“Global debt dynamics – IV”

Household sector debt dynamics

The key chart

**Trends in HH debt ($tr) and HH debt ratios (% GDP) since GFC** (Source: BIS; CMMP)

The key message

The household (HH) sector was at the epicentre of the Global Financial Crisis (GFC). Since then, three key structural shifts have changed the sector’s potential impact on macro policy, growth and financial stability:

a shift away from HH debt towards NFC debt within private sector debt
a shift away from HH debt towards government debt within total debt
a regional shift away from advanced economies towards emerging economies (EMs) driven largely, but not exclusively, by Chinese HH debt dynamics

The US ($17tr) accounts for almost a third of total HH debt. The level of US debt is almost 2x China’s HH debt and over 5x Japanese HH debt (the next two largest markets by size). The US and China collectively account for half of global HH debt. Once again, neither rank among the top ten most indebted HH economies, however.

Of the 43 BIS reporting economies, only 11 have HH debt ratios above the maximum threshold level (compared with 20 in the NFC sector). Of these 11, eight also have “above-threshold” NFC debt ratios – Switzerland, Norway, Canada, Denmark, Korea, the Netherlands, Sweden and Hong Kong.

Risks associated with excess HH debt growth in advanced economies are lower than in EM and, in contrast to NFC debt dynamics, are in economies with relatively low levels of HH indebtedness (eg, France and Germany). Growth risks also remain in Norway, Sweden, New Zealand, Canada and Switzerland among advanced economies.

Elevated affordability risks among advanced economies exist in Sweden and Norway where HH debt service ratios are not only high in absolute terms, but they are also above their respective LT averages.

Among the top ten economies that account for over 80% of total HH debt, Korea stands out due to elevated risks relating to HH indebtedness, excess HH debt growth, affordability and house price appreciation. This may explain why some Koreans feel that they are playing a real-life version of the “Squid Game”?

Household debt dynamics

Household debt hit a new high of $55tr during 2021 (see chart above). The HH debt ratio (67% GDP) remains elevated by historic standards but is below its 4Q20 peak (71% GDP) and below the BIS’ maximum threshold level of 85% GDP. This is in contrast to the NFC sector, where global indebtedness (105% GDP) is above the sector’s maximum threshold level of 90% GDP.

**Trends in the breakdown of PSC (% total) since the GFC** (Source: BIS; CMMP)

There has been a shift away from HH debt since the GFC towards greater levels of corporate (NFC) debt within private sector debt (PSC) and towards government debt within total global debt. HH debt’s share of total PSC has fallen from 45% to 39% over the period (see chart above).

**Trends in the breakdown of total debt (% total) since the GFC** (Source: BIS; CMMP)

More significantly, HH debt’s share of total debt has fallen from 32% to 25% over the period, while the share of government debt has increased from 29% to 37% (see chart above). This second shift, driven by advance economy debt dynamics (and the US and UK especially), has important implications for financial stability (see “Global Debt Dynamics – I”).

**Trends ($tr) and geographic breakdown of HH debt and EM share (% total) since GFC** (Source: BIS; CMMP)

Since the GFC, there has also been a significant geographic shift away from advanced economies towards emerging markets. This shift has been driven largely, but not exclusively, by Chinese debt dynamics. The share of total HH debt accounted for by EMs has risen from 10% to 31%. China’s share of total HH debt has risen from 2% to 19%, while EM x China’s share has risen from 8% to 12%. Note that China accounts for 61% of total EM HH debt alone and that China, Korea, India and Brazil account for 82% of EM HH debt collectively.

**Top 20 BIS reporting economies ranked by outstanding HH debt ($tr)** (Source: BIS; CMMP)

The US ($17tr) accounts for almost a third of total HH debt alone. The outstanding stock of HH debt at the end of 2Q21 in the US was 1.7x the stock of Chinese HH debt (the second largest HH debt market) and 5.3x the stock of Japanese HH debt (the third largest HH debt market). Collectively the US and China account for more than half of global HH debt outstanding (see chart above).

**Top 22 BIS reporting economies ranked by HH debt ration (% GDP)** (Source: BIS; CMMP)

Once again, neither rank among the top-ten most indebted HH markets, however (see chart above). The US ranks #12 while China ranks #22. In contrast, Canada, Australia, Korea and Switzerland rank inside the top-ten rankings based on both the level of HH debt ($tr) and the level of HH indebtedness (% GDP).

**HH and NFC debt ratios (% GDP) for BIS reporting economies** (Source: BIS; CMMP)

Of the 43 BIS reporting economies, 11 have HH debt ratios that exceed the BIS’ maximum threshold of 85% of GDP. Of these 11, eight also have NFC debt ratios above maximum thresholds – Switzerland, Norway, Canada, Denmark, Korea, the Netherlands, Sweden and Hong Kong. The remaining three economies with above-threshold HH debt ratios but below-threshold NFC debt ratios are Australia, New Zealand and the UK (see chart above).

**Excess HH debt growth (RGF) plotted against HH debt ratio for advanced economies** (Source: BIS; CMMP)

The rate of “excess HH debt growth” in advanced economies (2.1%) is lower than the global (3.8%) and EM (8.7%) averages (click here for an explanation of the underlying methodology). In contrast to NFC sector dynamics, the highest rates of excess HH debt growth among advanced economies occurred in economies with relatively low levels of HH indebtedness. As can be seen in the chart above, France (4.2%) and Germany (3.8%) have seen the highest rates of excess HH debt growth over the past three years. Their HH debt ratios are 67% GDP and 58% GDP respectively, below the advanced economy average of 77% GDP and the BIS maximum threshold level of 85% GDP.

Risks associated with excess HH debt growth are also elevated in Norway, Sweden, New Zealand, Canada and Switzerland among advanced economies. In each case, growth in HH debt is outstripping growth in nominal GDP despite high absolute and relative levels of HH indebtedness (see chart above).

**HH debt service ratios and deviation from LT average** (Source: BIS; CMMP)

HH affordability risks within our sample of advanced economy are elevated in Sweden and Norway. In these economies, the HH debt service ratios (DSR) are not only high in absolute terms, but they are also above their respective LT averages despite low absolute HH borrowing costs. HH DSRs are also relatively high in Canada, Australia, the Netherlands and Denmark in absolute terms. However, in each of these cases the current DSR is below the respective LT average.

HH financial stability heatmap

**Financial stability heatmap – HH debt** (Source: CMMP)

(* Note HH DSR ratios are only available for selected BIS reporting economies)

Significant variations exist in the impact of HH debt dynamics on financial stability among the ten economies that collectively account for 81% of total HH debt. Key themes include:

Korea stands out among this sample in terms of elevated risks associated with HH indebtedness, the rate of excess HH credit growth and the affordability of debt (in aggregate terms*). Note also that risks are elevated in terms of the growth in house prices (see chart below). I will return to Korean debt dynamics in more detail in a subsequent post

**Trends in house prices (% YoY, real terms) since GFC** (Source: BIS; CMMP)

Four of the five economies with the largest levels of outstanding debt – US, China, Japan and Germany – have HH debt levels below the maximum threshold level
The US, which accounts for 31% of total HH debt, has relatively low risks in terms of HH indebtedness, the rate of excess growth in HH debt and the affordability of HH debt
China has elevated risks associated with the rate of excess HH debt growth and the affordability of debt (at the aggregate level)

**Trends in composite cost of French HH borrowing for house purchase** (Source: ECB; CMMP)

France has elevated risks associated with the rate of excess HH debt growth. France is also the only economy in this sample where the HH debt service ratio is above its LT average. This is despite the fact that the composite cost of HH borrowing is at an all-time low (see chart above).

The next post in this series focuses on EM debt dynamics.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Global debt dynamics – III”

Corporate sector debt dynamics

The key chart

**Trends and breakdown of NFC debt ($tr) and trend in debt ratio (% GDP) since GFC**
(Source: BIS; CMMP)

The key messages

Corporate debt hit a new high in 2021 ($86tr) and increased its market share of total private sector debt (PSC) to 61%, up from 55% at the time of the GFC. The aggregate debt ratio was 105% of GDP at the end of 2Q21, 25ppt above the BIS’ maximum threshold level (albeit below its 4Q20 peak of 110%).

Since the GFC, there has been a significant structural shift away from advanced economies towards emerging economies. Chinese debt dynamics have driven this shift almost exclusively.

China and the US collectively account for 52% of total NFC debt. However, while China ranks #6 globally in terms of NFC indebtedness, the US ranks only #22.

Of the 43 BIS reporting economies, 20 have NFC debt ratios above the maximum threshold. Among advanced economies only seven have “below-threshold” NFC debt ratios – the US, Germany, Italy, Greece, the UK, New Zealand and Australia (note, however, that the last three have “above-threshold” levels of HH debt).

Some of the highest rates of excess NFC growth have occurred in economies where debt ratios are already high and above average – Switzerland, Japan, France, Sweden and Canada. Excess growth has also occurred in other relatively indebted economies – Norway, Spain and Denmark – but at slightly slower-than-average rates. Elevated NFC affordability risks exist in Sweden, France, Canada and Norway.

Among the ten economies that collectively account for almost 80% of total NFC debt, five have above-threshold levels of NFC debt – France, China, Canada, Japan and South Korea. Of these, Japan, South Korea and France have also experienced above-average rates of excess NFC debt growth. Despite low borrowing costs, NFC debt service ratios are above their LT averages in France, Japan, Canada, Germany and the US. In contrast, NFC affordability risks are relatively low in the UK and Italy. Outside this sample, risks associated with NFC indebtedness, excess rates of NFC debt growth, and affordability of NFC debt are noticeably elevated in Sweden.

Corporate sector debt dynamics

Corporate (NFC) debt hit a new record high of $86tr in 2021 (see chart above). It accounted for 61% of total private sector debt (PSC) at the end of 2Q21, up from 55% at the time of the GFC. The aggregate debt ratio of all 43 BIS reporting economies was 105% GDP at the end of 2H21, above the maximum threshold limit of 90% GDP but below the 4Q20 peak of 110% GDP.

**Structural shifts in NFC debt since the GFC** (Source: BIS; CMMP)

Since the GFC, there has been a significant structural shift away from advanced economies towards emerging economies (EM), driven almost exclusively by China’s NFC debt dynamics. Advanced economies still account for the largest amount of outstanding NFC debt (49tr) but their share has fallen from 79% at the time of the GFC to 56% at the end of 2Q21 (see chart above). Emerging economies’ NFC debt totalled $38tr at the end of 2H21, 44% of total NFC debt from 21% at the time of the GFC. Note that China accounts for 71% of EM NFC debt and 31% of total NFC debt alone (see chart below). Excluding China, EMs share of NFC debt is largely unchanged since the GFC.

**Trends in China’ share of EM NFC debt and total NFC debt** (Source: BIS; CMMP)

**Top 20** **BIS reporting economies ranked by outstanding NFC debt** ($tr) (Source: BIS; CMMP)

China ($27tr) and the US ($18tr) collectively account for 52% of total NFC credit. However, while China ranks #6 in terms of NFC indebtedness, the US ranks only #22. Indeed, among the five economies that collectively account for 80% of total NFC debt – China, the US, Japan, France, and Germany – only China and France (#5) rank among the top-ten economies ranked by NFC indebtedness. Once again, debt levels and levels of indebtedness tell us very different things.

**Top 20 BIS reporting economies ranked by NFC debt ratio (% GDP)** (Source: BIS; CMMP)

Of the 43 BIS reporting economies, 20 have NFC debt levels that exceed the BIS’ maximum threshold. Of these 20 economies, eight also have HH debt ratios about maximum thresholds – Hong Kong, Sweden, the Netherlands, Norway, China, Denmark, Canada and South Korea. The other 12 economies with NFC debt ratios above the maximum threshold are Luxembourg, Ireland, France, China, Belgium, Singapore, Finland, Japan, Chile, Spain, Portugal and Austria.

Note that among advanced economies, there are only seven economies with NFC debt ratios below the maximum threshold – the US, Germany, Italy, Greece, the UK, New Zealand, and Australia. Of these, the final three have HH debt ratios above maximum thresholds however (see chart above).

**Excess NFC growth (RGF) plotted against NFC debt ratio for advanced economies**
(Source: BIS; CMMP)

Some of the highest rates of excess NFC growth have occurred in economies where NFC debt ratios are already high. As can be seen in the chart above, excess NFC growth rates in Switzerland, Japan, France Sweden and Canada all exceed the average excess growth rate for advanced economies despite the relatively high NFC debt ratios in each of these economies. Excess credit growth has also occurred in other relatively indebted economies – Norway, Spain, and Denmark – but at a slower-than-average rate.

**NFC debt service ratios and deviations from LT average** (Source: BIS; CMMP)

Elevated affordability risks in the NFC sector exist in Sweden, France, Canada and Norway. In each of these economies, NFC debt ratios are not only high in absolute terms (above 50%) but they are also above the respective LT averages, notably in Sweden and France.

NFC financial stability heatmap

**Financial stability heatmap – NFC debt** (Source: CMMP)

Important variations exits in relation to the impact of NFC debt dynamics on financial stability among the ten economies that account for just under 80% of total NFC debt (see heatmap above). Note that:

Five of these economies – France, China, Canada, Japan and South Korea – have NFC debt ratios that exceed the 90% GDP BIS maximum threshold
Three of these five – Japan, South Korea and France –also exhibit well-above-average rates of excess NFC credit growth
Despite relative low costs of NFC borrowing, DSRs are above their respective LT averages in France, Japan, Canada, Germany and the US
Outside this sample, risks associated with the level of NFC indebtedness, excess growth in NFC debt and the affordability of debt are noticeably elevated in Sweden, an economy ranked #16 in terms of the absolute level of NFC debt but #3 in terms of NFC indebtedness.

The next post in this series focuses on household debt dynamics

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Global debt dynamics – II”

Private sector debt dynamics

The key chart

**Financial stability heatmap for economies that account for 80% of outstanding PSC**
(Source: CMMP)

The key message

In contrast to conventional economic theory, CMMP analysis emphasises the impact of private sector debt dynamics on macro policy, global growth, investment decisions and risks to financial stability. Attention extends beyond the absolute level of debt to include the level of indebtedness, the rate of growth in debt and the affordability of debt. Key themes from the latest BIS data release include:

The structure of global PSC has shifted towards corporate (NFC) and emerging market (EM) debt. The latter shift reflects China debt dynamics exclusively
Absolute debt levels and debt ratios tell us very different things. China and the US account for over half of outstanding PSC, but neither ranks among the top ten most indebted economies
Eight BIS reporting economies have NFC and HH debt ratios that both exceed maximum BIS threshold levels – Hong Kong, Switzerland, Norway, the Netherlands, Sweden, Denmark, Canada and South Korea
Some of the highest rates of “excess credit growth” among advanced economies have occurred in economies where debt ratios are already high – Japan, France, Switzerland, Sweden, Canada (and Norway).
Elevated affordability risks exist in Sweden, Switzerland, France, Japan, Finland and Canada among advanced economies and in Turkey, China, Brazil and South Korea among EMs

Significant variations exist in the impact of PSC dynamics on financial stability among the ten economies that account for 80% to total global PSC (see heatmap above):

In China, risks are elevated in relation to NFC indebtedness, the rate of growth in HH debt and the affordability of PSC
In contrast, risks in the US are relatively low with the exception of the affordability of NFC debt
In North America, risks are more elevated in Canada, however, due to the levels of NFC and HH indebtedness and the affordability of debt in the NFC sector
Within the larger euro area economies, France stands out due to elevated risks associated with NFC and HH indebtedness, the rate of growth of debt and affordability in both sectors
In Asia, South Korea stands out for the levels of NFC and HH indebtedness, the rate of growth in debt in both sectors and the affordability of PSC

Private sector debt dynamics

The level and structure of global PSC

**Trend and breakdown of PSC ($tr) and trend in debt ratio (% GDP) since GFC** (Source: BIS; CMMP)

Global PSC hit a new record high of $141tr in 2021 (see chart above). NFC debt of $86tr accounted for 61% of total PSC, up from 55% at the time of the GFC, while household (HH) debt of $55tr accounted for 39% of total PSC, down from 45% at the time of the GFC.

Advanced economies’ debt of $87tr accounted for 62% of total PSC, down from 84% at the time of the GFC. In contrast, EM debt of $54tr accounted for 38% of total PSC, up from 16% over the same period (see chart above). Note that China accounted for $37tr or 69% of total EM debt alone. As highlighted in “Global Debt Dynamics – I”, the EM debt story is increasingly a China debt story (see also the final post in this series). Excluding China, EMs’ share of total PSC has remained unchanged since the GFC.

Key theme #1: The structure of global PSC has shifted towards greater shares of NFC debt (at the borrower level) and EM debt (at the regional level). The latter shift reflects debt dynamics in China exclusively.

**Top 20 BIS reporting economies ranked by level of debt ($tr)** (Source: BIS; CMMP)

China ($37tr) and the US ($35tr) have the highest levels of PSC among the BIS reporting countries and account for 51% of total PSC collectively (see chart above). Neither economy ranks among the top ten most indebted economies, however. China is ranked #11 and the US is ranked #21 (see chart below).

**Top 21 BIS reporting economies ranked by debt ratio (%GDP)** (Source: BIS; CMMP)

Of the five economies that have the highest levels of outstanding PSC, only France is included in the top ten most indebted economies (see chart above).

Key theme #2: Debt levels and debt ratios tell us very different things – something that popular/populist US debt narratives often overlook (see “Houston, do we have a problem?”).

PSC and financial stability risks

In assessing risks to global financial stability, CMMP analysis extends beyond the level of debt to include the level of indebtedness (a stock-flow perspective), the rate of growth in debt, and the affordability of debt (a flow-flow perspective).

Private sector debt ratios

The chart below plots the 43 BIS reporting nations according their NFC debt ratios (x-axis) and HH debt ratios (y-axis). The two red lines indicated the maximum threshold levels identified by the BIS of 90% GDP for NFC debt and 85% for HH debt. The BIS considers debt above these levels to be a drag on future growth.

**HH and NFC debt ratios (% GDP) for all 43 BIS reporting economies** (Source: BIS; CMMP)

Key theme #3: Of the 43 BIS reporting nations, eight have NFC and HH debt ratios that both exceed the maximum BIS threshold levels of 90% and 85% of GDP respectively – Hong Kong, Switzerland, Norway, the Netherlands, Sweden, Denmark, Canada and South Korea.

A further twelve economies have excess NFC debt ratios and three economies have excess HH debt ratios. Note, in contrast, that the US is one of only four advanced economies to have NFC and HH debt ratios below the BIS threshold (along with Germany, Italy and Greece). Note also that the traditional distinction between advanced economies and EMs is increasing irrelevant/unhelpful, especially when analysing Asian debt dynamics (see “D…E…B…T, Part II”).

Excess PSC growth (RGF analysis)

CMMP analysis has 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.

**Excess PSC growth plotted against PSC debt ratio (% GDP)** (Source: CMMP)

The chart above plots PSC RGFs against the PSC debt ratio as at the end of the 2Q21. The red lines represent the average levels for all advanced economies. The economies located in the top right hand quadrant have experienced above average excess credit growth despite having above average PSC debt ratios.

Key theme #4: A peculiar feature among advanced economies is the fact that some of the highest rates of “excess credit growth” have occurred in economies where PSC debt ratios are already high – Japan, France, Switzerland, Sweden, Canada (and Norway).

Affordability of debt

The BIS provides debt service ratios for the private non-financial sector on a quarterly basis. DSRs provide important information about the interactions between debt and the real economy as they measure the amount of income used for interest payments and amortisations (ie, a flow-to-flow comparison). While the BIS applies a consistent methodology to derive these ratios, they are unable to remove country-specific factors completely. For this reason, the BIS typically focuses in trends in national DSRs over time. CMMP analysis incorporates both the level of the DSR and its deviation from long-term averages.

**Debt service ratios – deviations from LT average versus current level** (Source: BIS; CMMP)

Key theme #5: Elevated affordability risks exist in Sweden, Switzerland, France, Japan, Finland and Canada among advanced economies and in Turkey, China, Brazil and South Korea among EMs.

In each case, the DSRs are not only relatively high in absolute terms, they are also above the 10-year average levels seen in each economy.

Financial stability heatmap

Significant variations exist in the impact of private sector dynamics among the ten economies that account for 80% of global debt (see heatmap above) and also within regions (eg N America, the euro area) and between different advanced and emerging economies:

In China, risks are elevated in relation to NFC indebtedness, the rate of growth in HH debt and the affordability of PSC
In contrast, risks in the US are relatively low with the exception of the affordability of NFC debt
In North America, risks are more elevated in Canada, however, due to the levels of NFC and HH indebtedness and the affordability of NFC debt
Within the larger euro area economies, France stands out due to elevated risks associated with NFC and HH indebtedness, the rate of growth of debt and affordability in both sectors
In Asia, South Korea stands out for the levels of NFC and HH indebtedness, the rate of growth in debt in both sectors and the affordability of PSC

The next post in this series focuses on NFC debt.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Global debt dynamics – I”

Why does the changing nature of global debt matter?

The key chart

**Changes in breakdown of global debt (% total) since the GFC** (Source: BIS; CMMP)

The key message

“Private debt causes crises – public debt (to some extent) ends them.”
Professor Steve Keen, June 2021

While a great deal of attention is focused on the fact that global debt levels hit new highs during 2021, too little attention is given to the important changes that have taken place in the structure of global debt since the GFC.

This matters because conventional macro theory struggles to deal with the implications here, since it typically ignores private debt while seeing government debt as a problem rather than as a solution.

There has been an important shift away from household (HH) debt towards government debt at the aggregate, global level since the Global Financial Crisis (GFC). Debt dynamics in advanced economies have driven this shift, most notably in the US and the UK. In contrast, the structure of emerging economies’ (EMs) debt remains broadly unchanged, with a structural bias towards private sector debt. These trends matter for a number of reasons:

First, and in contrast conventional theory, we know that government deficits increase the supply of money (not the demand for money), crowd-in investment private spending (as opposed to crowding it out) and depress interest rates (rather than driving them up).
Second, and from this, we also know that while private sector debt typically causes crises, public sector debt typically limits their damage/ends them.
Third, the structure of US and UK debt is now the mirror image of the pre-GFC period, which reduces associated risks since governments face different financial constraints to HHs and NFCs and cannot, as currency issuers, become insolvent. Risks associated with excess credit growth exist more obviously in other advanced economies.
Fourth, EMs face very different risks to advanced economies. These are associated largely with the level of NFC debt, the growth rate in HH debt and the increasing dominance of China in EM debt.

Global debt dynamics – I

Debt dynamics since the GFC

In the “Seven lessons from the money sector in 2021”, I noted that our understanding of global debt dynamics is improved significantly by extending analysis beyond the level of debt to include its structure, growth and affordability.

In this first post of 2022, and the first in a series of five posts reviewing current global debt dynamics, I focus on the implications of the changes that have taken place in the structure of global debt since the Global Financial Crisis (GFC).

**Global debt levels ($tr) and debt ratios (% GDP) as at end 2Q21** (Source: BIS; CMMP)

A great deal of attention has focused on the fact that global debt levels hit new, record highs in 2021 (see chart above). According to BIS statistics released on 6 December 2021, total debt (to the non-financial sector) reached $225tr at the end of 2Q21. NFC debt reached $86tr (38% total), government debt reached $83tr (37% total) and HH debt reached $55tr (25% total).

Note that while it is common to aggregate these three categories of debt together, it is also important to recognise that NFC and HH debt sit on the liabilities side of private sector balance sheets, while government debt sits on the assets side of private sector (and RoW) balance sheets.

Note also, that while debt levels are at record highs, debt ratios (ie, debt as a percentage of GDP) are below their 4Q20 peaks in each category.

Too little attention has focused, however, on the important changes that have taken place to the structure of global debt since the GFC (see chart above). While NFC debt’s share of total debt has remained relatively stable at just under 40%, there has been an important shift away from HH debt to government debt over the period. HH debt’s share of total debt has fallen from 32% to 25% (see chart below). In contrast, government debt’s share of total debt has risen from 29% to 37%.

**Trends in shares of HH and government debt (% total debt) since GFC** (Source: BIS; CMMP)

Debt dynamics in advanced economies have driven this shift, most notably in the US and the UK (see chart below). In advanced economies, the US and the UK the share of HH debt has fallen from 34% to 26%, from 42% to 28% and from 43% to 30% respectively. In contrast, the respective shares of government debt to total debt have risen from 29% to 42%, from 26% to 44% and from 20% to 45% respectively. Similar shifts have also taken place in the EA, albeit in a much more muted fashion. This reflects a much lower (27%) share of HH debt at the time of the GFC in the EA.

**Changes in structure of global debt by region** (Source: BIS; CMMP)

The structure of EM debt remains broadly unchanged, however, with a bias towards private sector debt. At the end of 2Q21, the shares of HH, NFC and government debt to total debt in EM were 22%, 50% and 28% respectively.

**Trends in structure (% total) of EM debt since GFC** (Source: BIS; CMMP)

Note that China’s share of total EM debt has risen from 31% to 64% over the period. In other words, the EM debt story is increasingly a “China debt” story. For reference, China’s share of total global debt has also increased from 5% to 21% over the same period (see chart below). In contrast, EM excluding China’s share of total global debt has remain unchanged.

**Trends in EM share of global debt since GFC** (Source: BIS; CMMP)

Why does this matter?

This matters for a number of reasons. First, and in contrast conventional theory, we know that government deficits increase the supply of money (not the demand for money), crowd-in investment private spending (as opposed to crowding it out) and depress interest rates (rather than driving them up).

Professor Steve Keen has written extensively on this subject. He notes that, “rather than deficits meaning that the government has to take money away from the private sector – which is what the mainstream thinks the government does when it sells bonds to cover the deficit – the deficit creates money by increasing the bank deposits of the private sector”. In simple terms, by not studying the accounting involved in government deficits, Keen argues that they (mainstream economists) have wrongly classified them as increasing the demand for money, when in fact they increase the supply of money. I agree.

The implication here is that many arguments regarding global debt are in fact, back-to-front. Government deficits crowd in private spending and investment by increasing the supply of money. They also typically drive down interest rates rather than driving them up.

Second, and from this, we also know that while private sector debt typically causes crises, public sector debt typically limits their damage/ends them. Consider the EA’s fiscal rules that put limits on government debt and deficits but completely ignored private debt and credit and the history of Spanish debt dynamics after the introduction of the euro (see chart below).

**Ignore excess private sector debt growth at your peril I – Spain** (Source: BIS; CMMP)

After the introduction of the euro, government debt in Spain fell from 70% to 36% in March 2008. In contrast, private sector debt rose from 80% of GDP to 208% of GDP over the same period before peaking at 227% in 2Q10 at the height of the Spanish banking crisis (see chart above). Similar trends were also seen in other advanced economies. The chart below illustrates trends in private sector credit and government debt in the US.

Ignore excess private sector growth at your peril II – the US (Source: BIS; CMMP)

Excess growth in private sector debt up to a crisis point is followed by increases in government debt post-crisis in response to the collapse in demand as credit growth turns negative and the private sector reduces leverage. In short, recent history supports Professor Keen’s hypothesis that private debt causes crisis, while public debt ends them (or limits their damage). This topic and these case studies are developed in more detail in other posts/CMMP research.

**Shift from US and UK HH debt to government debt (% total debt) since GFC** (Source: BIS; CMMP)

Third, the structure of US and UK debt is now the mirror image of the pre-GFC period (see chart above). This reduces associated risks since governments face different financial constraints to HHs and NFCs and cannot, as currency issuers, become insolvent.

**Rates of excess credit growth in EM** (Source: CMMP)

Fourth, EMs face very different risks to advanced economies. These are associated largely with the level of NFC debt, the growth rate in HH debt (see chart above) and the increasing dominance of China in EM debt – subjects that I will address in the final post in this series.

Conclusion

Global debt dynamics are a core element of CMMP analysis. While it is natural to focus initially on the new highs in global debt levels, it is also important not to miss the important messages associated with changes in the structure, growth and affordability of global debt.

The shift in the structure of global debt from HH debt to government debt has important implications for the severity of recessions, monetary dynamics, inflation, rates and investment risks. The nature of these implications also vary depending on whether governments are currency issuers (eg, US and UK) or currency users (eg, EA governments). The risks of a return to pre-pandemic policy mixes remain in all areas, however.

In the next post, I will examine dynamics in global private sector debt.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Seven key lessons from the money sector in 2021”

What have the “messages from the money sector” taught us?

**Visual summary of the CMMP framework linking all economic sectors together** (Source: CMMP)

The key message

Over the past twelve months, the “messages from the money sectors” have taught us more about:

The true value in analysing global banks
How to improve our understanding of global debt dynamics
What does (and does not) constitute a pragmatic and responsible fiscal outcome
Why official forecasts for UK government spending remain flawed
How QE fuelled the “wrong type of lending” and what the ECB thinks should be done about it
How to avoid misinterpreting trends in monetary aggregates
How the behaviour of UK and euro area households reached an important inflexion point at the start of 4Q21

Unfortunately, there is a risk that the renewed rise in COVID-19 cases and emergence of the omicron variant may have masked the final lesson over the Christmas period.

Nonetheless, a final positive message from 2021 is that firmer economic foundations (and higher levels of vaccinations) suggest that both the UK and euro area regions are in a stronger position to face renewed COVID-related challenges now than they were at the start of the year.

Seven key lessons from 2021

Lesson #1: where is the true value in analysing banks?

The true value in analysing global banks comes from understanding the implications of the relationship between the money sector and the wider economy for macro policy, corporate strategy, investment decisions and asset allocations.

Based on this core foundation, CMMP analysis incorporates:

A quantifiable and objective framework linking all domestic economic sectors with each other and the rest of the world (see key chart above)
A deep understanding of global debt dynamics (see lesson #2 below)
Unique insights into the impact of global money, credit and business cycles on corporate strategy and asset allocation

Lesson #2: how can we improve our understanding of global debt dynamics?

**Household and government debt as a share (% total) of global debt** (Source: BIS; CMMP)

Our understanding of global debt dynamics is improved significantly, at the macro level, by extending analysis beyond the level of debt to include its structure, growth and affordability and, at the micro level, by distinguishing between productive (COCO-based) and non-productive sources of debt (FIRE-based), at the micro level (see lesson #5 below).

A great deal of attention focused on the fact that global debt levels hit new highs during 2021. Much less attention focused on the key structural changes that have taken place in the structure of global debt since the GFC:

There has been an important shift away from household (HH) debt towards government debt at the aggregate, global level (see chart above)
Advanced economy dynamics have driven this structural shift, especially in the US and UK
In contrast, the structure of EM debt remains broadly unchanged, with a bias towards private sector debt

I will explore the implications of these (and other structural changes) in my first post in 2022.

Lesson #3: what constitutes a pragmatic and responsible fiscal outcome?

**UK financial sector balances (4Q rolling averages, £bn)** (Source: ONS; CMMP)

“Pragmatic” and “responsible” fiscal outcomes are those that deliver a balanced economy not a balanced budget.

The three key sectors in any modern economy – the domestic private sector, the domestic government and the RoW – each generate income and savings flows over a given period. If a sector spends less than it earns it creates a surplus. Conversely, if it spends more than it earns it creates a deficit.

Extending fundamental accounting principles, we know that any deficit run by one or more economic sectors must equal surpluses run by other sector(s). This leads to the key identity pioneered by the late Wynne Godley:

Domestic private balance + domestic government balance + foreign balance (must) = zero

**UK private and public sector net savings/borrowings as %age of GDP** (Source: OBR; CMMP)

Contrary to popular political rhetoric, budget outcomes are inappropriate goals in themselves. Worse still, fiscal surpluses reduce the wealth and financial savings of the non-government sectors.

The good news during the pandemic was that the unprecedented shifts in net savings of the private sector were matched by equally unprecedented shifts in the net deficits of the public sector (see chart above for the UK experience). In other words, policy responses were both timely and appropriate. The risk looking forward is that policy makers ignore these lessons and repeat the mistakes of the post-GFC period (see also lesson #4).

Lesson #4: where are the flaws in offical UK forecasts

**Historic and forecast UK sectoral net lending – % GDP, rolling annual average** (Source: OBR; CMMP)

Forecast improvements in UK government finances from the OBR rely on dynamic adjustments by other economic sectors and unusual patterns of behaviour beyond that. The assumed end-result is one where sustained, twin domestic deficits are counterbalanced by significant and persistent current account deficits (see chart above).

The OBR described this as a “return to more normal levels.” CMMP analysis suggest it is anything but. Viewed from a sector balances perspective, the risks appear tilted to the downside ie, government finances may not recover as quickly as forecast.

Lesson #5: has QE fuelled the wrong type of lending?

**Contribution (ppt) of COCO-based and FIRE-based lending to growth (% YoY) in total lending in the euro area** (Source: ECB; CMMP)

Unorthodox monetary policy has fuelled growth in the wrong type of lending. There has been a shift away from productive COCO-based lending towards less-productive FIRE-based lending. The stock of productive lending in the euro area, for example, only returned to its previous January 2009 peak last month (November 2021).

**Outstanding stock (EUR bn) of productive COCO-based lending in the euro area** (Source: ECB; CMMP)

In other words, the aggregate growth in lending since then has come exclusively from non-productive FIRE-based lending. According to the latest ECB data, for example, FIRE-based lending accounted for 2.7ppt of the total 3.7% YoY growth in private sector lending in November 2021 (see chart below).

**What’s driving private sector lending in the euro area?** (Source: ECB; CMMP)

In its latest, “Financial Stability Review” (November 2021), the ECB calls for a policy shift away from short-term measures towards “mitigating risks from higher medium-term financial stability vulnerabilities, in particular emerging cyclical and real estate risks”.

This is a welcome development given the negative implications that the rise in FIRE-based lending has for future growth, leverage, financial stability and income inequality. Within the EA, Germany stands out given current house price and lending dynamics, the extent of RRE overvaluation and the absence of targeted macroprudential measures.

Lesson #6: how can we avoid misinterpreting monetary aggregates?

**Growth in euro area M3 (% YoY) and contribution (ppt) from M1 and private sector lending** (Source: ECB; CMMP)

Trends in monetary aggregates provide important insights into the interaction between the money sector and the wider economy but headline YoY growth figures can be easily misinterpreted, leading to false narratives regarding their implications.

The message from rapid broad money growth in the pre-GFC period, for example, was one of (over-) confidence and excess credit demand. In contrast, the message from rapid broad money growth during the COVID-19 pandemic was one of elevated uncertainty and subdued credit demand (see chart above). Very different drivers with very different implications…

CMMP analysis has focused on three key signals throughout 2021 to help to interpret recent trends more effectively: monthly household deposit flows (behaviour); trends in consumer credit demand (growth outlook) and the synchronisation of money and credit cycles (policy context).

Lesson #7: has HH behaviour in the UK and EA reached an inflexion point?

**Monthly HH money flows as a multiple of pre-pandemic levels** (Source: BoE; ECB; CMMP)

The behaviour of UK and euro area households reached a potentially important inflexion point at the start of 4Q21. Monthly money flows moderated sharply (see chart above) while monthly consumer credit flows hit new YTD highs ie, positive developments in two of the three key signals.

The recent rise in COVID-19 cases, the emergence of the omicron variant and renewed restrictions imposed by governments may result in these points being missed or, worse, still, reversed.

That said, and to finish on a positive note, firmer economic foundations (and higher levels of vaccinations) suggest that both the UK and euro area regions are in a stronger position to face renewed COVID challenges than they were at the start of the year.

Thank you for reading and very best wishes for a very happy and healthy new year.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Missing the point?”

Household behaviour at an inflection point

The key chart

The key message

The behaviour of UK and euro area households reached a potentially important inflexion point at the start of 4Q21. Household (HH) money flows moderated sharply in October 2021 while monthly flows of consumer credit hit new YTD highs.

Recall that HHs increased their money holdings significantly during the pandemic and built up (estimated) excess savings of £162bn in the UK and €285bn in the EA – a combination of forced and precautionary savings. This meant that the rise in broad money during the pandemic was a reflection of the deflationary forces of increased savings and delayed consumption.

The accumulation of money holdings peaked during 2Q20 and again in 4Q20 and the low point in terms of YoY declines in consumer credit demand was passed in February 2021. Monthly flows of consumer credit have been positive for the past six months and hit YTD highs in October 2021 in both regions. At the same time, the accumulation of money holdings has fallen back to 1.2x and 0.6x pre-pandemic levels in the UK and EA respectively.

Unfortunately, the recent rise in COVID-19 cases, the emergence of the omicron variant and renewed restrictions imposed by the UK and EA governments may result in these points being missed, or, worse still, the positive trends being reversed. That said, firmer economic foundations in both the UK and EA (and higher levels of vaccinations) suggest that both regions are in a stronger position to face renewed COVID challenges than they were a year ago.

Missing the point – the charts that matter

HH money flows

HHs in the UK and EA increased their money holdings significantly during the COVID-19 pandemic. Monthly flows peaked at 6x pre-pandemic levels in the UK in May 2020 (see chart above) and 2.4x pre-pandemic levels in the EA a month earlier (see chart below). At the start of 4Q21, they had moderated to 1.2x and 0.6x pre-pandemic levels in the UK and EA respectively. A key building block for a sustained economic recovery.

**Monthly HH deposit flows in the EA (EUR bn) and multiple (x) of 2019 average flow** (Source: ECB; CMMP)

Excess HH savings

In aggregate, and as a result, HHs have built up excess savings in the form of bank deposits of £162bn in the UK (see chart above) and €285bn in the EA (see chart below) since February 2020. These reflect a combination of forced savings (that may be released relatively quickly to support economic activity) and precautionary savings (that are unlikely to move straight into investment of consumption).

**Estimated build up of excess HH savings in the EA (EUR bn)** (Source: CMMP estimates)

As noted back in May (see “More bullish on UK consumption”) and confirmed by the ECB in August 2021 (see “Economic Bulletin, Issue 5”). The majority of these accumulated savings have accrued to HHs that already have sizeable savings, have higher incomes, and are older. Such HHs typically spend less from any extra savings they accumulate i.e. they have relatively low marginal propensities to consume. The release of these excess savings is likely to be only partial and gradual, therefore.

Impact on monetary aggregates

**M1 as a percentage of M3 in the UK and EA** (Source: BoE; ECB; CMMP)

HH behaviour had a marked impact on money supply dynamics during the pandemic with narrow money (M1) representing an ever-larger share of broad money (M3) in both the UK and EA (see chart above). As an example, overnight deposits contributed 6.8ppt to the total EA broad money growth of 7.6% in October 2021 alone (see chart below).

**Contribution of M1 (ppt) to growth rate in EA M3 (% YoY)** (Source: ECB; CMMP)

This matters because the expansion of broad money during the pandemic reflected the deflationary force of HHs increasing their savings and delaying consumption. Money sitting in overnight deposits contributes to neither growth nor inflation.

HH demand for consumer credit

**Growth rates in consumer credit in the UK and EA (% YoY)** (Source: BoE; ECB; CMMP)

Annual growth rates in consumer credit reached a low point in February 2021 in both the UK (-10% YoY) and the EA (-3% YoY). The rate of decline has narrowed subsequently to -1.0% in the UK in October. In the EA, annual growth rates turned positive two months later in April 2020 (see chart above).

**Monthly consumer credit flows in the UK (£ bn) and EA (EUR bn)** (Source: BoE; ECB; CMMP)

More importantly, monthly flows of consumer credit have been positive for the past six months and reached their highest levels YTD in both the UK (£0.7bn) and EA (€2.7bn) respectively (see chart above).

Conclusion

A moderation in monthly HH money flows and a recovery in demand for consumer credit represent important foundations for a sustained recovery in the UK and the EA. The rise in COVID-related risks comes at a very delicate and unfortunate time, therefore, for the recovery in both regions. It remains too early to say whether recent events will reverse these dynamics in a meaningful manner. The positive news is that firmer economic foundations in both the UK and EA suggest that both regions are in a stronger position to face these challenges than they were a year ago.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Not what the doctor ordered”

Rising UK COVID-19 risks come at an unfortunate time

The key chart

**Trends in monthly HH money flows (£bn) compared to 2019 average monthly flows** (Source: BoE; CMMP)

The key message

The rise in COVID-19 cases and the discovery of the new Omicron variant come at a delicate and unfortunate time for the UK economic recovery (and associated recovery trades).

According to the Bank of England’s latest “Money and Credit” release for October 2021, monthly household money flows were moderating and demand for consumer credit was recovering at the start of 4Q21 – positive trends in two of our three key signals for 2021. So called “faster indicators” such as credit and debit card payments also indicate that positive trends continued into mid-November 2021.

There is never a good time for COVID-related risks to be rising, but it is particularly unfortunate that the threat of renewed uncertainty and restrictions on economic activity has coincided with an apparent inflexion point in the messages from the UK money sector.

Not what the doctor ordered in either a literal or metaphorical sense.

Not what the doctor ordered

The rise in COVID-19 cases and the discovery of the new Omicron variant come at a delicate and unfortunate time for the UK economic recovery and associated recovery trades.

**COVID cases and deaths (7 day MVA) in the UK** (Source: UK government; CMMP)

The number of people who tested positive has risen to 42, 583 according to the latest data provided on 29 November 2021. This represents an increase of 4,574 cases (12%) since the end of October 2021 (see chart above). In response to the identification of the new variant, the UK government has tightened restrictions on face coverings and entry into the UK. The booster programme for vaccines has also been accelerated. It remains too early to know if further restrictions will be required.

Why the timing is so bad

**Key signal #1: looking for a moderation in HH money flows** (Source: BoE; CMMP)

According to the Bank of England’s latest “Money and Credit” release for October 2021, monthly household money flows slowed sharply at the start of 4Q21.

These flows represent a useful proxy for household uncertainty. They peaked at £28bn (6x pre-pandemic levels) in May 2020 and again at £21bn (4x pre-pandemic levels) in December 2020. Note that money flows combine forced and precautionary elements of household savings. During periods of “lockdown” (see black bars in chart above), they averaged 4x their pre-pandemic levels reflecting the added impact of forced savings. Between lockdowns and since lockdowns they have averaged 2x their pre-pandemic levels.

Monthly flows fell from £9bn (2x pre-pandemic levels) in September 2021 to £5bn (1.2x pre-pandemic levels) in October 2021, the lowest monthly flow since February 2020.

**Key signal #2: looking for a recovery in consumer credit demand (£bn LHS, % YoY RHS)** (Source: BoE; CMMP)

UK households borrowed £0.7bn in consumer credit in October 2021, the strongest net borrowing since July 2020 (see chart above). Monthly flows have been positive since April 2021 – seven consecutive months of positive net borrowing. The majority of this borrowing (£0.6bn) was additional borrowing on credit cards, which was also the strongest since July 2020 (£0.9bn).

The annual growth rate in consumer credit remains negative, however (green line in chart above). That said, the YoY growth rate has narrowed to -1.0% in October from -1.7% in September and the low of -9.1% in January 2021.

**Credit and debit card payments (7d rolling average) in aggregate and on delayable goods in relation to pre-pandemic levels** (Source: ONS; CMMP)

So called “faster indicators” such as credit and debit card payments also indicate that these positive trends continued into mid-November 2021. After a sharp recovery in payments in March and April 2021 (following the easing of restrictions) momentum slowed in 2Q21 and 3Q21. Aggregate card payments rebounded in November, however, to reach 103% of pre-pandemic levels (see chart above).

**The build up in excess HH savings (£bn) during the COVID-19 pandemic** (Source: BoE; CMMP estimates)

Spending on “delayable” goods such as clothing and furniture has also recovered to 104% of pre-pandemic levels during November. This matters because spending on delayable goods is a useful indicator regarding the extent to which the £160bn in excess savings built up during the pandemic is returning to the economy via household consumption. The evidence to date is that while the build up of excess savings has slowed, this cash has yet to be spent (see chart above). A positive note to carry into the new year.

Conclusion

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“Enough is enough”

Growth in the wrong type of lending triggers ECB call for policy shift

The key chart

**Growth rates (% YoY) in average RRE prices and loans for house purchase** (Source: ECB; CMMP)

The key message

In its latest “Financial Stability Review” (November 2021), the ECB calls for a policy shift away from short term support measures towards “mitigating risks from higher medium term financial stability vulnerabilities, in particular emerging cyclical and real estate risks.”

This is a welcome development given the extent to which (unorthodox) policy measures have fuelled growth in the “wrong type of lending” to date, and the negative implications this has for future growth, leverage, financial stability and income inequality.

Macroprudential instruments include capital measures (e.g. higher risk weights) and borrower-based measures (e.g. LTV limits). Their adoption varies across the euro area currently, with six economies adopting a combination of both instruments, nine economies adopting borrower-based measures alone, and four economies having no measures in place (Germany, Spain, Italy and Greece).

Further tightening of existing instruments may be required in several economies where RRE vulnerabilities are continuing to build up, but Germany stands out given current house price and lending dynamics, the extent of RRE overvaluation and the absence of targeted macroprudential measures.

“Enough is enough”

Over the past two years, I have been highlighting the hidden risk that unorthodox monetary policies in the euro area (and elsewhere) were fuelling growth in the “wrong type of lending”. From this, I have argued that the resulting shift from productive COCO-based lending towards less-productive FIRE-based lending (see chart below) has negative implications for leverage, growth, financial stability and income inequality in the future.

**Outstanding stock of private sector lending (EUR bn, LHS) broken down by type and share of FIRE-based lending in total lending (%, RHS)** (Source: ECB; CMMP)

Earlier this month, I also argued that it was appropriate, therefore, to expect new macroprudential measures for residential real estate soon. The ECB agrees (finally). In their latest “Financial Stability Review” (November 2021), the ECB is calling for a policy shift away from short-term support towards mitigating risks from higher medium-term financial stability vulnerabilities including residential real estate (RRE) risks.

**2Q21 RRE price growth (% YoY) plotted against level of pre-pandemic valuation** (Source: ECB; CMMP)

The ECB’s analysis includes three key risk factors:

First, nominal house prices grew at 7.3% in 2Q21, the fastest rate of growth since 2005 (see key chart above)

Second, house price and lending dynamics have been much stronger in many countries with pre-existing vulnerabilities. For example, despite above average degrees of over-valuation pre-pandemic (ie, >4% estimated overvaluation), RRE prices grew at above-average rates (ie, >7% YoY) in Luxembourg, the Netherlands, Austria, Germany, and Belgium in the year to end 2Q21 (see chart above)

Third, there is evidence of a progressive deterioration in lending standards, as reflected in the increasing share of loans with high LTV ratios. The share of new loans with LTVs above 90% reached 52% in 2020 compared with only 32% in 2016 (see chart below)

The ECB also notes “high and rising levels of HH indebtedness”, but this is less of a risk, in my opinion, given that the HH debt ratio of 61% GDP is well below the BIS’ threshold of 85% GDP.

**Share of loans with LTV >90% in total new loan production** (Source: ECB; CMMP)

Macroprudential instruments include capital measures (eg higher risk weights) and borrower-based measures (eg, LTV limits). Their adoption varies across the euro area with six economies adopting a combination of both instruments (green bubbles in chart below), nine economies adopting only borrower-based measures (orange bubbles in chart below), and four economies having no measures in place – Germany, Spain, Italy and Greece (red bubbles in chart below, although Greece not shown).

**RRE price growth plotted against mortgage loan growth 1H21 v 1H20. Size of bubbles represents HH debt ratio and colour represents current macroprudential framework** (Source: ECB; CMMP)

Further tightening of existing instruments may be required in several economies where RRE vulnerabilities are continuing to build up, but Germany stands out given the combination of house price and lending dynamics, the extent of overvaluation and the lack of macroprudential measures.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“How much? How productive?”

ECB claims from a CMMP perspective

The key chart

**Annual growth (% YoY) in EA private sector lending split between FIRE-based and COCO-based lending** (Source: ECB; CMMP)

The key message

Is the ECB correct to argue that, “monetary policy measures continue to support lending conditions and volumes” in the euro area? Yes, but only up to a point.

On the supply-side, the APP, PEPP and TLTRO III programmes are having a positive impact on banks’ liquidity positions and overall market financing conditions. On the demand side, borrowing costs are at (mortgages) or close to (NFC loans) historic lows in nominal terms and at historically low and negative levels in real terms. So far, so good.

That said, lending volumes are unexciting in relation to recent trends and previous cycles and currently negative in real terms. No compelling volume story here.

More importantly, current policy measures are supporting the “wrong type of credit”.

Less-productive lending that supports capital gains through higher asset prices (FIRE-based lending) contributed 2.5ppt to the 3.2% total loan growth in September 2021. Worryingly, this is part of longer-term trend. While the outstanding stock of private sector loans hit a new high in September, the stock of productive lending that supports production and income formation (COCO-based lending) remains below its January 2009 peak.

This matters for two key reasons. First, the shift from COCO-based lending to FIRE-based lending has negative implications for leverage, growth, financial stability and income inequality (expect new macroprudential measures for residential real estate soon). Second, it re-enforces the importance of an on-going policy response that remains “fiscal, first and foremost”.

“How much? How productive?”

In its latest “Euro area bank lending survey”, the ECB argues that, “monetary policy measures continue to support lending conditions and volumes” in the euro area (EA). Is this correct?

The supply-side

**“Liquidity-providing” monetary policy operations in EUR bn** (Source: ECB; CMMP)

On the supply-side, EA banks report that “the ECB’s asset purchase programme (APP), the pandemic emergency purchase programme (PEPP), and the third series of targeted longer-term refinancing operations (TLTRO III) continues to have a positive impact on their liquidity positions and market financing conditions” (see chart above).

The demand-side

**Composite cost-of borrowing for house purchases and NFC loans in nominal and real terms** (Source: ECB; CMMP)

One the demand side, borrowing costs are at (mortgages) or close to (NFC loans) historic lows in nominal terms and at historically low and negative levels in real terms (see chart above). In September 2021, the composite cost-of-borrowing for house purchases hit a new low of 1.30% (-2.03% in real terms). The composite cost of borrowing for NFC’s was 1.48%, 0.8ppt above its March 2021 low, but a new low in real terms (-1.86%).

How exciting is the volume story?

**Annual growth (% YoY) in private sector lending in nominal and real terms** (Source: ECB; CMMP)

Lending volumes are unexciting in relation to recent trends and previous cycles and currently negative in real terms. Lending to the private sector grew 3.2% YoY in September 2021 both on a reported basis and after adjusting for loan sales and securitisation. In nominal terms, lending growth has been relatively stable since March 2021 but is 2ppt lower than the recent peak growth recorded in May 2020 (5.2% YoY). Lending growth in the current cycle is relatively subdued, however, in relation to past cycles (see chart above). Furthermore, in real terms, lending in September fell slightly when adjusted for HICP inflation.

No compelling volume story here.

Loan growth from the ECB perspective

**Annual loan growth with ECB breakdown by borrower** (Source: ECB; CMMP)

As an aside, the ECB typically classifies lending by type of borrower – households (HHs), non-financial corporations (NFCs), non-monetary financial corporations (NMFCs) and insurance companies and pension funds (ICPFs) – with further subdivisions based in the type of HH borrowing and the maturity of NFC borrowing.

In September 2021, HH lending contributed 2.2pt to the total 3.2% YoY growth, essentially mortgages. NFCs and NMFCs contributed 0.6ppt and 0.5ppt respectively but lending to ICPFs made a slight negative contribution of -0.1ppt.

Loan growth from the CMMP Perspective

CMMP analysis presents an alternative classification based on the productivity of credit use. Broadly speaking, lending can be spilt into two distinct types: lending to support productive enterprise; and lending to finance the sale and purchase of existing assets. The former includes lending to NFCs and HH consumer credit (and other HH lending) and is referred collectively here as “COCO-based” lending (COrporate and COnsumer). The latter includes loans to non-bank financial institutions (NBFIs) and HH mortgage or real estate debt and is referred collectively here as “FIRE-based” lending (FInancials and Real Estate).

Note that COCO-based lending typically supports production and income formation while FIRE-based lending typically supports capital gains through higher asset prices.

Supporting the “wrong type of credit”

**Annual loan growth with CMMP breakdown by productivity of use** (Source: ECB; CMMP)

Viewed from a CMMP perspective, current policy measures are supporting the “wrong type of credit”. Less-productive lending that supports capital gains through higher asset prices (FIRE-based lending) contributed 2.5ppt to the 3.2% total loan growth in September 2021 (see chart above).

**Annual loan growth broken down by productivity of use since September 2006** (Source: ECB; CMMP)

Worryingly, this is part of a longer-term trend. As can be seen from the chart above, higher volumes in the pre-GFC period were more balanced with more-productive COCO-based lending accounting for 56% of total outstanding loans. Today, that share has fallen to 48%.

**Outstanding stock (EUR bn) of COCO-based lending** (Source: ECB; CMMP)

As noted in August 2021, while the outstanding stock of credit hit a new high in September, the stock of productive COCO-based lending (€5,470bn) remains below its January 2009 peak (€5,517bn). In other words, the aggregate growth in lending since early 2009 has come exclusively from FIRE-based lending which now accounts for 52% of the outstanding stock of loans (see chart below).

**Outstanding stock (EUR bn) of COCO-based and FIRE-based lending** (Source: ECB; CMMP)

Conclusion

The ECB is entitled to argue that monetary policy measures have supported lending conditions and volumes. However, current lending volumes are unexciting in relation to previous cycles and negative in real terms. Policy is also supporting the “wrong type” of credit – fuelling FIRE-based lending rather than productive COCO-based lending that supports production and income formation.

This matters for two key reasons. First, the shift from COCO-based lending to FIRE-based lending has negative implications for leverage, growth, financial stability and income inequality. During the COVID-19 pandemic, some national authorities eased macroprudential measures for residential real estate (RRE). This week, however, the ECB argued that further macroprudential measures should be considered where RRE vulnerabilities continue to build up. (Watch this space.) Second, it re-enforces the importance of an on-going policy response that remains “fiscal, first and foremost”.

Please note that the summary comments and charts above are extracts from more detailed analysis that is available separately.

“A return to abnormality”

Looking behind the OBR’s forecasts of improving UK government finances

The key chart

The key message

The OBR’s forecasts of a rapid improvement in UK government finances (the good news) assume unusual behaviour on the part of the UK private sector and the RoW and imply a “return to the abnormality” of sustained domestic UK deficits counterbalanced by significant and persistent current account deficits (the bad news). Viewed from a sector balances perspective, the risks appear tilted to the downside ie, government finances may not recover as quickly as forecast.

The OBR published its latest “Economic and fiscal outlook” on Wednesday, 27 October 2021. The Office recognised the positive impact of the UK government’s fiscal response in protecting household and corporate incomes during the pandemic and through 2021. Looking further forward, the OBR forecasts a rapid improvement in the government’s finances, with borrowing falling back below £100bn next year and stabilising around £44bn (<2% of GDP) in the medium term.

The forecasts assume certain behaviours from the other economic sectors, namely the domestic private sector (households and corporates) and the RoW. Under the latest forecasts, the UK household sector, which is typically a net saver, shifts (unusually) to a net deficit position over the forecast period. Given the high level of existing debt, this requires HHs to sustain historically low savings ratios of c.5%. The NFC sector, which is typically a net borrower, returns to a deficit position in 2Q22 and then runs relatively high deficits of c.3% of GDP over the rest of the period. To offset these twin domestic deficits, the RoW runs equal and historically high counterbalancing surpluses vis-à-vis the UK.

In short, the forecast improvements in UK government finances rely on dynamic adjustments by other economic sectors and unusual patterns of behaviour beyond that. This suggests obvious risks that the forecasts will not be met. Furthermore, the assumed end-result is one where sustained, twin domestic deficits are counterbalanced by “significant and persistent current account deficits. The OBR describes this as a “return to more normal levels”. CMMP analysis suggests it is anything but.

“Returning to abnormality”

The OBR published its latest “Economic and fiscal outlook” on Wednesday, 27 October 2021. The outlook sets out the Office’s forecasts for the economy and public finances to 2026-27 and provides an assessment of whether the Government is likely to achieve its fiscal targets.

**The impact of COVID on UK sectoral net lending postions – % GDP, rolling annual average** (Source: OBR; CMMP)

The OBR recognised the positive impact of the UK government’s fiscal response in ensuring that household (HH) and corporate (NFC) incomes did not fall “nearly as much as this expenditure or output” during the pandemic.

Government net borrowing rose to 12.5% of GDP in 2020, to pay for the fiscal support (see chart above). The HH net surplus rose to 7.8% of GDP, versus a 1Q04-1Q21 average of 2.5%. The NFC deficit moved into balance versus a 1Q04-1Q21 average deficit of -0.8% of GDP. Hence, the private sector’s net surplus rose to 7.8% of GDP versus a 1Q04-1Q21 average of 1.7% of GDP. These imbalances have persisted into 2021 as restrictions and support remained in place, albeit to a lesser degree.

**UK public sector net lending – % GDP, rolling annual average** (Source: OBR; CMMP)

Looking forward, the OBR forecasts a rapid improvement in the UK government’s financial position (see chart above, which compares the latest forecasts with the previous version), with borrowing falling “back below £100bn next year, declining more slowly thereafter to stabilise at around £44bn (1.5% of GDP) in the medium term.” Such and improvement would be sufficient for Rishi Sunak, the Chancellor of the Exchequer, to meet his fiscal target of getting “underlying debt falling as a share of GDP by the third year of our forecast (2024-25)”.

Domestic government balance + domestic private balance + foreign balance (must) = zero

These forecasts assume certain behaviours from the other economic sectors, namely the domestic private sector and the RoW. Recall that, from national accounting principles (see identity above), we know that the deficits run by one or more economic sectors must equal surpluses run by other sector(s).

**UK household sector net lending – % GDP, rolling annual average** (Source: OBR; CMMP)

Over the forecast period, the UK household sector, which is typically a net saver, shifts (unusually) to a net borrowing position. The OBR expects the HH net surplus to peak at 10% GDP in 1Q21, fall to 5.7% of GDP by 4Q21 and then (unusually) move into deficit by 4Q22 and for much of the forecast period out to 1Q27. Note that for any sector to run a deficit it must either increase its borrowing and/or reduce its accumulation of net financial assets.

**UK HH and NFC debt ratios – % GDP** (Source: BIS; CMMP)

Given the high level of HH debt, this requires HHs to sustain historically low savings ratios. At the end of 1Q21, the UK HH debt ratio was 91% of GDP, 6ppt above the BIS threshold limit and only 5ppt below its all-time high (see chart above). This suggests that HH are unlikely to increase borrowing levels significantly over the period.

Unsurprisingly, therefore, the OBR forecasts place a greater emphasis on HH savings. First, they assume that HHs will spend c.5% of the excess savings built up during the pandemic, a reasonable assumption. Second, and following on from this, they assume that the HH savings ratio will fall rapidly and stabilise at or around historic lows of c.5%, a more aggressive assumption (see chart below). History suggests that the risks to these assumptions lie clearly to the downside.

**Historic and forecast HH savings ratio** (Source: OBR; CMMP)

The NFC sector, which is typically a net borrower, returns to a deficit position in 2Q22 and then runs relatively high deficits of c.3% of GDP over the rest of the period (see chart below). This compares with a 1Q04-1Q21 average deficit of just under 1% of GDP. Again, given the current level of NFC borrowings the risks to these forecasts and to the level of NFC investment appear tilted to the downside.

**UK non-financial corporation sector net lending – % GDP, rolling annual average** (Source: OBR; CMMP)

To offset these twin domestic deficits, the RoW runs equal and historically high counterbalancing surpluses vis-à-vis the UK. The net surplus of the RoW is forecast to increase fro 3.3% of GDP currently (in-line with historic average) to 5.3% in early 2023 and then stabilise at c.4.5% for the rest of the forecast period. In other words, the UK is assumed to be increasingly reliant on the RoW as a net lender.

**RoW sector net lending – % GDP, rolling annual average** (Source: OBR; CMMP)

Conclusion

The forecast improvements in UK government finances rely on dynamic adjustments by other economic sectors and unusual patterns of behaviour beyond that. This suggests obvious risks that the forecasts will not be met.

Furthermore, the assumed end-result is one where sustained, twin domestic deficits are counterbalanced by “significant and persistent current account deficits. The OBR describes this as a “return to more normal levels”. CMMP analysis suggests it is anything but.

Please note that summary comments and charts above are extracts from more detailed analysis that is available separately.