The conventional model of infections is known as SEIR for “Susceptible/Exposed/Infected/Recovered”. This paper is one of many to produce such a model, with the relatively novel feature that it includes “resusceptibility”: the possibility that people who have been infected and have recovered might lose immunity and get it again.

Figure 1: The paper

In equations, it is as follows (in a simplified form omitting births and ordinary deaths, which is a reasonable simplifying assumption, given how quickly Covid-19 spreads):

Figure 2: The ordinary differential equations of the core model

Bryan Wisk, who is the founder of Asymmetric Return Capital, a long-time friend, and one of my patrons, volunteered to have this model developed by his staff in Minsky, and asked for some quick guidance on how to do so: hence this video. In it, I start to develop this model but don’t finish it—I’ll leave that for Bryan’s staff.

The paper itself has a “dashboard” of the model, but to run it, you need a copy of the commercial program in which it was written: Simulink, Matlab’s system dynamics program. This program is used by engineers all over the planet, and it is very expensive for non-academics. Getting a price upfront from Matlab is very difficult, but let’s say you won’t get much change out of $2,000 for an annual Simulink licence.

Figure 3: The Matlab Dashboard

Simulink has a lot of features and capabilities that Minsky doesn’t have, but there are shortcomings in its core functionalities that we’ve attempted to overcome in Minsky.

One is that, in Simulink, all calculations are passed “by wire”: if you want to use the output of one set of equations as an input to another, you have to draw a wire from one to the other. In Minsky, you can name the result of a set of equations—for example, “Die”—and then use that variable name elsewhere on the diagram, without needing to draw wires. This reduces model clutter compared to Simulink and almost all other system dynamics programs.

Figure 4: A Simulink model of a helicopter Flight Control System

Minsky also supports the mathematical formatting language LaTeX. In Simulink and to my knowledge all other system dynamics programs, if you want to use a variable called “”, you literally have to write the text “gamma”, and that’s what you see. In Minsky, you type \gamma, and what you see on its design canvas is . You can also use superscripts and subscripts, using the control characters _ and ^ respectively.

These are definite advances for Minsky, but if that were all there were to it, Minsky wouldn’t even exist. Minsky’s real reason for being is the unique double-entry bookkeeping feature we call “Godley Tables”. These are used to ensure that all financial flows are modelled properly, as having a source and a destination. Though our intention with the Godley Tables was to allow financial dynamics to be modelled easily, it also makes sense here when you are recording movements of people between different mutually exclusive categories. The first step in designing this Minsky model was to enter the total population (N) as an Asset, the number susceptible (S), Exposed (E), Infected (I) and Dead (D) as Liabilities, and those who have Recovered (R) as the Equity.

Minsky takes this as an input and generates the Ordinary Differential Equations automatically in the background. These are identical in structure to the equations in Figure 2, but the individual components have yet to be defined:

Figure 5: The initial equations in Minsky

The next step in building the model was to enter the parameters in the paper, and here there were two problems: they were scattered throughout the paper; and there were unnecessary steps taken by the authors that shows (I think!) that they are unfamiliar with the basic system dynamics concept of a time constant. This is a measure of how quickly a system state would take to reach a target level, expressed in the unit of time that makes sense for the system. With the Coronavirus, the sensible unit of time is a day, and one key “time constant” is how fast it takes for someone to go from being exposed to the disease to being actually infected. In the paper, this is called the incubation time, set at 5.1 days, and the symbol they use for it is .

This is all very sensible in system dynamics terms. The parameter is easily interpreted: if you increase its value to, say, 7, you are modelling the case where it takes about 7 days to get infected after exposure. Reduce it to 3, you are modelling where the process takes 3 days.

Unfortunately, they don’t use in their equations, but instead use , which they define on page 4 as “”. Then has the incomprehensible value of 0.196078. This is how I reproduced that in Minsky:

Figure 6: Defining as in Minsky

If I was doing this work myself and had the time, I would rewrite the equations in terms of time constants and get rid of this unnecessary step. But since I was doing this mainly to develop an instructional video for Bryan’s staff, I stuck with their equations and did this for several parameters in the model.

Figure 7: All the parameters in the model

The next step was to copy the stock (N,S,E,I,D, and R) and flow (Exp, Get, Die, Rec and Get_Again) variables from the Godley Table, which in common with so many aspects of Minsky, is on the right-mouse-button menu:

Figure 8: Copying the stock and flow variables onto the canvas

I didn’t complete the task—again, this was to instruct someone else in how to use Minsky rather than a job I intended doing from go to whoa—but I did complete a few of the definitions, including exposure, infection, and the death rates for the two different cohorts, young and over 65.

Figure 9: Defining Exposure and Infection in Minsky

Figure 10: Definitions for Die and Die_Old in Minsky

One thing that will prove a bit tricky for Bryan’s staff is the use of a time delay in the original model between when the disease and its first infections occur and when policy is developed:

Figure 11: The time delay of between the occurrence of the disease and infections and the policy response

Minsky doesn’t support time delays, largely for purist technical reasons. They introduce a discrete time element into a continuous time modelling framework, and I believe that discrete time modelling—dividing time into arbitrary units called “periods”—has been a major factor in Post Keynesian economics making far less progress in dynamics than it should have. So what you have to use instead is a first order time lag: you define another variable (say S_lag) and define this as something that converges to S with a lag. As an equation, this is:

Figure 12: First order time lag mathematics

As a Minsky flowchart, it is:

Figure 13: Implementing a first order time lag in Minsky

These variables S lag and I lag then replace and in the model:

This means that the Minsky model won’t quite match the simulation by the Simulink data, and some fine tuning will be needed to go from the delay they used (30 days) to a suitable time lag (I guessed at 14 days here). But those, in the customary words of the University lecturer, I leave as an exercise for the reader.

Over to you, Bryan and staff.

Merryn Somerset Webb has just recorded a podcast with me about the economic impact of the Coronavirus and what to do about it. This is a brief post to provide some of the data that I referenced in that discussion. Her podcasts are here, and the recording should be up soon.

While mainstream economists obsess about the level of government debt, the real cause of economic crises is not government debt but private debt. The UK’s data here is simply stunning. Between 1880 and 1982, private debt never exceeded 72% of GDP, and it averaged 57%. But it exploded after the deregulations that allowed the banking sector to lend to finance house purchases (and the privatisation of council housing and so on), rising to a peak of 195% of GDP in 2009.

That debt was split relatively equally between the household and corporate sector. After the 2008 crisis, both sectors have stabilized with almost three times the debt level, relative to GDP, that they had before financial deregulation.

The impact of that increased debt for the household sector has been simply higher house prices.

The causal mechanism runs from new mortgage debt to house prices. Putting it simply, most houses are bought primarily with mortgage debt, rather than out of income. So the monetary flow of demand for housing is primarily the flow of new mortgage debt. Divide this by the number of houses for sale, and you have a rough measure of the average demand price per house. Given how inflexible the supply of housing is, the change in this flow of demand is the primary determinant of the change in the house price level. So all this additional debt has done is simply drive up house prices by higher leverage.

This in turn has made Western nations in particular far more financially vulnerable than they were at the time of the last pandemic, in 1918, when private debt levels in the UK were at a historic low of 33% of GDP. With interest rates almost as low as today back then, the debt servicing burden on the economy was 1/5^th of what it is today.

This is why a proposal that I put forward as long ago as 2012—a “Modern Debt Jubilee”—is essential. Without it—and without income support from the government right now as well—the financial system could well collapse. A Twitter correspondent called it a “Universal Basic Bailout”, and that’s not a bad description in modern terms.

I’ll post this now and edit later to include an updated version of the argument I first made 8 years ago for a Modern Debt Jubilee. For now, to see the concept, please follow this link.

A friend on a discussion group I’m part of asked me this morning about the impact of debt repayment on the money supply:

So how does money and debt work in reverse? Has there ever been a deflation model based in real data… You know what you teach about how money is created by banks, what’s it look like in reverse, is money extinguished in deflation like money is created during inflation. If banks can lend money into existence using credit, does it work in reverse and can it be exponential?

That was easy to answer, since I’ve already modelled this extensively in Minsky:

Debt repaid reduces demand and money just as new debt creates both. Bankruptcy does the same via a fall in bank equity. Search for Patreon posts on loanable funds versus endogenous money [this is one of the posts I was thinking of why I wrote this] and you’ll see an instance.

It’s my Keen model on steroids. You could do the double entry in Minsky; I’m thinking off trying myself. Set up a multi bank model (3 should be enough) with rent from capitalists and landlords to banks, then halve the cash flow of both and see what happens. Halve output per worker as well.

The “Keen model” I referred to, as it’s now known in the literature, is my 1995 model of Minsky’s Financial Instability Hypothesis, where a series of credit-financed booms & busts leads to a final bust where debt repayment overwhelms the economy & causes a total economic collapse (click here for an accessible PDF). That is too complicated for what I want to examine here, but the alternative model in Minsky is looking pretty complicated as well. Here’s a first pass, with four banks—one each for firms, capitalists, landlords and workers—plus a Central Bank and a Treasury

What I’m planning on doing is setting up the financial flows so that the model-economy hums along OK, though with a high level of private debt (mimicking current US data, which for those who haven’t seen it before, is reproduced below:

Then I’ll introduce a “Coronavirus shock” that causes both output and employment to collapse, and see what happens to the solvency of the social classes in the model, as well as to the banks themselves.

Finally, I’ll bring in a “Modern Debt Jubilee“—both in a timely fashion, as soon as the Coronavirus shock hits, and belatedly.

The motivation of course is that policy ideas that I always thought had less than a snowflake’s chance in Hell of being implemented are now not merely being discussed but are, to some extent, being trialled in many parts of the world. This is not because the politicians and policy advisors who are doing this have read my posts of course: it’s simply that when something as serious as the Coronavirus strikes, the conventional wisdoms (of Neoclassical economics!) get thrown out the window as people panic, and find that what they used to say was either impossible or stupid is now both possible and sensible.

I’d be very pleased if other people here who are skilled at modelling in Minsky have a crack at this as well, either by editing the model I’ve attached here, or by working on their own. Global leaders are really flying blind right now, and maybe one of them will take a look at the work we do here.

There are many pundits arguing against government action now, on the basis that it will cause hyperinflation, and/or give our children an unsustainable burden of government debt to carry in the future. Here is a sample of such assertions.

Coronavirus hyperinflation risk looms, buy gold: Peter Schiff (USA, Fox News, March 25^th)

The extreme measures taken by the U.S. government and the Federal Reserve to combat the COVID-19 pandemic could push the U.S. into an episode of hyperinflation and boost gold, according to Peter Schiff.

Hysteria has forced the UK into lockdown, crashed the economy and will kill more than coronavirus (UK, The Sun, March 29^th)

Hysteria has been fanned by broadcasters with round-the-clock 24/7 crisis bulletins and correspondents declaring: “Protecting public health must come before protecting the economy.”

Wrong. We MUST protect the economy — industry, commerce, retail and financial businesses without whose taxes our precious NHS will shrivel, not grow.

The cost of this lockdown on schools, sport, gyms, pools, golf and civil liberty is incalculable — and not just in hard cash.

We are building a colossal national debt which will take our children’s and grandchildren’s lifetimes to pay off.

Helicopters? Bailouts? Central banks move to stem coronavirus crisis (Reuters, April 3^rd)

BUT ARE CENTRAL BANKS RISKING HIGH INFLATION?

The idea of central banks helping governments spend more has raised concerns about a rise in inflation and even drawn parallels with the disastrous hyperinflation of 1930s Germany and 1990s Zimbabwe.

Central bankers dismiss such comparisons, saying those cases involved unstable governments printing notes and handing them out to the public.

But JP Morgan strategist Jan Loeys said that if central banks eventually shift from their existing bond-buying programmes to direct funding of government spending, then inflation – which is currently low – might reawaken.

Bank of England won’t print more money to help tackle coronavirus – Governor Andrew Bailey (UK The Express, April 6^th)

“It would also ultimately result in an unsustainable central bank balance sheet and is incompatible with the pursuit of an inflation target by an independent central bank.”

The idea of central banks helping governments to spend more using monetary financing, whereby a central bank prints new money for governments to use rather than the governments acquiring money through taxation or borrowing has raised concerns about a rise in inflation in the future.

It has even drawn parallels with the disastrous hyperinflation of 1930s Germany and 1990s Zimbabwe.

There is no doubt that we’re in an unprecedented situation in economics as well as in health—one look at the US initial weekly unemployment claims data is enough to confirm that. So it’s quite possible that applying any existing experience or any existing theory—including mine—could lead to conclusions that turn out to be wildly wrong.

That said, my expectations are that, in the absence of the sort of government rescues that are now being tried around the world, the likely outcome of this crisis is serious deflation. This will be caused by a mechanism that I call “Fisher’s Paradox”, in honour of Irving Fisher, who first identified it as the primary cause of the Great Depression.

Fisher argued that the Great Depression was caused by the twin coincidence of too high a level of private debt, and too low a level of inflation. In this situation, debtors resorted to distress selling, cutting their prices in order to attract a cash flow to themselves rather than their competitors. But because everyone was doing it, prices fell across the board, taking GDP down with it. Debts therefore fell less than GDP, and the private debt ratio actually rose. In his words:

if the over-indebtedness with which we started was great enough, the liquidation of debts cannot keep up with the fall of prices which it causes. In that case, the liquidation defeats itself. While it diminishes the number of dollars owed, it may not do so as fast as it increases the value of each dollar owed. Then, the very effort of individuals to lessen their burden of debts increases it, because of the mass effect of the stampede to liquidate in swelling each dollar owed. Then we have the great paradox which, I submit, is the chief secret of most, if not all, great depressions: The more the debtors pay, the more they owe. The more the economic boat tips, the more it tends to tip. It is not tending to right itself, but is capsizing. “The Debt-Deflation Theory of Great Depressions” (Fisher 1933, p. 344)

Fisher’s Paradox was ignored by mainstream economics, because they subscribe to the fantasy model of banking known as “Loanable Funds”, in which banks are simply intermediaries between savers and borrowers. Fisher was not so stupid (well, not after he was effectively bankrupted by the Great Crash of 1929 anyway). Unlike today’s idiotic mainstream economists—here’s looking at you, Ben Bernanke (Bernanke 2000) and Paul Krugman, amongst many others—Fisher knew that a bank debt was very different to a debt between one non-bank and another:

the payment of a business debt owing to a commercial bank involves consequences different from those involved in the payment of a debt owing from one individual to another. A man-to-man debt may be paid without affecting the volume of outstanding currency. for whatever currency is paid by one, whether it be legal tender or deposit currency transferred by check, is received by the other, and is still outstanding. But when a debt to a commercial bank is paid by check out of a deposit balance that amount of deposit currency simply disappears. Booms and Depressions: Some First Principles (Fisher 1932, p. 15)

The empirical data bears Fisher out: America’ private debt to GDP ratio rose between 1929 and 1933 while the level of private debt was actually falling:

The raw dollar numbers make it even more obvious what happened: GDP fell faster than private debt:

As Fisher argued, the fall in the price level amplified the impact of the decline in real output. Falling prices combined with falling output to mean that the fall in nominal GDP was actually bigger than the fall in real (inflation-adjusted) GDP. Since debts are also measured in nominal terms, the fall in the price level made the rise in the private debt ratio worse: “the more debtors pay, the more they owe”.

This is why reflation, by Roosevelt’s New Deal (and also his “Bank Holidays”, which allowed insolvent banks to be wound up and their depositors funds transferred to solvent ones), was so important. If the injection of new money by the government hadn’t happened, this private sector chain reaction of liquidation leading to falling prices and an ever-rising debt level could have continued unabated: “The more the economic boat tips, the more it tends to tip. It is not tending to right itself, but is capsizing.”

I don’t care whether you’re a raving Austrian (Hi Peter!) or a raving Marxist, you don’t want this to happen. This is Hyman Minsky’s Financial Instability Hypothesis in the absence of a government sector, and as I showed in my PhD thesis and 1995 paper (Keen 1995), the end result is an economy with an infinite private debt ratio and zero employment.

What’s the relevance of this historical story to today’s situation? It is that the Coronavirus crisis has hit when we still haven’t addressed the runup of private debt that caused the Great Recession in 2007. Private debt today is higher than it was at the peak of the Great Depression.

We are therefore on the brink of a debt-deflation, and our policymakers don’t even know it because they take advice from Neoclassical economists who don’t understand the role of private debt and credit in the economy. We need a Modern Debt Jubilee now, or otherwise the damage the Coronavirus is doing to our health and capacity to produce now will be followed by the devastation of our financial system as well.

With the Coronavirus smashing both wages and profits in the US and global economies, the last thing we need is for workers that can’t pay their rents and mortgages, and firms that can’t pay their rents and service their corporate debts, to go bankrupt now. Inflation, which is already low, will turn negative, and the private debt ratio will explode once more, as it did in 1930-1933. Bankruptcies would cause a chain reaction of further failures, taking the banks down as well as the debtors. There would be no floor, especially since the Coronavirus has smashed not just demand but supply as well. Money would be destroyed by both the attempt of debtors to service their debts, and by the collapse of the banking sector as almost all debts turned bad.

So even if a massive injection of government money now would cause inflation in the future, the alternative is far, far worse.

References

Bernanke, B. S. (2000). Essays on the Great Depression. Princeton, Princeton University Press.

Fisher, I. (1932). Booms and Depressions: Some First Principles. New York, Adelphi.

Fisher, I. (1933). “The Debt-Deflation Theory of Great Depressions.” Econometrica
1(4): 337-357.

Keen, S. (1995). “Finance and Economic Breakdown: Modeling Minsky’s ‘Financial Instability Hypothesis.’.” Journal of Post Keynesian Economics
17(4): 607-635.

A lot of people still don’t seem to get the concept of exponential growth, even though we’ve had over two months of watching an exponential process unfold with the Coronavirus. I hope some simple illustrations using current data might help.

John Hopkins University is doing an excellent job of collating the cumulative number of cases reported around the world with its GIS database Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). They’ve made the raw time series data available too. Aggregated to the world level, this is what cumulative COVID-19 cases looked like as of late on April 4^th:

This is simply the total number of recorded cases, which includes tested cases where the carrier has only mild symptoms, people who got the disease way back when it began and have since recovered, those who have died, those who are still in intensive care, etc. The global total was just over 1.2 million on April 4^th.

A simple regression of this data onto an exponential function yields the prediction that, if the rate of transmission and the rate of doubling of the disease reflects what has happened to date from January 21^st, when the JHU time series begins, in a week’s time there will be twice as many cases: 2.5 million compared to today’s 1.2 million.

That’s a lot of cases, but it’s still way short of the total world population of about 7.5 billion. It took about ten weeks to go from 555 cases (the number recorded on January 21^st at the start of this data series) to over 1 million. How long will it take to get to a significant number compared to the planet’s population—say, half a billion cases?

It will take about another 8 weeks.

The red line in each of these graphs is the same red line.

Now only a fraction of those infected are going to be current cases—basically, those who were identified in the preceding 2-4 weeks—and only a fraction of those—perhaps about 20%–are going to require hospitalization. But that’s still a huge number of people, far more than can be handled in the world’s emergency medical facilities.

This is why this disease is not “just another flu”. It is far more contagious (and we also don’t have any innate resistance to it). We have to “Flatten the curve”, we can’t cope with the number of cases doubling every week, as is the case now.

The Coronavirus was not caused by Climate Change: it obviously correlates with climate change, but “correlation is not causation”.

However, when two trends do correlate, one reason can be that they are both caused by the same underlying factor. In the cases of both Coronavirus and Climate Change, that factor is the load that industrialized humanity has placed upon the Earth’s biosphere.

The stronger case for this can actually be made for the Coronavirus, rather than Climate Change. The academic paper “The biomass distribution on Earth” measured the relative mass of lifeforms (including viruses) on Earth, in terms of their carbon mass. It estimated that humans, at 0.06 Gigatonnes of carbon, represent almost ten times the mass of all wild mammals on Earth (0.007 Gt), while livestock are in turn almost 20 times the mass of humans (0.1 Gt: see Figure 1). Had an alien civilization done an audit of life on Earth like this 100,000 years ago, humans would have constituted only a tiny fraction of the roughly 0.1 Gigatonnes of mammals on this planet. Now, as it was summarized by one media outlet humans, and the animals we breed for our own use, constitute 96% of the mammal biomass of Planet Earth.

Figure 1: Biomass of lifeforms on Earth by Gigatonnes of Carbon

Several characteristics of humans that let us become the peak predator on this planet are key factors that have led to this crisis—and the many other crises that will follow it.

Because we are the peak predator, we (and our livestock) are also the best mammalian environment for pathogens. Any virus that infects a wild mammal peak predator—say a lion—will have a limited existence on Earth, because its host’s numbers are declining. Ours have been rising exponentially ever since industrialization, from under 1 billion in 1800 to over 7.5 billion today.

Unlike other predators, we are sociable between groups as well as within them (this sociability includes our wars, since the victors occupy the territory of the losers, and live amongst them). Lions are sociable within a pride, but not sociable between them (apart from a male killing the male and cubs of another pride, and taking over the females). A pathogen that infects one pride of lions is not highly likely to infect another. A pathogen that infects one group of humans is, on the other hand, highly likely to infect other groups.

Livestock are also sociable, so that a disease that springs up in one herd will spread through it—hence, for example, the death of something close to 50% of China’s pigs due to a swine fever last year. Livestock also constitute by far the biggest potential host for mammalian pathogens—which is one reason that many of our biggest diseases originate in chicken farms, pig farms, etc. But livestock are not mobile (of their own accord): they can’t move from one location to another if humans don’t want them to. It’s also easy to stamp out a pathogen in livestock by killing the herds that carry it—as was done with China’s swine fever outbreak in its pig farms.

We, on the other hand, are by far the most mobile, sociable species that has ever existed, and we don’t take kindly to killing our own kind—at least in comparison to how blithely we kill other species. So, what better environment could there be for pathogens to develop in than humans? A pathogen that infects humans will grow in numbers as our numbers grow, will spread thanks to our sociability, and will super spread thanks to our industrialized mobility.

In her brilliant 1994 book The Coming Plague, Laurie Garrett warned that it was only a matter of time before a successor to the Spanish Flu evolved, and wreaked havoc upon humanity. Garrett pointed out that pathogens evolve along two primary dimensions: transmissibility and virulence. Normally an increase in one dimension results in a decline in the other. But inevitably, a pathogen would evolve that was both more transmissible and more virulent.

The most dangerous combination is substantial transmissibility and moderate virulence. Substantial transmissibility lets a pathogen spread rapidly. Moderate lethality is more effective than high lethality, because with high lethality the pathogen can kill its host before it gets a change to be transmitted. Coronavirus hits this evolutionary sweet spot, with the additional dangerous characteristic that it can be spread by people who lack symptoms: simply avoiding people who are obviously sick is not a strategy to avoid Coronavirus. It is also inherently infectious: we have no acquired immunity to it as we have with influenza (the virus that Garrett expected would be the source of the next pandemic).

So the danger that Garrett anticipated a quarter of a century ago has come to pass. Had we designed our health and production systems to cope with the inevitable event, we would have:

• Increased the capacity of our health systems, and trained doctors and nurses in excess of underlying demand;
• Produced stocks of standard emergency equipment like masks and ventilators (Garrett anticipated, correctly, that The Coming Plague would be a respiratory illness);
• Made our economies as robust as possible to a health crisis, with short supply chains, and an emphasis upon local rather than globalized production;
• Established free—indeed, be-paid-to-be-tested—health monitoring systems, to ensure that we can easily identify disease carriers during a pandemic; and
• Extended our monetary systems to finance normal expenditure by the bulk of the population in the event of a pandemic.

Of course, we have done the exact opposite. We have instead:

• Reduced the capacity of our health systems to cope with even standard episodic health issues, in the belief that not spending on social infrastructure was “saving for a rainy day“;
• Designed an economic system in which production is focused in low-wage countries and exported to the rest of the world, via lengthy supply chains that involve as many as, for example, 43 countries in producing an iPhone; and
• Allowed the private sector to run up the highest level of corporate and household debt in history, which has made the financial sector both incredibly powerful and incredibly fragile at the same time.

Why? It’s primarily because politicians and bureaucrats, above all else, follow the advice of economists. When they listen to health professionals, it is within the context of a budget and a direction of social evolution set by economists. The advice of health professionals will help determine how the health budget is spent, but not how big that budget is, nor whether it is administered in a manner that helps or hinders our management of a pandemic.

This is because, when politicians are students, they don’t study epidemiology, or engineering, or even mathematics. Instead, if they study any analytic discipline at university, it is almost always economics. The UK in particular is dominated by politicians who have done the “Philosophy, Politics and Economics” degree at Oxford University, as this long read for the Guardian pointed out:

This training in economics makes politicians and bureaucrats incapable of understanding a crisis like this. They are, however, very susceptible to the advice of economists. They therefore enacted policies that reduced our capacity to cope with a pandemic, crafted systems of production and distribution that drastically amplified its damaging impact when it did arrive, and ridiculed warnings of people like Garrett as “alarmist” and “Malthusian”. For these reasons, Neoclassical economics itself bears a heavy responsibility for the severity of the coronavirus health and economic crisis.

Neoclassical economists will of course ridicule this claim. One thing I’ve learnt from fifty years of fighting these well-meaning but deluded bastards is that they’re great at taking credit when the economic system is doing well, but quick to deflect criticism by feigning impotence when a crisis actually arises. After it, they will merrily throw around their favourite explanation for why they couldn’t have seen it coming, that it was caused by an “exogenous shock”. Witness Ben Bernanke’s pronouncements before and after the Global Financial Crisis:

• Before it, Bernanke took credit (on behalf of both the economics profession and the Federal Reserve) for what he called the “Great Moderation”: “Recessions have become less frequent and milder, and quarter-to-quarter volatility in output and employment has declined significantly as well. The sources of the Great Moderation remain somewhat controversial, but as I have argued elsewhere, there is evidence for the view that improved control of inflation has contributed in important measure to this welcome change in the economy” (Bernanke 2004, “What Have We Learned Since October 1979?”);
• After it, he absolved “economic science” from any blame for the crisis: “Do these failures of standard macroeconomic models mean that they are irrelevant or at least significantly flawed? I think the answer is a qualified no. Economic models are useful only in the context for which they are designed. Most of the time, including during recessions, serious financial instability is not an issue. The standard models were designed for these non-crisis periods, and they have proven quite useful in that context. Notably, they were part of the intellectual framework that helped deliver low inflation and macroeconomic stability in most industrial countries during the two decades that began in the mid-1980s” (Bernanke 2010, “Implications of the Financial Crisis for Economics”).

This isn’t because Neoclassical economists are inherently liars or weasels by the way: it’s because they have a paradigm that they sincerely believe does describe capitalism accurately, and as a result they can’t comprehend that in fact it doesn’t. So whenever their paradigm fails, as it did in 2007, they look for reasons why it didn’t really fail—such as that the crisis couldn’t have been predicted, and that criticizing them for not anticipating it was like criticizing a mathematician for not predicting next week’s winning Lotto numbers.

As I said in response to this comment at the time, this is Neoclassical bullshit. This is no different to a Ptolemaic astronomer telling Halley that he couldn’t predict the date of the return of the comet that bears his name, because in the Ptolemaic paradigm, comets were unpredictable atmospheric phenomena. As with Ptolemaic astronomers, it’s the Neoclassical paradigm that is at fault, and not the critics who reject it. **

So before they get up a head of obfuscating steam with respect to this crisis, let’s cut them off at the pass:

• In the aftermath to this crisis—and possibly even during it—they will say that the influence of economics on policymakers is exaggerated: politicians took the decisions to cut medical funding and the like on their own accord.
  • But if so, why did Paul Samuelson, the author of the most influential post-WWII economics textbook, and the true father of modern economics,*** state that “I don’t care who writes a nation’s laws—or crafts its advanced treaties—if I can write its economics textbooks“? He knew that the economic ideas of an age largely determine what its lawmakers and administrators do. His descendants today know likewise. The 1995 article linked to in this dot point describes the rise of Gregory Mankiw’s ubiquitous textbook, and states that he was the most promising of several “proselytizers” who “are jumping at the chance to mold the minds of the next generation of political leaders, executives, image makers and other members of the American elite“.
  • This molding occurs primarily in the first year economics course that the vast majority of modern political leaders and bureaucrats take, in courses like Econ 101 in American universities, and in degree programs like Philosophy, Politics and Economics (“PPE”) in the UK. Mainstream economics is the main analytic tool they learn—very few learn mathematics, or engineering, let alone microbiology—and it’s the toolbox they first turn to when a new policy issue arises. ****
  • Consequently, the perspective of all other disciplines doesn’t rate a mention compared to the impact of economics.
• Economists will claim that it’s impossible to integrate all aspects of society into their analysis, so they have to make “simplifying assumptions” that, for example, omit the health system, population dynamics, and so on, from their underlying analysis.
  • This has been false for sixty years, ever since the brilliant engineer Jay Forrester invented System Dynamics: a methodology to enable the analysis of multiple interlocking systems operating out of equilibrium, and having feedback effects on each other. This methodology still exists today, but it has received very little development support. Why? Because economists—and in this instance, particularly William Nordhaus, the recipient of the 2018 “Nobel Prize in Economics”—disparaged this methodology without understanding it in the first place. Economists, with their equilibrium methodology, continued to receive the lion’s share of funding, and system dynamics has wallowed along on trivial funding.

Economists cannot avoid responsibility for the fact that production is heavily globalized, both via the promotion by economists of free trade over self-sufficiency, and by their support for the relocation of production from the West to the Third World. Consequently, a disease like this hit the whole world when it hit just one country—though it helped that the one country initially was China, to which much of the world’s production was outsourced.

In the aftermath to this crisis, we have to revoke the carte blanche that economists were given to reshape the economy in the image of their textbooks. It’s time to let real sciences manage humanity’s impact upon this planet.

Footnotes

**    There is an alternative paradigm (represented by people like the late Wynne Godley, as well as by myself, Michael Hudson, Ann Pettifor, Dirk Bezemer, and several others) in which private debt and its annual rate of change (which I call credit) play a pivotal role in macroeconomics, and their made a crisis inevitable. That’s what actually happened, but because private debt and credit play no role in the Neoclassical paradigm, they continue ignoring data about it. This is not because the data is not available, or is not compelling, but because it simply does not fit into their way of thinking about the world. So they ignore data which shows that every America’s three major crises were driven by a collapse in credit:

And they ignore the overwhelming correlation between credit and unemployment:

***    Both strands of mainstream macroeconomics—the so-called “New Classicals”, who are extreme free-market advocates and bear no resemblance to the actual Classical school of economic thought, and the so-called “New Keynesians”, who are moderate free-market advocates and bear no resemblance to the original ideas of Keynes—use the analytic tools that Samuelson invented, to generate what he called the “Neoclassical-Keynesian Synthesis“. What uninformed critics disparage as “Keynesian economics” should really be called “Samuelsonian Economics”.

****    A colleague of mine—the historian Chris Shiels, who wrote a brilliant critique of water privatisation in Australia called Water’s Fall—used to work in the Department of the Prime Minister and Cabinet when Paul Keating was Australia’s Prime Minister. He described how there would be panic amongst the staff at some new issue, which would only dissipate when someone suggested an approach that could be found in a first year economics textbook. Since almost all the advisors shared that paradigm, the idea would be readily adopted.

As I noted in my first update, I had decided that for both medical and visa reasons, the best place to be during the Coronavirus crisis was Thailand. Outside of China (the epicentre of this crisis), the world’s governments have been dominated by the Neoliberal emphasis upon efficiency, with a total ignorance of the need for resilience as well in a complex system. I didn’t expect any of them to be able to respond effectively as this exponential crisis exploded, so the safest thing was to go for the highest level of social isolation possible—and southern Thailand, below the major tourist spots, made sense on that ground alone. There was also nascent research implying that heat and humidity slow the spread of the virus. This is from the abstract for the paper:

This paper investigates how air temperature and humidity influence the transmission of COVID-19. After estimating the serial interval of COVID-19 from 105 pairs of the virus carrier and the infected, we calculate the daily effective reproductive number, R, for each of all 100 Chinese cities with more than 40 cases. Using the daily R values from January 21 to 23, 2020 as proxies of non-intervened transmission intensity, we find, under a linear regression framework for 100 Chinese cities, high temperature and high relative humidity significantly reduce the transmission of COVID-19, respectively, even after controlling for population density and GDP per capita of cities. One degree Celsius increase in temperature and one percent increase in relative humidity lower R by 0.0383 and 0.0224, respectively. 

I had already started to make this inference from the statistics from the John Hopkins University site. Thailand began with the second highest number of cases to China, but the number of cases rose far more slowly than in the rest of the world. On January 31^st, Thailand had 19 cases, while Australia had 9, the Netherlands zero, and the UK 2. The Netherlands recorded its first cases on February 27^th, finishing the day with 2 cases; by this stage, Australia had 23 cases, the UK 15 and Thailand was still far higher at 40 cases. However, as of March 19^th, Australia had about 700 cases, The Netherlands and the UK about 2500 each, and Thailand had under 250. This time series plot from my soon-to-be-released program Ravel illustrates the divergence of Thai data from the rest of the world—or rather the three other countries where I could have considered living during this crisis.

My partner and I arrived in Bangkok on Thursday March 19^th, one day before Thailand started closing its border to non-nationals (my partner is a Thai citizen, though she hasn’t lived here for over 25 years). One day later, and I would have had to continue on my own to Australia, which is mishandling this crisis as impressively as any other Western government.

We then flew and drove to Trang, which is south of the usual tourist spot of Phuket, and has mainly Thai visitors as tourists.

Even Thai tourists are thin on the ground now, as Thailand has wisely cancelled its annual Thai New Year holiday and festival. We went to a popular beach yesterday looking for potential places to stay for a year, and it was almost empty.

We’re now looking for a house to rent here, for the year that I think it will take before there’s any prospect of a post-Covid-19 “normal” developing.

The during-Coronavirus “normal” is the exponential growth of the infections, and the lagged reaction of authorities and the public to a crisis that can only be addressed by being pro-active. It is absurd that it has taken until now for the social and political powers-that-be to appreciate the scale of this crisis. Social isolation protocols and financial supports should have been in place two months ago: all large gatherings, from weddings up, should have been banned; preparations should have been made for military-regulated distribution of food, rather than the free-for-all panic buying the public has been forced into; and direct money payments to all citizens should have been made to enable financial transactions from rents and mortgages to household services to be paid for even when the virus forces people to cease working. We are seeing the collapse of a social order that does not understand itself.

Neoclassical economics bears a major responsibility for this pathetic state of affairs. It encouraged the emphasis upon efficiency over all other aspects of a complex society—especially, as we can now see, of its resilience. It lulled policymakers into thinking in equilibrium terms when there is nothing like equilibrium in a runaway exponential process like a new virus’s transmission. We have a globalised supply chain that is incredibly fragile, thanks to the fantasy of comparative advantage running industrial policy across the West. Once I have settled, and before I catch the virus—because almost all of us will, given how fast it is spreading and how long it takes for a vaccine to be developed, tested, manufactured in global bulk (7.5 billion doses?!) and distributed.

In the end, I think this crisis will prove—at least to the citizens of China, and to a lesser extent other Asian nations which have a military and/or collectivist background—the superiority of their societies over those of the West. The West works brilliantly when things are good, and falls apart when they are bad. Its guiding philosophy of Neoclassical economics is a, if not the, major factor in this systemic fragility. This next graphic from Ravel indicates how well China has gotten on top of the outbreak, after the initial disaster of trying to suppress news about it.

Keep safe. Practice as close to total social isolation as you can. Prepare as best you can. Go on a rent strike and a mortgagor strike, especially if you can organize something through relevant political movements. Our governments have failed us in this crisis. They don’t respond when renters and mortgagors become distressed. They do when landlords and banks cry foul. So let’s trigger them into action by hitting them where it hurts.

Note: This post is also freely available on my Patreon page www.patreon.com/profstevekeen. Support from my patrons lets me operate as an independent scholar, and they decided that they wanted my posts to be freely available to help communicate my ideas. Only podcasts have restricted access.

The coronavirus could cause the financial system to collapse unless something is done to enable basic payments to continue during the fight against it. While some businesses are doing very well out of it—toilet paper and hand sanitizer produces come to mind—many, if not most, could collapse as their sales collapse and/or their workers become unable to turn up to work. Workers—especially those in the jovially-named “gig economy”—will be unable to pay their rents and mortgages. If we insist on these payments being honoured, mass bankruptcy could result that could take viable companies down with it—even toilet roll producers.

So what to do?

The answer is fundamentally simple: the Treasury issues “Coronabonds” that raise a substantial sum—enough to cover say 3 months of standard mortgage, rent and food payments for an average family. These Coronabonds could be priced at zero percent yield: interest rates are at that level anyway, and given the current stockmarket carnage, financial corporations would jump at the opportunity to park their money in an asset that won’t fall in value.

Using the US Economy as our template, let’s say that $1 trillion of these bonds were issued. They would then be bought by the financial sector—raising $1 trillion to be spend by the government on tenants, mortgagees and firms. The cost to the Treasury would be zero because that would be the yield of the bonds. The public debt would rise, but it would be debt carrying no servicing costs.

The inevitable question from our budget-assessed world is “how would we pay for it?”, and the basic mechanics are outlined in the Minsky model shown in the screenshot below. I haven’t filled in sample flows for the model, but the Godley Tables show that the entire scheme works in an accounting sense. The government could raise $1 trillion, spend it into the economy, and enable tenants to pay their rents, mortgagees to service their mortgages, and corporations to avoid bankruptcy.

We need something like this, now, before the Coronavirus overwhelms our monetary system in the same way that it has overwhelmed the emergency medical systems of many countries already.

Any of you who know me personally know, and many of the rest of you may suspect, that my personal life is as complicated as Neoclassical economics is simplistic.

I am an Australian citizen and UK resident with a flat and partner in Amsterdam. I am with her using the visa waiver scheme; she is a Netherlands resident but not yet a citizen. If I stay here then I will certainly breach the “no more than 90 out of the last 180 days” provisions of the Schengen visa. If things get really tough—and I expect that they will—neither of us speak the local language, me at all and my partner not fluently (everyone you meet here speaks English better than the English). But if there are police/army on the street, and you don’t have a residency card (I don’t) or get a non-English speaking “grunt”, we’re both in trouble.

The Netherlands has also recently joined the rest of Europe in an explosion of cases. I was watching this data (using the John Hopkins site: https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6) while in Australia, and couldn’t fathom why the Netherlands, a major tourist destination, was showing no cases at all.

That changed abruptly last week, a few days before I left Sydney to come here for my partner: it was 1 one morning when I woke, 2 when I went to bed, 6 when I woke up… and now it is 1136.

On the opposite end of this scale lie Australia and (even more so) Thailand, my partner’s country of birth and citizenship:

Certainly in Australia’s case, that is not due to good management. Thailand may be taking it more seriously, or underreporting numbers, but the data seems to indicate that the pandemic is growing linearly there rather than exponentially. I have seen some academic research arguing that the virus lives for longer on surfaces in cold climates than warm ones, and that may explain both country’s relative out-performance.

Below is a screenshot of a new commercial program I’ve been working on with Russell Standish for some time, using Minsky as a base. Called Ravel, though it is in a pre-alpha stage right now (ie, before we’re ready to release it to beta-testers, let alone the general public). But even in its primitive state it lets you compare trends in selected countries easily, something no other existing Dashboard that I’ve seen does. These trends were a major factor in my decision: we can’t stay here, because we lack citizenship rights that I expect; I will breach the visa if I do, and if I’m stopped on the streets while shopping and asked to show ID, I could find myself forcibly deported (yes I expect it to get that bad—or at least to be interred in a foreigner’s quanrantine).

So we had to go to one of the countries we are citizens, either together or apart. For obvious reasons, we chose the together option, which means Thailand (my partner’s tourist visa there has lapsed, and it’s a lot more expensive to live in Australia anyway). We are flying there this Wednesday, arriving Thursday, and moving to a beachside non-tourist town where we can easily and cheaply rent a standalone bungalow for a year, which I intend to be our quarantine period.

I’ll use the quarantine productively of course. I’m 1 chapter in to the revised and final 3^rd edition of Debunking Economics, I have a book contract with Polity on “Economics Matters Because” which is due in August, Russell, Wynand and I are working on both Minsky and Ravel… Boredom will not be an issue (it may be tougher on my partner). And I will keep actively posting here, and commenting in whatever media outlets enable me—and that includes Russia Today, despite some people thinking

I won’t be posting or replying to comments for the next couple of days for obvious reasons: everything has to be thrown into preparing for the trip and locking up my flat here for a year or more.

Keep safe everyone. I’ll do my best to argue for the sane and extraordinary policies that are needed to cope with this threat: the Modern Jubilee and the Coronabonds that I’ve already posted about, and done an interview on with Ross Ashcroft of Renegade Inc. I’ll post that here shortly, after I put this one up.

Finally, a personal word of thanks to you all. The fact that I am able to be this flexible is due to you. The fact that I can devote myself to this issue 100%—after I do the best to secure my own safety—is thanks to you. Hopefully I can delay catching this thing—I don’t think there’s any chance to avoid getting it, in the end—and when I get it, I get either a low effect infection, or anti-virals are available.

If not? Well, I’ll let you know first. I hope it doesn’t come to that, for any of us. But these are such dangerous times for the over-65s amongst us, and for all of us, given how this systemic threat will overwhelm our episodic (and austere!) medical systems.

The one good thing that might come of this is that the deluded morons (looking at you William Nordhaus and Richard Tol and Bjorn Lomborg and the many politicians who’ve fallen for their bullshit) who’ve led us into this maelstrom might finally lose influence and power. But I won’t hold my breath.

I wish you all the very, very best of luck.

A first version of this post used raised to a power, rather than 2 raised to a power. My apologies there, and many thanks to my Patreon supporter Rudolph Kammerer for pointing this out. Figures in this post are now corrected for that error.

One reason why we react far too slowly to threats like the Coronavirus is that thinking about processes that involve exponential growth just doesn’t come naturally to us: we tend to extrapolate linearly instead. That is seriously hampering our reactions to this threat. If we did think exponentially, we’d be practicing serious containment, right now. I want to illustrate why with a simple graph.

There are roughly 100,000 serious Coronavirus cases around the world now, and without public health measures, the infections appear to double every six days. That rate will not be sustained as more people get infected, and many may have only mild symptoms. That said, if the base rate of doubling did continue, and if the serious cases were the only ones that existed (which they’re not of course: there are many carriers who are asymptomatic right now), then the entire human population of the planet would be infected in three months.

What if we slow the doubling rate down a bit, to ten days, by better hygiene, not congregating in large crowds, etc? Then it would take five months for everyone to be infected.

We could do better than that though: by really limiting social interaction, really ramping up personal hygiene in public. If we slowed the doubling rate to once every month, it would take one and a half years to infect the whole planet’s population.

And if we did even better, perhaps with something approaching China’s controls, and reduced the doubling rate to two months? Then it would be three years before the virus infected everybody.

This is why it’s necessary to impose strict limits on social interaction now, not later. The longer we leave it, the longer the doubling rate stays at 6 or so days. All it takes is a hundred such days, and it’s too late: everyone already has it.

So a sensible containment policy would ban large gatherings, where carriers (many of whom are non-symptomatic) can infect many others. Sporting events should stop—or rather events could still happen, but be watched by near-empty auditoriums, and broadcast. Schools and universities should shut down—or conduct classes online. Churches should hold services online as well. Since it seems to take about 15 minutes of sustained exposure within 1-2 metres to pass the disease on, actions that eliminate such gatherings now could slow down the disease’s momentum, and give us more time to develop vaccines, anti-virals, pre-symptomatic screening systems.

The trouble is, this reaction will be seen as too extreme, and resisted—until such time as the number of infections have hit such a level that everyone panics. So I worry that we won’t politically accept extreme confinement measures until we’ve hit a terrifying number of serious cases and deaths—perhaps once 100,000 people have died.

We’re currently at 3,000 deaths from 90,000 reported serious cases. How long will it take us to get to 100,000 deaths, if the doubling rate sticks at the current 6-day level? One month: by the beginning of April.

I don’t think it will be that fast by the way—changing personal behaviour might increase the doubling rate a lot, to say, every two weeks. How long does that give us till we hit 100,000 deaths? About 70 days—or early May.

Many other factors will come in to play, some good, some bad. Hygiene and isolation will both improve—but this will challenge our financial system, as people stop earning an income and businesses go bankrupt. So we have to plan for that: as I suggested in my previous post, we need to stop the ordinary rules of capitalism, which are suited for episodic events, making this systemic crisis even worse. Some ideas include

• a “modern Jubilee”, similar to what Hong Kong has already done, where they have given every citizen HK$10,000, or roughly US$1250. Give everyone a direct cash injection into their bank accounts on a per capita basis. This will allow people to pay their rents and service their mortgages, even if they’ve been sacked, lost their “gig economy” job, or had to shut their restaurant;
• Put a hold on bankruptcy proceedings, for businesses likely to be affected adversely by the crisis, and maybe give those firms a Central Bank money injection too, on a “share of market” basis. Obviously, airlines, sporting venues, restaurants, personal service industries, are all going to be affected adversely.
  • Toilet roll manufacturers, sanitation producers, etc., are going to do very well—so maybe what we need there are price controls, combined with the same Central Bank money injection.
• Direct support for share prices by direct Central Bank purchases of shares, as Japan’s Central Bank has been doing for some time. This is to stop a stock market collapse triggering financial collapses, especially by banks.
• Modify bankruptcy rules for the interim for banks banks. Banks should be able to operate even if they end up in negative equity, to keep the payments system going.