreading globally (IMF, Fiscal Monitor, April 2020). These contrasting trends are illustrated in the graph above which shows IMF forecasts of LIDC interest to tax revenue ratios increasing from 20% in 2019 to 33% in 2020e. This compares with a ratio of 12% in 2009 and the current ratio of 10% for advanced economies (which is largely unchanged since 2009 despite the increase in government debt levels).
Trends in EA budget deficits (% GDP) – the EA policy response has been impressive in scale Source: European Commission; Haver; CMMP analysis
The EA policy response has been impressive in scale but assymetric in delivery and risk. All member states have introduced fiscal measures aimed at supporting health services, replacing lost incomes and protecting corporate sectors. Measures have included tax breaks, public investments and fiscal backstops including public guarantees or credit lines. According to European Commission forecast, the 2020e budget deficit for the EA will total -8.5% of GDP but will vary widely from between -4.8% in Luxembourg to -11.1% in Italy. The ECB notes that, while this projected headline is signficantly larger than during the GFC, it is comparable to the relative decline in GDP growth.
Debt levels across the EA are forecast to increase by between 4ppt (Luxembourg) and 24ppt (Italy), taking the aggregate EA government debt ratio to 103% GDP in 2020e. In its May 2020 Financial Stability Review, the ECB also notes that a number of countries, including Italy, Spain, France, Belgium and Portugal, “face substantial debt repayments needs over the next two years”. The key point here is that while current fiscal measures are important in terms of mitigating against the cost of the downturn and hence providing some defence against debt sustainability concerns, a worse-than-expected recession would give rise to debt sustainability risks in the medium term.
“Limited headroom” – forecast changes in government debt to GDP ratios plotted against 2019 actual debt to GDP ratios Source: European Commission; Haver; CMMP analysis
A major complicating factor here is that the countries with the weakest economies, which includes those that have been hit hardest by Covid-19, have limited fiscal headroom to do whatever it takes to stimulate their economies. The largest percentage point increased in government debt ratios are forecast to occur in Italy (24ppt), Greece (20ppt), Spain (20ppt) and France (18ppt) – compared with an increase of 17ppt for the EA as a whole – economies that ended 2019 with above average government debt to GDP ratios (135%, 177%, 95% and 98% GDP respectively).
Differences in funding costs for different EA economies versus Germany (spread in respective 10Y bond yields in ppt, 26 May 2020) Source: Haver; CMMP analysis
The sustainability of government debt levels in already highly indebted EA countries would be put at risk by a more severe and prolonged economic downturn. Funding costs are already higher in Greece (2.1ppt), Italy (2.0ppt), Spain (1.2ppt) and Portugal (1.1ppt) than in Germany based on current 10Y bond yields and more volatile – see graph of the spread between Italian and German 10Y bond yields below.
The spread between Italian and German 10Y bond yields continues to be volatile, highlighting the on-going debt sustainability risks (spread in ppt) Source: Haver; CMMP analysis
The enduring myth that this is “the hour of national economic policy” means that these risks cannot be discounted. The May 2020 Bundesbank Monthly Report states, for example, that, “fiscal policy is in a position to make an essential contribution to resolving the COVID19 crisis. [But] This is primarily a national task.” This view is also supported by the so-called “frugal four” ie, the Netherlands, Austria, Denmark and Sweden who have been opposed to various “common solutions”, most recently the EC proposal to issue joint debt to fund grants to those countries hit hardest by the crisis.
The EC is supported, however, by the ECB. In a recent interview, Christine Lagarde, the President of the ECB, argues that, “The solution, therefore, is a European programme of rapid and robust fiscal stimulus to restore symmetry between the countries when they exit from the crisis. In other words, more help must be given to those countries that need it most. It is in the interests of all countries to provide such collective support.”
The balance of power is shifting towards a common-European solution recently but execution risks remain. As I write this post (27 May 2020), Ursual von der Leyen, the EC President, has announced plans to borrow €750bn to be distributed partly as grants (€500bn) to hard-pressed member states – the “Next Generation EU” fund. Added to her other plans, this would bring the total EA recovery effort to €1.85trilion.
The scale of this intervention/borrowing is unprecedented and includes plans to establish a yield curve of debt issuance with maturities out to 30 years. Repayments would not start until 2028 and would be completed by 2058. France’s President Macron was among EA leaders who quickly welcomed this proposal and pressure is mounting on the so-called “frugal four” countries – Austria, Denmark, the Netherlands and Sweden – to soften their opposiion to the use of borrowed money for grants.
Investment returns, including the impact of country and sector effects, will be driven to a large extent by how this debate concludes, as will the future of the entire European project.
Please note that the summary comments above are extracts from more detailed analysis that is available separately
