Steve Keen on "bad weathermen"

I've made quite a lot of the analogy between the dynamics of an economy or financial market and the weather. It's one of the basic themes of this blog, and the focus of my forthcoming book FORECAST. I don't pretend to be the first one to think of this at all. I know that the head of the Bank of England Mervyn King has talked about this analogy in the past, as have many others.

But the idea now seems to be gathering more popularity. Steve Keen even writes here specifically about the task of economic forecasting, and the entirely different approaches used on weather science, where forecasting is now quite successful, and in economics, where it is not:

Conventional economic modelling tools can extrapolate forward existing trends fairly well – if those trends continue. But they are as hopeless at forecasting a changing economic world as weather forecasts would be, if weather forecasters assumed that, because yesterday’s temperature was 29 degrees Celsius and today’s was 30, tomorrow’s will be 31 – and in a year it will be 395 degrees.

Of course, weather forecasters don’t do that. When the Bureau of Meteorology forecasts that the maximum temperature in Sydney on January 16 to January 19 will be respectively 29, 30, 35 and 25 degrees, it is reporting the results of a family of computer models that generate a forecast of future weather patterns that is, by and large, accurate over the time horizon the models attempt to predict – which is about a week.

Weather forecasts have also improved dramatically over the last 40 years – so much so that even an enormous event like Hurricane Sandy was predicted accurately almost a week in advance, which gave people plenty of time to prepare for the devastation when it arrived:

Almost five days prior to landfall, the National Hurricane Center pegged the prediction for Hurricane Sandy, correctly placing southern New Jersey near the centre of its track forecast. This long lead time was critical for preparation efforts from the Mid-Atlantic to the Northeast and no doubt saved lives.

Hurricane forecasting has come a long way in the last few decades. In 1970, the average error in track forecasts three days into the future was 518 miles. That error shrunk to 345 miles in 1990. From 2007-2011, it dropped to 138 miles. Yet for Sandy, it was a remarkably low 71 miles, according to preliminary numbers from the National Hurricane Center.

Within 48 hours, the forecast came into even sharper focus, with a forecast error of just 48 miles, compared to an average error of 96 miles over the last five years.

Meteorological model predictions are regularly attenuated by experienced meteorologists, who nudge numbers that experience tells them are probably wrong. But they start with a model of the weather than is fundamentally accurate, because it is founded on the proposition that the weather is unstable.

Conventional economic models, on the other hand, assume that the economy is stable, and will return to an 'equilibrium growth path' after it has been dislodged from it by some 'exogenous shock'. So most so-called predictions are instead just assumptions that the economy will converge back to its long-term growth average very rapidly (if your economist is a Freshwater type) or somewhat slowly (if he’s a Saltwater croc).

Weather forecasters used to be as bad as this, because they too used statistical models that assumed the weather was in or near equilibrium, and their forecasts were basically linearly extrapolations of current trends.

How did weather forecasters get better? By recognizing, of course, the inherent role of positive feed backs and instabilities in the atmosphere, and by developing methods to explore and follow the growth of such instabilities mathematically. That meant modelling in detail the actual  fine scale workings of the atmosphere and using computers to follow the interactions of those details. The same will almost certainly be true in economics. Forecasting will require both lots of data and also much more detailed models of the interactions among people, firms and financial institutions of all kinds, taking the real structure of networks into account, using real data to build models of behaviour and so on. All this means giving up tidy analytical solutions, of course, and even computer models that insist the economy must exist in a nice tidy equilibrium. Science begins by taking reality seriously.

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"Unemployment is an illusion and recessions are voluntary"

An illuminating speech by Paul Krugman:

... I assume that most of those hearing or reading this speech at all closely are aware of the great divide that emerged in macroeconomics in the 1970s. For those who aren’t familiar with the story: in the 1930s Keynesian economics emerged as a response to depression, and by the 1950s it had come to dominate the field. There was, however, an undercurrent of dissatisfaction with that style of modeling, not so much because it fell short empirically as because it seemed intellectually incomplete. In “normal” economics we assume that prices rise or fall to match supply with demand. In Keynesian macroeconomics, however, one simply assumes that wages and perhaps prices too don’t fall in the face of high unemployment, or at least fall only slowly.

Why make this assumption? Well, because it’s what we see in reality – as confirmed once again by the experience of peripheral European countries, Portugal included, where wage declines have so far been modest even in the face of very high unemployment. But that’s an unsatisfying answer, and it was only natural that economists would try to find some deeper explanation.

The trouble is that finding that deeper explanation is hard. Keynes offered some plausible speculations that were as much sociological and psychological as purely economic – which is not to say that there’s anything wrong with invoking such factors. Modern “New Keynesians” have come up with stories in terms of the cost of changing prices, the desire of many firms to attract quality workers by paying a premium, and more. But one has to admit that it’s all pretty ad hoc; it’s more a matter of offering excuses, or if you prefer, possible rationales, for an empirical observation that we probably wouldn’t have predicted if we didn’t know it was there.

This, understandably, wasn’t satisfying to many economists. So there developed an alternative school of thought, which basically argued that the apparent “stickiness” of wages and prices in the face of unemployment was an optical illusion. Initially the story ran in terms of imperfect information; later it became a story about “real” shocks, in which unemployment was actually voluntary; that was the real business cycle approach.

And so we got the division of macroeconomics. On one side there was “saltwater” economics – people, who in America tended to be in coastal universities, who continued to view Keynes as broadly right, even though they couldn’t offer a rigorous justification for some of their assumptions. On the other side was “freshwater” – people who tended to be in inland US universities, and who went for logically complete models even if they seemed very much at odds with lived experience.

Obviously I don’t believe any of the freshwater stories, and indeed find them wildly implausible. But economists will have different ideas, and it’s OK if some of them are ones I or others dislike.

What’s not OK is what actually happened, which is that freshwater economics became a kind of cult, ignoring and ridiculing any ideas that didn’t fit its paradigm. This started very early; by 1980 Robert Lucas, one of the founders of the school, wrote approvingly of how people would giggle and whisper when facing a Keynesian. What’s remarkable about that is that this was all based on the presumption that freshwater logic would provide a plausible, workable alternative to Keynes – a presumption that was not borne out by anything that had happened in the 1970s. And in fact it never happened: over time, freshwater economics kept failing the test of empirical validity, and responded by downgrading the importance of evidence.

Read the whole thing.

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Microfoundations -- fact and fiction

UPDATE AT THE END

I generally try not to write about things I know almost nothing about, but here goes. Take everything that follows here as a kind of "thinking out loud" -- a struggle to put into words my thoughts about some apparently odd ideas in macroeconomics. I say "apparently" because I don't know enough to be sure. Maybe they are all very sensible. I would greatly appreciate any further insight from anyone out there who knows.

The idea puzzling me is "microfoundations." As I understand it, the rational expectations revolution in macroeconomics, linked to the names Robert Lucas, Edward Prescott, Thomas Sargent and others, demanded that macroeconomic theories shouldn't just be built as coarse-grained effective theories operating at the macroscale and written in terms of macroscopic variables such as inflation, unemployment, etc. Rather, a good theory henceforth was to link macroeconomic outcomes back to the behaviour of the individual agents in an economy, i.e. to their microeconomics behaviour. Such as theory would have "microfoundations."

To my physicist mind, this seems entirely sensible, so far. A difficult project, no doubt but sensible. By analogy, of course, this just seems like the effort to derive thermodynamics (a macroscopic theory) from the underlying behaviours of individual particles, which is the project of statistical mechanics. Deriving theories at higher levels from behaviours at lower levels is, when possible, a natural scientific project -- it offers unification or, if it can't be carried through, points to problem areas from which new ideas are likely to come.

Now, I have also read that much of the impetus for the rational expectations movement was the famous Lucas Critique which, if I understand it correctly, says that you can't reliably base policy interventions on simple regularities observed in macroeconomic data (a historically observed tradeoff between unemployment and inflation, for example). That regularity existed, after all, in the context of the policies prevailing in the past. Change the policies and those changes, by influencing the way people act and anticipate the future, may well strongly change or destroy the regularity on which you had based your plans. Again, plausible and sensible, it seems to me.

So, I can see the attraction of theories with microfoundations -- theories, that is, giving a plausible account of how macroeconomic reality emerges out of the micro reality and actual behaviour of millions of people and firms in interaction.

Now my puzzlement. As far as can tell, the idea of "microfoundations" as actually used in macroeconomics isn't quite how I described it above, i.e. seeking to base macro theory on a plausible account of the behaviour of individuals. Rather, in economics (through the work of Lucas) it has come to mean theories in which individuals and firms are hyperrational optimizers of their utility over a span of time (they solve a complicated optimization problem over their lifetime). This no longer seems so plausible, and on this point, a commenter from Mark Thoma's blog captures my feelings on this quite clearly:

hrsaccount said...

Microfoundations would be important if there were clear evidence that they represented the truth. For example, if there had been a series of experiments demonstrating that individuals are rational and make decisions so as to maximize some measurable quantity called utility, it would be important that macro models were consistent with this and the most direct way of ensuring that would be to incorporate rational utility-maximizing households into the model.

The fact is that there is no such evidence. Microeconomics is not based on empirical evidence, and the approach used in microeconomics has no special claim to the truth. So, leaving aside the fact that the way macroeconomics uses micro (i.e., in a way that many microeconomists don't approve, ignoring aggregation issues) there's no logical reason why macro needs to even be consistent with micro.

His point seems to me very well put -- if "microfoundations" as currently interpreted don't give foundations to anything, then a theory having them has no advantage. Theories with microfoundations (as interpreted in this odd sense) have no more claim to relevance than anything else. Indeed, we might say they are even worse as they are almost certainly demonstrably inconsistent with real behaviour at the micro level.

Again, I'm not an expert on this. But I see this kind of argument breaking out over and over among economists. I often think I must have it wrong, so please if I do, someone let me know.

UPDATE

While writing the above, I happened to find and read a couple of things that clarified matters quite a bit for me. My take seems to be shared by economists as well, although I'm not sure the few things I read are representative. First, Maarten Janssen of the Tinbergen Institute published an excellent short review of the idea of microfoundations in 2008. He describes the history, but notes that key criticisms of the idea do center in the "plausibility" of the rational expectations approach. That is, including expectations in macromodels is sensible, but everything depends on how you include them:

The approaches discussed so far... all postulate rational behavior on the part of economic agents and some notion of equilibrium. If expectations are important, it is postulated that agents’ expectations concerning important variables coincide with the model’s predicted values concerning these same variables.

And he mentions several branches of research criticizing this view and testing it, in particular, testing whether in a decentralized economy economic agents may learn over time to have expectations that are consistent with those that are assumed by the rational expectations hypothesis:

The general conclusion of this literature is that due to the feedback from expectations to economic behavior, the outcomes of an economic model with learning agents do not converge to the rational expectations solution. It then follows that the microfoundations literature mentioned so far has not really succeeded in deriving all macroeconomic propositions from fundamental hypotheses on the behavior of individual agents. The requirements of methodological individualism have thus not been satisfied by the microfoundations literature that has pre-dominantly presumed that individuals behave rationally...

I cannot say I'm surprised. So we're left with theories that only go one short step toward the idea of microfoundations, and, in my view, can't claim they have given microfoundations to anything -- the use of the word in these models is totally unwarranted, and I think way overstates what they achieve.

I think much the same point of view is expressed by Michael Woodford, himself a big name in macro modelling. In a response to an essay by John Kay critical of modern macroeconomics and its unrealistic assumptions, Woodford in a roundabout way eventually says, well, yes, I agree:

 

It has been standard for at least the past three decades to use models in which not only does the model give a complete description of a hypothetical world, and not only is this description one in which outcomes follow from rational behavior on the part of the decision makers in the model, but the decision makers in the model are assumed to understand the world in exactly the way it is represented in the model. More precisely, in making predictions about the consequences of their actions (a necessary component of an accounting for their behavior in terms of rational choice), they are assumed to make exactly the predictions that the model implies are correct (conditional on the information available to them in their personal situation).

This postulate of “rational expectations,” as it is commonly though rather misleadingly known, is the crucial theoretical assumption behind such doctrines as “efficient markets” in asset pricing theory and “Ricardian equivalence” in macroeconomics. It is often presented as if it were a simple consequence of an aspiration to internal consistency in one’s model and/or explanation of people’s choices in terms of individual rationality, but in fact it is not a necessary implication of these methodological commitments. It does not follow from the fact that one believes in the validity of one’s own model and that one believes that people can be assumed to make rational choices that they must be assumed to make the choices that would be seen to be correct by someone who (like the economist) believes in the validity of the predictions of that model. Still less would it follow, if the economist herself accepts the necessity of entertaining the possibility of a variety of possible models, that the only models that she should consider are ones in each of which everyone in the economy is assumed to understand the correctness of that particular model, rather than entertaining beliefs that might (for example) be consistent with one of the other models in the set that she herself regards as possibly correct.

So I feel that my suspicions and objections aren't misplaced, despite my vast ignorance. One other excellent article I recommend is this one from 2011 in which Woodford details the history of modern macroeconomics over the past century. Nothing I've read has given such a complete and clearly explained exposition, while it seems being balanced along the way (or so it seems, to my physicist's eyes).

UPDATE

Ole Rogeberg kindly let pointed me to this post by economist Noah Smith who makes some of the same points -- but from the position of someone with far economics domain knowledge than myself.

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Learning in macroeconomics...

I've posted before on macroeconomic models that try to go beyond the "rational expectations" framework by assuming that the agents in an economy are different (they have heterogeneous expectations) and are also not necessarily rational. This approach seems wholly more realistic and believable to me.

In a recent comment, however, ivansml pointed me to this very interesting paper from 2009, which I've enjoyed reading. What the paper does is explore what happens in some of the common rational expectations models if you suppose that agents' expectations aren't formed rationally but rather on the basis of some learning algorithm. The paper shows that learning algorithms of a certain kind lead to the same equilibrium outcome as the rational expectations viewpoint. This IS interesting and seems very impressive. However, I'm not sure it's as interesting as it seems at first.

The reason is that the learning algorithm is indeed of a rather special kind. Most of the models studied in the paper, if I understand correctly, suppose that agents in the market already know the right mathematical form they should use to form expectations about prices in the future. All they lack is knowledge of the values of some parameters in the equation. This is a little like assuming that people who start out trying to learn the equations for, say, electricity and magnetism, already know the right form of Maxwell's equations, with all the right space and time derivatives, though they are ignorant of the correct coefficients. The paper shows that, given this assumption in which the form of the expectations equation is already known, agents soon evolve to the correct rational expectations solution. In this sense, rational expectations emerges from adaptive behaviour.

I don't find this very convincing as it makes the problem far too easy. More plausible, it seems to me, would be to assume that people start out with not much knowledge at all of how future prices will most likely be linked by inflation to current prices, make guesses with all kinds of crazy ideas, and learn by trial and error. Given the difficulty of this problem, and the lack even among economists themselves of great predictive success, this would seem more reasonable. However, it is also likely to lead to far more complexity in the economy itself, because a broader class of expectations will lead to a broader class of dynamics for future prices. In this sense, the models in this paper assume away any kind of complexity from a diversity of views.

To be fair to the authors of the paper, they do spell out their assumptions clearly. They state in fact that they assume that people in their economy form views on likely future prices in the same way modern econometricians do (i.e. using the very same mathematical models). So the gist seems to be that in a world in which all people think like economists and use the equations of modern econometrics to form their expectations, then, even if they start out with some of the coefficients "mis-specified," their ability to learn to use the right coefficients can drive the economy to a rational expectations equilibrium. Does this tell us much?

I'd be very interested in others' reactions to this. I do not claim to know much of anything about macroeconomics. Indeed, one of the nice things about this paper is its clear introduction to some of the standard models. This in itself is quite illuminating. I hadn't realized that the standard models are not any more complex than linear first-order time difference equations (if I have this right) with some terms including expectations. I had seen these equations before and always thought they must be toy models just meant to illustrate the far more complex and detailed models used in real calculations and located in some deep economic book I haven't yet seen, but now I'm not so sure.

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