“By their fruits shall ye know them”

25 Aug, 2013 at 19:48 | Posted in Economics, Politics & Society | Comments Off on “By their fruits shall ye know them”


St. Augustine economy

25 Aug, 2013 at 10:25 | Posted in Economics | Comments Off on St. Augustine economy

In general, trying to do policy-relevant macroeconomics these past 5 years has felt like the curse of Sisyphus: you labor mightily to get some simple but essential point across, you think that maybe, finally, you’re getting through. Then along comes some famous economist or report from an influential agency that rolls the level of the discussion right back down to the bottom.

The central fact of macro policy in these times isn’t subtle:
In normal times, the central bank can offset fiscal contraction by cutting interest rates. Since late 2008, however, the interest rates the Fed can control have been limited by the zero lower bound. This means that there is no offset to the negative effects of fiscal consolidation — which means that this is not the time to be doing such consolidation, which should wait until we emerge from this condition. We’re in a St. Augustine economy: Grant me chastity and continence, but not yet.

This isn’t complicated, and it isn’t new — it’s what we’ve been saying for almost 5 years. There are arguments one can make on the other side, although the two main ones — expansionary austerity and the supposed existence of a red line on debt at 90 percent of GDP — have imploded.

Paul Krugman

S beska budskap till ungdomen

24 Aug, 2013 at 22:28 | Posted in Politics & Society | Comments Off on S beska budskap till ungdomen

7733899552_564228b3f6_z”Vi socialdemokrater lovar att göra dina morgnar till ett helvete. I alla fall om du är ung och arbetslös.” Vallöftet formulerades i förrgår av partiets ekonomisk-politiska talesperson Magdalena Andersson i en debattartikel i Svenska Dagbladet. Om det nu inte bara var en presskommuniké från Pyongyang som faxats fel. ”Vår vision är tydlig: Varenda ung kvinna eller man ska få känna känslan av en klocka som ringer vid 6-tiden när det fortfarande är becksvart ute. De ska hälla i sig en kopp kaffe och traska iväg mot en arbetsplats eller ett lärosäte som väntar på dem. Det kan kännas beskt – men vårt budskap till Sveriges ungdomar är enkelt: Vi står för en jobbigare morgon – men ett bättre liv.” Det är möjligt att hon inte menar precis så. Men allt övrigt i artikeln förbleknar och glöms inför dessa pregnanta rader. Plussa på en pissig lön och en otrygg anställning så har vi den nya blandekonomin i ett nötskal. En auktoritär stat och en fri marknad. Det sämsta av två system. Gå upp i ottan för att stapla kartonger på Ica eller bli inringd i hemtjänsten för en spottstyver. Det är livet det. Denna vision ställer Andersson mot borgerlighetens skattesänkningar. Här går ”den tydliga skiljelinjen inför valet 2014”. Vad månde ungdomen välja?

Petter Larsson

Svar från Roland Paulsen – Uppsala Universitet:

Hej! Mitt namn är Magdalena Andersson. Jag tycker om att åka längdskidor, långfärdsskridskor och att paddla kanot. Båda mina föräldrar vara akademiker och jag är gift med en professor i nationalekonomi. Jag tjänar 99000 i månaden och det har jag förtjänat. Jag gick direkt från gymnasiet till Handels. Det var jättetufft. Undervisning började redan tio på morgonen. Det var till och med tänkt att jag skulle doktorera där, men jag orkade inte skriva klart den där avhandlingen. Så jag åkte en vårtermin till Harvard istället. Här är min politik: “Varenda ung kvinna eller man ska få känna [ångest-] känslan av en klocka som ringer vid 6-tiden när det fortfarande är becksvart ute. De ska hälla i sig en kopp kaffe [ta sin cipralex] och traska iväg mot en arbetsplats eller ett lärosäte [eller ett plusjobb] som väntar på dem. Det kan kännas beskt – men vårt budskap till Sveriges ungdomar är enkelt: Vi står för en jobbigare morgon – men ett bättre liv.”

(h/t Jan Milch)

Paul Krugman — at last — admits IS-LM is deficient !!!

24 Aug, 2013 at 11:14 | Posted in Economics | 4 Comments

In a new post on his blog Paul Krugman now admits that there has been misunderstandings on his defense of IS-LM, and that

much of the blame probably rests with yours truly: I probably haven’t been explicit enough about what I’m doing and why …

images-15But in this more complex world, where even the definition of the money supply becomes highly dubious, why even talk about an LM curve? Well, before 2008 most macroeconomists didn’t! They talked instead about interest rate targets, Taylor rules, and all that. Mike Woodford, who is probably our leading macroeconomist’s macroeconomist, has even made one of his signature modeling tricks the building of models in which there is (almost) no outside money. Sensible macroeconomists have known for a long time that quantity-theory type models, if they were ever useful, aren’t much use in the modern economy.

So why am I bringing IS-LM into the discussion? First of all, I should have been much clearer than I have been that the LM curve I’ve been drawing is for a given monetary base, not a given M1, M2, or whatever. I guess I haven’t said that clearly …

But still, why use any kind of “quantity-centric” approach at all? The answer is, to refute the bad guys! … So, if and when we finally emerge from this trap and reenter the world of significantly positive short-term interest rates, will I still be talking in terms of IS-LM? In normal times central bank monetary policy is conducted in terms of, and best thought of in terms of, the target interest rate … So the LM curve will go back into the drawer. But I will keep it there in case I need it again; it has come in very useful these past five years.

That’s good. At last Paul Krugman admits that IS-LM — if not from a tactical point of view, at least from a theoretical one — belongs in “the drawer”!

That’s really good because — simpliciter — there is no such thing as a Keynes-Hicks macroeconomic theory!

Nothing in the post-General Theory writings of Keynes suggests him considering Hicks’s IS-LM anywhere near a faithful rendering of his thought. In Keynes’s canonical statement of the essence of his theory in the 1937 QJE-article there is nothing to even suggest that Keynes would have thought the existence of a Keynes-Hicks-IS-LM-theory anything but pure nonsense. So of course there can’t be any “vindication for the whole enterprise of Keynes/Hicks macroeconomic theory” – because “Keynes/Hicks” never existed.

John Hicks, the man who invented IS-LM in his 1937 Econometrica review of Keynes’ General TheoryMr. Keynes and the ‘Classics’. A Suggested Interpretation – returned to it in an article in 1980 – IS-LM: an explanation – in Journal of Post Keynesian Economics. Self-critically he wrote that “the only way in which IS-LM analysis usefully survives — as anything more than a classroom gadget, to be superseded, later on, by something better – is in application to a particular kind of causal analysis, where the use of equilibrium methods, even a drastic use of equilibrium methods, is not inappropriate.” What Hicks acknowledges in 1980 is basically that his original review totally ignored the very core of Keynes’ theory – uncertainty (and doing this he actually turned the train of macroeconomics on the wrong tracks for decades).

Now that Krugman seems to be on the right track, I would suggest he goes on reading another economist who had a profound understanding of what Keynes really was up to:

The determination of investment is a four-stage process in The General Theory. Money and debts determine an “interest rate”; long-term expectations determine the yield – or expected cash flows – from capital assets and current investment (i.e., the capital stock); the yield and the interest rate enter into the determination of the price of capital assets; and investment is carried to the point where the supply price of investment output equals the capitalized value of the yield. The simple IS-LM framework violates the complexity of the investment-determning process as envisaged by Keynes …

minskys keynesbokThe Hicks-Hansen model, by making explicit the interdependence of the commodity and money markets in Keynes’s thought, is a more accurate representation of his views than the simple consumption-function models. Nevertheless, because it did not explicitly consider the significance of uncertainty in both portfolio decisions and investment behavior, and becasue it was an equilibrium rather than a process interpretation of the model, it was an unfair and naïve representation of Keynes’s subtle and sophisticated views …

The journey through various standard models that embody elements derived from The General Theory has led us to the position that such Keynesian models are either trivial (the consumption-function models), incomplete (the IS-LM models without a labor market), inconsistent (the IS-LM models with a labor market but no real-balance effect), or indistinguishable in their results from those of older quantity-theory models (the neoclassical synthesis).

It’s about time that neoclassical economists follow Krugman and now start to set the record straight and stop promoting something that the creator himself admits was a total failure. Why not study the real thing itself – General Theory – in full and without looking the other way when it comes to non-ergodicity and uncertainty?

Keynes for kids

23 Aug, 2013 at 13:36 | Posted in Economics | Comments Off on Keynes for kids


At last something worth watching for our youngsters on the web – a website on Keynes for kids!   (h/t Naked Keynesianism)

On mathematics and economics

22 Aug, 2013 at 10:57 | Posted in Economics, Theory of Science & Methodology | 6 Comments

Neoclassical economic theory today is in the story-telling business whereby economic theorists create mathematical make-believe analogue models of the target system – usually conceived as the real economic system. This mathematical modeling activity is considered useful and essential. Since fully-fledged experiments on a societal scale as a rule are prohibitively expensive, ethically indefensible or unmanageable, economic theorists have to substitute experimenting with something else. To understand and explain relations between different entities in the real economy the predominant strategy is to build mathematical models and make things happen in these “analogue-economy models” rather than engineering things happening in real economies.

Formalistic deductive “Glasperlenspiel” can be very impressive and seductive. But in the realm of science it ought to be considered of little or no value to simply make claims about the model and lose sight of reality.

With his profound knowledge of mathematics, Keynes realized the limits of its applicability to the real world — and that it was certainly not enough for a relevant social science to prove things about thought up worlds:

But I am unfamiliar with the methods involved and it may be that my impression that nothing emerges at the end which has not been introduced expressly or tacitly at the beginning is quite wrong … It seems to me essential in an article of this sort to put in the fullest and most explicit manner at the beginning the assumptions which are made and the methods by which the price indexes are derived; and then to state at the end what substantially novel conclusions has been arrived at … I cannot persuade myself that this sort of treatment of economic theory has anything significant to contribute. I suspect it of being nothing better than a contraption proceeding from premises which are not stated with precision to conclusions which have no clear application … [This creates] a mass of symbolism which covers up all kinds of unstated special assumptions.

Keynes to Frisch 28 November 1935

Neoclassical economists often hold the view that criticisms of its one-sided, almost religious, insistence on mathematical-axiomatic-deductivist modeling as the only scientific activity worthy of pursuing in economics, are the conclusions of sadly misinformed and misguided people who dislike and do not understand much of it. This is really a gross misapprehension. To be careful and cautious is not the same as to dislike. And as any perusal of the works of people like for example John Maynard Keynes or Tony Lawson shows, the critique is put forward by respected authorities. I would argue, against “common knowledge”, that they do not misunderstand the crucial issues at stake. Quite the contrary. They know them all too well – and are not satisfied with the validity and philosophical underpinning of the assumptions made for applying its methods:

The fundamental problem of modern economics is that methods are repeatedly applied in conditions for which they are not appropriate … Specifically, modern academic economics is dominated by a mainstream tradition whose defining characteristic is an insistence that certain methods of mathematical modelling be more or less always employed in the analysis of economic phenomena, and are so in conditions for which they are not suitable.

tony-lawsonFundamental to my argument is an assessment that the application of mathematics involves more than merely the introduction of a formal language. Of relevance here is recognition that mathematical methods and techniques are essentially tools. And as with any other tools (pencils, hammers, drills, scissors), so the sorts of mathematical methods which economists wield (functional relations, forms of calculus, etc.) are useful under some sets of conditions and not others.

The specific conditions required for the sorts of mathematical methods that economists continually wield to be generally applicable, I have shown, are a ubiquity of (deterministic or stochastic) closed systems. A closed system is simply one in which an event regularity occurs. Notice that these closures are as much presupposed or required by the ‘newer’ approaches to mathematical economics, those often referred to as non-linear modelling, complexity modelling, agent-based modelling, model simulations, and so on (including those developed under the head of behavioural or neuro- economics), as they are by the more traditional forms of micro, macro and econometric modelling.

The most obvious scenario in which a prevalence of such closures would be expected is a world 1) populated by sets of atomistic individuals or entities (an atom here being an entity that exercises its own separate, independent, and invariable effect, whatever the context); where 2) the atoms of interest exist in relative isolation (so allowing the effects of the atoms of interest to be deducible/predictable by barring the effects of potentially interfering factors). Not surprisingly the latter two (ontological) presuppositions are easily shown to be implicit in almost all contemporary economic modelling contributions …

However, explicit, systemic and sustained (ontological) analysis of the nature of social reality reveals the social domain not to be everywhere composed of closed systems of sets of isolated atoms. Rather social reality is found to be an open, structured realm of emergent phenomena that, amongst other things, are processual (being constantly reproduced and transformed through the human practices on which they depend), highly internally related (meaning constituted though [and not merely linked by] their relations with each other – e.g., employer/employee or teacher/ student relations), value-laden and meaningful, amongst much else …

Clearly if social phenomena are highly internally related they do not each exist in isolation. And if they are processual in nature, being continually transformed through practice, they are not atomistic. So the emphasis on the sorts of mathematical modelling methods that economists employ necessarily entails the construction of economic narratives – including the sorts of axioms and assumptions made and hypotheses entertained – that, at best, are always but highly distorted accounts of the complex phenomena of the real open social system … It is thus not at all surprising that mainstream contributions are found continually to be so unrealistic and explanatorily limited.

Employing the term deductivism to denote the thesis that closed systems are essential to social scientific explanation (whether the event regularities, correlations, uniformities, laws, etc., are either a prior constructions or a posterior observations), I conclude that the fundamental source of the discipline’s numerous, widespread and long lived problems and failings is precisely the emphasis placed upon forms of mathematical deductivist reasoning.

Tony Lawson

Krugman vs. Galbraith on math and models

21 Aug, 2013 at 18:06 | Posted in Economics, Theory of Science & Methodology | 10 Comments

James K. Galbraith

Krugman’s main point is that he represents the “nerds” of economics, whereas I and the distinguished writer Robert Kuttner are “literati,” who would like the profession to be less mathematical than it is. Leaving Kuttner to speak for himself, this view also totally misrepresents not only my position but also Paul Krugman’s own professional one.

This may come as a surprise to outsiders, but Krugman is not a mathematical theorist (and I have heard him admit this, to a knowing audience). Krugman’s mathematics are not deep, and he has no interest in complicated manipulations of data. He owes his fame, instead, to an exceptional grace and lucidity of formal presentation. With these gifts, Paul has expanded the range of neoclassical economics in several notable directions, especially international trade theory. Krugman’s professional work is mathematically literate, of course. The point is that it is also literate, and, for many economists, that is its appeal.

My own work is mathematical when it needs to be …

So if the issues between Krugman and myself are neither hermeneutic nor mathematic, what are they? The actual issues are philosophical and theoretical.

Paul’s worldview rests on the belief that useful implications for important questions of public policy can be derived, essentially from first principles, with the help of a well-structured logic. Well-structured deduction from metaphysical first principles is the Krugman forte.

I don’t accept that much of use can be learned about policy in this way. When the world deviates from the principles, as it usually does, the simple lessons go astray. This is not a complaint against math. It is a complaint against indiscriminate application of the deductive method, sometimes called the Ricardian vice, to problems of human action. Mine is an old gripe against much of what professional economists do; not against science but against scientism, against the pretense of science. To combat it, I spend my research time wrestling with real-world data, and I spend much of my writing time warring against the policy ideas of aggressive, ahistorical deductivists …

In the final analysis, Krugman’s argument is that there is a simple distinction between the “serious” economists–who agree with him–and the “critics,” who are, by definition, not serious. It is true, of course, that economic-policy discussions are magnets for cranks. But from this it does not follow, and is not in fact true, that all “serious” economists hold to some single position. It is even more absurd to suppose that one gains access to this wisdom by passing an exam in algebra. In this respect, Krugman’s argument is so shallow, so actually illogical (a fallacy of induction, in this case), that it is evidently aimed at rubes. I hope not many will be taken in.

Paul Krugman

images-14Economics is at least partly about quantities and their relationships; so you can’t make sense of it unless you are willing to do some arithmetic and even some algebra to make sure that the stories you tell hang together–and that they are consistent with the evidence. This doesn’t sound like much, but experience shows that there are many influential intellectuals who are prepared to make sweeping pronouncements on economics without doing the arithmetic …

Galbraith, like many critics of economics, seems to believe in the following syllogism:

1) Economists disagree about some important issues, and some economists with impeccable credentials say silly things.

2) Therefore, there is no need for a smart individual to brush up on economics–say by reading an undergraduate textbook–before making pronouncements on the subject.

Although Galbraith systematically exaggerates and misrepresents the actual disagreements, 1) is obviously true about economics–and about medicine, and physics, and law, and any other discipline you choose to name. Did you know that astronomers cannot agree on the age of the universe, and that the current best estimates suggest that the oldest stars are older than the universe in which they shine? So maybe Copernicus was wrong!

The point is that in each of these disciplines, we all understand that while there are major disagreements about some questions, there is also a large area on which the experts do agree, and in which their expertise is real …

Because of this attitude, most of the criticism economists face is not over issues where there is legitimate disagreement. Instead, the heavy majority of the challenges are simply wrong on the arithmetic. That is, the doctrines asserted either do not add up, can be shown to be flatly untrue using readily available data, or can be shown by simple calculations to involve effects much too small to bear the weight being placed on them …

Now we all make mistakes. But the peculiar thing here is that in each of these cases, the proponents imagine themselves to have achieved a higher level of understanding, to have transcended the narrowness of conventional economics. Somebody needs to point out to them and to their audiences that, on the contrary, they are simply misunderstanding basic arithmetic.

Post Keynesian Archive

(h/t Jan Milch)

Added (GMT 20:20): And, coincidentally, Krugman has a post on – yes, math – on his blog today, now — 17 years later — writing:

What is true is that all too many economists have lost sight of this purpose; they treat their models as The Truth, and/or judge each others’ work by how hard the math is. It sounds as if Smith was taught macro by people like that. And there are a lot of people in macro, some of them fairly prominent, who are what my old teacher Rudi Dornbusch used to call “fearful plumbers” — people who can push equations around, but have no sense of what they mean, and as a result say quite remarkably stupid things when confronted with real-world economic issues.

With age comes humility and wisdom …

Popular myths about inflation

20 Aug, 2013 at 20:53 | Posted in Economics | 1 Comment

We’re told that inflation is a necessary cost of improving the economy. And in fact, that’s exactly what monetarist macroeconomists (think of Mike Woodford, Miles Kimball, etc.) tell us that it is. We must accept higher inflation, they tell us, in order to also get better GDP growth. But given our ‘druthers, they tell us, we’d rather have very low inflation. No one wants to become like Zimbabwe, or the Weimar Republic, right??

I’m not so sure this is true, and I’ll explain why later. But first, let me dispel a couple of popular myths about inflation.

no-mythsPopular Inflation Myth 1: “Inflation means I can’t buy as much stuff.”

Wrong. Remember, inflation is an increase in the overall price level. But when the price of everything goes up, your wage should rise as well. Why? Because on average, we are all sellers of something. If you work in a tea shop and the price of tea goes up, your wage can be expected to go up as well, and so forth. Remember, every dollar that one person spends becomes the income of another person!

So when prices go up, wages should go up as well. Read this paper. The authors find that “higher prices lead to higher wage growth”.

Of course, wages are affected by other things besides inflation – for example, labor’s share of total income. So “price inflation” and “wage inflation” aren’t exactly the same. But they tend to be similar …

Economists have a term for how much you can buy with your wages. It’s called the “real wage”. Real wages are wages AFTER accounting for inflation. So to look at how much you can buy, don’t look at inflation, look at your real wage. Your real wage tells you your real cost of living; inflation does not.

To see that inflation doesn’t reduce your real wage, just think about Weimar Germany. Prices went up by a factor of one trillion. But people did not starve en masse as a result. Remember that guy with the wheelbarrow full of cash, going to buy bread? HOW DO YOU THINK HE GOT HIS HANDS ON A WHEELBARROW OF CASH IN THE FIRST PLACE? The answer: That was not his life’s savings. He did not sell the family farm. He had a wheelbarrow full of cash because as prices skyrocketed, wages skyrocketed too!

“But don’t employers take advantage of inflation to screw over workers and make them take wage cuts?”

Maybe. People don’t pay close attention to inflation when it’s low, and so a small amount of inflation can allow employers to cut real wages without people noticing. (Actually, some economists who want “wage flexibility” like a small amount of inflation for exactly this reason.)

But for larger amounts of inflation, no. When inflation gets big, people start noticing, and demanding higher wages …

Anyway, once more: Inflation does not make your real wage fall.

Noah Smith

Post-structuralist support hotline

20 Aug, 2013 at 20:29 | Posted in Varia | Comments Off on Post-structuralist support hotline

[Tongue-in-cheek and h/t Jan Milch]

Keynes and Knight on uncertainty — what’s the difference?

19 Aug, 2013 at 14:04 | Posted in Economics | 2 Comments

davidsonA couple of months ago yours truly had an interesting discussion – on the Real-World Economics Review Blog – with Paul Davidson, founder and editor of the Journal of Post Keynesian Economics, on uncertainty and ergodicity. It all started with me commenting on Davidson’s article Is economics a science? Should economics be rigorous? :

Davidson’s article is a nice piece – but ergodicity is a difficult concept that many students of economics have problems with understanding. To understand real world ”non-routine” decisions and unforeseeable changes in behaviour, ergodic probability distributions are of no avail. In a world full of genuine uncertainty – where real historical time rules the roost – the probabilities that ruled the past are not those that will rule the future.

Time is what prevents everything from happening at once. To simply assume that economic processes are ergodic and concentrate on ensemble averages – and a fortiori in any relevant sense timeless – is not a sensible way for dealing with the kind of genuine uncertainty that permeates open systems such as economies.

When you assume the economic processes to be ergodic, ensemble and time averages are identical. Let me give an example: Assume we have a market with an asset priced at 100 €. Then imagine the price first goes up by 50% and then later falls by 50%. The ensemble average for this asset would be 100 €- because we here envision two parallel universes (markets) where the asset-price falls in one universe (market) with 50% to 50 €, and in another universe (market) it goes up with 50% to 150 €, giving an average of 100 € ((150+50)/2). The time average for this asset would be 75 € – because we here envision one universe (market) where the asset-price first rises by 50% to 150 €, and then falls by 50% to 75 € (0.5*150).

From the ensemble perspective nothing really, on average, happens. From the time perspective lots of things really, on average, happen.

Assuming ergodicity there would have been no difference at all.

Just in case you think this is just an academic quibble without repercussion to our real lives, let me quote from an article of physicist and mathematician Ole Peters in the Santa Fe Institute Bulletin from 2009 – “On Time and Risk” – that makes it perfectly clear that the flaw in thinking about uncertainty in terms of “rational expectations” and ensemble averages has had real repercussions on the functioning of the financial system:

“In an investment context, the difference between ensemble averages and time averages is often small. It becomes important, however, when risks increase, when correlation hinders diversification, when leverage pumps up fluctuations, when money is made cheap, when capital requirements are relaxed. If reward structures—such as bonuses that reward gains but don’t punish losses, and also certain commission schemes—provide incentives for excessive risk, problems arise. This is especially true if the only limits to risk-taking derive from utility functions that express risk preference, instead of the objective argument of time irreversibility. In other words, using the ensemble average without sufficiently restrictive utility functions will lead to excessive risk-taking and eventual collapse. Sound familiar?”


Lars, if the stochastic process is ergodic, then for for an infinite realizations, the time and space (ensemble) averages will coincide. An ensemble a is samples drawn at a fixed point of time drawn from a universe of realizations For finite realizations, the time and space statistical averages tend to converge (with a probability of one) the more data one has.

Even in physics there are some processes that physicists recognize are governed by nonergodic stochastic processes. [ see A. M. Yaglom, An Introduction to Stationary Random Functions [1962, Prentice Hall]]

I do object to Ole Peters exposition quote where he talks about “when risks increase”. Nonergodic systems are not about increasing or decreasing risk in the sense of the probability distribution variances differing. It is about indicating that any probability distribution based on past data cannot be reliably used to indicate the probability distribution governing any future outcome. In other words even if (we could know) that the future probability distribution will have a smaller variance (“lower risks”) than the past calculated probability distribution, then the past distribution is not is not a reliable guide to future statistical means and other moments around the means.


Paul, re nonergodic processes in physics I would even say that most processes definitely are nonergodic. Re Ole Peters I totally agree that what is important with the fact that real social and economic processes are nonergodic is the fact that uncertainty – not risk – rules the roost. That was something both Keynes and Knight basically said in their 1921 books. But I still think that Peters’ discussion is a good example of how thinking about uncertainty in terms of “rational expectations” and “ensemble averages” has had seriously bad repercussions on the financial system.


Lars, there is a difference between the uncertainty concept developed by Keynes and the one developed by Knight.

As I have pointed out, Keynes’s concept of uncertainty involves a nonergodic stochastic process . On the other hand, Knight’s uncertainty — like Taleb’s black swan — assumes an ergodic process. The difference is the for Knight (and Taleb) the uncertain outcome lies so far out in the tail of the unchanging (over time) probability distribution that it appears empirically to be [in Knight’s terminology] “unique”. In other words, like Taleb’s black swan, the uncertain outcome already exists in the probability distribution but is so rarely observed that it may take several lifetimes for one observation — making that observation “unique”.

In the latest edition of Taleb’s book , he was forced to concede that philosophically there is a difference between a nonergodic system and a black swan ergodic system –but then waves away the problem with the claim that the difference is irrelevent.


Paul, on the whole, I think you’re absolutely right on this. Knight’s uncertainty concept has an epistemological founding and Keynes’s definitely an ontological founding. Of course this also has repercussions on the issue of ergodicity in a strict methodological and mathematical-statistical sense. I think Keynes’s view is the most warranted of the two.

BUT – from a “practical” point of view I have to agree with Taleb. Because if there is no reliable information on the future, whether you talk of epistemological or ontological uncertainty, you can’t calculate probabilities.

The most interesting and far-reaching difference between the epistemological and the ontological view is that if you subscribe to the former, knightian view – as Taleb and “black swan” theorists basically do – you open up for the mistaken belief that with better information and greater computer-power we somehow should always be able to calculate probabilities and describe the world as an ergodic universe. As both you and Keynes convincingly have argued, that is ontologically just not possible.


Lars, your last sentence says it all. If you believe it is an ergodic system and epistemology is the only problem, then you should urge more transparency , better data collection, hiring more “quants” on Wall Street to generate “better” risk management computer problems, etc — and above all keep the government out of regulating financial markets — since all the government can do is foul up the outcome that the ergodic process is ready to deliver.

Long live Stiglitz and the call for transparency to end asymmetric information — and permit all to know the epistemological solution for the ergodic process controlling the economy.

Or as Milton Friedman would say, those who make decisions “as if” they knew the ergodic stochastic process create an optimum market solution — while those who make mistakes in trying to figure out the ergodic process are like the dinosaurs, doomed to fail and die off — leaving only the survival of the fittest for a free market economy to prosper on. The proof is why all those 1% far cats CEO managers in the banking business receive such large salaries for their “correct” decisions involving financial assets.

Alternatively, if the financial and economic system is non ergodic then there is a positive role for government to regulate what decision makers can do so as to prevent them from mass destruction of themselves and other innocent bystanders — and also for government to take positive action when the herd behavior of decision makers are causing the economy to run off the cliff.

So this distinction between ergodic and nonergodic is essential if we are to build institutional structures that make running off the cliff almost impossible. — and for the government to be ready to take action when some innovative fool(s) discovers a way to get around institutional barriers and starts to run the economy off the cliff.

To Keynes the source of uncertainty was in the nature of the real – nonergodic – world. It had to do, not only – or primarily – with the epistemological fact of us not knowing the things that today are unknown, but rather with the much deeper and far-reaching ontological fact that there often is no firm basis on which we can form quantifiable probabilites and expectations.

Why we are better at forecasting drizzle than financial crises

18 Aug, 2013 at 16:08 | Posted in Economics, Statistics & Econometrics | 3 Comments

The analysis of probability originates in games of chance, in which the rules are sufficiently simple and well-defined that the game can be repeated in more or less identical form over and over again. If you toss a fair coin repeatedly, it will come up heads about 50 per cent of the time. If you can be bothered, you can verify that fact empirically. Perhaps more strikingly, the theory of probability tells you that if you repeatedly toss that coin 50 times you will get 23 or more heads about 67 per cent of the time, and you can verify that prediction empirically too.

It is a stretch, but perhaps not a very long stretch, to extend this analysis of frequency to single events, and to say that the probability that England will win the toss in the fifth Ashes cricket test against Australia is 50 per cent. And that the probability the home side will win the toss at least 23 times in a decade of five-test match series is 67 per cent. Tosses to start sporting contests are repeated at similar events, and theory and experience validate the probabilistic approach.


Perhaps one could stretch the approach further and apply it to the probability of rain. The Met Office might form a view of tomorrow’s weather. Records might show that it rains on 10 per cent of similar days. The difficulty is defining exactly what is meant by “a similar day”. “A typical April day in England” is a rather loose concept.

However, this is not, in fact, what weather forecasters do. Their analysis is based on elaborate computer models and they tweak the assumptions of these models to generate many different predictions. What they mean when they say the probability of rain is 10 per cent is that rain occurs in 10 per cent of these simulations. The validity of that prediction depends on two rather implausible assumptions; that the model correctly describes the physical world, and that the range of assumptions made by the modellers properly reflects the full range of possible assumptions.

Despite these difficulties – and popular derision comparable to that experienced by economic forecasters – weather forecasters do rather well …

In contrast, severe recessions, property bubbles and bank failures are relatively infrequent, and calibration by economists has come to mean tweaking models to better explain the past rather than revising them to better predict the future – a particularly dangerous methodology when there are many reasons to think that the underlying structure of the economy is in a state of constant flux.

The further one moves from mechanisms that are well understood and events that are frequently repeated, the less appropriate is the use of probabilistic language. What does it mean to say: “I am 90 per cent certain that the extinction of the dinosaurs was caused by an object hitting the earth at Yucatán?” Not, I think, that on 90 per cent of occasions on which the dinosaurs were wiped out, the cause was an asteroid landing in what is now Mexico. There is a difference – often elided – between a probability and a degree of confidence in a forecast. It is one reason why we are better at avoiding drizzle than financial crises.

John Kay

To me this wonderful little article shows how important it is in social sciences — and economics in particular — to incorporate Keynes’s far-reaching and incisive analysis of induction and evidential weight in his seminal A Treatise on Probability (1921).

treatprobAccording to Keynes we live in a world permeated by unmeasurable uncertainty – not quantifiable stochastic risk – which often forces us to make decisions based on anything but “rational expectations.” Keynes rather thinks that we base our expectations on the confidence or “weight” we put on different events and alternatives. To Keynes expectations are a question of weighing probabilities by “degrees of belief,” beliefs that often have preciously little to do with the kind of stochastic probabilistic calculations made by the rational agents as modeled by “modern” social sciences. And often we “simply do not know.”

How strange that social scientists and mainstream economists as a rule do not even touch upon these aspects of scientific methodology that seems to be so fundamental and important for anyone trying to understand how we learn and orient ourselves in an uncertain world. An educated guess on why this is a fact would be that Keynes concepts are not possible to squeeze into a single calculable numerical “probability.” In the quest for measurable quantities one puts a blind eye to qualities and looks the other way.

Ekonomi och matematik

18 Aug, 2013 at 10:36 | Posted in Economics | Comments Off on Ekonomi och matematik

Neoklassisk nationalekonomi har under de senaste femtio åren kommit att i allt högre grad innebära ett granskande av världen genom “matematikens järngaller”. Precis som Bertrand Russell har många ekonomer hoppats på att med tiden konstruera “en matematik för mänskligt beteende som är lika exakt som matematiken för maskiner” . För ekonomerna har detta ofta kommit att innebära att om ett fenomen inte låter sig passas in i gallret så avvisas det som falskt. Och tyvärr har trivialitet och irrelevans ofta blivit det pris de fått betala för formalism och deduktivism.

Fotolia_44095455_XSDe regler som gäller för manipulerandet av matematiska storheter behöver inte motsvaras av de regler och lagar som styr det verkliga systemet. Detta är säkert också en av orsakerna till att så många matematiska ekonomiska teorier varit utan framgång. Istället för att okritiskt anamma en matematisk representationsform borde man fråga sig vilka förutsättningar som de reala processerna och objekten måste uppfylla för att matematiska representationer av dem ska vara adekvata.

Att ekonomisk vetenskap är mer kvantitativ än andra samhällsvetenskaper beror till en viss del på att dess studieobjekt naturligt till stor del är kvantitativa (pengar, räkenskaper, löner, vinster, m m). Detta kan dock inte utgöra ett försvar för att driva matematiseringen in absurdum eller för att avstå från att fråga sig vad de matematiska modellerna och kvantitativa måtten är modeller för och mått av.

Att så mycket av dagens ekonomiska vetenskap — fortfarande — struntar i att söka orsaksrelationer och istället nöjer sig med att fastslå korrelationer och ömsesidiga samband beror till del på det matematiska språk man använder sig av. Matematik kan användas för att kalkylera och för logisk härledning. Men axiom och teorem förklarar per se inte ett fenomen i termer av orsak. Det matematiska språket räcker ofta inte till för våra förklaringsaspirationer.

En av de främsta orsakerna till att många ekonomiska fenomen aldrig fått någon förklaring kan vara att många i sig intressanta egenskaper hos ekonomin (processer, strukturer, etc) bara beaktas i den mån de låter sig reduceras till regelbundna händelser och matematiskt identifierbara mönster.

Matematik kan inte representera interna relationer och strukturer. De som utvecklar de ekonomiska matematiska modellerna har därför en tendens att avstå från förklaringar av vad det ekonomiska handlandet beror på och nöjer sig i stället med att kalkylera och beräkna effekterna av handlandet. Detta gör att de matematiska ekonomerna ofta förblir påfallande omedvetna om de samhälleliga relationer och strukturer som styr de variabler man laborerar med i sina modeller. Komplext handlande reduceras till en kombination av enkla handlingar, som i sin tur reduceras till responser på stimuli – som om stimuli och respons var oberoende av det kontextuella sammanhanget. Kunskap om kvalitativa förhållanden kastas bort för att man i stället ska kunna koncentrera sig på tillvarons kvantifierbara dimensioner. Resultatet blir allt för ofta att modeller och matematik får bli ett substitut för tänkande. Den franske 1800-talsdiplomaten Charles Talleyrand hävdade att människor fått talets gåva för att dölja sina tankar. Ibland kan man tyvärr få intrycket att ekonomernas matematiska modeller fyller samma funktion.

Matematiseringsvågen har gjort ekonomerna alltför fixerade vid sina formella, matematiska modeller. Ställda inför kritiken att de inte löser verkliga problem reagerar många av dagens matematiska ekonomer likt Saint-Exupérys Store Geograf som på den Lille Prinsens frågor svarar att han är för upptagen med sitt vetenskapliga arbete för att kunna säga något om verkligheten. Ställd inför den ekonomiska teorins uppenbart dåliga verklighetsförankring retirerar man till modellernas underbara värld. Istället för att konstruera teorier utifrån empiriska fakta överger man den verkliga världen och bevisar saker om tänkta världar. Istället för att acceptera att en lägre grad av säkerhet är oundviklig ägnar man sig åt axiomatiska och rationalistiska modellkonstruktioner som möjliggör säker kunskap. Om målet är kunskap om den verkliga världen, är värdet av dessa dock minst sagt oklart.

Hade nationalekonomerna varit lika exakta och matematiska när de väl använder sina modeller på verkligheten som när de bygger modellerna, hade det kanske inte varit så farligt. Men i stället är det oftast så att de är extremt oansvariga när de etablerar sambandet mellan teori och verklighet. De samband de menar sig kunna bevisa i sina ”tänkta” ekonomier används kritiklöst för att hävda saker om verkliga ekonomier. Problemet är alltså att ekonomerna sällan etablerar ett samband mellan sina teorier och verkligheten, och när de väl gör det sker det på ett felaktigt sätt.

De antaganden som nationalekonomerna utgår från i form av jämvikt, rationalitet och kalkylerbara risker är som jag visat i dålig överensstämmelse med verkligheten, där ojämvikt, irrationalitet och genuin osäkerhet är legio. Detta väljer dock många nationalekonomer att blunda för med hänvisning till Milton Friedmans tes att antagandenas realism är betydelselös så länge teorins förutsägelser är korrekta. Den ekonomiska teorins bristande överensstämmelse med verkligheten förnekas inte. En nobelpristagare i ekonomi – Robert Lucas – medger till exempel att teorin beskriver en “patenterat artificiell värld” med “robotimitationer av människor”. Andra förespråkare har framhållit att den självklart är overklig och till och med att detta skulle vara meningen med den.

Men när förutsägelserna sällan eller aldrig slår in, vad gör man då? Det naturliga vore kanske att se sig om efter andra, bättre teorier. Bygga nytt. Men nationalekonomerna drar i stället oftast åt skyddsbältet ännu hårdare om teorins kärna och reparerar. Man går in i redskapsboden – och stannar där inne. Där hänger man sig i världsfrånvändhet åt avancerade teknisk-matematiska analyser som inte tillför någon substantiellt ny kunskap om verklighetens ekonomi. Medan de ekonomiska problemen ute i verkligheten växer, leker man glatt vidare med den matematiska verktygslådans senaste inneprylar.

Matematiseringen skapar också en ny obegriplighet. Den snäva inriktningen på att bygga abstrakta matematiska modeller och teorier, där precision, elegans och förfining får gå före relevans, leder till att man saknar överblick och att nationalekonomin idag mer bidrar till den tillämpade matematikens utveckling än till samhällsvetenskapernas. I stället för att göra matematiken till ett självändamål hävdar kritiker att de som tvingas leva i den av de möjliga världar som kallas den verkliga nog hade varit mer betjänta av att man försökt bidra till lösandet av verkliga problem. Kanske var det detta den amerikanske ekonomen Kenneth Boulding avsåg när han kallade den moderna nationalekonomin för “en icke-existerande världs himmelska mekanik”.

En outsiders väg

18 Aug, 2013 at 10:15 | Posted in Varia | Comments Off on En outsiders väg


QE doesn’t work at ZLB – Koo explains why

16 Aug, 2013 at 20:31 | Posted in Economics | 1 Comment


Latvia and Sweden — the ultimate Keynes killers?

16 Aug, 2013 at 09:46 | Posted in Economics | 1 Comment

Some people seem to consider the case of Latvia the ultimate Keynes killer, showing that austerity policies suffice to get you out of deep recessions and not having to fall back on Keynesian stimulus.

Hmm …

What are the facts? Latvia today has a real GDP that still is far below its pre-crisis peak. Its unemployment rate is close to 15 %. Indeed an impressive success …

Still not convinced of the futility of austerity measures as enhancers of growth and prosperity? Perhaps Paul Krugman may be of assistance:

It really is kind of pathetic to see European leaders claiming vindication after one whole quarter of positive growth, at the thrilling annual rate of 1.2 percent. Just to say the obvious: when you’ve suffered a huge hit to output and employment, you’re supposed to have a long period of fast growth to make up the lost ground. Otherwise you’re making the definition of success way too easy.

To illustrate my point, here’s a comparison I’ve been looking at. It’s between Latvia — which is the closest thing we have to an actual austerity success story, since it has been growing fast, even if it’s still far below pre-crisis levels — and another country, which isn’t Latvia. Here’s the chart:


Two big success stories, right? But who is Not Latvia?

Well, it’s the United States from 1929 to 1935 …

But how about Sweden then? Haven’t we over and over again been told that it successfully applied fiscal austerity measures in the mid-1990s, measures that led to a strong economic recovery? According to Swedish economist Lennart Erixon the facts are really quite different:

There was indeed a recovery of investment and consumption in the mid-90s. Nevertheless, Sweden’ s recovery was not investment- or consumption-led (in comparison with other OECD countries, Sweden’ s consumption and investment was modest), and the recovery in investment did not primarily reflect the reductions in real interest rates. Instead, the recovery was due to ICT -induced investments and export-induced investment which increased because of high external demand and profits as well as the depreciation of the SEK.

Erixon explained that there were several short-run effects of Sweden’s tight fiscal measures in the mid-90s. On the one hand, the restrictive fiscal policy caused the disappearance of the public budget deficit by 1998, within four years. On the other hand, the restrictive fiscal and monetary policy did have contractionary effects and caused a delay in recovery. Sweden experienced lower GDP growth on average than other OECD countries in 1996-7 and unemployment continued to increase until late 1997, reaching 10% – despite favourable circumstances such as the depreciation of the SEK, a large increase in productivity, an international recovery and a high Solowian growth after the crisis.

However, the determinants of long-term GDP growth between the years of 1994 and 2007 were not a result of the fiscal restraint in the mid-90s. Sweden’s recovery and growth was export-led and aided by the depreciations of the SEK in 1993 and again in 1996-2001. The aforementioned technology-led ICT boom was the reason for high Swedish GDP growth from 1995-2000 and contributed to the “productivity miracle” experienced between 1995-2007, during which period Sweden placed third among OECD countries in terms of productivity growth. China’s increased share in Swedish exports led to an increase in the prices of Swedish products and contributed to the recovery of traditional Swedish industries, such as raw materials and investment goods, particularly in the 2000s.

Erixon concluded that the real effects of restrictive fiscal policy were contractionary in the short run (1994-1998) and that fiscal austerity was not a major factor behind high Swedish GDP growth in the long run (1994-2007) but instead that export- led growth played a key role.

Conclusion — austerity policies is total horseshit.

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