How exposed are banking sectors to elevated private sector credit risks?
The key chart
Trends in selected bank credit ratios (% GDP) (Source: BIS; CMMP)
The key message
How exposed are banking sectors to elevated private sector debt risks in Sweden, France, Korea, China and Canada?
Recall that these five economies have private sector debt ratios that exceed the “peak-bubble” level seen in Japan in 4Q94 and debt service ratios that are not only high in absolute terms but are also elevated in relation to their respective 10-year, average affordability levels. Twin warning signs.
The banking sectors in China and Korea have the highest exposures to elevated private sector debt risks among this sample (see key chart above):
China: bank credit accounts for 84% of total private sector credit and the bank credit ratio of 184% GDP exceeds the peak-Spanish bank credit ratio of 168% GDP;
Korea: bank credit accounts for 73% of total private sector credit. The bank credit ratio of 161% GDP is slightly below the peak-Spain level but well above the peak-Japan level of 112%.
Selected private sector credit ratios (% GDP) broken down by bank and non-bank credit (Source: BIS; CMMP)
In contrast, risks in Sweden, France and Canada are shared more equally between banks and investors (see chart above). Bank sector credit accounts for 51%, 50% and 49% of total private sector credit in Sweden, Canada and France respectively (reflecting the greater development of alternative sources of credit in advanced economies).
This does not mean that banks are not exposed, however. The bank credit ratio in Sweden is 138% GDP, above the peak-Japan level. In France and Canada these ratios are the same or slightly below the peak-Japan level (112% GDP and 109% GDP respectively).
In short, risks remain real and elevated. In a world, that sees public sector debt as a problem but largely ignores private sector debt, this matters, or at least it should do…
Please note that the comments and charts above are abstracts from more detailed research 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
The central focus remains on the shift in risk to the Chinese and Indian HH sectors (trends in relative growth factors for the HH and NFC sectors 2014-2019) Source: BIS; Haver; CMMP analysis
The key messages
As the COVID-19 pandemic hit Asia, the risks associated with the level, growth and affordability of debt varied considerably across the region.
The divergence in debt levels in Asia is well known – in relation to BIS “threshold levels”, Korea has relatively high levels of HH and NFC debt, Australia and New Zealand relatively high levels of HH debt, and Hong Kong, China, Singapore and Japan have relatively high levels of NFC debt.
The level of debt is only one part of the story, however, and the risks involved are understood better, when the level of debt is compared to its growth rate. For EM as a whole, the risks associated with “excess credit growth” increased in 4Q19, but remained much lower than in previous cycles. The striking feature in Asia is that relatively high excess growth risks are concentrated in economies where debt levels are already relatively high (Hong Kong, Korea and, to a lesser extent Singapore).
Across EM, excess growth risks have shifted from the NFC to the HH sector. In China, Hong Kong and India, the CAGR in HH credit has exceeded the CAGR in nominal GDP by 6ppt over the past three years. In 1Q20, China’s HH credit growth has slowed in absolute terms but has outstripped nominal GDP growth resulting in a further increase in the HH debt ratio from 54% in 4Q19 to 62% in 1Q20. Indian HH debt, largely housing finance, also continued to grow strongly in 1Q20 but slowed more clearly in April 2020.
Finally, the risks associated with the affordability of debt are elevated in Hong Kong and China where debt service ratios are high in absolute terms and in relation to their historic LT trends.
Asia remains a very heterogeneous region in terms of debt dynamics and associated risks, but the key central focus remains on the Chinese and Indian HH sectors.
Please note that the summary comments above are extracts from more detailed analysis that is available separately
The other key charts
The divergence in debt levels across Asia is well known, as are the risks associated with excess HH and NFC debt levels (red lines indicate BIS “threshold levels”) Source: BIS; Haver; CMMP analysisExcess growth risks have increased but remain much lower than in previous cycles (trends in EM 3-year RGFs since 2002) Source: BIS; Haver; CMMP analysisThe striking feature in Asia – high excess growth rates are concentrated in economies where debt levels are already relatively high (3-year RGF analysis) Source: BIS; Haver; CMMP analysisDivergent trends in RGFs in China, Hong Kong, Korea and Singapore Source: BIS; Haver; CMMP analysisExcess growth risks have shifted from the NFC to the HH sector across EM Source: BIS; Haver; CMMP analysisChina, Hong Kong and India exhibit the highest excess growth risks in the HH sector (4Q19) Source: BIS; Haver; CMMP analysisChina’s HH debt ratio continues to rise sharply in 1Q20 Source: National Bureau of Statistics; Haver; CMMP analysisIndian HH credit growth outstripping growth in wider non-food credit (YoY growth in real terms) Source: Haver; CMMP analysisAffordability risks concentrated in Hong Kong and China – DSRs high in absolute terms (x-axis) and in relation to LT trends (y-axis) Source: BIS; Haver; CMMP analysis
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
Global finance is shifting East but are current Asian PSC debt dynamics sustainable?
The key chart
Figure 1: A striking feature in Asia is that the highest levels of “excess credit growth” (3-year RGF 1Q19) have occured in economies where debt ratios are already high Source: BIS; Haver; CMMP analysis
Summary
In “The Changing Face of Global Debt”, I argued that global finance was shifting East and towards emerging markets. In this post, I summarise my analysis of the sustainability of current Asian PSC trends. The key points:
Classifications of Asian economies as either “advanced” or “emerging” economies are over-simplistic and unhelpful
Relative growth factor (RGF) analysis provides a simple, first tool for assessing the sustainability of debt dynamics
The risks associated with “excess credit growth” across EM are much lower than in previous cycles
The striking feature in Asia, however, is the fact that the highest levels of “excess credit growth” have occurred in economies that already exhibit high debt levels (Hong Kong, China, Korea and Japan)
In Hong Kong and China, these risk are compounded by debt service ratios that are close to peak levels and well above LT averages (“affordability risk”)
RGF-related risks appear relatively low in Asia’s two large and “genuine emerging markets” – India and Indonesia
Relatively high excess HH growth rates in India and China remain a key focus point.
Time for new classifications?
The BIS classifies Asian reporting countries into two categories: three “advanced” economies (Japan, Australia and New Zealand) and eight “emerging” economies (China, Hong Kong, India, Indonesia, Korea, Malaysia, Singapore and Thailand).
Such broad classifications are unhelpful, at best, and inaccurate, at worst. The classification of Japan, Australia and New Zealand as advanced economies is logical but masks different exposures to HH (Australia and New Zealand) and NFC (Japan) debt dynamics.
Figure 2: HH and NFC debt ratios (% GDP) for Asian reporting economies plotted against BIS threshold levels (in red) Source: BIS; Haver; CMMP analysis
The grouping of China, Hong Kong, India, Indonesia, Korea, Malaysia, Singapore and Thailand together as emerging economies 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 is unique in terms of having NFC and HH debt ratios that exceed both advanced economy averages and the BIS thresholds above which debt becomes a drag on future growth. Hong Kong and Singapore are both distinguished by their roles as regional financial centres but have different HH debt dynamics.
Malaysia and Thailand can be considered intermediate markets given that either both HH and NFC debt ratios (Malaysia) or one debt ratio (Thailand HH) exceed the average for emerging markets ex China. This leaves India and Indonesia as genuine emerging markets among the BIS reporting economies, with debt ratios below the emerging markets ex China average and well below BIS threshold levels (see Figure 2 above).
RGF analysis – “excess credit growth”
The theory
I have used the simple concept of relative growth factor (RGF) analysis since the early 1990s as a first step in analysing the sustainability of debt dynamics. 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 relative growth factor. 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 rates 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.
Low average risk in EM
Figure 3: Risks associated with “excess credit growth” across emerging markets are lower than in previous cycles (Trends in EM 3-year RGFs since March 2002) Source: BIS; Haver; CMMP analysis
Figure 3 above, illustrates rolling 3-year RGF trends for EM economies highlighting previous unsustainable levels that peaked in 1Q04, 3Q09, 4Q11 and 2Q15. The current excess growth rate of 1.3% suggests, however, that EM sustainability risks are relatively low. If anything, the lack of growth/slowing growth are more immediate challenges
How does Asia stand out?
Figure 4: The key chart repeated! Asia RGF analysis illustrated as at end 1Q19 (3-year CAGR) Source: BIS; Haver; CMMP analysis
Spotlight on Asia’s unique markets
A striking feature across Asia has been that some of the fastest rates of excess credit growth have occurred in economies where debt levels are already very high – Hong Kong, China, Korea and Japan (see Figure 4 above).
Figure 5: Trends in RGF for Asian economies with already high PSC debt ratios. China and Hong Kong slowing rapidly, Japan recovering. Source: BIS; Haver; CMMP analysis
The level of excess credit growth is already slowing sharply in Hong Kong and China from peak levels in excess of 6% (Figure 5). With debt service ratios in both economies close to peak levels and well above LT averages (Figures 6 and 7) a return to recent periods of excess growth is (1) unlikely and/or (2) would be associated with high levels of risk.
Figure 6: Hong Kong’s PSC debt service ratio is close to its historic high and well above LT average Source: BIS; Haver; CMMP analysis
Figure 7: China’s PSC debt service ratio is also close to its historic high and well above LT average Source: BIS; Haver; CMMP analysis
In contrast, Japanese PSC growth is recovering from sustained periods of deficient credit demand, helped by relatively low debt service ratios that are well below their LT averages (Figure 8 below). The recent uptick in excess Korean growth is unlikely to be sustainable, however, given that both HH and HFC debt levels are above BIS thresholds (Figure 2 above)
Figure 8: Japan’s PSC debt service ratio displays a very different dynamic – the DSR is low in absolute terms and well below LT average Source: BIS; Haver; CMMP analysis
Asia’s intermediate and emerging markets
RGF factors for intermediate and emerging Asian markets indicate relatively low levels of sustainability risk. Both India and Indonesia have been through periods of adjustment from previous phases of excess credit growth.
Figure 9: Rolling 3-year RGFs for Asia’s intermediate and emerging economies Source: BIS; Haver; CMMP analysis
In the former case, there are very different dynamics between the rapidly growing HH and slow growing NFC sector. The risks associated with excess credit growth in the HH sector (from a low base) are rising but remain relatively low in the NFC sector which is still in an adjustment phase.
Figure 10: India’s HH and NFC sectors are displaying sharply contrasting debt dynamics Source: BIS; Haver; CMMP analysis
Indonesia’s growth rates have adjusted from the 2000-14 period of “super-charged” growth which was driven largely by exogenous factors including the commodities super-cycle and portfolio inflows during the period of global QE and record low US interest rates.
In summary, the risk associated with excess credit growth across EM are lower than in previous cycles. Asia stands out, however, because the highest rates of growth have occured in economies that already have high debt ratios. In China and Hong Kong, these risks are compounded by high debt service ratios indicating rising “affordability” risks. RGFs in both economies are adjusting sharply lower in response. Risks in intermediate and emerging Asian economies appear lower, but the relatively high excess HH growth rates in India and China remain a key focus point.
Please note that the summary comments above are abstracts from more detailed analysis that is available separately.
