Archive

Author Archive

How money is created

March 13, 2018 67 comments

from Lars Syll

Everything we know is not just wrong – it’s backwards. When banks make loans, they create money. This is because money is really just an IOU. The role of the central bank is to preside over a legal order that effectively grants banks the exclusive right to create IOUs of a certain kind, ones that the government will recognise as legal tender by its willingness to accept them in payment of taxes.

There’s really no limit on how much banks could create, provided they can find someone willing to borrow it … For the banking system as a whole, every loan just becomes another deposit. What’s more, insofar as banks do need to acquire funds from the central bank, they can borrow as much as they like; all the latter really does is set the rate of interest, the cost of money, not its quantity …

The real limit on the amount of money in circulation is not how much the central bank is willing to lend, but how much government, firms, and ordinary citizens, are willing to borrow.

David Graeber 

Sounds odd, doesn’t it?

This guy must sure be one of those strange and dangerous heterodox cranks?

Well, maybe you should reconsider …  Read more…

Econometric disillusionment

March 10, 2018 6 comments

from Lars Syll

reality header3

Because I was there when the economics department of my university got an IBM 360, I was very much caught up in the excitement of combining powerful computers with economic research. Unfortunately, I lost interest in econometrics almost as soon as I understood how it was done. My thinking went through four stages:

1. Holy shit! Do you see what you can do with a computer’s help.
2. Learning computer modeling puts you in a small class where only other members of the caste can truly understand you. This opens up huge avenues for fraud:
3. The main reason to learn stats is to prevent someone else from committing fraud against you.
4. More and more people will gain access to the power of statistical analysis. When that happens, the stratification of importance within the profession should be a matter of who asks the best questions.

Disillusionment began to set in. I began to suspect that all the really interesting economic questions were FAR beyond the ability to reduce them to mathematical formulas. Watching computers being applied to other pursuits than academic economic investigations over time only confirmed those suspicions. Read more…

What austerity preachers do not get

March 7, 2018 11 comments

from Lars Syll

We are not going to get out of the economic doldrums as long as we continue to be obsessed with the unreasoned ideological goal of reducing the so-called deficit. The “deficit” is not an economic sin but an economic necessity …

idle all around us.

Alexan

austerity22

The administration is trying to bring the Titanic into harbor with a canoe paddle, while Congress is arguing over whether to use an oar or a paddle, and the Perot’s and budget balancers seem eager to lash the helm hard-a-starboard towards the iceberg. Some of the argument seems to be over which foot is the better one to shoot ourselves in. We have the resources in terms of idle manpower and idle plants to do so much, while the preachers of austerity, most of whom are in little danger of themselves suffering any serious consequences, keep telling us to tighten our belts and refrain from using the resources that lay der Hamilton once wrote “A national debt, if it be not excessive, would be for us a national treasure.” William Jennings Bryan used to declaim, “You shall not crucify mankind upon a cross of gold.” Today’s cross is not made of gold, but is concocted of a web of obfuscatory financial rectitude from which human values have been expunged.

William Vickrey

Wren-Lewis and the dangerous MMT

March 4, 2018 26 comments

from  Lars Syll

Professor Simon Wren-Lewis recently wrote: “The dangers of pluralism in economics: the case of MMT” …

mmtWren-Lewis argues that MMT concepts can be explained using mainstream terminology. Since I tend to use fairly standard terminology, I cannot disagree with that argument. However, I would phrase it differently. Mainstream discussion of fiscal policy is almost invariably clouded with theoretical junk (“fiscal sustainability”, “budget constraints”, “intergenerational transfer”, “bond vigilantes”) that it takes considerable effort to strip the junk out to get the correct description, which almost always ends up being the MMT description. The MMT jihad against various phrasings and framing terms reflects the need to think clearly about fiscal policy …

Modern Monetary Theory is evolving outside the journals that are locked down by the mainstream, and is focussed on real economic issues. Meanwhile, the mainstream is using dubious mathematics to painfully re-derive results that have been part of the post-Keynesian tradition for decades. You do not need a degree in the history of the philosophy of science to guess what the outcome is going to be. What we are seeing is the inevitable blowback of the attempt to stifle debate; since criticism cannot work through academic channels, it is instead funneled through non-academic ones.

Brian Romanchuk

On testing and learning in a non-repetitive world

March 3, 2018 10 comments

from Lars Syll

marquesThe incorporation of new information makes sense only if the future is to be similar to the past. Any kind of empirical test, whatever form it adopts, will not make sense, however, if the world is uncertain because in such a world induction does not work. Past experience is not a useful guide to guess the future in these conditions (it only serves when the future, somehow, is already implicit in the present) … I believe the only way to use past experience is to assume that the world is repetitive. In a non-repetitive world in which relevant novelties unexpectedly arise testing is irrelevant …

These considerations are applicable to decisions in conditions of radical uncertainty. If the actions that I undertake in t0 will have very different consequences according to the eventual state of the world in t1, it is crucial to gather reliable knowledge about these states. But how could I evaluate in t0 my beliefs about the state of the world in t1? If the world were repetitive (governed by immutable laws) and these laws were known, I could assume that what I find out about the present state is relevant to determine how the future state (the one that will prevail) will be. It would make then sense to apply a strategy for gathering empirical evidence (a sequence of actions to collect new data). But if the world is not repetitive, what makes me think that the new information may be at all useful regarding future events? …

Conceiving economic processes like sequences of events in which uncertainty reigns, where consequently there are “no laws”, nor “invariants” or “mechanisms” to discover, the kind of learning that experiments or last experience provide is of no use for the future, because it eliminates innovation and creativity and does not take into account the arboreal character and the open-ended nature of the economic process … However, as said before, we can gather precise information, restricted in space and time (data). But, what is the purpose of obtaining this sort of information if uncertainty about future events prevails? … The problem is that taking uncertainty seriously puts in question the relevance the data obtained by means of testing or experimentation has for future situations.

Read more…

The biggest trouble with modern​ macroeconomics

February 28, 2018 10 comments

from Lars Syll

romer-paul_picThe trouble is not so much that macroeconomists say things that are inconsistent with the facts. The real trouble is that other economists do not care that the macroeconomists do not care about the facts. An indifferent tolerance of obvious error is even more corrosive to science than committed advocacy of error.

Paul Romer 

New-Classical-Real-Business-Cycles-DSGE-New-Keynesian microfounded macromodels try to describe and analyze complex and heterogeneous real economies with a single rational-expectations-robot-imitation-representative-agent. That is, with something that has absolutely nothing to do with reality.

Opting for cloned representative agents that are all identical is of course not a real solution for analyzing macroeconomic issues. Representative agent models are — as I have argued at length here — rather an evasion whereby issues of distribution, coordination, heterogeneity — everything that really defines macroeconomics — are swept under the rug.

Of course, most macroeconomists know that to use a representative agent is a flagrantly illegitimate method of ignoring real aggregation issues. They keep on with their business, nevertheless, just because it significantly simplifies what they are doing.

Continuing to model a world full of agents behaving as economists — ‘often wrong, but never uncertain’ — is a gross misallocation of intellectual resources and time.

Keeping the dream alive

February 27, 2018 1 comment

from Lars Syll

akerlof_photo_01For me, the study of asymmetric information was a very first step toward the realization of a dream. That dream was the development of a behavioral macroeconomics in the original spirit of Keynes’ General Theory. Macroeconomics would then no longer suffer from the ad hockery of the neoclassical synthesis, which had over-ridden the emphasis in The General Theory on the role of psychological and sociological factors, such as cognitive bias, reciprocity, fairness, herding, and social status. My dream was to strengthen macroeconomic theory by incorporating assumptions honed to the observation of such behavior …

Keynes’ General Theory was the greatest contribution to behavioral economics before the present era. Almost everywhere Keynes blamed market failures on psychological propensities (as in consumption) and irrationalities (as in stock market speculation). Immediately after its publication, the economics profession tamed Keynesian economics. They domesticated it as they translated it into the “smooth” mathematics of classical economics. But economies, like lions, are wild and dangerous. Modern behavioral economics has rediscovered the wild side of macroeconomic behavior. Behavioral economists are becoming lion tamers. The task is as intellectually exciting as it is difficult.

George Akerlof

Keynes’ core in​sight

February 27, 2018 5 comments

from Lars Syll

rBut these more recent writers like their predecessors were still dealing with a system in which the amount of the factors employed was given and the other relevant facts were known more or less for certain … At any given time facts and expectations were assumed to be given in a definite and calculable form … The calculus of probability, tho mention of it was kept in the background, was supposed to be capable of reducing uncertainty to the same calculable status as that of certainty itself …

The fact that our knowledge of the future is fluctuating, vague and uncertain, renders Wealth a peculiarly unsuitable subject for the methods of the classical economic theory …

By “uncertain” knowledge, let me explain, I do not mean merely to distinguish what is known for certain from what is only probable … The sense in which I am using the term is that in which the prospect of a European war is uncertain, or the price of copper and the rate of interest twenty years hence … About these matters there is no scientific basis on which to form any calculable probability whatever. We simply do not know.

John Maynard Keynes

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 cannot simply be assumed to be those that will rule the future.  Read more…

Economics — a science with wacky views of human behaviour​

February 25, 2018 46 comments

from Lars Syll

There is something about the way economists construct their models nowadays that obviously doesn’t sit right.

The one-sided, almost religious, insistence on axiomatic-deductivist modelling as the only scientific activity worthy of pursuing in economics still has not given way to methodological pluralism based on ontological considerations (rather than formalistic tractability). In their search for model-based rigour and certainty, ‘modern’ economics has turned out to be a totally hopeless project in terms of real-world relevance.

grumpy-economics-catIf macroeconomic models — no matter of what ilk — build on microfoundational assumptions of representative actors, rational expectations, market clearing and equilibrium, and we know that real people and markets cannot be expected to obey these assumptions, the warrants for supposing that model-based conclusions or hypotheses of causally relevant mechanisms or regularities can be bridged to real-world target systems, are obviously non-justifiable. Incompatibility between actual behaviour and the behaviour in macroeconomic models building on representative actors and rational expectations microfoundations shows the futility of trying to represent real-world target systems with models flagrantly at odds with reality. As Robert Gordon once had it:

 

Rigor competes with relevance in macroeconomic and monetary theory, and in some lines of development macro and monetary theorists, like many of their colleagues in micro theory, seem to consider relevance to be more or less irrelevant.

Science and the quest for truth

February 23, 2018 26 comments

from Lars Syll

28mptoothfairy_jpg_1771152eIn my view, scientific theories are not to be considered ‘true’ or ‘false.’ In constructing such a theory, we are not trying to get at the truth, or even to approximate to it: rather, we are trying to organize our thoughts and observations in a useful manner.

Robert Aumann

 

What a handy view of science.

How reassuring for all of you who have always thought that believing in the tooth fairy make you understand what happens to kids’ teeth. Now a ‘Nobel prize’ winning economist tells you that if there are such things as tooth fairies or not doesn’t really matter. Scientific theories are not about what is true or false, but whether ‘they enable us to organize and understand our observations’ …   Read more…

The future — something we know very little about

February 20, 2018 18 comments

from Lars Syll

All these pretty, polite techniques, made for a well-panelled Board Room and a nicely regulated market, are liable to collapse. At all times the vague panic fears and equally vague and unreasoned hopes are not really lulled, and lie but a little way below the surface.

check-your-assumptionsPerhaps the reader feels that this general, philosophical disquisition on the behavior of mankind is somewhat remote from the economic theory under discussion. But I think not. Tho this is how we behave in the marketplace, the theory we devise in the study of how we behave in the market place should not itself submit to market-place idols. I accuse the classical economic theory of being itself one of these pretty, polite techniques which tries to deal with the present by abstracting from the fact that we know very little about the future.

I dare say that a classical economist would readily admit this. But, even so, I think he has overlooked the precise nature of the difference which his abstraction makes between theory and practice, and the character of the fallacies into which he is likely to be led.

John Maynard Keynes

Economics education — teaching cohorts after cohorts of students useless theories

February 18, 2018 6 comments

from Lars Syll

Nowadays there is almost no place whatsoever in economics education for courses in the history of economic thought and economic methodology.

This is deeply worrying.

A science that doesn’t self-reflect and asks important methodological and science-theoretical questions about the own activity, is a science in dire straits.

How did we end up in this sad state?

Philip Mirowski gives the following answer:

philAfter a brief flirtation in the 1960s and 1970s, the grandees of the economics profession took it upon themselves to express openly their disdain and revulsion for the types of self-reflection practiced by ‘methodologists’ and historians of economics, and to go out of their way to prevent those so inclined from occupying any tenured foothold in reputable economics departments. It was perhaps no coincidence that history and philosophy were the areas where one found the greatest concentrations of skeptics concerning the shape and substance of the post-war American economic orthodoxy. High-ranking economics journals, such as the American Economic Review, the Quarterly Journal of Economics and the Journal of Political Economy, declared that they would cease publication of any articles whatsoever in the area, after a prior history of acceptance.

Once this policy was put in place, and then algorithmic journal rankings were used to deny hiring and promotion at the commanding heights of economics to those with methodological leanings. Consequently, the grey-beards summarily expelled both philosophy and history from the graduate economics curriculum; and then, they chased it out of the undergraduate curriculum as well. This latter exile was the bitterest, if only because many undergraduates often want to ask why the profession believes what it does, and hear others debate the answers, since their own allegiances are still in the process of being formed. The rationale tendered to repress this demand was that the students needed still more mathematics preparation, more statistics and more tutelage in ‘theory’, which meant in practice a boot camp regimen consisting of endless working of problem sets, problem sets and more problem sets, until the poor tyros were so dizzy they did not have the spunk left to interrogate the masses of journal articles they had struggled to absorb.

Read more…

The problem of extrapolation

February 17, 2018 43 comments

from Lars Syll

steelThere are two basic challenges that confront any account of extrapolation that seeks to resolve the shortcomings of simple induction. One challenge, which I call extrapolator’s circle, arises from the fact that extrapolation is worthwhile only when there are important limitations on what one can learn about the target by studying it directly. The challenge, then, is to explain how the suitability of the model as a basis for extrapolation can be established given only limited, partial information about the target … The second challenge is a direct consequence of the heterogeneity of populations studied in biology and social sciences. Because of this heterogeneity, it is inevitable there will be causally relevant differences between the model and the target population.

In economics — as a rule — we can’t experiment on the real-world target directly.  To experiment, economists therefore standardly construct ‘surrogate’ models and perform ‘experiments’ on them. To be of interest to us, these surrogate models have to be shown to be relevantly ‘similar’ to the real-world target, so that knowledge from the model can be exported to the real-world target. The fundamental problem highlighted by Steel is that this ‘bridging’ is deeply problematic​ — to show that what is true of the model is also true of the real-world target, we have to know what is true of the target, but to know what is true of the target we have to know that we have a good model  …   Read more…

The arrow of time in a non-ergodic world

February 16, 2018 8 comments

from Lars Syll

an end of certaintyFor the vast majority of scientists, thermodynamics had to be limited strictly to equilibrium. That was the opinion of J. Willard Gibbs, as well as of Gilbert N. Lewis. For them, irreversibility associated with unidirectional time was anathema …

I myself experienced this type of hostility in 1946 … After I had presented my own lecture on irreversible thermodynamics, the greatest expert in the field of thermodynamics made the following comment: ‘I am astonished that this young man is so interested in nonequilibrium physics. Irreversible processes are transient. Why not wait and study equilibrium as everyone else does?’ I was so amazed at this response that I did not have the presence of mind to answer: ‘But we are all transient. Is it not natural to be interested in our common human condition?’

Time is what prevents everything from happening at once. To simply assume that economic processes are ergodic and concentrate on ensemble averages — and hence in any relevant sense timeless — is not a sensible way for dealing with the kind of genuine uncertainty that permeates real-world economies.

Ergodicity and the all-important difference between time averages and ensemble averages are difficult concepts — so let me try to explain the meaning of these concepts by means of a couple of simple examples.

Read more…

The limits of probabilistic reasoning

February 13, 2018 9 comments

from Lars Syll

Probabilistic reasoning in science — especially Bayesianism — reduces questions of rationality to questions of internal consistency (coherence) of beliefs, but, even granted this questionable reductionism, it’s not self-evident that rational agents really have to be probabilistically consistent. There is no strong warrant for believing so. Rather, there is strong evidence for us encountering huge problems if we let probabilistic reasoning become the dominant method for doing research in social sciences on problems that involve risk and uncertainty.

probIn many of the situations that are relevant to economics, one could argue that there is simply not enough of adequate and relevant information to ground beliefs of a probabilistic kind and that in those situations it is not possible, in any relevant way, to represent an individual’s beliefs in a single probability measure.

Say you have come to learn (based on own experience and tons of data) that the probability of you becoming unemployed in Sweden is 10%. Having moved to another country (where you have no own experience and no data) you have no information on unemployment and a fortiori nothing to help you construct any probability estimate on. A Bayesian would, however, argue that you would have to assign probabilities to the mutually exclusive alternative outcomes and that these have to add up to 1 if you are rational. That is, in this case – and based on symmetry – a rational individual would have to assign probability 10% to become unemployed and 90% to become employed.  Read more…

New Classical macroeconomists — people having their heads fuddled with nonsense

February 11, 2018 13 comments

from Lars Syll

McNees documented the radical break between the 1960s and 1970s. The question is: what are the possible responses that economists and economics can make to those events?

robert_solow4One possible response is that of Professors Lucas and Sargent. They describe what happened in the 1970s in a very strong way with a polemical vocabulary reminiscent of Spiro Agnew. Let me quote some phrases that I culled from the paper: “wildly incorrect,” “fundamentally flawed,” “wreckage,” “failure,” “fatal,” “of no value,” “dire implications,” “failure on a grand scale,” spectacular recent failure,” “no hope” … I think that Professors Lucas and Sargent really seem to be serious in what they say, and in turn they have a proposal for constructive research that I find hard to talk about sympathetically. They call it equilibrium business cycle theory, and they say very firmly that it is based on two terribly important postulates — optimizing behavior and perpetual market clearing. When you read closely, they seem to regard the postulate of optimizing behavior as self-evident and the postulate of market-clearing behavior as essentially meaningless. I think they are too optimistic, since the one that they think is self-evident I regard as meaningless and the one that they think is meaningless, I regard as false. The assumption that everyone optimizes implies only weak and uninteresting consistency conditions on their behavior. Anything useful has to come from knowing what they optimize, and what constraints they perceive. Lucas and Sargent’s casual assumptions have no special claim to attention …   Read more…

The flawed premises of mainstream​ economic theory

February 10, 2018 22 comments

from Lars Syll

Misbehaving.inddYou know, and I know, that we do not live in a world of Econs. We live in a world of Humans. And since most economists are also human, they also know that they do not live in a world of Econs …

Nevertheless, this model of economic behavior based on a population consisting only of Econs has flourished, raising economics to that pinnacle of influence on which it now rests. Critiques over the years have been brushed aside with a gauntlet of poor excuses and implausible alternative explanations of embarrassing empirical evidence …

It is time to stop making excuses. We need an enriched approach to doing economic research, one that acknowledges the existence and relevance of Humans. The good news is that we do not need to throw away everything we know about how economies and markets work. Theories based on the assumption that everyone is an Econ should not be discarded. They remain useful as starting points for more realistic models. And in some special circumstances, such as when the problems people have to solve are easy or when the actors in the economy have the relevant highly specialized skills, then models of Econs may provide a good approximation of what happens in the real world. But as we will see, those situations are the exception rather than the rule.

Economath — a device designed to fool the feebleminded

February 8, 2018 27 comments

from Lars Syll

Many American undergraduates in Economics interested in doing a Ph.D. are surprised to learn that the first year of an Econ Ph.D. feels much more like entering a Ph.D. in solving mathematical models by hand than it does with learning economics. Typically, there is very little reading or writing involved, but loads and loads of fast algebra is required. Why is it like this?

The first reason is that mathematical models are useful …

A second beneficial reason is signalling. This reason is not to be discounted given the paramount importance of signalling in all walks of life … Smart people do math. Even smarter people do even more complicated-looking math …

ecoA third reason to use math is that it is easy to use math to trick people. Often, if you make your assumptions in plain English, they will sound ridiculous. But if you couch them in terms of equations, integrals, and matrices, they will appear more sophisticated, and the unrealism of the assumptions may not be obvious, even to people with Ph.D.’s from places like Harvard and Stanford, or to editors at top theory journals such as Econometrica. A particularly informative example is the Malthusian model proposed by Acemoglu, Johnson, and Robinson in the 2001 version of their “Reversal of Fortune” paper …

What’s interesting about the Acemoglu et al. Malthusian model is that they take the same basic assumptions, assign a particular functional form to how population growth is influenced by income, and arrive at the conclusion that population density (which is proportional to technology) will be proportional to income …

The crucial assumption, unstated in words but there in greek letters for anyone to see, was that income affects the level of population, but not the growth rate in population. Stated differently, this assumption means that a handful of individuals could and would out-reproduce the whole of China and India combined if they had the same level of income … Obviously, this is quite a ridiculous assumption when stated in plain language. A population can grow by, at most, a few percent per year. 100 people can’t have 3 million offspring. What this model does successfully is reveal how cloaking an unrealistic assumption in terms of mathematics can make said assumption very hard to detect, even by tenured economics professors at places like MIT. Math in this case is used as little more than a literary device designed to fool the feebleminded …

Given that this paper then formed part of the basis of Acemoglu’s Clark medal, I think we can safely conclude that people are very susceptible to bullshit when written in equations …

Given the importance of signaling in all walks of life, and given the power of math, not just to illuminate and to signal, but also to trick, confuse, and bewilder, it thus makes perfect sense that roughly 99% of the core training in an economics Ph.D. is in fact in math rather than economics.

Douglas L. Campbell

Indeed.

No, there is nothing wrong with mathematics per seRead more…

Modern economics — confusing models with reality

February 3, 2018 30 comments

from Lars Syll

What does concern me about my discipline … is that its current core — by which I mainly mean the so-called dynamic stochastic general equilibrium approach — has become so mesmerized with its own internal logic that it has begun to confuse the precision it has achieved about its own world with the precision that it has about the real one …

While it often makes sense to assume rational expectations for a limited application to isolate a particular mechanism that is distinct from the role of expectations formation, this assumption no longer makes sense once we assemble the whole model. Agents could be fully rational with respect to their local environments and everyday activities, but they are most probably nearly clueless with respect to the statistics about which current macroeconomic models expect them to have full information and rational information.

bThis issue is not one that can be addressed by adding a parameter capturing a little bit more risk aversion about macro-economic, rather than local, phenomena. The reaction of human beings to the truly unknown is fundamentally different from the way they deal with the risks associated with a known situation and environment … In realistic, real-time settings, both economic agents and researchers have a very limited understanding of the mechanisms at work. This is an order-of-magnitude less knowledge than our core macroeconomic models currently assume, and hence it is highly likely that the optimal approximation paradigm is quite different from current workhorses, both for academic and policy​ work. In trying to add a degree of complexity to the current core models, by bringing in aspects of the periphery, we are simultaneously making the rationality assumptions behind that core approach less plausible …

The challenges are big, but macroeconomists can no longer continue playing internal games. The alternative of leaving all the important stuff to the “policy” type​ and informal commentators cannot be the right approach. I do not have the answer. But I suspect that whatever the solution ultimately is, we will accelerate our convergence to it, and reduce the damage we do along the transition, if we focus on reducing the extent of our pretense-of-knowledge syndrome.

Ricardo J. Caballero

A great article that also underlines — especially when it comes to forecasting and implementing economic policies  — that the future is inherently unknowable, and using statistics, econometrics, decision theory or game theory, does not in the least overcome this ontological fact.

Read more…

It’s high time to bury Milton Friedman’s natural rate hypotheis

February 1, 2018 4 comments

from Lars Syll

Fifty years ago Milton Friedman wrote an (in)famous article arguing that (1) the natural rate of unemployment was independent of monetary policy and that (2) trying to keep the unemployment rate below the natural rate would only give rise to higher and higher inflation.

The hypothesis has always been controversial, and much theoretical and empirical work has questioned the real-world relevance of the ideas that unemployment really is independent of monetary policy and that there is no long-run trade-off between inflation and unemployment.

In the latest issue of Journal of Economic Perspectives there are three articles — by Greg Mankiw/Ricardo Reis, Robert Hall/Tom Sargent, and Olivier Blanchard — on Friedman’s natural rate hypothesis.

The first two articles are of the nowadays common Chicago-New Keynesian mumbo jumbo ilk and will not be further commented on here.

Although Blanchard has his doubts — after having played around with a ‘toy model’ and looked at the data — he lands on the following advice:  Read more…