Confessions - 1

I was an economist before I knew the word. Born in an industrial town in West Yorkshire, born, actually, in what has a good case to be thought of as the industrial town of the region - so much a pattern of spontaneous industrial development that a biography of the World Bank put its name on the cover of what every society could aspire to - how could I not be an economist?

Economic history was unavoidable. Go to a pub in my village and you’re in the place the Luddites stopped over as they fled their murder of a local mill-owner. Go to the swankies golf club, and eventually you’d discover that in Victorian times the steward at the grand house there was Richard Oastler, a prime mover behind the factory acts of the 19th century outlawing child labour. But also every morning count the number of chimneys on the way to school, because as the mills closed down, so the forest thinned out and thinned out. And my family? Yes, one of the mill-owning families, and my childhood memories include the too-often lament from my father: ‘trade’s bad’.

This is a true story: when I was twelve, my father took me round one of the knitting sheds, put his father hand on my shoulder, looked me in the eye and said: ‘Take a good look around son, because one day. . . . none of this will be here.’

Of course, he was right: very little remains of West Yorkshire’s once mighty textile industry. About 10 years later, I was running around Guangdong province as its own industrial revolution got underway. And there in Dongshan (I think), I was taken round a knitting shed. Same product, same Italian machines, same dust, same business. Somewhere in Guangdong, right now, I’ve no doubt a father is coming home tired, and lamenting to his family ‘trade’s bad’.

So my engagement with economics has always been not so much instinctive (though it is that) as actually visceral.

It turns out this is unusual. I get surprised by how people react to my work. Recently I was taken aback when I was introduced at an investment conference as ‘unusual, because he’s more of a philosophical economist than most’. More worryingly, another client quite casually told me ‘of course, you’re pretty much obsessive/compulsive about this stuff’.

My take: if you’re going to be visceral about economics, you’d better be philosophically aware, and you’d better be pretty obsessive about it.

I think this introduction is necessary because my Confession is also radical: although there’s a good appreciation that economics has clocked up a record of failure, there’s still a profound unwillingness to acknowledge how deep the roots of this failure go. I have become convinced that so utterly fundamental is its failure that it is no longer a question just of models being wrong or inadequate. The problems economics as a thought-game face will not, and indeed, cannot be solved by constructing better models. All the AI in the world cannot save it.

Why? Because many of the fundamental concepts of economics, the very words we use when we talk or write economics, are vacuous. Vacuous as in ‘empty of content’, carrying meaning only within the specific closed language game of academic economics. Quite unknowingly, in crucial and central ways, it has morphed into a sort of medieval metaphysics, the sort where exceptionally intelligent and dedicated people devote their lives to working out the number of angels able to dance on the head of a pin. If the fundamental concepts are emptied out of genuine meaning, genuine reference to the world it purports to explain, no amount of intellectual dedication and subtlety can rescue the endeavour.

If economics is to rescue itself, if it is to be a help rather than a hindrance in understanding and furthering mankind’s aspirations, it is going to have to tear itself down, right down to the roots of language itself.

This is what I will try to do: these are my confessions.

China: Trouble and Strikes

Regardless of the underlying issues of economic and strategic competition, the immediate dynamics of the US-China trade/investment/IP face-off look like poker: who will blink first? In this game, the immediate economic hit suffered by both China and the US matters less than the political pressures they generate. Crucially, if, for example, manufacturing companies find themselves unable to maintain payrolls, or are late in paying wages, will this pose a challenge to 'weiwen' (trans: maintaining social stabilty) policies?

Getting a handle on this requires two things: first, an indicator of the degree of disruption being felt in the industrial economy; and second, a measurement of the social/political response.

I track momentum shifts in the industrial economy by measuring movements vs 5yr seasonalized trends in exports (both Rmb and volume), industrial production, and electricity production. In May, industrial production growth slowed to 5% yoy with a monthly movt 0.5SDs below trend; electricity production slowed to just 0.2% yoy, with a 0.6SD deflection below trend, and exports managed a 0.8% yoy gain with a 0.5SDs deflection above trend. It is not easy to see beyond the dramatic volatility which always plagues China's 1Q data, but the overall message is that so far the industrial economy is weathering the storm no worse than one might expect.

remi cn.jpg

In assessing the likely political fall-out, I have used data from the China Labour Bulletin, and in particular its database of strikes. Historically, Guangdong has been the most province with most reported strikes (1,415 strikes recorded since 2014), but other provinces with a track record for relative labour militancy are (in order): Jiangsu, Henan, Shandong, Sichuan, Shaanxi, and Zhejiang. These provinces, and Shanghai (peaceable - only 235 strikes since 2014) are the ones I have totalled to provide a proxy for overall strike activity.

Strikes are always costly things of last resort, and we can assume that both management and labour will make great efforts to avoid them. If so, then rather like bankruptcies, one would expect to see them only after problems have persisted for a long time. Consequently, I've compared the incidence of strikes with 12ma movements of my industrial momentum indicator.


I draw two conclusions from this chart:

First, there is absolutely no sign of any upsurge in labour militancy yet. In fact, during Jan-May, this database counted only 299 strikes, down from 375 in the same period last year. Moreover, not only is the number of strikes falling, but it is doing so from a historically low base.

Whatever political pressures Xi Jinping may feel from US-China relations, pressure from labour markets is not yet one of them.

Second, the experience of 2014-2015 nevertheless tends to confirm that China can expect an outbreak of labour militancy if the breakdown in US-China relations only if it involves heavy costs to China's industrial economy over an extended period (say, 18 months minimum).

The Modest and Excellent Mr Powell

Jerome Powell's remarks last week accompanying the Fed's decision to stand pat on interest rates and pause the contraction of its balance sheet seem to me to be unusually excellent. His willingness to eschew grand theories of either economics or central banking but rather to laud the qualities of patience whilst keeping a vigilant eye on the economic data, incomplete though it always will be, is a welcome outbreak of conceptual modesty and good sense. More, his overall observations seem sound: headline inflation is indeed in retreat this year, and whilst there was an unexpected slide in economic data around the turn of the year, the measures I use to assess cyclical pressures (return on capital indicator, capital stock growth, Kalecki profits, labour productivity, private sector savings surplus) are not flashing red.

Indeed, not only do they not suggest a marked slowdown this year, they don't suggest a recession in 2020 either, despite the genuinely ominous inversion of the 2yr - 3m yield curve during the last week.

In this context, what are we to make of the FOMC's decisions? First, let's consider the attitude towards the size of the Fed's balance sheet. Since 2017, the Fed has been shrinking its balance sheet by not re-investing all the securities it holds which mature. In practice, during the last 12 months that has resulted in the balance sheet shrinking on average by $36bn a month. The rate of this 'run-off' is to slow from May, and cease entirely in September. After September, further movements of the Fed's balance sheet will be made primarily in response to the normal exigencies of conducting monetary policy, which I take to mean the desire to tweak the level of bank reserves.

Pause a moment right there: savour the lack of bombast, the absence of messianic certainty and mission. Doesn't that feel good? Doesn't that feel . . . novel?

Now consider the context: 2018 was a year in which a sharply expansionary fiscal policy was offset by a sharply contractionary monetary policy. Thus, every month President Trump's fiscal deficit had the effect of putting more dollars into private hands than the government took out; but at the same time, the Federal Reserve's shrinking of the balance sheet meant it kept taking money back from the private sector. As far as the private sector is concerned, the positive cashflow from fiscal policy is at least partly reversed by the cash grab by the Federal Reserve.

How does this balance? In the 12m to end-February, the fiscal deficit came to $932bn, whilst the contraction of the Federal Reserve balance sheet amounted to $430bn.

fed assets.jpg

With one offsetting the other, the balance of fiscal deficit minus balance sheet contraction left a positive cashflow to the private sector of $502bn. This was, in fact $147bn less than $649bn net positive cashflow seen in the 12m to February 2018. These numbers rather undermine the belief that the strength of the US economy in 2018 was primarily the result of the rising fiscal deficit, opening the possibility that what was doing the lifting was the supply-side implications of fiscal policy, rather than mere multiplier effects.

fed and fiscal.jpg

Turning now to the slump in data seen during the turn of the year. Tracking this is made more difficult by the lingering tailback of data which piled up during the government shut-down. However, what data we have tells us retail sales ex-autos fell 0.1% mom in November and 2.1% in December, with the broader measure of personal spending falling 0.5% mom in December, despite a 1% rise in personal income. In response, December's manufacturing production fell 0.5% mom and this was followed by a 0.4% fall in January. Regional manufacturing surveys for January showed marked weakness in the Dallas Fed survey, the Richmond Fed survey, the Chicago PMI and the Empire State manufacturing index. The weakness extended into February in the Kansas Fed survey and the Philadelphia Fed survey, with only partial rebounds elsewhere.

This weakness was responding to the opening of a disequilibrium between industrial supply and demand which had opened up in 4Q18. Subtracting movements in momentum of manufacturers' demand indicators (sales, inventories) from supply indicators (manufacturing output), the chart below tracks how that disequilibrium opened up, reversing the position from earlier in the year. There are two things about this to notice. First is the reversal of the nature of the disequilibrium: from manufacturers struggling to keep up with demand in the first half of the year, to oversupplying the market in the final quarter of the year. The second thing to notice is that the disequilibrium, though unexpected, is actually rather modest.

industrial equilibrium.jpg

Nonetheless, the impact of the disequilibrium showed up where one would expect it: in inventory positions. Manufacturers' shipments fell consistently between October and January, whilst their inventories rose. In January, for example, shipments fell 0.4% mom but inventories rose 0.5%. As a result the inventory/shipment began to rise quite sharply, reversing the falling trend seen since 2016.

man invent ship.jpg

Again as one would expect, the impact was felt more keenly by wholesalers: their economic function is, after all, precisely to smooth short-term volatilities in supply and demand. Inventory holdings began to rise quite sharply in August 2018, and have continued to rise since: in January wholesalers' inventories rose 1.2% mom. By contrast, wholesalers' sales fell continuously between October and December, though they rose 0.5% in January. The result is that wholesalers' inventory/shipment ratio by January had risen to the highest point since July 2016.

wholesale inv ratio.jpg

The rise in these inventory/shipment ratios tells us that manufacturers' disequilibrium has not yet been fully resolved: we should expect further signs of production weakness in the short term.

The mechanics of that disequilibrium are easy enough to track, but the underlying cause is more difficult to fathom. Partly this is because we (still) do not have the full personal income and personal spending data beyond December. However, what December's numbers show is dramatic: whilst total income rose 1% mom and disposable income rose 1.1%, personal spending fell 0.5% mom, implying a Grinchier Christmas than any seen since December 2008 (when income was down 1.1%). Spending on foods fell 1.9% mom and spending on services rose 0.1% only.

Meanwhile, interest rate payments rose 1.4% mom, and personal saving jumped 25.4% mom and 28.2% yoy, rising to 7.6% of disposable income from 6.2% in December 2018.

I have previously suggested that movements in interest payments, and movements in the savings ratio together describe movements in the revealed financial stress felt by households. Since 2016, this measure of household financial stress has been rising, gradually and gently, true enough, but still rising. One interpretation of the extreme financial caution seen in December's jump in savings is that it acts to de-fuse some of that financial stress, allowing the overall ratio to stabilize.

financial stress.jpg

If this interpretation is correct, it tells us that although the industrial disequilibrium is real but modest, it was exacerbated by the underlying signals of financial stress from the household sector which remain fundamentally unaddressed. (And which has its roots ultimately in the historically extreme ratio of profits to wages.) In other words, there is a latent fragility in the current US economic structure which can be expected to resurface periodically, but which does not necessarily imply imminent recession.

In these circumstances, the virtues of patience and data-vigilance accompanying a fundamental lack of aggression in either economic modelling or monetary policy conviction seem self-evident.

With luck, it may finally signal the end of an era in which central bankers were completely unjustifiably elevated to the status of omniscient and omnipotent economic superheroes. That was better economic governance lies. . . .

End of Days

This is a long piece - probably too long to be read easily in a blog post. A pdf of the article is available here. Might be a good idea. . .

Recently, investors have asked me repeatedly whether we are staring at the ‘End of Days’. After some thought, my answer is ‘Yes’. This longish piece is an attempt to explain and elaborate what I mean by it, why I think it is upon us, and where we go from here.

First, what do I mean by it? I mean that the assumptions and policy reactions underpinning economic policy, and generating outcomes both for the economy and for financial markets, are exhausted. Rather than solving problems, the default conventional wisdom is now compounding problems. As a result, the incentive structures within which we think and work, currently are more likely to result in bad choices rather than good ones. Our attempts to project a future based on those familiar stimuli and familiar assumptions, are likely to be either ineffective or, at worst, actively mislead us.

If this seems a baffling or obscure way of explaining what I mean by something as apocalyptic as End of Days, I can perhaps make things clearer by explaining what it was like last time we entered such a phase (of economic policy, of financial markets, of economic wisdom). I was born in 1961, and for better or more probably for worse, I have been trying to understand economics, and why economies go wrong, since I was about 12 years old. (Yes, I was that tiresome and precocious child.) I was initiated into this by the constant struggle with which my father attempted to keep the family textile firm alive. By the mid-1970s, as he explained the way various demand and supply-side forces affected his business, it was just abundantly clear that the bastardized late-period ‘Keynesian’* policies of government intervention were no longer capable of addressing the problems they had fostered. Indeed, they were observably doing more harm than good, even as he was paid subsidies to maintain his payrolls.

Nonetheless, all public commentary was framed within that ‘Keynesian consensus’, and, when people started teaching me ‘economics’, first at school and then at Oxford, it was that framework which still crowded out the syllabus.

But I got lucky: in the late 1970s, whilst I was still at school, I was bought Hayek’s 1975 book of essays. With its emphasis on how the microeconomics of firms’ production could be distorted into inefficiency by transitory inflationary demand, its account of the damage done to investment patterns by ‘Keynesian inflation’, and, most of all, its insistence that the whole justification for markets was their ability to discover information which was discoverable in no other way, it was a revelation. I cannot tell you how exciting it was to figure out just how things could go wrong even when marginal revenue equalled marginal cost!. It was a revelatory because it allowed me to understand how and why the current understanding of economics had become damaging. And, almost literally, I could see its truth written on the worry-lines of my father’s face.

Whatever one may think of his legacy, Hayek had correctly identified the End of Days.

Ultimately, though, the test was not whether Hayek was right in all his analysis and policy prescriptions. The test was that the answer to the question ‘if we carry on with the policies we’ve always used,, will things get better’ had become obviously and emphatically ‘No’.

It took a few years of compounding misery (aka ‘the ‘70s’) before the End of Days was recognized in the election of Margaret Thatcher’s Conservatives in 1979, and more years still before the collection of assumptions, attitudes, errors, indulgences and blind-alleys which resulted hardened into the sort of settled consensus which the Keynesian consensus had been before it.

It is in this sense that I think we have reached another End of Days. If we ask ‘will the policy defaults, underpinned by economic assumptions, which have guided us over the last few decades, solve the problems currently facing our economies?’, then I think the answer is emphatically ‘No.’ Doubling down on the globalization of the economy, global financialization (by which I mean that the major recipient of global credit creation turns out to be the financial industry itself), global ‘free trade’ and ‘flexible labour markets’ at this stage is likely to compound current miseries, not relieve them.

At this stage, I need to ask for your patience and indulgence: of course I understand that these descriptions are imprecise and perhaps even contentious. That is partly a pretty inescapable product of some of the conceptual and practical errors obfuscated in the language generally in play in economic and financial discussions. Things may get more precise as the argument develops. In fact they must, because some of those errors concealed in the obfuscatory language turn out to be important.

Starting Point: The Hinge of the Global Economy

The logical place to start in describing the exhaustion of the current model of globalization/financialization is in recognizing the central dynamic relationship which dominates current global production and investment. The central hinge upon which the global economy turns is the relationship, very broadly, between Western demand and Asian production. This relationship between global supply and global demand determines not only global current and capital flows, but is also inescapably a major factor in determining domestic financial activity (saving, borrowing, investment) on both sides of the equation. Although there have been periodic attempts to believe that NE Asia is decoupling out of this relationship, the evidence suggests, if anything, that the relationship has become tighter over time. The link can be illustrated by comparing changes in G3 import demand and NE Asia export performance.

g3m neax.jpg

If, in fact, we are facing the End of Days, we need to ask if this applies at both ends of this central relationship, or whether the breakdown is confined to either the Western Demand end of the model, whilst the East Asian Supply model remains vigorous and viable?

The Supply Side Issue

It is easiest to start at East Asian Supply side of the equation, because the central actor here is China, and it has been obvious to all - and not least to China’s leadership - that the model which drove China’s historically-unprecedented rise has been pressing against its limits. More specifically, it was starting to generate problems which were genuinely threatening to its continued viability.

China has been the largest ever practicing exponent of exogenous growth theory. Whittled down to its core, this theory asserts that a major reason why one country is poorer than another is because its productivity is lower, which in turn is a function of the amount of capital each worker brings to the task. Hence, rapid growth and rapid productivity growth can be generated by a policy of financial repression to discourage consumption and provide a plentiful flow of cheap savings for investment. At the early stage of the model, rapid accumulation of surplus savings to fund capital accumulation is what matters above all, certainly more than concerns about return on that capital. With domestic consumption restricted and relatively indiscriminate capital stock growth accelerated, the country will inevitably produce more than it can consume. The surplus production, then, is exported, with the assumption being that there will always be sufficient exogenous demand to soak up the surplus production. Note that excessive trade surpluses are not the aim of the policy, but rather its inevitable and logical outcome.

The model ultimately develops several problems. First, when the economy approaches its ‘technological barrier’ then, in association with the law of diminishing returns, it becomes more and more expensive to generate addition output. This is a complex area which is not fully avoided by simply discovering access to the latest technology, or even by ensuring the workforce is sufficiently educated to deploy that technology. For ‘technological barriers’ will also tend to include a series of institutional factors, including the predictability of the legal system and legal protections for both physical and intellectual property.

Second, as the technological barrier is approached, and further relative progress becomes more and more expensive, so the hazards of neglecting return on capital begin to be discovered. At first this can be seen simply as an ever-rising demand for leverage in response to falling returns. If this demand is always indulged, it must eventually morph into systemic bad-debt problems and systemic financial weakness as banks discover not only have they a load of bad loans on their books, but that the pricing of other financial assets has also been wrong.

And third, owing simply to China’s size relative to the rest of the world, the assumption that all surplus production can be painlessly exported will come into question. The limits can be expected to be discovered sector by sector,

After decades of unprecedented success, it is clear that China is coming up against its technological barrier, and that the long-term problems inherent in the exogenous growth model have arrived. The evidence surfaces in a number of areas, and tells the story consistently.

At the crudest level, my return on capital directional indicator, which expresses nominal GDP as a flow of income from a stock of fixed capital, has shown two separate periods of decline. The first period of decline showed up in the later 1990s, and although this decline was arrested throughout the mid-2000s, the second decline set in in the aftermath of China’s credit-splurge in came in 2009/10.

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More directly, we can measure how securing market share of Northeast Asia’s exports became more and more expensive in terms of accumulating capital stock. The following chart compares the relative build-up of China’s capital stock and its share of Northeast Asia’s exports. Between 1990 and the early 2000s, the equation was fairly simple: build capital stock in part by encouraging industrial relocation out of Japan, S Korea and Taiwan, and export market share was gained accordingly. However, by the later 2000s, the numbers were already showing that it was becoming increasing expensive to ‘buy’ market share simply by raising relative capital stock.

capstock and xshare.jpg

As the second chart shows, the gains became more difficult to sustain after around 2005, and after the financial crisis China has had to throw more capital stock into the competitive battle than the rest of NE Asia in order to win or even sustain market share of exports. That decline has not yet stabilized.

marg x and capstock.jpg

The natural result is that the efficiency of finance has deteriorated sharply. Even taking into account the recession of 2000/2001 in the five years to 2005, an extra Rmb 1bn in bank lending to the economy was associated with approximately Rmb 1bn of extra nominal GDP. Subsequently, that relationship has soured dramatically, and despite attempts to discipline bank lending, in the five years to 2018, Rmb 1 bn in extra lending was associated with only Rmb 480 mn in extra nominal GDP.

marginal efficiency of finance lt.jpg

The good news is that China’s authorities are extremely clear-eyed about the problem, having fretted about it, and laid plans to deal with it, for at least a decade. The bad news is that making the change from this sort of exogenous growth model to one which is driven by consumer demand and return on capital is about the trickiest traverse in economic governance. Doing it successfully whilst avoiding a major financial crisis is rare. Nevertheless, this is what China is trying to do.

This is recognition that at least one side of the global economic model - the China supply-side - has reached its limits.

But merely laying out how China’s growth model is running up against its inevitable limits actually misses the whole point of the exercise: the model has been fantastically good at lifting hundreds of millions of Chinese out of grinding poverty and into material decency, and even affluence. I suspect that no such mass alleviation of poverty has been achieved ever in the history of mankind. It is a genuinely stunning achievement.

And yet,this success is also being challenged and to some extent undermined by a problem which is also undermining the demand side of the picture: rising inequality. Taking data from the Standardized World Income Inequality Database (, the rise in China’s Gini coefficient has been dramatic. This measure of income inequality pitches china as having the most dramatic inequality of any significantly industrialized economy: more unequal than Singapore (where the Gini coefficient runs at 38.6) and only slightly less unequal than Hong Kong (Gini coefficient of 41).

gini table.jpg

Below I shall argue that there are economic costs to widening inequality, particularly if profits are to any major extent dependent on domestic demand. I cannot honestly claim to know how this inequality is experienced in China, or to what extent it has become a significant factor depressing the potential for generating profits from domestic demand. I simply do not have the necessary data.

However, it is said that the unofficial neologism ‘qiou’ has has been dubbed the word of the year for 2018. It is a mashup between three characters - 'qiong', meaning poor, 'chou', meaning ugly, and 'tu', meaning earth. Taken together, the character essentially means "poor as dirt and ugly." ‘Dirt poor’ - the word of the year in China.


Western Demand: Profits & Wages

The symptoms of the exhaustion of China’s exogenous growth model are easy to understand, easy to illustrate, and not controversial. What about the other side of the supply and demand equation: Western demand? Here the problem is more difficult to articulate and demonstrate. However, an initial stab at the locating the problem is to recognized that China’s production has been satisfying Western demand which previously would have been met by Western production. To some extent it is true, then, that elements of Western production have been idled as capacity has relocated to China.

So what? After all, the argument goes, if China offers cheaper goods than domestically-produced ones, then the consumer gets a better deal, releasing more spending power for other areas of economic activity. Everyone benefits from discovering and exercising comparative advantages in free trade. And if globalization results in rising profits for domestic companies, those profits will be recycled back into the economy via the financial system - Say’s Law after all ensures it. Eventually, globalization drives up outcomes for everyone.

If that argument is correct, then talk of the End of Days is mere panic-mongering. But the problem with Say’s law is that as inequality rises, so its smooth operation becomes increasingly dependent on an effective and efficient financial sector being able to re-allocate the savings surpluses of the rich in a way which compensates for the demand shortfall of the poor. And here we already find two problems: first, that the financial systems of the West have tended to re-allocate the savings of the rich around the globe, rather than in the domestic economy. Second, the GFC demonstrated quite effectively that the West simply doesn’t have an effective and efficient financial sector.

But there is a third problem with assuming that Say’s law will alleviate the problems of the displaced West. For it assumes that the problem to be solved is essentially one of maturity mismatch, in which the savings of the rich can be lent to the recently displaced who are suffering an unexpected but essentially temporary disappointment in their income. But if the problem is not cyclical or temporary but is essentially the result of cyclical change, lending to the displaced sector of the Western economy is no answer. Rather, the accumulating household debt accelerates the underlying pauperisation of those displaced by ‘globalization.’

There are also terrible problems with the ‘comparative advantage’ assumptions, which are commonly heard to justify the ‘short-term displacements’ of productive activity from the West to the East. The argument of comparative advantage upon which the doctrine of the benefits of free trade is based is among the most elegant in economic theory. It is hugely appealing. But in a world in which capital, knowledge, technology and skilled labour are all globally mobile, these arguments simply fail. In fact, given the proper incentive structures and sufficient provision of capital, almost any ‘national comparative advantage’ can be bought and constructed. This is, after all, the assumption at the very heart of ‘exogenous growth theory’.

Moreover, to the extent that these days ‘comparative advantage’ is found mainly the economic benefits generated by industrial clusters, there’s a likelihood that competitive advantage can and will be bought outright.

The alarming implication is that right now ‘free trade’ does not necessarily grant the win-win result for both economies as is commonly assumed. Indeed, it is quite likely to result in a win-loss result.

For both these reasons - the likely absence of Says Law, and the breakdown of free trade arguments - this is the right time to acknowledge a crucial part of the evidence which tends to be overlooked in our neck of the woods. It is time to think about the rise in income inequality.

The Global Rise of Income Inequality

A starting point here is to acknowledge the rise in the Gini coefficient, which tracks the cumulative proportions of the population against cumulative proportions of income they receive. Perfect income equality results in a score of zero, perfect income inequality (ie, one person receiving all the income) results in a score of 100.

gini coefficients.jpg

Everywhere, Gini coefficients have risen since 1980, with the rises being particularly sharp in China, Japan and the US, and relatively muted in the Eurozone (proxied here by the average of Germany, France, Italy and Spain). In China and the UK, and perhaps in Japan also, there are signs that the coefficient has peaked. In the UK at least, this decline since 1999 is almost certainly a reflection of the total rise in the rate of employment, from an average of 72% in 1999 to 75.5% in the latest 12m.

However, it may be that broad measure of the Gini coefficient is not capturing the structural change and challenge of inequality. For the problems associated with rising inequality, and the political repercussions it is bringing, may be accentuated by new patterns which are fundamentally regional, rather than simply ‘class’ based. This is certainly suggested by the geographic fissures expressed in the current wave of Western political discontent, seen in the rebellions in the US (the Trump presidency), France (the gilet jaunes protests), Germany (the rise of the AfD) and Italy (etc).

But this is not easy to demonstrate. However, data from the UK provides one way of illustrating the way in which rising regional inequality is breaking down the cohesion and coherence of the ‘national’ economy. In a ‘coherent sample’ of regional income distribution in a single economy one would expect to see a basically Zipfian distribution pattern, with a tight and predictable relationship between the size of income and its relative frequency, albeit with exceptions at the top and bottom ends of the distribution. The UK has produced annual surveys of average household income broken down into 179 regions since 1997. The 1997 survey expressed a basic Zipfian distribution pattern reasonably well.

(See this piece.)

1997 coherence.jpg

This coherence was maintained over the next decade. But by the 2016 survey, the relationship was looking extremely ragged. Indeed, I suspect if you put an AI engine to work on the data, it would suggest at least two different relationships emerging here.

2016 coherence.jpg

If rising regional inequality is undermining the assumption that the UK is, economically, a ‘coherent sample’ it has profound implications both for politics and rational economic policy-making. The political implications are obvious: the web of commercial and financial relationships by which a society is bound together is coming apart. Or to put it bluntly, what happens in, say, Weybridge no longer has economic implications for, say, Leicester. (My apologies for picking on Leicester: it features here because its citizens have a gross disposable household income of less than £13,000 pa). And this has two further implications: first, what is spent in Weybridge may have no implications for demand in Leicester. And second, the assumption that economic, monetary and fiscal policies set at national level can be expected to ‘deal with’ problems in Leicester is undermined.

How much more at risk is the assumption that policies designed to promote ‘globalization’ are likely to help Leicester. Note, in fact, that in all likelihood the flaws in ‘globalization’, with its likely structural interruption of Say’s Law and its blindness to the failure of comparative advantage, are likely to be contributing directly to Leicester’s plight.

To which one possible answer is: ‘So what? End of days for Leicester, perhaps, but hardly a reason to involve the rest of us.’

Inequality and Profits - Cyclical and Structural

The answer is twofold. First, of course, is that the Leicesters of the Western world are already in revolt, and some sort of policy response to that revolt is inevitable. Pressing on with the policy-assumptions which have produced that revolt only make it more likely that the eventual policy responses will tend to be destructive rather than constructive.

The second answer is that eventually inequality can not only torpedo the business cycle, but undermine profits over both tactical and strategic time-frames. These outcomes are not immediately obvious, and consequently do not feature in most current economic analysis. I have, however, written about them recently in this piece.

‘The signal I am watching is the fluctuating relationship between profits and wages. At some level of description it must be true that there is a relationship between how much profit companies can make and the amount of money they pay their employees. If so, then when the balance between the two reaches a local extreme, it is likely to beckon a recession.

wages and profits.jpg

‘In inflationary times, this is easily understood: when labour markets become extremely tight (for whatever reason, crucially including the incentives embedded in the economy's political structure) and wages rise, a combination of rising inflation and declining profits can undermine return on capital, investment spending, with obvious cyclical consequences. The crucial signal, in this regime, is when wages peak relative to profits.

‘In disinflationary times, the situation is less easy to understand and spot for at least two reasons. First, since the crucial signal we need to watch is the when profits are peaking relative to wages, by definition it occurs at a time when profits are booming. Second, whereas the inflationary impact of sharply rising wages is obvious and invites a monetary tightening response from central banks; the disinflationary opposite shows itself as an otherwise inexplicable inanition of demand, which can at least initially be offset precisely by increased consumer leverage, which delays the onset of recession and disguises its underlying motivation. But notice this: if consumer leverage is used to delay or offset the imbalance, the result would be a build-up of consumer debt which over time will tend to tighten the relationship. Leverage initially disguises the pauperisation of the middle class, but eventually confirms it.’

For the track record of the relationships between the peaks and troughs of this relationship, and the onset of recessions, please check out the full piece.

At present, the relationship between wages and profits has been sliding since around 1980, and fell to the lowest level since 1929 in 2014. After a distinctly feeble rally, it began to fall again in 2018.

My earlier piece suggested: ‘If we are looking for a disequilibrium which gets its resolution through a recession, then perhaps this is it. Perhaps the slow-acting pauperisation of the middle class generates a profits recession by sheer financial inanition.’

Profits Have Peaked Already

That remains a mere suggestion. But what is already observable fact is that by 2018, in most economies, profits had already peaked, and in most cases were in retreat. The analysis which shows this is the Kaleckian profits equation, in which changes in profits are exhaustively determined by:

  1. Net investment

  2. Changes in household savings positions

  3. Changes in government savings positions

  4. Changes in the net savings position of the rest of the world with the domestic economy.

The great attraction of this Kaleckian insight is that it has the logical force of a straightforward accounting identity, whilst at the same time granting an insight into the ‘source’ of profits at a macroeconomic level, rather than a company level. If Dupont analysis is the definitive key to understanding changes in a corporate’s return on equity, Kaleckian profits analysis is the definitive key to understanding changes in profits at a macroeconomic level.

Here’s what the Kaleckian profits calculations are showing in the 12m to Sept 2018:

  • US: +8.9% yoy 12ma

  • UK :+2.9% yoy 12ma

  • Eurozone: Down 1.9% yoy 12m

  • Germany: Down 7.5% yoy 12ma

  • Japan: Down 12% yoy 12ma

  • S Korea:: Down 14.1% yoy 12ma

  • Taiwan: Down 4.5% yoy 12ma

In every major economy I track except the US and the UK, profits are falling. And even in the US, it is not entirely clear that profits have not already peaked: on a 12m basis, there was no growth between the 2Q and 3Q.

kalecki us.jpg

Moreover, in every case except the UK and Taiwan, the change in contribution towards profits made by the change in household savings behaviour undershot the overall movement in profits. In all these cases, then, pressure on the household sector resulting in more cautious financial behaviour is undermining profits growth.

H’hold’s contribution to Kalecki Profits:

  • US: 2.5%

  • UK: +3.4%

  • Eurozone: Down 6.6% yoy

  • Germany: Down 42% yoy

  • Japan: Down 14.9%

  • S Korea: Down 47.2%

  • Taiwan: +1.1%

There is not a single case in which household sector choices are any longer driving profits growth.

In the US , the proportion as a % of GDP has been essentially unchanged since 2010/2011/, in the UK stable since around 2016;

In the Eurozone it has been in continuous decline since 2010; in Germany it has been in decline since 2006;

In Japan it has been in decline since 2014; in S Korea it has been in decline since 2010/2011; in Taiwan it has been in decline since 2013.

End of Days - Summary & Conclusions

The piece has argued that on both sides of the global supply and demand hinge, the models which have previously driven behaviour have exhausted themselves. On the supply side, China’s exogenous growth model some years ago reached the point of quite dramatically diminishing returns as the country approached its ‘technological barrier’. It is currently engaged in the difficult and financial dangerous attempt to traverse from an exogenous growth model to an endogenous growth model. It is the most difficult traverse in the literature, and has defeated many political systems before now (for example, the USSR).

On the demand side, globalization’s internal logic has undermined the economic advantages expected by ‘comparative advantage’ arguments for ‘free trade’, and at the same time has interrupted the workings of Says Law in domestic economies. Moreover, by mistaking the disruptions and dislocations caused by a radical re-allocation of the global means of production as a temporary/cyclical phenomenon rather than a structural shift, debt dynamics have at first delayed but subsequently asserted the pauperisation of the working and increasingly middle classes. Income inequality has risen everywhere, but the broad totals probably mask even more damaging regional inequalities which threaten to undermine the coherence and inter-connectedness of national and even regional economies.

This has now reached the stage where not only is there widespread concerted political revolt, but in addition, the resulting pressures on the household sector have become a drag on the ability to grow profits. In the short term, it is possible that this is a cyclical phenomenon - although it appears to have become so widespread over the last decade that this seems unlikely. More radically, the relationship between wages paid and profits made has become more strained than at any time since the 1920s, suggesting that, at best, new limits are being explored.

The arguments I have put forward here are, I think, consistent and coherent, although the evidence for each stage of the argument has been drawn from a number of different economies. The main reason for this is the availability of data - this argument has not, after all, drawn on many of the mainstream ideas currently fashionable. Still, such cherry picking may give a misleading impression of uniformity of circumstance, and ascribe a fake universality to the picture I have drawn.

However, set against this caveat, let’s remember that the question that needs to be answered is this: ‘If we carry on doing things as we have been doing, will our problems be solved?’ If we accelerate industrial relocation, accelerate globalization of capital and income flows, accelerate the casualization of a global labour force, and rely upon credit creation to deal with the consequences felt by the Western working and middle classes, will the problems identified get better. I find it hard to imagine the answer is ‘Yes’. If you can’t answer ‘Yes’, then we are drawn to the conclusion that our current model is exhausted, and it is, in fact, the End of Days, 40 years after the last End of Days.

One final thought.There is a vicious cycle in which bad policies make for bad economies, which in turn foster worse policies. It is one of the worst and most depressing ironies that in a number of Western economies (UK, US for example) the political response to current woes is Socialism. In the UK particularly, the sort of bone-headed socialism currently offered to the electorate is a sort of reductio ad absurdam of the vicious cycle. The good news is that it looks quite possible to address the situation without recourse to such self-harm: ultimately what is needed are sets of incentives which encourage firms to retain and invest in their workforce, which in turn encourages workers to re-discover the returns to loyalty, and which recognizes that the social costs of the casualization of the workforce will be recovered from companies whose business model depends upon it. Re-imagining a fiscal system to accomplish this does not seem utopian.

What About the Workers? Wages, Profits and Recessions in the US

As the year closes, I'm worried about a piece I wrote in early October: 'Nine Ways to Spot a US Recession'. I was 'looking at a broad range of possible culprits to see which, if any, are showing the sort of form which might be turn out to be a harbinger of a US recession in 2020. I have identified nine different contenders, and tracked how they behaved in the run-up to the last two US recessions (in the Millennial recession of 2000/01 , and in the GFC recession 2008/09).

'Spoiler alert: none are flashing red, or even amber, yet.'

That just doesn't feel right, does it? Particularly given that the plunge in stockmarket values has been accompanied both by a genuinely pernicious flattening of the US yield curve involving both the capital risk premium and TIPS rates, and by a really sharp collapse in the US shocks & surprises index over the last two months:

ss us.jpg

I have revisited those signals, and though they aren't absolutely conclusive, most remain at worst cyclically neutral, and would more usually be thought pro-cyclically positive.

Even so, that conclusion still doesn't 'feel right'.

It is possible that I am looking for the wrong thing. Generally, recessions happen when, and because, disequilibria in economic and financial behaviour have emerged which remain unaddressed, or even unacknowledged, before being corrected by the recession. Most commonly, the disequilibria have been in prices (ie, inflationary boom followed by bust); bank leverage (credit booms and busts) and associated asset bubbles (usually real estate); labour markets (tight labour markets generating wage rises substantially higher than productivity gains can justify); inventory cycles; and, for smaller economies, excesses associated with capital flows exaggerated by mistaken fx policies.

I am going to suggest a further possible disequilibrium which might instigate a recession. I do so rather nervously because it doesn't feature in popular discussions of business cycles, and, so far as I know, has little direct academic tradition to support it. Indeed, it could be misunderstood as flirting with breaching Says Law (any economic theory which demands a breach of Says Law should be treated with great suspicion). Set against that, it is intuitively attractive and measures a phenomenon which is widely recognized. Moreover, history suggests that whilst it is neither necessary nor sufficient by itself to trigger a recession, it has more often than not been seen loitering in the close vicinity when the crime is committed. It is, in other words, a suitable subject for investigation.

The signal I am watching is the fluctuating relationship between profits and wages. At some level of description it must be true that there is a relationship between how much profit companies can make and the amount of money they pay their employees. If so, then when the balance between the two reaches a local extreme, it is likely to beckon a recession.

wages and profits.jpg

In inflationary times, this is easily understood: when labour markets become extremely tight (for whatever reason, crucially including the incentives embedded in the economy's political structure) and wages rise, a combination of rising inflation and declining profits can undermine return on capital, investment spending, with obvious cyclical consequences. The crucial signal, in this regime, is when wages peak relative to profits.

In disinflationary times, the situation is less easy to understand and spot for at least two reasons. First, since the crucial signal we need to watch is the when profits are peaking relative to wages, by definition it occurs at a time when profits are booming. Second, whereas the inflationary impact of sharply rising wages is obvious and invites a monetary tightening response from central banks; the disinflationary opposite shows itself as an otherwise inexplicable inanition of demand, which can at least initially be offset precisely by increased consumer leverage, which delays the onset of recession and disguises its underlying motivation. But notice this: if consumer leverage is used to delay or offset the imbalance, the result would be a build-up of consumer debt which over time will tend to tighten the relationship. Leverage initially disguises the pauperisation of the middle class, but eventually confirms it.

And there is a third factor: no one watches it.

wages and profits.jpg

So let's take a look: the chart above (so good I've run it twice) shows, as a % of GDP, wages & salaries minus profits from 1929 to Sept 2018. Two notes: wages and salaries is not the same as 'compensation', since 'compensation includes a range of mandatory 'payments' which are cannot, in fact, go towards discretionary spending. Back in 1929, the gap between the two was negligible; but rose relentlessly until it peaked at 10.8% of GDP in the early 1990s. Since then it has stabilized, and currently stands at 10% of GDP. Profits, meanwhile, is broadly defined to include corporate profits, proprietors' income and rental income. from 1929 to 3Q2018.

What is immediately apparent is that there are a couple of inflection points.

  • Between 1929 to the late 1940s the tendency was for the portion of wages/salaries to decline relative to profits - this was the essentially the deflation of the 1930s.

  • In the post-war period up to around 1980 (as one might suspect) wages/salaries tend to rise relative to profits - these were generally inflationary years.

  • Finally, after 1980s, the general tendency has been for wages/salaries to fall relative to profits - our time has been basically disinflationary tending towards actual deflation.

  • And here's how these inflection points were associated with the onset of recessions:

Peak of Wages to Profits

  • 1945 - Recession Feb - Oct 1945

  • 1953 - Recession July 52 to Oct 54

  • 1960 - Recession April 60 to Feb 61

  • 1970 - Recession Dec 69 to Nov 70

  • 1974 - Recession Nov 74 to March 75

  • 1980 - Recession Jan - July 1980, and July 81 to Nov 82

For the disinflationary years post-1980, the relationship changes, and the ability to use monetary and credit policy to delay or stave off recession makes it less obvious. Nevertheless, some sort of relationship survives.

Peak of Profits to Wages

  • 1985 - Recession July 1990 to March 91

  • 1997 - Recession March 2001 to Nov 2001

  • 2007 - Recession Dec 2007 to March 2009

  • 2014 - Industrial 'mini-recession' 2015 to mid-2016

What is clear is that since 2010:

  • the ratio of wages to profits has fallen to previously unknown lows, and

  • there has been no significant recovery accompanying the pickup in economic activity and

  • it appears that there has been a further modest decline in 2018.

If we are looking for a disequilibrium which gets its resolution through a recession, then perhaps this is it. Perhaps the slow-acting pauperisation of the middle class generates a profits recession by sheer financial inanition.

If this is the fundamental disequilibrium which breeds danger for the economic cycle, then we need to look closely at trends specifically in movements in financial stress of the household sector (ie, in terms of servicing current debts), and the availability of further credit.

In the 'Nine Ways to Spot a US Recession' piece I presented a ratio which combines two elements of observable financial stress: changes in interest payments relative to disposable income, and changes in the savings/disposable income. Back in the original piece I wrote: 'This index flashed red in both recessions: prior to the Millennial recession, this index showed a sustained leap in 1Q99 which was maintained until 4Q01; prior to the GFC recession the index jumped sharply in 1Q05, with no let-up until 1Q08. This looks like a useful early indicator of household-sector driven recession: at present it is not signalling recession in the short to medium term.'

Revisiting that ratio with data up to November 2018 shows us that by end-2018 this stress ratio had risen to its highest since early 2010.

hhold financial stress.jpg

As for household's access to credit, Fed data shows growth in bank's lending to consumer credit and residential real estate slowed to 2.7% yoy in November, and that underlying momentum was running 0.2SDs below 5yr seasonalized trends. This is not encouraging, but neither is it necessarily anything more than a sub-cyclical slowdown which can be expected to right itself in 2019 (to growth of around 3.5%).

More worrying is the tightening showing up in the little-watched credit union sector. Credit unions are an increasingly important vehicle for household financing: in the year to September, credit unions' loan books rose $89.2bn, whilst banks consumer and mortgage book rose $135bn. In other words, credit union loans were approximately two-thirds the size of bank loans to the household sector. The problem is that whilst credit union loan growth is still robust (up 9.5% yoy in 3Q, but slowing), deposit growth has slowed to 5% only, and the sector's loan/deposit ratio has risen to 85%, up from 81% in 3Q17, and an average of 74% since 2010. In other words, this source of household credit is (finally) running out of steam.

credit union ldr.jpg

Conclusion: By now, it is possible sketch the outline of forces which could produce a US recession:

  • 1. Wages growing at a pace insufficient to support continued profits growth;

  • 2. A slow accumulation of household financial stress resulting from years of 1.

  • 3. The exhaustion of financing ability from the credit union sector, ultimately the result of slowing deposit growth (see 1. and 2.)

It doesn’t make me ‘feel good’, but it does feel realistic.

The Campaign Against Prosperity

A useful axiom: bad policies result in bad economies, which in turn result in more bad policies. By contrast, good policies result in good economies, which in turn generate the space for more good policies.

We live in an age when growth in world trade has slowed to a crawl. Between 2000 and 2007, Northeast Asia’s exports rose an average 17.7% a year. After the violent shocks of the GFC are shaken out of the yoy data, between 2012 and 2018, those exports have grown only 2.6% yoy on average. And it is against this background of stalled world trade growth that future trade growth is compromised still further both by rising US-Sino trade frictions, and the threatened collapse of UK-EU trade relations.

What is little realized is that these potential overt trade dislocations do not come out of the blue. Rather, they are the logical extension of an aggressive campaign against international trade which has been waged by all major trading economies, and with increasing intensity, since the GFC. Bad policies have resulted in bad economies, which in turn are provoking even worse policies. This, then, is the story of trade wars foretold.

neax lt.jpg

One can reach for purely economic reasons to account for this dramatic curtailment of trade growth: changing patterns of domestic saving and cross-border investment clearly have a part to play. But using economics as a sole explanation overlooks a simpler and powerful explanation: the slowing of global trade growth to a crawl is (also) a result of deliberate policy aggressively pursued.

Trade has slowed in part because regulators in every major economy have raised obstacles to trade in goods, in the form of Non-Tariff Barriers (NTBs). NTBs are not usually noticed much, because they don’t immediately lend themselves to direct economic quantification. ‘Trade policy can take many different forms: tariffs, quotas, non-automatic licensing, antidumping duties, technical regulations, monopolistic measures, subsidies etc. How can one summarise in a single measure the trade restrictiveness of a 10% tariff, a 100-ton quota, a complex non-automatic licensing procedure and a $1 million subsidy?’ (Estimating Trade Restrictiveness Indices - Kee, Nicita, and Olarreaga, 2009)

Nevertheless, econometric calculation allows the authors to construct an Ad-Valorem Equivalent (AVE), which compares the impact of NTBs directly with direct trade tariffs. They conclude: ‘The importance of NTBs as a protectionist tool is substantial, especially considering that in 55% of tariff lines subject to core NTBs, the AVE of core NTB is higher than the tariff.’ ‘On average, they add an additional 87% to the restrictiveness imposed by tariffs. Moreover, in 34 out of the 78 countries in our sample, the restrictiveness of NTBs is larger than the restrictiveness of tariffs.’ The malign impact rises as a country grows richer, with the average AVE of NTBs rising with GDP per capita.

Those conclusions were reached using data from the early 2000s, when the US, EU, China and Japan had deployed comparative NTBs to impede trade. Since then the rate at which they have growth, and continue to grow, is extraordinary: back in early 2000, between them the US, EU, Japan and China had put up only 2,028 NTBs. As of end-November 2018, there are 12,612 NTBs either initiated or in force. More than two new NTBs are added by these economies every working day.

The means to track it are publicly available: the NTB tallies in this piece were all taken from the WTO’s Integrated Trade Intelligence Portal.


This wild proliferation of specific trade barriers has continued unabated even as the trade which they are designed to hinder has almost stopped growing. This looks like a classic case of bad policies producing bad economies, which in turn produce even worse policies.

One way of illustrating the interaction between NTBs and trade volumes is to chart the number of NTBs to be overcome by every US$1bn of monthly imports made by these countries.

ntbs per billion.jpg

The number of obstacles set in the way of every US$1bn of imports prior to the crisis fell gently from 13.6 at the beginning of 2004 to a low of 11.2 in 3Q08.

Since then, the rise has been dramatic, albeit disrupted by the business cycle. Still, it reached a peak of 21.8 per billion in 2016, and currently stands at 19.2. In other words, the number of barriers to trade has roughly doubled since the crisis. If the AVE of these NTBs is merely as expensive as a tariff on the goods, then it seems likely that post-GFC, we have seen the equivalent of a doubling in import tariffs.

This is our generation’s equivalent of Smoot-Hawley.

Yet this relentless campaign against trade - against prosperity - is for all intents and purposes invisible. It attracts no headline, courts no controversy. So I think I shall start to include monthly checks on the numbers of NTBs in my Shocks & Surprises work.

Which countries, then, are currently the worst prosecutors against world trade, and where are the instincts to damage world trade most virulent at the moment? Using the same metric (NTBs per US$ billion of imports per month), there is a quite clear order: Japan is by far the most protective, with 37.2 NTBs per US$1 billion of imports. The least active on this regulatory front - much to my surprise, I must admit - is the EU, with 11.1 NTBs per billion. The US is one of the most litigious economies in the world, so it is perhaps not surprising that it is heavily protective, with 27.8 NTBs per billion, whilst China, which only really started playing this game by WTO standards, has no reached 15.2 NTBs per billion.

ntb regions.jpg

The other thing this chart shows is that the campaign against trade really intensified dramatically in 2015 and 2016, when these economies added 947 and 687 new NTBs respectively. And whilst everyone was at it - this was the point at which trade regulators were gaming the system, presumably driven by Prisoner’s Dilemma rationalizations - the two most fervent gamers were Japan and China. Japan started 2014 with 1,240 NTBs, but by end -2016 they had 1,556. China’s regulatory activity was similar: at end-2014 it had 2,031 NTBs in force; by end-2016 it had 2,527.

This is a dark picture, and darkening by the day. But even in the darkest picture there is some relief, and in this case, it is that the regulatory enthusiasm seen in 2015 and 2016 abated somewhat in 2017, which produced only 503 new NTBs. As markets twitch to the latest twist in US-Sino trade diplomacy, it is clear that without a de-escalation in the NTB trade wars, the prospects for global trade, and global prosperity, will remain deliberately and profoundly compromised. Bad policies make for bad economies, which make for worse policies.

US & Asia: 3Q's Big Inventory Build

One feature which is common to 3Q national accounts for the US and for those parts of Asia for which we have a detailed GDP breakdown is an unusually sharp build-up of inventories. These have inflated nominal and real GDP growth on both sides of the Pacific in 3Q, disguising a slowdown in final spending. The 3Q inventory build-up potentially represents a time-bomb under GDP growth in coming quarters. However, assessing the timing and strength of that threat will partly depend on what prompted 3Q’s build-up in the first place. Was it US-Sino trade threats to supply chains, or commodity prices? Or both?

First, a methodological warning: when it comes to inventory, I use the nominal numbers, rather than the deflated ‘real’ numbers. There’s a good reason for this: change in inventory behaviour, and by extension changes in inventory prices are at the very heart of business cycle dynamics. The claim that deflators can be accurately calculated is not just implausible in practice but, I think, flawed in principle. Similar reasons lie behind my use of nominal investment tallies when it comes to calculating my Return on Capital Directional Indicators. Let’s first see where we can see inventory-building inflating 3Q GDP growth significantly:

  • In the US, the $ 80.4bn nominal additions to inventories in 3Q reversed a $10.4bn drawdown in 2Q. This was the biggest quarterly turnaround in inventories since 4Q12, and accounted for 0.4pps of the 1.2pps qoq rise in 3Q nominal GDP growth. That's the highest proportion since 1Q15. Nominal GDP grew 4.9% annualized in 3Q, but final spending on domestic product (ie, GDP less inventory changes) rose only 3.1% (vs 8.6% in 2Q).

  • In Hong Kong, 3Q saw the biggest nominal rise in private inventories in 3Q for years, adding 1.9pps to nominal gdp growth of 6.7%. Perhaps more clearly, the rise in gross fixed capital formation was HK$19.12bn yoy, whilst the change in private inventories HK$12.86bn yoy. Nominal GDP growth came in at 6.7% yoy, but final spending on domestic product rose only 4.8%.

  • In Thailand, 3Q saw the biggest addition to private inventories since 1Q13 - an addition which added 5.7pps to the nominal 5.5% growth! So nominal GDP growth 5.5%, but final spending on domestic product actually fell 0.2% yoy.

  • In Singapore, the story is less obviously dramatic, but still material. Inventory additions accounted for only 1.5pps of 3Q’s 4.5% yoy nominal growth, but accounted for slightly more than all of the qoq growth. Nominal GDP rose 4.5% yoy, with a quarterly rise 0.2SDs above historic seasonal trends; final spending on domestic product, however, rose only 3.1% yoy with the quarterly gain 0.8SDs below trend.

  • Taiwan’s first estimate of 3Q GDP does not break out an estimate of inventory changes, but the extraordinary jump in gross capital formation (which includes inventory changes) strongly suggests the build-up was dramatic. In constant dollar terms, 3Q GDP rose 2.28% yoy, within which investment spending jumped 17.5% yoy, and accounted for 336bps of the 228bps of 3Q GDP growth.

  • I commented at the time: ‘It is an extraordinary number. Not only is it the first positive yoy comparison since 2Q17, it also the highest since the rebound-year of 2010, and before that since 2004. What accounts for it? . . . . Gross capital formation includes changes in inventory. Starting in 3Q17 and carrying on through to 1Q18, Taiwan was losing inventory fast. The sharpest inventory-dumping came in 3Q17, with the change in inventories equivalent to 1.4 percentage points of GDP growth. However, in 2Q18 there was a small addition of inventory, and if this continued into 3Q18 this could have contributed powerfully to overall investment growth. Indeed, even if there were no inventory building, but only a quarter-on-quarter standstill, this would still have represented approximately 6.3 percentage points of growth for total yoy investment spending.’

  • And in Europe, too, it seems something similar happened in Germany. In nominal terms, Germany’s 3Q GDP rose 1.8% qoq and 3% yoy, with gross capital formation rising 19.3% qoq and 12.4% yoy. However, within that, gross fixed capital formation (ie, investment excluding inventories) rose only 1.2% qoq and 6.3% yoy. The implied inventory growth is dramatic, and accounts for 1.4pps of 3Q’s 3% yoy growth. Nominal GDP grew 3% yoy, final spending on domestic product rose only 1.6%yoy

What accounts for it? There are two obvious contenders, both of which may be at work:

  • first, the scramble to secure and deliver supplies in anticipation of escalating US - Sino trade frictions;

  • second, a response to the the belief that the dollar is weakening and (thus) commodity prices rising.

US-Sino trade frictions explanations are consistent with when and where the inventory-builds are most obviously found: ie, in the US, Hong Kong, and probably Taiwan. However, It is not obvious why this should have been extended to Thailand (but not Indonesia). It is also noticeable that there is no obvious inventory build implicated in the UK’s strong 3Q GDP result (0.6% qoq), whilst the Eurozone’s disappointing 3Q GDP (0.2% qoq) result leaves little room to hide an inventory bulge.

Movements in commodity prices, and expected movements in commodity prices, regularly produce significant inventory shifts. Indeed, inventory additions and clearances are a major factor in commodity prices whipsawing at inflection points.

There are good reasons to expect that these inventory additions were in part the result of expected commodity price rises - namely movements in the dollar, in inflation, in bond market inflationary expectations, and in direct movements in commodity prices.

dollar crb.jpg

Throughout 2017 and the first half of 2018, the dollar had been almost continuously weakening against the SDR: between Jan 2017 and mid-April, it had lost 8.1% against the SDR basket of currencies. More often than not, the corollary of a weakening dollar is strengthening (dollar-based) commodity prices: and as the chart shows, this time was no exception, with the CRB index rising 26.7% between June 2017 and May 2018.

ss inflation.jpg

Those expecting these trends to continue had plenty of evidence going for them. Although it was not difficult to spot that in yoy terms global inflationary trends had peaked around July 2018 and were likely to retreat, the data showing that would only have arrived around late-August and early September, and it required a degree of confidence to recognize it at the time. Not least because between May 2018 and early August 2018, global inflation announcements had been sharply more inflationary than consensus expected, as shown in my global Shocks & Surprises inflation index.

inflation risk premium.jpg

Moreover, in the US, bond markets were at that stage signalling no retreat in inflationary expectations, with the inflation risk premium (10yr Treasuries minus 10yr TIPS) rising from a low of 167bps in late June 2018 to a peak of around 220bps in late May, from where it did not noticeably retreat until mid-October.

Which of these two possible reasons for 3Q’s inventory build was dominant matters because they imply different trajectories in the near term.

If the dominant factor was simply a reaction to the rise in commodity prices and the expected continued rise in commodity prices, then the strengthening of the dollar, the retreat of global yoy inflation prints, the moderation in inflation shocks & surprises, the retreat of commodity prices and finally the retreat also of inflation assumptions embedded in US bond markets all suggests that inventory holders will be dumping inventory overhangs as quickly as possible - and consequently that we can expect this to show up in noticeably weaker GDP growth in 4Q.

If the dominant factor is a desire to secure certainty of short- and medium term supply in the face of US-Sino trade frictions, then it is less clear that the 3Q buildup will be revoked quickly, or at all. For if the expectation is that trade frictions are likely to be a continuing feature of US-Pacific trade relations, it is likely that this will be answered by a longer-term increase in working capital tied up in inventory for both buyers and sellers.

China: Exploring the Shadowlands

A few weeks ago I was challenged to produce a 'bull case for China'. It's a tough ask, and the best I could do was show how we can expect that profits growth will be strongly leveraged to the recovery, (when it arrives). This is because the efficiency gains (efficiency of finance, of asset-usage, and of labour productivity) which were won in the early stage of the credit squeeze will endure for at least the early stages of the recovery (when it arrives). (This is despite the evidence that the continued squeeze is, right now, eroding those initial gains.)

But when will it arrive? The belief that recovery will arrive sooner rather than later is made tougher by the run of data, as October's monetary, industrial and demand data showed this week.

Not that any of October's industrial or demand data was exceptionally grim. Rather, it was just uniformly disappointing: industrial output rose 5.9% yoy (0.3SDs below trend), electricity output rose 4.8% (0.5SD below trend) and exports (in Rmb and volume terms) came in 0.1SD below trend. For demand indicators, retail sales rose 8.6% yoy (0.8SDs below trend), auto sales fell 13% (0.6SDs below trend), urban investment rose 5.7% ytd (0.3SDs below trend), PMI employment indexes were 0.7SDs below trend, and only the real estate climate index managed a positive result (0.2SDs above trend). Industrial indicators have leaked momentum for four of the last five months; demand indicators for the last two months.

remi cn.jpg
ddmi cn.jpg

But then there's October's monetary numbers. Interpreting China's monthly monetary and finance data is becoming a bewildering puzzle, because although we know that great efforts are being made to scale back or close down the 'shadow banking' sector, we have no way really of telling how this is affecting banks' ability to lend, companies' ability to get credit from the banking system, and, moreover, how it is affecting government finances.

The key point is this: whilst the 'shadow banking system' of wealth management product, trust loans and entrusted loans started out with a good claim to be vehicles which could usefully circumvent interest rate ceilings for savers and institutional credit hurdles for companies, they morphed into something quite different.

In recent years, 'shadow banking' operations have tended instead to act primarily as ways in which certain types of commercial banks could sidestep overall credit limits, essentially by offloading loans to special vehicles (such as trust companies) in exchange for participation in 'Trust Benefit Receipts' which count as investments rather than loans. Over time, this has developed into a series of tightly interlocking financial relationships between various parts of the banking system and parts of the 'shadow banking system' which are very largely opaque.

To get a really good idea of the issues involved, I can recommend the BIS Working Paper No 701 'Mapping shadow banking in China: structure an dynamics.' This is a brilliant paper, and, if nothing else, one should take a look at the BIS's schematised map of China's shadow banking system, starting with the 'easy' map on p4.

BIS writes: crucially, 'direct shadow credit to ultimate borrowers has slowed considerably in recent years, whereas the volume of shadow funding as well as structured shadow credit intermediation has grown at a fast pace.' I think this is BIS being diplomatic: what it means is that in recent years, the principal driver for 'shadow banking' activity has been the need or desire to circumvent banking regulations by converting 'expensive' on-balance-sheet loans into 'investment receivables' from the trust company in which those loans have been parked.

That's good news and bad news. The good news is that winding down the 'shadow banking activity' as seen in the monthly aggregate financing numbers probably hitting banking operations more than credit creation. In other words, the slowdown in total aggregate financing probably overstates the slowdown credit created for ultimate users. The bad news is that we simply have no idea how those 'tight interlinkages' are going to be unwound, and what 'unknown unknowns' will make themselves unavoidably 'known'.

However, one conclusion - and no conclusions in this case are 'obvious' or even certain - is that during the expansion of the shadow banking system, the monthly scores of total aggregate financing are likely to have been inflated by an unknown degree of double counting. If so, it is quite possible that the current slowdown in total aggregate financing (just Y729bn in October, with bank lending accounting for Rmb714bn) with the contractions consistently recorded in trust loans and entrusted loans, is correspondingly less dramatic than it seems. Quite how the dis-integration of the shadow banking system and the banking system will affect, or is affecting, final credit provision is, I think, impenetrably obscure.

However, some light is shed by the inclusion this year of 'special local government bonds' as a separate line-item in total aggregate financing. What seems fairly obvious is that these bonds have been issued at a pace directly to offset the fall in the 'shadow banks' trust and entrusted loans.

During Jan-Oct this year, there has been a net repayment of Rmb1.847tr of trust and entrusted loans. Since trust and entrusted loans were the favoured vehicle for local governments to finance themselves, it looks like it is local governments which have been doing the repaying: during the same period, the issuance of 'special local government bonds' has amounted to Rmb1,782tr. The high-interest rate (and for banks' customers, high-risk) trust and entrusted loans are being repaid by the proceeds of the local government bonds.

shadow and bonds.jpg

But whilst these bonds are looking after the interests of local government finances, it is far less clear what the knock-on effect on final credit provision for other economic entities must be.

Nevertheless, it has the further consequence that we are getting a less unrealistic picture of the state of China's government finances. Consider, for example, that the total published fiscal deficit for Jan-Sept 2018 came to Rmb1.749tr, whilst the new local govt bond issues for Jan-Oct came to Rmb1,782tr. At some point we should start counting these new debts as evidence of previously unregistered deficits (rather than assuming they represent current fiscal gaps).

For those with long memories, the rather baroque system of 'tight interlinkages' which now characterise China's shadow banking system is reminiscent of S Korea's financial system prior to its 1997 crisis. There, the fundamental problem the system was trying to solve (or evade) was that the legacy of a command-banking system meant not only that credit where available was mispriced, but also that great swathes of S Korea's commercial economy couldn't access official credit markets at all. For small companies, the problem wasn't the price of credit, it was the lack of all access to official credit, whilst for chaebol, credit was price too cheaply. There are distinct echoes of this in the difficulties China's major banks still have in the preferential lending to SOEs and similar.

In S Korea, the financial system first developed derivative-institutions which attempted to address this problem. However, whenever economy-wide cashflows faltered, those institutions tended to fail, because a) they were not yet good at credit-pricing; b) they tended to have major liquidity mis-matches, and c) when cashflows into the financial system got crimped, these derivative institutions would be banks' first to get their lines cut. In one form or another, this sequence of events was repeated about three times before S Korea began to solve the underlying problem.

In China's case, the two underlying problems are the unacknowledged fiscal problems at local level, and the dominant giant banks' historic mistrust of lending outside the traditionally favoured areas. The blooming of the shadow banks represented a dangerous attempt to solve (or evade) those problems. Even if the current efforts to de-fang the mistakes doubtless made by the shadow banking system are successful, we should expect some sort of re-iteration until the twin problems are solved.

US Productivity - Out of the Slow Lane?

Most economists and policymakers believe that since around 2005 the US has been stuck in a 'low productivity growth' regime in which labour productivity oscillates around an average of 1.33% yoy, compared with the previous 'high productivity growth' regime which held from early 1997 to late 2004 in which productivity averaged 2.9% a year.

The assumption that there’s a ceiling on US labour productivity growth, coupled with an assumption of a demographically-constricted ceiling on employment growth feeds into calculations about sustainable growth rates. And those calculations will go a long way to determining how the FOMC feels obliged to act.

But the low-productivity assumption is under challenge now, with recent readings knocking up against the ceiling: in 2Q labour productivity rose an annualized 3%, and the first-estimate of 3Q this week came in at an annualized 2.2%.

Taking real GDP per worker as a crude but easily calculable measure of productivity, the 1997 to 2004 average comes out at 2.2% with a standard deviation of 0.8%, whilst the 2005-current average comes in at 0.9% with a standard deviation of 1%. If we exclude the exceptional 'recovery period' of 4Q09 to 3Q10 (when this measure of productivity growth averaged 3.5%), then the low regime of productivity growth averages 0.7%, with a standard deviation of 0.7%.

If we now consider the last four quarters performance (4Q17 1%, 1Q18 1%, 2Q18 1.2%, 3Q18 1.3%), we can see that this is now consistently pushing towards the ceiling of this 'low productivity' regime.

productivity regimes.jpg

There are two possible interpretations of this, and both are in different ways destabilizing. One view is that there is no reason to expect the low-productivity regime to be challenged. In which case, we must expect to see the performance of the last two quarters as exceptional peak-cycle phenomena which will be swiftly followed by a cyclical decline. This is as good as it gets.

The alternative view is that there is nothing sacrosanct about the 'low productivity regime' and that the gains of the last two quarters are presaging a reversal back to a higher productivity regime.

What view you, and policymakers, take of this is absolutely critical, because it will be one of the assumptions which determine the possible sustainable growth trajectory of the US, and consequently what is the 'natural rate of interest' around which the Fed will attempt to guide the economy.

Despite the ambiguous/ambivalent structure of 3Q’s 3.5% GDP growth, I think there is a good reason to believe that the US is transitioning to a higher productivity regime. That good reason is to do with how capital stock per worker helps determine labour productivity growth.

As the chart below shows, between 2010 and late 2016, growth in labour productivity was constrained by negative or historically very weak growth in capital stock per worker. In fact, when one stripped out the impact of capital per worker, the performance of output per worker was markedly better than in the so-called 'high labour productivity' period.

Since 2016, growth in capital per worker has accelerated back towards the lower boundary of pre-crisis normality, but with surprisingly little deterioration in output per worker less capital per worker. Even into 3Q18, this measure remains noticeably better than what was usually achieved prior to the crisis. By itself, this chart gives no reason at all to expect any deterioration in overall output per worker in the near future. In other words, no reason to discount the exit from the post-2004 'low productivity regime'.

elements of productivity.jpg

UK Regional Inequality: Is the UK Still a Coherent Sample?

The previous piece (UK - The Curse of Regional Inequalities) ended by warning that if regional income inequalities continue to widen, at some point the UK loses coherence as a statistical sample. Or, to put it plain English, the inequalities can become so great that in economic terms we're no longer really talking about a single integrated society.

For better or worse, these judgements need not be made on the basis of prejudice or political outlook. Rather, it is the data which does the talking. The underlying premise is that many social and economic phenomena show a Zipfian pattern of distribution. (How to describe Zipfian distributions? It is a mathematical pattern which was first observed in the frequency of words in a language. Wikipedia to the rescue:'Zipf's law states that given a large sample of words used, the frequency of any word is inversely proportional to its rank in the frequency table. So word number n has a frequency proportional to 1/n. Thus the most frequent word will occur about twice as often as the second most frequent word, three times as often as the third most frequent word, etc.'

Zipfian distributions are also regularly observed in economic geography, most famously in the size/frequency distribution of cities within a nation (which, by the way, is how you can tell that London is the capital of Europe, rather than the UK).

We can use it to test whether the rising regional inequality in the UK is threatening its coherence as a society. As before, I am using the ONS's exemplary survey of household per capita disposable income, available annually from 1997 to 2016. In this case, I am using the NUTS3 breakdown of the UK into 179 different regions (NUTS stands for Nomenclature of Territorial Units for Statistics and is based on areas of local government). Basically, I am counting the number of NUTS3 units which fall into per capita annual income bands, stepping with increments of £500. The chart then logs both the frequency and the income (income along the x-axis, frequency along the y-axis).

In a single society one would expect the relationship between per capita income and frequence to be very regular - in fact, one would expect it to be roughly Zipfian. So how's it looking? First, this is the distribution pattern in 1997:

1997 coherence.jpg

There are three, maybe four, outliers of significant poverty, and three, maybe four, outliers of significant wealth. But these are comparatively rare, with the income/frequency of most of the regions clearly cleaving to a strong log/log trend. You might (or might not) be worried about the outliers at either end, but overall the sample looks strongly coherent.

And so on to 2007.

2007 coherence.jpg

The pattern hasn't changed much. The positive outliers are perhaps a little more obvious, and the negative outliers slightly more frequent, but the chart is still dominated by a very clear and strong trend linking income and frequency in a predictable relationship. The centre, we might say, is holding.

You cannot say the same thing for 2016's data-set.

2016 coherence.jpg

One can still see a rough sort of relationship at work, but it takes an uncomfortable effort of will. Had you not seen the pattern of 1997 and 2016, one would be tempted to see two conflicting trendlines at work here: one sloping upward and to the right, and the other sloping downward and to the left. Or one might see, perhaps four bands of frequency (at roughly 2.5, 2, 0.7 and zero).

I think the 2016 chart is very unsettling. Not primarily because of the evidence of inequality, but because it suggests that the complicated and extended network of economic relationships which normally result in a coherent pattern of economic activity and hence income distribution are looking extremely frayed. That suggests that the economic fortunes of different parts of the country no longer have the same impact or implication (positive or negative) on other parts that they used to. A rise of income in, say, Hounslow, no longer means much to, say, Wolverhampton or Leicester. Conversely, even a dramatic fall in fortunes in, say, Southampton, may not longer have any noticeable implications for Oxfordshire. So why should either region have any interest in the economic welfare of the other? Once again, putting things horribly simply, if the society no longer expresses (among other things) a complicated chain of commercial co-dependence, what does it express?

UK - The Curse of Regional Inequalities

I rarely write about the UK economy, because I fear delusion and confirmation bias. (Economists suffer badly from confirmation bias.) Nevertheless, there is one thing that needs to be understood by anyone who claims to know what the future holds for the UK. It is this: regional inequalities in income and wealth within the UK, and most particularly within England, are worse than at any time for which I have the data.

For decades, these inequalities have been widening and widening without significant political consequence. They may finally have become so wide that they constrain all sorts of policy-choices (for example, I suspect the Brexit vote is one consequence). There are a couple of economists who begin to be concerned - Jim O’Neill is one, and Bank of England’s Andy Haldane are both on the roll of honour. But I expect that the London-based financial services industry have neither the knowledge nor interest to prevent themselves from being repeatedly blindsided by the policy implications.

This is short-sighted, because without acknowledging the deep economic foundations of political dissatisfaction, analysts are unlikely to understand its durability or its longer-term consequences. The assumption that the political settlement which has produced this inequality can continue unchallenged must, surely, be naive.

The available data is unambiguous and damning. It is easiest to demonstrate by using the gap between London and elsewhere in the UK as the benchmark. The ONS has been producing extremely fine-grained survey data on household income by region and city since 1997. Back in 1997, the average London disposable per capita household income came to £13,183, compared to a UK average of £10,817 - a multiple of 1.22x. By 2018, London’s average had risen 106% to £27,151, whilst the UK’s average had risen only 80% to £19,432 - the multiple had risen to 1.40. There’s no reason to believe the multiple isn’t even higher today.

london uk income multiple.jpg

But this is not just a story about London’s success, it is also, alas, a story about failure elsewhere. In the North East, the rise in per capita income since 1997 is just 68%, and its 2016 £15,595 average is below anything London has had to get by on any time this century! (London’s income is 1.74x that of the North East).

The regional income inequalities continue to worsen. There are two ways one can illustrate this. First, one can express the standard deviation of regional disposable income as a percentage of the mean: the higher the number, the greater the relative dispersal of regional income. In 1997 the standard deviation of incomes was 13.7% of the mean: by 2016 it had risen to 18.6%.

standard deviation to mean.jpg

Second, by comparing the median to the mean, one can capture the degree to which the sample is skewed at the upper end. The same story emerges: back in 1997 the mean reading of per capita disposable income was 106% of the median - a level which it maintained with little change until around 2004. Peak-finance prior to the crash lifted the mean to around 108% of the median, where again it stayed, with wobbles, until around 2012. However, since then the ratio has taken off once again, and by 2016 it stood at 109%. In short, the regional dispersal of household income is increasingly skewed towards the richest regions.

mean to median.jpg

(Nor is it simply a story of London vs the rest: within London itself, the inequality has burgeoned. Consider: between 1997 and 2016, average disposable income in Hackney & Newham jumped 199%, whilst Bexley and Greenwich had to settle for a mere 66.3%. In 1998 the mean income of boroughs was 103% of the median, by 2016 that had risen to 122%.)

When it comes to wealth, the story is of course similar. The most obvious evidence comes from the property market, and in particular the way in which London house prices diverged from the rest of the UK in the aftermath of the GFC, and in particular after the introduction of quantitative easing by Bank of England in 1999. Between 2007 and 2016, average UK house prices (ie, including London houses) rose 13.9%, whilst during the same period London house prices rose 58.5% (the data comes from the ONS house price index series).

At the beginning of 2007, the average London house price was 1.5x that of the national average: by end-2016 the multiple had risen to 2.2x.

Since the national average price includes London itself, the expansion of the London multiple is unrealistically muted. Consider, then, the divergent course between prices in London and in Yorkshire (where I live). In the period that London’s prices rose 58.5%, Yorkshire’s prices rose. . . 1.6%. The London/Yorkshire multiple rose from 1.9x to about 3.2x. Or, to look at it from a Yorkshire point of view, when the City helped blow up the world financial system, quantitative easing gave Londoners a free house. Still, the current fall in London house prices provides the first suggestion that the epic divergence is discovering its limits.

london house multiple.jpg

Issues of inequality are easier to lament than either to diagnose or correct. Measures of disposable income and property wealth are neither complete or sufficient indicators of regional disparities. This piece could be extended to cover regional disparities of public spending on education, health and infrastructure (transport!). Conversely, it would also be possible to mount a rearguard defence of the widening inequalities as merely the result of a free market.

For now, though, the point is simpler: underlying every society is an assumption that it is coherent. In statistical terms, we can say that the distribution of resources and outcomes represent a coherent, usually Zipfian, sample. When inequalities become sufficiently great, they threaten to disrupt the coherence of the sample. If you don’t expect the disintegration of the UK, then you should expect policies designed - successfully or not - to close the regional inequalities which have opened up since the financial crisis.

China: Time's Up for Credit Squeeze - Upward Inflection Mid-2019

The race to pass judgement on China’s economy peaks four times a year, when China releases its quarterly GDP estimates. It involves a spectacular suspension of disbelief: does anyone really believe it is possible to measure an economy as large, complex and opaque as China’s to within a tenth of a percentage point?

There is little sensible to be said, therefore, about last week’s news that 3Q GDP growth slowed to 6.5% from 6.7% in 2Q.

But there are two conclusions one can draw about the structure of China’s economy, and its likely medium-term trajectory.

The first is that time’s up for the credit squeeze. The determination to improve the discipline of credit allocation was well-founded - back in 2011 every 100 yuan in new aggregate financing was associated with approximately 60 yuan in extra nominal GDP; but by 1Q16 this addition to GDP had fallen to just 26 yuan. From an economic point of view, credit creation was running into the sands.

However, two years into the attempt to discipline the allocation of credit the question China’s authorities have to face is this: does the efficiency of finances continue to rise, or has the negative economic impact of restraining credit growth led to an overall deterioration in financial efficiency?

Between 1Q16 and 2Q18 the credit crunch undoubtedly produced positive results in terms of the impact of extra finance upon nominal GDP: in the 12m to 1Q16, 100 yuan of extra aggregate financing was associated with only 26 yuan of extra nominal GDP; but by 2Q18 this had risen to 47 yuan. These sorts of gains are destined to be more difficult in the second year of a credit crunch as the easy gains have been made, the improvised sources of extra financing will already have been mobilized, and more companies will be hitting the wall. This is now showing in the 12m to 3Q, with the amount of extra GDP associated with 100 yuan of extra aggregate financing falling to 45.5 yuan.

And that, I think, accurately indicates the point at which maximum pressure for a policy loosening is felt, for not only is the pain of continued stringency now laid bare, but in addition, it becomes obvious to banks and monetary policymakers that the erosion of credit quality will itself tend to constrain further credit growth beyond what had been initially envisaged. We are now past that point.

financial efficiency.jpg

Now that we have now entered the phase where policies are set to limit the unforeseen/unexpected damage done by the previous credit restriction, what results can be expected from the current and likely ongoing policy relaxation?

I construct a monetary conditions indicator for China monitoring monetary growth (M1 and M2), changes in real interest rates and yield curves, and the size and historic volatility of changes in the SDR value of the Rmb. Significant changes in that indicator (on a 12ma basis) have in the past been associated with similar changes in the growth of private nominal domestic demand nine months later.

mci pri domestic demand.jpg

This chart suggests three things:

First: even on a 12m basis, China’s monetary conditions are now being loosened, quite aggressively, with 3Q18 being the upward inflection point.

Second: although the slowdown in growth of private domestic demand is moderating, it still has a further six to nine months before we should see a convincing upward inflection point. We can expect good news as a result of policy loosening . . . but not just yet

Third: each time monetary conditions have been loosened, dramatically, the positive impact on nominal GDP growth has weakened. The very sharp upswing seen in 2008 topped out at 26.1% yoy; in 2010 and 2011 it topped out at around 21%; in 2013 a similar loosening resulted only in nominal private sector domestic demand growth topping out at 13.8%. The positive upturn to be expected in 2H19 will probably be weaker still. If so, the upturn in 2019 may seem more like mere stabilization.

Investing, Fast & Slow. Part 3: Slow

Investing: Fast gave some hints as to how we can explore the likely market impact of System 1 type of thinking about economies and markets. The long-term results, I think, speak for themselves, but they are the result only of cumulative short-term investment tactics. System 2 type investment thinking aims at improving longer-term strategic positioning, allowing a longer investment horizon, less costly in terms of day-to-day effort and cost.

If the energy devoted to analytical and deliberative thinking about investment were easily repaid, the ‘strategic advice’ industry would be even bigger than it is.

Conversely, and ironically, it is the very sustained failure of these attempts that keeps the industry afloat: if anyone ever managed to think their way to consistent investing success, they would keep very quiet about it. But the history of technology demonstrates that key breakthroughs often have multiple discoverers who enjoy the same Eureka moment quite independently of each other around the same time. So even the most determined IP lawyer would be unable to stop the market-busting breakthrough finding a wider audience. At which point, there would be no point in markets anyway, since everyone would ‘know’ the information the market discovers beforehand.

So far, so negative. However, whilst no System 2 process will deliver a strategic method guaranteeing 100% success, there are economic tools which which quantitative analysis confirms do add value, systematically raising your chances of being invested in the right places at the right time. Here I’ll introduce two of them (albeit in conceptual terms only) which have survived the quant analysts’ autopsies: first, return on capital; and second, profits.

Both sound not mere familiar but bone-headedly obvious: why would anyone think of investing in equities if they didn’t have a view on return on capital and profits? Answer: because they’re macro-economists, and macro-economics historically has been relatively incurious about returns and profits.

Taken together these two not only help form the foundation of understanding where a particular economy is in its business cycle, but also, of course, builds a basis for comparison between the position and likely medium-term trajectory of other economies competing for your investment.

Return on Capital

I construct a Return on Capital Directional Indicator (ROCDI) by treating GDP as a flow of income from a stock of capital, and as that income fluctuates relative to the stock of capital. This is a simple idea, in macroeconomics related to Incremental Capital Output Ratio (ICOR) and in equity research to the asset turns (Sales/Total Assets) element of the Dupont Analysis decomposition of return on equity.

The key difficulty is estimating the size and growth of capital stock. I make an estimate by depreciating the gross fixed capital formation line-item in quarterly national accounts over a 10yr period. Whilst such a straightforward approach refuses to engage in a number of obvious (and interesting) questions, in practice the results concur closely with the results of more scrupulous surveys, where available.

Crucially, these calculations are made using only nominal data (rather than real): ‘real’ counts of investment in capital goods seem to me to be hopelessly compromised by a) the issues arising from the Cambridge Capital Controversies; and b) the key characteristic of capital goods is that their price fluctuates dramatically with business cycle, but in balance sheet accounting terms they remain on the books at purchase cost. That difference between capital goods market price and book price is, quite obviously, a key element in the business cycle dynamics we want to understand.

The result is that we can see not only the fluctuations in trends in return on capital, but also how investment activity fluctuates (and is likely to fluctuate) in response.

Here, for example, is how it looks for the US.


Kalecki Profits

Getting a grip on profits is less simple, but one can treat changes in corporate profits, or corporate saving, as a function of the changes in net investment plus the changes made in savings flows from the household sector, the government sector, and the ‘rest of the world’. To put it crudely, one sector at a time:

if the household sector’s savings ratio (defined as compensation minus consumer spending) diminishes and everything else is held constant, then corporate savings (ie, profits) will rise by the same amount;

If the government’s net (dis)savings position changes (ie, the fiscal deficit rises or narrows), and everything else is held constant, then corporate savings will fall or rise by the same amount;

If the rest of the world’s saving position with the economy (ie, the trade balance in its wide description) changes, and everything else is held constant, corporate savings will fluctuated by the same amount.

This is, in fact, nothing more than an economic accounting identity. To my knowledge, it was first articulated by a Polish Marxist-influenced economist Michal Kalecki in the 1930s, who initially used it to analyse the exploitation of the workers. Whilst it is not necessarily always easy (or possible) to calculate it with certainty, the results are extremely useful in observing the trajectory and force of business cycle dynamics.

kalecki profits.jpg

A Scamper Through Gold's Monetary History

If you find money mysterious - and I think anyone who has thought hard about it must - then monetary history is a constant source of revelation. One strand which is retreating into history concerns the role of gold. I have a piece on ‘Gold as Monetary Arbiter’ in the Global Dispatches magazine - it’s a quick scamper through some monetary history which you might not be familiar with.

More broadly, over the last few months I have been trying to read through the entire accumulated transcripts of the FOMC from the post-war meetings where the Fed is trying to finance the Cold War, to the 1971 abandonment of the dollar gold standard, to the extraordinary practical, philosophical and academic debates which engulfed the FOMC during and after the Great Financial Crisis.

It is the history of highly intelligent, highly motivated and informed people constantly discovering their mistakes, and repeatedly finding that even the basis on which they made those mistake were themselves mistaken.

On one level, it is an on-going demonstration of Hayek’s contention that economic policy-making faces impossible information problems. On another level, it is a history of people grappling with the fundamental contradiction of any reserve currency: too little money inhibits its use as a medium of exchange, too much money erodes its use as a store of value. But more mundanely, it is confirmation that no theoretical economic policy, and no econometric approximations, survives contact with unfolding reality for long. Everyone is constantly doing their best, and only fitfully finding that their best is, for the time being, good enough.

It is easy, then, to run through the history pointing to the errors, to the hubris of FOMC efforts. But truly this would be dishonest. The general tenor of FOMC discussions throughout the decades is one not inviting hubris, but irony: earnest irony. Even during what from current perspectives were the FOMC’s finest hours, board members quite openly acknowledge that they aren’t entirely sure what they are doing. Indeed, some of the most dramatic policy decisions are ventured despite profound uncertainty about whether the outcome might be good, or disastrous.

The thread which connects all the attempts of FOMC’s personnel to determine policy is the tension between reacting to current circumstances whilst at the same time protecting the value of money. This tension is always present, and even when seeming financial emergencies command the FOMC’s urgent attention, the philosophical backlash arrives rapidly after the immediate emergency retreats. What are we doing? What have we done?

In a free-floating monetary world, the search for a standard, a lever from which to move the world, goes on. Quite possibly it always will.

Investing, Fast and Slow. Part 2: Fast!

I don't mean frantic day-trading, chasing micro-trends before they evaporate. Rather, I mean working to create insight into what drives System 1 thinking about investment. If a portion of market-pricing at any one time is the result of System 1 thinking, we should expect it to be the result of impressions and feeling and instincts which eventually surface as the explicit beliefs expressed in the deliberate choices of System 2 thinking.

But these impressions and feelings will not be random. To quote Kahneman, System 1 type thinking 'has also learned skills . . . and understanding nuances of ... situations. Some skills . . . are acquired only by specialized experts. Others are widely shared.' The approach I adopt, then, is to work out what generates those impressions and feelings, and the understandings they generate. If my beliefs about the inputs into System 1 investment thinking are correct, it opens the possibility that a careful tracking of those inputs will allow me to understand and anticipate the results of System 1 investment choices.

This is what I have done, using as feedstocks the shocks & surprises indexes generated by my unusually broad and detailed tracking of global economic data. The very name 'shocks and surprises' conveys the hint - that these are precisely the data which System 1 type thinking is likely to notice and react to. Yet as Kahneman warns 'the automatic operations of System 1 generate surprisingly complex patterns of ideas,' and the intuitive belief that movements in asset prices will simply mimic the trajectory of shocks & surprises indexes turns out to be wrong. Such a simple interpretation will, alas, lose you money (so DO NOT TRY THIS AT HOME).

Nevertheless, further exploration has borne fruit. Alternating investment choices among the world's major stockmarkets using models approximating System 1 thinking has allowed a consistent and ultimately rather spectacular outperformance of the MSCI World Index since I started this at the beginning of 2014.

system 1 model.jpg

Since that period, the MSCI World Index has gained 25.2%, whilst my model has gained 80.7%. The average weekly gain for the MSCI World Index during that period is 0.11%, with a standard deviation of 1.74%; the weekly average for my System 1 model is +0.26%, with a standard deviation of 1.89%.

Conclusion? Investing Fast isn't about turning over your portfolio at rapid speed, it's about understanding that System 1 thinking is part of how market prices emerge in the short term.

Investing, Fast & Slow. Part 1

My starting point is that, one way or another, investing is and will remain a fundamentally human activity.

To be more specific, investing is and will remain a cultural phenomenon that has evolved in a way which contributes to the growing role of intelligence in the universe. Fairly obviously, that evolution is itself evolving different tool sets to help do the job. Quantitative modelling has developed a whole sert of tactics, strategies and expressions which are new branches on the tree, but the tree remains fundamentally the same.

That the task has remained fundamentally the same is not obvious: as each new tool has arrived, intelligent people have feared that the game is changed. (Here's how Robert Mayo, then head of the Chicago Fed discussed with the FOMC the rise of the options market in the 1970s: 'My elbow is still uneasy about this. There is a counterculture, if you want to distinguish it that formally, developing now with the evolution of puts, that will counterbalance the calls, and the market will be better again. But this is getting into real mystique. I don’t think anyone really knows what he’s talking about.')

Even when computer-driven trading represents the majority of stockmarket activity, I'm prepared to take it as axiomatic that investment will remain a fundamentally human activity. That's partly because no matter how much data is fed into the algorithms, market pricing will retain its ability to discover information which can be discovered in no other way (Hayek's thesis). Indeed, if computer programs alone were able to remove unprogrammable surprise element from pricing, then there would be essentially no purpose to markets in the first place - we'd be better off simply allowing the computers, not markets, to allocate resources. We know how that ends, and it's not well (ironically, we might say the data is in on it.)

The ultimate impact of computer-driven trading in all its variety is mitigated by the enduring fact that at both the top and bottom of the investment-decision tree, humans get involved. At the bottom of the tree, we have humans making decisions about whether to invest and how to invest. Having made the decision to save, and save in equities, what governs the choice between single stocks, mutual funds, ETFs, family offices, hedge funds, or CDFs and derivatives of various kinds? Price, fashion, advice?

When an institutional vehicle is chosen, the way that institutional vehicle runs itself is constrained by irreducible human factors, including fashion, 'respectability', theoretical justification (portfolio theory etc). the regulatory environment, and the sensitivities of investors and trustees. And finally, at the top of the investment decision, the entire investment environment is affected by the decisions of the 12 people on the FOMC. History provides abundant evidence of human intelligence and fallibility in their decisions.

Essentially then, investing is a human activity, and therefore an expression of human thought.

Which brings us to Daniel Kahneman and Amos Tversky and the book 'Thinking, Fast and Slow'. My guess is that you'll have recognized the reference in this piece's title. Kahneman's book gave birth to the field of behavioural economics and in its wake there have been a large number of usually unsuccessful attempts to deploy the insights of behavioural economics (ie, loss aversion etc) into investment strategy.

But it may be more useful to consider what he has to say more widely. At the heart of 'Thinking, Fast & Slow' is the description of two types of thinking. System 1 thinking is fast thinking, what we do, very often unknowingly or instinctively, to make snap decisions about situations we encounter all the time. By contrast, System 2 thinking is slow and deliberative, demanding an expenditure of energy in conscious effort. (And System 2 thinking is expensive: as someone said, 'Most of the world's problems can be solved with five minutes thought. But thinking is hard, and five minutes is a long time.')

It strikes me that since investing is an essentially human activity, we should understand that the results will always represent a mixture between the results of System 1 thinking and System 2 thinking. The suggested corollary is that if you rely solely on System 1 thinking (ie, you are a day-trader) you will sooner or later get beaten out of the market by the results of System 2 thinking/investing. But it's probably no less true that if you rely only on System 2 thinking, investing only in line with your carefully worked-out strategic insights, you will spend a lot of time getting killed by the 'irrational' activities of System 1 day-traders (who might well turn out to be algos anyway).

In other words, if investing is a fundamentally human activity, you need to have an approach which acknowledges and incorporates both System 1 and System 2 investing. You need to think about Investing, Fast & Slow.

I’ll start doing that in Part 2.

Korea Households Now in Net Debt

S Korea's 2Q flow of fund accounts, released today, at first sight look rather dour as far as the household sector is concerned. On deeper inspection, however, they are worse than that.

But first a caveat: taken broadly, the household sector remains in fine financial conditions, with net financial assets of W1,994.4tr (or US$1.78tr at 3Q exchange rate), and equivalent to 113% of GDP. The household sector has, in other words, net financial assets equivalent to more than an entire year's output.

Nevertheless, there are three problems:

First, during 2Q the household sector’s position deteriorated, falling by 0.7% qoq, or W14.68tr, thanks to a W18.2tr fall in holdings of equities. The 2Q results will, of course, have caught the full force of June's 8% fall in the KOSPI, from which there has as yet been no significant recovery. Still, the fall in net financial assets is a rare event: since 2009 it has happened only three times. In yoy terms, the growth has slowed to 4.1%, compared with a nominal GDP growth rate of 4.8%, and net financial assets/GDP ratio has been essentially stagnant since 2015.

The second problem owes nothing to market volatility: S Korea's households are now net debtors to the nation's credit institutions. During 2Q, household holdings of deposits are currency rose W16.78tr qoq, but loans rose W27.06tr. As a result, the net position of households with credit institutions deteriorated W10.29tr qoq to end the quarter with a net debt position of W5.1tr.

This is merely an extension of the continuing deterioration in household's banking position that's been continuing since 2015, but it is only the second time we've seen an actual net debt position. It is worth pointing out that it is now quite unusual in developed economies for the household sector to be net debtors to the banking system: net deposit positions are now the norm - a legacy of the financial crisis.

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Third, the willingness of the household sector to take on net debt has been useful in helping sustain S Korean domestic demand. In fact, the W10.29tr qoq deterioration in the position was equivalent to 69% of the qoq nominal GDP growth seen in 2Q. Over the last year, the deterioration came to W16.1tr, which was equivalent to 20% of the rise in nominal GDP growth. The implication is that if the Korean household sector becomes reluctant to continue letting its banking position slide, the impact will be felt on nominal GDP growth. And are they reluctant?

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Asia's Economic Trajectories Diverge

It doesn’t take much thought to summarize current views on Asia: ‘Not interesting: US-China trade war; rising US interest rates.’ And the overall trajectory of Asia’s economic data doesn’t offer much challenge: Asia's overall shocks & surprises index has been mildly negative (with a short-lived reprieve in early June) since the end of January, and remains so today. However, the focus of weakness has changed sharply throughout the year.

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One of the advantages of tracking a large number of datapoints is that I can break this down these regional indexes into more specific countries or sub-regions. And that breakdown shows that there are quite distinct and divergent patterns of activity now emerging. Specifically, let’s look at the differences emerging between Greater China (China, Taiwan, HK), Japan, and the Rest of Asia.

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Since mid-July, Japan's data has tended to break consensus or trend positively, and the Japan index is now persuasively strong. More significantly, over the last year, its trajectory has begun to move in concert with trends in the US, suggesting that the economic ties between these two are beginning once again to tighten, having decoupled around the middle of 2016. On this basis, Japan looks the principal Asian beneficiary of the vigour of the US’s business cycle.

By contrast, Greater China has sustained a period of disappointing results since the beginning of August, in a way which reverses the surprises achieved earlier in the year. It is not difficult to believe that this sustained disappointment is connected with the evolution of US-Chinese trade disputes.

Maybe the most interest result, however, is coming from the 'Rest of Asia, which since early September has strung together a series of surprises for the first time since the middle of January. As with Japan, it looks as if the Rest of Asia is beginning to feel the updraft from the US expansion.

This is a genuinely surprising development. It has happened despite the scepticism which has enveloped emerging markets globally in response an earlier strengthening of the dollar and an assumption of repeated US interest rate rises. And it has happened despite the mounting weakness of economic data in some major Asian economies (principally S Korea). But the recovery of the last few weeks has also coincided with the stabilization/weakening of the dollar, and the upturn in the Funk Index.

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If it persists, the unexpected vitality of the 'rest of Asia' suggests that the positive impact on Asia of the US cyclical upswing is, at least for the time being, offsetting the negative impact of dollar strength and rising interest rates. It is an economic story which is being lost as commentators concentrate on US-China trade frictions and rising interest rates. If it continues, those stories will have to change.

Eurozone - Inflation Not 'Relatively Vigorous'

Messaging is taken as a crucial part of the central bank governor’s job, so we can’t be sure that headline writers and bond markets got it wrong this week when they latched on to ECB governor Mario Draghi’s description of Eurozone headline inflation as ‘relatively vigorous’. He did, after all, tell the European Parliament that ’underlying inflation is expected to increase further over the coming months as the tightening labour market is pushing up wage growth’.

In fact, the headlines belied Draghi’s rather drab forecasts: ‘Annual rates of HICP inflation are likely to hover around current levels in the coming months and are projected to reach 1.7% in each year between now and 2020. This stable profile conceals a slowing contribution from the non-core components of the general index, and a relatively vigorous pick-up in underlying inflation. Reflecting these dynamics, the ECB projections foresee inflation excluding food and energy reaching 1.8% in 2020.’

Given that in August, headline CPI was running at 2%, it is plain that ECB thinks headline inflation has already peaked, despite a modest uptick in core inflation (currently 1%). In general terms, that conforms with what one would expect if the deflections from 5yr seasonalized trends seen over the last six months are maintained. And given that those 6m deflections are already running at 0.8SDs for headline inflation and 0.9SDs for core inflation, these are already pretty punchy short-term forecasts.

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In fact, it remains very difficult to make a case for a sustained uptick in the Eurozone’s inflation picture, with even the ECB’s longer-term steady-state at 1.7% looking hard to justify.

Rather, what evidence we have, including labour market evidence, gives no real hint that we are at an upward inflection point in Eurozone inflation. That evidence encompasses the state of inflationary expectations; the continued inability to pass through rises in factory prices to the consumer; and, crucially, labour market and wage trends.

First, consider expectations. Unlike in the US, where the inflationary expectations curve is now inverted, surveyed expectations in the Eurozone continue to expect a very modest uptick in inflation. On a quarterly basis, the ECB surveys professional forecasters, and compares that with consensus economics, and the European Commission’s monthly survey of consumer expectations: over a 2yr period, the expectation is for inflation of 1.6%-1.7%, with longer-term expectations of 1.8%-1.9%. These longer-term inflation expectations are almost entirely unchanged over the past four years.

But not only are longer-term expectations unchanged, they have fallen relative to 1yr inflation expectations. The Eurozone inflation expectations curve has not inverted, but is has quite clearly flattened over the last few years. Expectations, in other words, are an increasing damper on inflation, not a driver of it.

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Second, there is no observable improvement of the ability of retailers to pass through increases in factory prices to consumers. Looking at the difference between monthly rises in PPI and monthly rises in CPI produces a CPI/PPI terms of trade. When it is rising, as it did between 2013 and 2016, it implies an improving ability of distributors of final goods and services to raise their margins. If there is underlying inflationary pressure from their suppliers, they are able to pass it along. But when the line falls, the reverse is true (ie, increased costs can’t be passed on to the consumer).

Since early 2017, the line has been stable, suggesting cost increases can be passed on, but final distributor margins are not rising. There is, in other words, consumer resistance to higher prices. As one would expect if underlying inflationary expectations are in retreat.

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The most curious feature of Mr Draghi’s presentation, however, was the apparent belief that inflation will be bolstered by wage pressures. This seems, on the face of it, utterly remarkable: the Eurozone’s unemployment rate is still above 8%: can it really be the case that the Eurozone’s labour market and supply-side rigidities are such that wage inflation kicks in at 8% unemployment? If so, the Eurozone is an extraordinary international outlier. The US unemployment rate of 3.9%, the UK rate of 4%, the Japanese rate of 2.5%, none of these has so far proved the foundation for inflationary wages rises.

If there is one economy within the Eurozone where this argument might develop some purchase, it is Germany, where the strictest definition of unemployment puts the rate at 3.4% (though the Bundesbank prefers a more generous figures of 5.2%).

But even in Germany, it is impossible to make the case that current wage rises are a potential source of inflation. In 2Q18, gross average monthly earnings growth was running at 2% yoy in Germany, which, deflated by CPI implies no real growth at all. Meanwhile, real GDP per worker was growing at 0.9% yoy. In other words, current wage rises are not even keeping up with productivity rises: if this continues for the medium term, the supply produced by Germany’s workers would therefore be rising faster than those worker’s ability to consume the product without either eroding savings or borrowing. Far from being inflationary, current wage settlements in Germany are currently disinflationary for the first time since 2012!

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Conclusion: If the Eurozone is about to see a modest sustained uplift in inflation, it will have to do so in the teeth of the underlying trends in wages vs productivity in its dominant economy.

Trade War Casualities or Business As Usual?

Let's imagine you are running a Chinese factory that exports to the US (maybe you are!), and all year President Trump has been tweeting his intentions to mess you up. How do you respond? I think your choices are: a) do nothing - he's bluffing; b) export like crazy because tomorrow you die; c) get your offshoring options nailed down.

What does this do to China's export statistics in the short term? a) nothing; b) spikes them around how; or c) depresses them but pushes up other Asian exports.

Now let's have a look at the evidence. First, China's exports are in only so-so health. The headline numbers are better than they have been for a few years: in August exports were up 9.5% yoy, and on a 12m basis they are rising 11.2%. But second, there's really no sign of any current sharp acceleration: in sequential terms, August's tally was 0.1SDs below where you'd expect it to be in August; in July the sequential movement it was down 0.5SDs. These results are not really consistent with the idea there's a lot of extra exporting in anticipation of Trump's tariffs.

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And third, putting China's export data in the context of regional export performance, there's no overall sign that its immediate neighbours (Japan, S Korea, Taiwan) are benefiting from much relocation of demand. In fact, China's share of Northeast Asian exports is rising, hitting 60.9% in August. But, as the chart shows, this recovery of market share has been underway since 2017, with little noticeable acceleration this year.

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For all the angst, then, the evidence seems to suggest that if you're a Chinese exporter, for now you shrug your shoulders and keep doing what you do best - exporting.