empiricism

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Humanities Scholars Baffled By Math

Via the Wall Street Journal:

In the latest study, Kimmo Eriksson, a mathematician and researcher of social psychology at Sweden’s Mälardalen University, chose two abstracts from papers published in research journals, one in evolutionary anthropology and one in sociology. He gave them to 200 people to rate for quality—with one twist. At random, one of the two abstracts received an additional sentence, the one above with the math equation, which he pulled from an unrelated paper in psychology. The study’s 200 participants all had master’s or doctoral degrees. Those with degrees in math, science or technology rated the abstract with the tacked-on sentence as slightly lower-quality than the other. But participants with degrees in humanities, social science or other fields preferred the one with the bogus math, with some rating it much more highly on a scale of 0 to 100.

Specifically, 62% of humanities and social science scholars preferred the paper with the irrelevant equation, compared with 46% from a background of mathematics, science and technology.

This is a significant result, and I hope the experiment is repeated and replicated. It is all well and good for humanities and social science scholars to mostly eschew the use of mathematics in their work. But if humanities scholars begin to take work more seriously simply for the inclusion of (faux-) mathematics without themselves understanding the mathematics, then maybe it’s time for humanities and social science scholars to increase their mathematical and statistical literacy so as not to be so easily tricked by faux-mathematical rigour.

And this isn’t just a case of not understanding the equation — it seems like a nontrivial chunk of humanities and social science scholars have quite an inferiority complex. That should be a great embarrassment; there is nothing inherently inferior about the study of the human condition, or its (mostly non-mathematical) tools.

Last year, I wrote:

Well-written work — whether in plain language or mathematics — requires comprehensible explanations and definitions, so that a non-specialist with a moderate interest in the subject can quickly and easily grasp the gist of the concepts, the theory, the reasoning, and the predictions. Researchers can use as complex methods as they like — but if they cannot explain them clearly in plain language then there is a transparency problem. Without transparency, academia — whether cultural studies, or mathematics, or economics — has sometimes produced self-serving ambiguous sludge. Bad models and theories produce bad predictions that can inform bad policy and bad investment decisions.  It is so crucial that ideas are expressed in a comprehensible way, and that theories and the thought-process behind them are not hidden behind opaque or poorly-defined words or mathematics.

But in this case, I think the only real solution is mathematical and scientific literacy.

On the other hand, prestigious mathematics journals have also recently been conned into publishing papers of (literally) incomprehensible gibberish, so it is not like only humanities and social science scholars have the capacity to be baffled by bullshit.

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Hurricanes and Broken Windows

It is relatively easy to debunk the Broken Window fallacy, the idea that hurricanes or more generally the destruction of capital may be a tragic economic stimulus. Indeed, much has already been written on the opportunity cost of the new spending that may be unleashed by a natural disaster — in the last few days by Robert Murphy and Jim Quinn (and many others) and historically by Henry Hazlitt and Fredric Bastiat. When a window is broken, and money is spent on a glazier, the labour, capital and resources is only moving the economy back to where it was, and it has an opportunity cost — whatever might have been purchased with the labour, capital and resources had the window not been broken.

A Krugmanite might respond to this with the idea that when an economy is in a depression state, where vast quantities of labour and capital are idle, then this opportunity cost is less relevant. But this is not so.

A natural disaster will undoubtedly result in new economic activity that would not have taken place otherwise. Undoubtedly, labour, capital and resources that may n0t have been employed otherwise will be employed because of an earthquake, or a flood or a fire. But believers in the Broken Window fallacy are looking at the economy through a distorted lens. What they define as “activity” (i.e. GDP) is only one side of the picture. Yes, a major hurricane like Sandy might require $100 billion or more spent to repair the damage. Yet to only look at spending is to only look at one side of the picture — the flow. An economy is both stock and flow. That $100 billion of spending is flow to replace damaged and destroyed capital stock (houses, factories, roads, etc).

To grasp the full picture we have to look at both sides of the equation. If a hurricane like Sandy causes $100 billion of damage requiring $100 billion of spending to fix, then after that spending we are in aggregate no better off than we were before the storm. Without the storm, resources would surely have been deployed differently. But without the preceding hurricane damage, all spending is a gain because the spending is not replacing capital stock that has been destroyed. Let us assume that Sandy had blown herself out without making landfall, and that without the need for a major reconstruction, only 10% ($10 billion) of the $100 billion necessary to repair the damage was deployed in the economy. In aggregate, we are $10 billion better off than with the $100 billion of spending in the wake of the storm, because that $100 billion was merely making up for losses via destruction.

I hope that we can put the Broken Window fallacy to bed at last and agree that the “stimulus” effect of natural disasters, is merely a transitory illusion based on flow, while ignoring that that flow is merely compensating for loss in stock. There are benefits to natural disasters — like learning not to build in areas prone to flooding or volcanism, or developing building materials and techniques or other innovations robust to earthquakes or flooding, or the concept of natural-disaster preparedness and survivalism — but these are informational and not an economic “stimulus”.

And certainly, unemployment is a tragedy. But there are far better ways to reduce unemployment — like slashing red tape and cutting taxes for small businesses and startups  — than the destruction of capital.

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The Shape of 40 Years of Inflation

I have written before that there is no single rate of inflation, and that different individuals experience their own rate dependent on their own individual spending preferences. This — among other reasons — is why I find the notion of single uniform rate of inflation — as central banks attempt to influence via their price stability mandates — problematic.

While many claim that inflation is at historic lows, those who spend a large share of their income on necessities might disagree. Inflation for those who spend a large proportion of their income on things like medical services, food, transport, clothing and energy never really went away. And that was also true during the mid 2000s — while headline inflation levels remained low, these numbers masked significant increases in necessities; certainly never to the extent of the 1970s, but not as slight as the CPI rate — pushed downward by deflation in things like consumer electronics imports from Asia — suggested.

This biflationary (or polyflationary?) reality is totally ignored by a single CPI figure. To get a true comprehension of the shape of prices, we must look at a much broader set of data:

Yet the low level of headline inflation has given central banks carte blanche to engage in quantitative easing, and various ultra-loose monetary policies like zero-interest rates — programs that tend to benefit the rich far more than anyone else. Certainly, lots of goods and services — especially things like foreign-made consumer goods and repossessed real estate — are deflating in price. But you can’t eat an iPad or a $1 burnt-out house in Detroit. Any serious discussion of monetary policy must not only consider the effects on creditors and debtors, but also the effects on those who spend a larger-than-average proportion of their income on necessities.

Another issue is that CPI leaves out both house prices as well as equity prices.

Below is CPI contrasted against equities and housing:

It is clear from this record that a central bank focused upon a price index that fails to include important factors like stock prices and house prices can easily let a housing or stocks bubble get out of hand. CPI can — as happened in both the 1990s as well as the early 2000s — remain low, while huge gains are accrued in housing and stocks. Meanwhile, central bankers can use low CPI rates as an excuse to keep interest rates low — keeping the easy money flowing into stocks and housing, and accruing even larger gains. However, because such markets are driven by leverage instead of underlying productivity, eventually the ability to accrue new debt is wiped out by debt costs,  hope turns to panic, and the bubble bursts.

Both of the above examples indicate that the contemporary headline price index measures of inflation are deeply inadequate. Attempts to measure the rate of inflation that ignore data like house or stock prices will lead to flawed conclusions (rendering any such notions of “price stability” as meaningless), which has tended to lead to failed policy decisions such as those which led to the bust of 2008.

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Zombie Economics

Occupy Wall Street seem to oppose banker bailouts because bailouts are unfair. Bankers — by and large the most privileged class in society — got at the last count over $14 trillion of interest free money from central banks and governments to keep on doing the same thing — getting rich from speculation, on the backs of workers and the productive economy. The rest of society — teachers, nurses, factory workers, entrepreneurs, the unemployed, etc — have to “share the pain” of unemployment, austerity and a depressed economy.

This is particularly unfair, because it is the bankers and speculators who caused the crisis in the first place. But there is a much deeper economic reason to oppose bailouts than simple unfairness. Bailing out failed and failing financial institutions creates a zombie economy. Why?

In nature, ideas and schemes that work are rewarded — and ideas and schemes that don’t work are punished. Our ancestors who correctly judged the climate, soil and rainfall and planted crops that flourished were rewarded with a bumper harvest. Those who planted the wrong crops did not get a bailout — they got a lean harvest, and were forced to either learn from their mistakes, or perish.

These bailouts have tried to turn nature on its head — bailed out bankers have not been forced by failure to learn from their mistakes, because governments and regulators protected them from failure.

So it should be no surprise that financial institutions have continued making exactly the same mistakes that created the crisis in 2008. That crisis was caused by excessive financial debt. Wall Street banks do not just play with their own equity — they borrow huge sums of money, too. This debt is known as leverage — and many Wall Street banks in 2008 had forty or fifty times as much leverage as they had equity. The problem with leverage is that while successful bets can very quickly lead to massive profits, bad bets can very quickly lead to insolvency — a bank that leverages itself 50:1 only has to incur a 2% loss on its portfolio to have lost every penny they started with. Lehman Brothers was leveraged 30:1.

Following 2008, many on Wall Street promised they had learned their lesson, and that the days of excessive leverage and risk-taking with borrowed money were over. But, in October 2011, another Wall Street bank was taken down by bad bets financed by excessive leverage: MF Global. Their leverage ratio? 40:1.

So why was the banking system bailed out in the first place? Defenders of the bailouts have correctly pointed out that not bailing out certain banks would have caused the entire system to collapse. This is because the global financial system is an interconnected web of debt. Institutions owe huge sums of money to one another. If a particularly interconnected bank disappears from the system, and cannot repay its creditors, the creditors themselves become threatened with insolvency. If a bank is leveraged 10:1 on assets of $10 billion, then its creditors may incur losses of up to $90 billion. Without state intervention, a single massive bankruptcy can quickly snowball into systemic destruction.

Ultimately, the system is extremely fragile, and prone to collapse. Government life-support has given Wall Street failures the resources to continue their dangerous and risky business practices which caused the last crisis. Effectively, Wall Street and the international financial system has become a government-funded zombie — unable to sustain itself in times of crisis through its own means, and dependent on suckling the taxpayer’s teat.

The darkest side to this zombification is that it takes resources from the productive, the young, the creative, and the needy and channels them to the zombies. Vast sums spent on rescue packages to keep the zombie system alive might have been available to increase the intellectual capabilities of the youth, or to support basic research and development, or to build better physical infrastructure, or to create new and innovative companies and products.

Zombification kills competition, too: when companies fail, it leaves a gap in the market that has to be filled, either by an expanding competitor, or by a new business. With failures now being kept on life-support, gaps in the market are fewer.

The system needs to change.

As Professor George Selgin of the University of Georgia put it:

Our governments chose to keep bad banks going and that is why quantitative easing has proven a failure. Quantitative easing failed because almost all the new money the government created has gone to shore up the balance sheets of irresponsible bankers. Now those banks sit on piles of idle cash while other businesses starve or cannot get started for want of credit.

It’s the same scenario that Japan has experienced for twenty years. They experienced a housing and stock market crash in 1990, bailed out their banking system, and growth never really recovered:

Ever since then, unemployment has been elevated:

That is the fate that Britain, Europe and America face by going down the Japanese zombification route: weak growth and elevated unemployment over a prolonged period of time. They face having the life sucked out of them by the zombie banks and corporations, and the burden of an every-growing public debt to finance more and more bailouts:


Instead of bailouts, we need to allow failed banks and corporations to fail and liquidate so that new businesses can take their place. Nature works best through experimentation. Saving zombie banks and zombie corporations kills experimentation, by rewarding failure, and preventing bad ideas from failing. If bad ideas and schemes cannot fail, it is impossible for good ideas and schemes to truly succeed.

The role of the government should be to provide a level playing field for experimentalism (and enough of a safety net for when experiments go wrong) — not pick winners. If experiments go badly, that is no bad thing: it just means that another idea, or system, or structure needs to be tested. People should be free to go bankrupt and start all over again with a different mindset and a different idea.

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Empiricism in Economics

It has long been held that there are two kinds of economics:

  1. Rationalist economics: starting out with theses about philosophy, money and reality (etc) and using logic and reason to reach conclusions about the present and predictions about the future.
  2. Empiricist economics: starting out with data and creating mathematical models representing these data, and using these models to reach conclusions about the present, and predictions about the future.

In traditional circles, the first class tends to include the various schools of Austrian and Marxian economics, and the second class tends to include the various schools of Keynesian and Monetarist economics.

Today, I want to put an entirely new spin on empiricism in economics, by focussing away from modelling. The process of mathematical modelling is just as rationalist as using logic and reason.

Why?

Economies are nonlinear systems.

From Wikipedia:

In mathematics, a nonlinear system is a system which is not linear, that is, a system which does not satisfy the superposition principle, or whose output is not directly proportional to its input. 

Effectively, a nonlinear system is one in which mathematical modelling mostly does not work. This, in a nutshell, is the reason why professional economists within the academic system, at the Federal Reserve, and within the IMF and the World Bank are often so desperately incorrect with their predictions, as we have seen so many times in the last few years. 

This is because nonlinearity is a direct result of incomplete information. Any map or model built will not be an exact replica of reality, and as Benoit Mandelbrot showed tiny divergences in an unmodelled (or unknown) variable can result in a humungous variation in the output of the system (i.e., the economy).

So in dealing with nonlinearity the model always fails — sometimes by a fraction, and sometimes by a huge amount.  The notion of accurate modelling was famously taken to a logical conclusion by the writer Jorge Luis Borges in On Exactitude in Science:

In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coin- cided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast Map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.

So if accurate modelling in complex dynamical systems such as economies is effectively impossible without mapping every input what hope can there be for empiricism in economics?

We have to approach it from another angle: if it is impossible to model economies in a laboratory, through equations, or in a supercomputer, the real world must be the testing-ground for ideas.

Actors in economies should be free to experiment. Good ideas should be free to succeed, and bad ones to fail. The role of the government should be to provide a level playing field for experimentalism (and enough of a safety net for when experiments go wrong) — not pick winners or “manage the economy”. People with ideas must be able to access capital so that those ideas can be tested in the market place. If experiments go badly, that is no bad thing: it just means that another idea, or system, or structure needs to be tested. People should be free to go bankrupt and start all over again with a different mindset and different idea.

The corporatist model that most nations around the world have adopted, or fallen into (i.e. “capitalism” led by governments and large corporations) is nothing like this. Small businesses struggle to access capital. Young men and women are thrown onto the scrapheap of unemployment without a chance to develop skills, or entrepreneurial ideas, or even sell their labour, and pushed into leeching off the wealth of the nation through welfare. Large banks and corporations whose business models have failed are routinely declared “infrastructurally important” or “too big to fail” and bailed out to leech off the nation.

This is not empiricism. This is a disaster. To restore society, we must restore empiricism into economies.