Why China Had To Crash Part 1

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In this post I consider the economy in general: I’ll cover asset markets in particular in the next column, but you’ll need to understand today’s post to comprehend the stock and property market dynamics at play. Having said that, the Shanghai Index fell another 7.5% on Tuesday, after losing 8.5% on Monday, and is now down over 45% from its peak—so I’ll try to write the stock-market-specific post by tomorrow. In this post I’ll show, very simply, why a slowdown in the rate of growth of private debt will cause a crisis, if both the level and the rate of change of debt are high at the time of the slowdown.

Click here to read the rest of this post.

About Steve Keen

I am Professor of Economics and Head of Economics, History and Politics at Kingston University London, and a long time critic of conventional economic thought. As well as attacking mainstream thought in Debunking Economics, I am also developing an alternative dynamic approach to economic modelling. The key issue I am tackling here is the prospect for a debt-deflation on the back of the enormous private debts accumulated globally, and our very low rate of inflation.
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23 Responses to Why China Had To Crash Part 1

  1. Tim Ward says:

    “…Given that we already have an estimate of the flow of new debt at a given point in time, the GDP figure is a proxy for the turnover of existing money at the same time. There is unavoidably some double-counting, but it will have to do: while double-counting will plague this analysis, the alternative of ignoring the impact of the change of debt on demand and income is a much bigger mistake.

    Given those caveats, we can treat total expenditure in the economy on both goods and services (GDP) and assets (property and shares) as GDP plus the change in debt. …”

    Just curious if it is possible to get a handle on some of the double counting.

    “…A new home that is built during a given year is counted in that year’s GDP, while the purchase of a previously owned house has already been counted in the GDP of the year it was constructed.” http://www.colorado.edu/economics/courses/econ2020/section6/GDP-components.html

    But there will be an addition to the debt for that same year, the construction financing (then replaced by the mortgage financing).

    So this seems to be an example of the double counting. A new house will add to both GDP and the change in debt in that year. But we have a good idea of the amount of new homes, compared to existing home sales. Very roughly 10% or something like that.

    Apologies if this isn’t a type of double counting, or if I have made some other error, or miscomprehend. E.&O.E. !

  2. igmos00 says:

    Steve I am I appreciate what you are trying to do. I saw that you have codes and you are trying to run simulations. Two issues. The double counting matters because it lowers the impact of the argument, correct? Second, why are you using 25% percent growth rates in debt in your table. Isn’t it more like slightly larger than 10% or are you saying that just in 2014 the growth rate in debt was say 20% and the gdp growth rate according to official figures was less than 10%. The explosion in debt has been going on for several years. I guess I have no idea why you chose the numbers you chose in the table. I would certainly read a blog post that discusses the definition and source of the numbers that should go in that table. It seems to me that it could make a big difference on the chances that china will be able to lower the rate of growth of debt without a major crash.

  3. igmos00 says:

    I see the debt to gdp has almost doubled in less than ten years. I am not an economist. A bit of background would be nice. So you are saying for that to happen debt must have been growing a lot faster than gdp. Say 20% and 10%. Ok so it is still not clear where in the process of achieving parity with the rate of growth of gdp is china at this point. The slow down in aggregate demand could have taken place in the past and could possibly result in yet another “japan” as you put it. It seems likely that you are right that china is in trouble but I am not sure where things stand at present based on what you have written. Anyway it is clear at least to me that there is reason to worry.

  4. Steve,

    “So total expenditure and income in our economy is the sum of the turnover of existing money, plus the change in private debt”

    I understand that this will be true in the first time period, but won’t the change in the private debt of the first period possibly get added to the turnover of existing money in the second period too? So even if the change in private debt is less in the second period there may still not be a deflationary effect.

    Or some it could be removed in taxation, or it could be saved. Then there would still possibly be a deflationary effect, but we’d need to know just how much was taxed away and how much was saved.

    It’s a genuine question. I’m not trying to be awkward!

    Thanks in advance.

    PM

  5. Steve Keen says:

    Hi Peter,

    Think of it as water revolving in a bucket (old Bill Phillips’s hydraulic model was a great insight!), with new water being added from a hose. The water in the bucket is the existing money supply. Its rotation in a year is the volume of existing-money-financed expenditure and income. The water coming in from the hose is the new debt-created money (and demand and income).

    Next think of how we record flows like this: at a single point in time, we record the volume and rate of flow of the water in the bucket in terms of megalitres per year; at the same time, the water flowing in from the hose is recorded in megalitres per year. At that point of recording, the two flows are distinct, so you can add them without double-counting.

    I might use that explanation–if it makes sense to you–in the next column!

  6. Steve Keen says:

    I rushed that piece out given the time urgency right now; in the next one or two posts I’ll include the actual stats for China for the last 8 years. The rate of growth of debt has been as high as 35% of GDP per year; it’s currently running at 25% of GDP a year.

  7. Steve Keen says:

    Coming in the next couple of posts, as noted in the previous comment.

  8. Steve Keen says:

    It’s more the poor quality of GDP recording that I was focusing on than the conceptual side of things. If the actual turnover of money was measured, rather than GDP, then there would be no double-counting worry–as explained in the reply to Peter Martin. It’s just that GDP measurement is likely to mix some things that are debt-financed up with non-debt financed. But given that–unfortunately!!–most debt is taken on to finance asset purchases in the first instance, there won’t be as much double-counting as there could have been back in the 1950s when banks actually financed business turnover.

  9. JohnSmith says:

    “[Richard Vague] found that every [..economic crises across the globe over the last one and a half centuries..] occurred when the private debt to GDP ratio exceeded 1.5 times GDP, and when the ratio had risen by 17% or more over a 5 year period.”

    Is there any explanation why the actual level of debt matters? Why 1.5*GDP? Is it the interest rates? Why does just the change of the ratio of debt to gdp matter? Why 17%/5years?
    Up to now I found the criterion of Prof Keen about the starting point of a financial crises (change in debt gets bigger than income, i.e. the acceleration(!) goes through zero) very convincing.
    Does this criterion still apply in these cases?

    Another question: Does anyone know about a criterion on how long a phase of deleveraging lasts?

  10. Tim Ward says:

    The change in debt level not associated with GDP changes (ie not double counted) could possibly be approximated by:

    The sum of new debt for stock buybacks & dividends + new margin debt + debt increases for existing home sales and existing commercial real estate. (and maybe + debt rollovers, where the debt is increased)

    These would all be debt increases associated with incomes. And they wouldn’t be in the GDP numbers.

  11. JohnSmith says:

    That sounds very reasonable!
    Do you think (or better: Is it quantifiable) if these kinds of debt not directly affecting GDP still indirectly affect the real economy (like employment, wages, production level, etc.)?

  12. Hi Steve,

    Thanks very much for your reply.

    I’ve been thinking about this and I’ve made your water spinning in a bucket into water circulating around the moat of a castle. We’ll assume the existence of pumps to make it do that. Also assume zero evaporation. So we can add water from a pipe to represent the created money, as you suggest, and add the two flows which can be regarded as separate in the first instance.But, what happens to the main flow as the level in the moat rises? As it will if we add water. If the water speed stays the same then even if the flow from the pipe drops, the total flow won’t decrease. But if the flow is governed by the capacity of the pumps then more water will mean less speed and what you say will be exactly right!

    So does this analogy really answer our question? It depends on how the main pumps operate. If their pumping capacity also drives the water in the pipe etc.

    To stay on your hydraulic analogy, I was thinking we could represent government spending as the release of water from a dam which for all intents and purposes was holding a lake of infinite size. So government spending can be whatever govt wants it to be. The released water forms a river which flows downhill into the sea, as rivers do, and the water entering the sea can represent taxation. Again we’ll assume no evaporation. So if there’s no interference with the river, spending must equal taxation revenue. But if the river flows too quickly we could have inflation. Too slowly means recession.

    But what happens if the inhabitants of our hypothetical land decide to pump some water out of our river and save it in their own smaller finite sized reservoirs? The amount of water entering the sea will be less than enters the river. ie Govt will be in deficit. If they then drain their reservoirs ie spend their savings , there will be more water entering the sea than enters from the govts dam and they govt will be in surplus.

    We can now postulate the existence of a bank which also has the capacity to lend water to the inhabitants. But unlike govt it wants back what it has lent out. So if it is net lending to the inhabitants the water flow in the river (which of course represents total demand) will increase and the govt may even be in surplus as more water enters the sea than leaves the govt dam. But if net lending slows or is even reversed then the water flow in the river will fall leading to lower demand and so increasing a tendency towards a recession. The govt can of course fix the problem by letting more water out of its own dam to compensate for the fall in lending. Govt just needs to learn to not fret about running out of water which it can’t do because its own dam is essentially infinite in size.

    So I now think you’re right. But it has taken a bit of thought to see that.

    Thanks again and Best Wishes

    PM

  13. Tim Ward says:

    “Do you think (or bet­ter: Is it quan­tifi­able) if these kinds of debt not directly affect­ing GDP still indi­rectly affect the real econ­omy (like employ­ment, wages, pro­duc­tion level, etc.)?”

    Yes, the other kinds of private debt have to affect the real economy, because increases in private sector debt decrease further creditworthiness, and they have to be serviced. It’s something like the private sector economy having a time variant creditworthiness, the total amount of possible serviceable debt. This total creditworthiness changes over time. It also depends on interest rates. But as you get close to the boundary, serviceable credit growth has to slow. Which means you run into a brick wall. So this speaks to the significance of the debt to GDP ratio, when it gets big enough, the creditworthiness/serviceability runs out. “All loaned up.” Empirically, the ratios are as Prof. Keen shows.

    I haven’t thought about it, but its perhaps something like the heat death of the universe. The cure is the debt jubilee.

  14. JohnSmith says:

    I was wondering about it, because of Prof. Keens plot, where he got the strong correlation (~-0.9) between unemploymentrate and change of private debt to gdp ratio. And there he did not adjust for the usage of the debt. So it seemed that it did not matter how the debt was spent to get the effect on unemployment.
    So could a big company just take a huge loan and buy whatever they want (like stocks, bonds, or nothing) and there will be (indirectly) jobs created by it?

  15. Tim Ward says:

    The category of debt having to do with stock buy backs, margin debt etc could be responsible for the correlation coefficient being less than the very high correlations, say ~0.97 – 0.995.

    LBOs, leveraged buy outs, in which companies are loaded up with debt, none of which goes into real capital, productive equipment, research and development, product development, new hires, etc, often wind up going bankrupt. Wiping out employment.

    (**Additional new debt for LBOs, M&A, and the like also looks like the type of debt that would be in the non-GDP, or non-double counted debt.**)

    Typically, high levels of M&A activity are a late cycle sign. And we’ve seen this.

    The new debt for the stock buy backs and dividend payouts looks something like a company is LBO-ing itself. Doom. Since the borrowed money has not gone into productive capital, product development etc, how has the company improved it’s ability to earn money to pay back the loan/service the bonds? What it has done is cripple it’s revenue/income, by increasing servicing costs, and decreasing profitability. And how can it then pay back the bonds/loans when the money has gone/been wasted? Only when the money goes into something useful does the company improve it’s ability to pay back the debt.

    So the surge in those kinds of debt looks like a very bad sign to me. Something like ~$2 trillion in bonds for buybacks, other junk bonds, leveraged loans, and CLOs has been created in recent years in the US, last 3 years or something. Debt with highly problematic serviceability. Declines in the underlying collateral will be disasterous. So when enough of this debt accumulates, it looks like a wipe out of employment is on the way. The high dollar exacerbates this, as demand for US products declines. So the slowdown in China and devaluation, and the commodity crash, with commodity producer currencies crashing, with high dollar, declining trade volumes, and large junk debt accumulations, and the now large debt to GDP in China, looks like very bad.

  16. JohnSmith says:

    “The cat­e­gory of debt hav­ing to do with stock buy backs, mar­gin debt etc could be respon­si­ble for the cor­re­la­tion coef­fi­cient being less than the very high cor­re­la­tions, say ~0.97 — 0.995.”

    This is an interesting and testable (!) hypothesis! Do you know where to get the data (debt/loans by usage)? So we could run some regression?

  17. Tim Ward says:

    NYSE margin debt; http://www.nyxdata.com/nysedata/asp/factbook/viewer_edition.asp?mode=table&key=3153&category=8

    Some of the other data might be more difficult to get, but sometimes bank research comes out with data for them. Could try searching Bloomberg, or the St. Louis Fed.

    http://www.bloomberg.com/politics/articles/2015-06-19/record-cash-wrung-from-bond-market-to-cover-u-s-stock-buybacks

    Bloomberg mentions Sundial Capital Research Inc., Jason Goepfert, SentimenTrader, as a source.

  18. Tim Ward says:

    Another idea to get at an estimate of corporate debt ‘wasted’ in the US, could be to subtract the FRED data for nonfinancial corporate business capital in some form, from total nonfinancial corporate business debt.

    But I don’t know the best series to use. eg. https://research.stlouisfed.org/fred2/series/NCBDBIQ027S
    subtract the capital from that, could give the ‘wasted’ debt.

  19. JohnSmith says:

    Thank you for the links!
    When i find time i will look into it. Some of the data seem to need some pre-processing or smoothing first.

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