LARS P. SYLL

Preferences that make economic models explode

Commenting on experiments — showing time-preferences-switching framing effects — performed by experimental economist David Eil, Noah Smith writes:

Now, here’s the thing…it gets worse … I’ve heard whispers that a number of researchers have done experiments in which choices can be re-framed in order to obtain the dreaded negative time preferences, where people actually care more about the future than the present! Negative time preferences would cause most of our economic models to explode, and if these preferences can be created with simple re-framing, then it bodes ill for the entire project of trying to model individuals’ choices over time.

This matters a lot for finance research. One of the big questions facing finance researchers is why asset prices bounce around so much. The two most common answers are A) time-varying risk premia, and B) behavioral “sentiment”. But Eil’s result, and other results like it, could be bad news for both efficient-market theory and behavioral finance. Because if aggregate preferences themselves are unstable due to a host of different framing effects, then time-varying risk premia can’t be modeled in any intelligible way, nor can behavioral sentiment be measured. In other words, the behavior of asset prices may truly be inexplicable (since we can’t observe all the multitude of things that might cause framing effects).

It’s a scary thought to contemplate, but to dismiss the results of experiments like Eil’s would be a mistake! It may turn out that the whole way modern economics models human behavior is good only in some situations, and not in others.

Bad news indeed. But hardly new.

In neoclassical theory preferences are standardly expressed in the form of a utility function. But although the expected utility theory has been known for a long time to be both theoretically and descriptively inadequate, neoclassical economists all over the world gladly continue to use it, as though its deficiencies were unknown or unheard of.

What most of them try to do in face of the obvious theoretical and behavioural inadequacies of the expected utility theory, is to marginally mend it. But that cannot be the right attitude when facing scientific anomalies. When models are plainly wrong, you’d better replace them! As Matthew Rabin and Richard Thaler have it in Risk Aversion:

It is time for economists to recognize that expected utility is an ex-hypothesis, so that we can concentrate our energies on the important task of developing better descriptive models of choice under uncertainty.

In his modern classic Risk Aversion and Expected-Utility Theory: A Calibration Theorem Matthew Rabin  writes:

Using expected-utility theory, economists model risk aversion as arising solely because the utility function over wealth is concave. This diminishing-marginal-utility-of-wealth theory of risk aversion is psychologically intuitive, and surely helps explain some of our aversion to large-scale risk: We dislike vast uncertainty in lifetime wealth because a dollar that helps us avoid poverty is more valuable than a dollar that helps us become very rich.

Yet this theory also implies that people are approximately risk neutral when stakes are small … While most economists understand this formal limit result, fewer appreciate that the approximate risk-neutrality prediction holds not just for negligible stakes, but for quite sizable and economically important stakes. Economists often invoke expected-utility theory to explain substantial (observed or posited) risk aversion over stakes where the theory actually predicts virtual risk neutrality.While not broadly appreciated, the inability of expected-utility theory to provide a plausible account of risk aversion over modest stakes has become oral tradition among some subsets of researchers, and has been illustrated in writing in a variety of different contexts using standard utility functions …

Expected-utility theory is manifestly not close to the right explanation of risk attitudes over modest stakes. Moreover, when the specific structure of expected-utility theory is used to analyze situations involving modest stakes — such as in research that assumes that large-stake and modest-stake risk attitudes derive from the same utility-for-wealth function — it can be very misleading.

In a similar vein, Daniel Kahneman writes — in Thinking, Fast and Slow — that expected utility theory is seriously flawed since it doesn’t take into consideration the basic fact that people’s choices are influenced by changes in their wealth. Where standard microeconomic theory assumes that preferences are stable over time, Kahneman and other behavioural economists have forcefully again and again shown that preferences aren’t fixed, but vary with different reference points. How can a theory that doesn’t allow for people having different reference points from which they consider their options have an almost axiomatic status within economic theory?

The mystery is how a conception of the utility of outcomes that is vulnerable to such obvious counterexamples survived for so long. I can explain it only by a weakness of the scholarly mind … I call it theory-induced blindness: once you have accepted a theory and used it as a tool in your thinking it is extraordinarily difficult to notice its flaws … You give the theory the benefit of the doubt, trusting the community of experts who have accepted it … But they did not pursue the idea to the point of saying, “This theory is seriously wrong because it ignores the fact that utility depends on the history of one’s wealth, not only present wealth.”

The works of people like Rabin, Thaler and Kahneman, show that expected utility theory is indeed transmogrifying truth. It’s an “ex-hypthesis”  — or as Monty Python has it:

This parrot is no more! He has ceased to be! ‘E’s expired and gone to meet ‘is maker! ‘E’s a stiff! Bereft of life, ‘e rests in peace! If you hadn’t nailed ‘im to the perch ‘e’d be pushing up the daisies! ‘Is metabolic processes are now ‘istory! ‘E’s off the twig! ‘E’s kicked the bucket, ‘e’s shuffled off ‘is mortal coil, run down the curtain and joined the bleedin’ choir invisible!! THIS IS AN EX-PARROT!!

Is calibration really a scientific advance? I’ll be dipped!

Noah Smith had a post up yesterday lamenting Nobel laureate Ed Prescott:

The 2004 prize went partly to Ed Prescott, the inventor of Real Business Cycle theory. That theory assumes that monetary policy doesn’t have an effect on GDP. Since RBC theory came out in 1982, a number of different people have added “frictions” to the model to make it so that monetary policy does have real effects. But Prescott has stayed true to the absolutist view that no such effects exist. In an email to a New York Times reporter, he very recently wrote the following:

“It is an established scientific fact that monetary policy has had virtually no effect on output and employment in the U.S. since the formation of the Fed,” Professor Prescott, also on the faculty of Arizona State University, wrote in an email. Bond buying [by the Fed], he wrote, “is as effective in bringing prosperity as rain dancing is in bringing rain.”

Wow! Prescott definitely falls into the category of people whom Miles Kimball and I referred to as “purist” Freshwater macroeconomists. Prescott has made some…odd…claims in recent years, but these recent remarks were totally consistent with his prize-winning research.

Odd claims indeed. True. There are many kinds of useless economics held in high regard within mainstream economics establishment today. Few – if any – are less deserved than the macroeconomic theory/method — mostly connected with Nobel laureates Finn Kydland, Robert Lucas, Edward Prescott and Thomas Sargent — called calibration.

Interviewed by Seppo Honkapohja and Lee Evans — in  Macroeconomic Dynamics (2005, vol. 9) — Thomas Sargent answered the question if calibration was an advance in macroeconomics:

In many ways, yes … The unstated case for calibration was that it was a way to continue the process of acquiring experience in matching rational expectations models to data by lowering our standards relative to maximum likelihood, and emphasizing those features of the data that our models could capture. Instead of trumpeting their failures in terms of dismal likelihood ratio statistics, celebrate the features that they could capture and focus attention on the next unexplained feature that ought to be explained. One can argue that this was a sensible response… a sequential plan of attack: let’s first devote resources to learning how to create a range of compelling equilibrium models to incorporate interesting mechanisms. We’ll be careful about the estimation in later years when we have mastered the modelling technology…

But is the Lucas-Kydland-Prescott-Sargent calibration really an advance?

Let’s see what two eminent econometricians have to say. In Journal of Economic Perspective (1996, vol. 10) Lars Peter Hansen and James J. Hickman writes:

It is only under very special circumstances that a micro parameter such as the inter-temporal elasticity of substitution or even a marginal propensity to consume out of income can be ‘plugged into’ a representative consumer model to produce an empirically concordant aggregate model … What credibility should we attach to numbers produced from their ‘computational experiments’, and why should we use their ‘calibrated models’ as a basis for serious quantitative policy evaluation? … There is no filing cabinet full of robust micro estimats ready to use in calibrating dynamic stochastic equilibrium models … The justification for what is called ‘calibration’ is vague and confusing.

Error-probabilistic statistician Aris Spanos — in  Error and Inference (Mayo & Spanos, 2010, p. 240) — is no less critical:

Given that “calibration” purposefully foresakes error probabilities and provides no way to assess the reliability of inference, how does one assess the adequacy of the calibrated model? …

The idea that it should suffice that a theory “is not obscenely at variance with the data” (Sargent, 1976, p. 233) is to disregard the work that statistical inference can perform in favor of some discretional subjective appraisal … it hardly recommends itself as an empirical methodology that lives up to the standards of scientific objectivity

And this is the verdict of Paul Krugman :

The point is that if you have a conceptual model of some aspect of the world, which you know is at best an approximation, it’s OK to see what that model would say if you tried to make it numerically realistic in some dimensions.

But doing this gives you very little help in deciding whether you are more or less on the right analytical track. I was going to say no help, but it is true that a calibration exercise is informative when it fails: if there’s no way to squeeze the relevant data into your model, or the calibrated model makes predictions that you know on other grounds are ludicrous, something was gained. But no way is calibration a substitute for actual econometrics that tests your view about how the world works.

In physics it may possibly not be straining credulity too much to model processes as ergodic – where time and history do not really matter – but in social and historical sciences it is obviously ridiculous. If societies and economies were ergodic worlds, why do econometricians fervently discuss things such as structural breaks and regime shifts? That they do is an indication of the unrealisticness of treating open systems as analyzable with ergodic concepts.

The future is not reducible to a known set of prospects. It is not like sitting at the roulette table and calculating what the future outcomes of spinning the wheel will be. Reading Sargent and other calibrationists one comes to think of Robert Clower’s apt remark that

much economics is so far removed from anything that remotely resembles the real world that it’s often difficult for economists to take their own subject seriously.

Instead of assuming calibration and rational expectations to be right, one ought to confront the hypothesis with the available evidence. It is not enough to construct models. Anyone can construct models. To be seriously interesting, models have to come with an aim. They have to have an intended use. If the intention of calibration and rational expectations  is to help us explain real economies, it has to be evaluated from that perspective. A model or hypothesis without a specific applicability is not really deserving our interest.

To say, as Edward Prescott that

one can only test if some theory, whether it incorporates rational expectations or, for that matter, irrational expectations, is or is not consistent with observations

is not enough. Without strong evidence all kinds of absurd claims and nonsense may pretend to be science. We have to demand more of a justification than this rather watered-down version of “anything goes” when it comes to rationality postulates. If one proposes rational expectations one also has to support its underlying assumptions. None is given, which makes it rather puzzling how rational expectations has become the standard modeling assumption made in much of modern macroeconomics. Perhaps the reason is, as Paul Krugman has it, that economists often mistake

beauty, clad in impressive looking mathematics, for truth.

But I think Prescott’s view is also the reason why calibration economists are not particularly interested in empirical examinations of how real choices and decisions are made in real economies. In the hands of Lucas, Prescott and Sargent, rational expectations has been transformed from an – in principle – testable hypothesis to an irrefutable proposition. Irrefutable propositions may be comfortable – like religious convictions or ideological dogmas – but it is not  science.

Or as Noah Smith puts it:

But OK, suppose for a moment – just imagine – that somewhere, on some other planet, there was a group of alien macroeconomists who made a bunch of theories that were completely wrong, and were not even close to anything that could actually describe the business cycles on that planet. And suppose that the hypothetical aliens kept comparing their nonsense theories to data, and they kept getting rejected by the data, but the aliens still found the nonsense theories very cool and very a prioriconvincing, and they kept at it, finding “puzzles”, estimating parameter values, making slightly different nonsense models, etc., in a neverending cycle of brilliant non-discovery.

Now tell me: In principle, how should those aliens tell the difference between their situation, and our own? That’s the question that I think we need to be asking, and that a number of people on the “periphery” of macro are now asking out loud.

The failure of DSGE macroeconomics

As 2014 begins, it’s clear enough that any theory in which mass unemployment or (in the US case) withdrawal from the labour force can only occur in the short run is inconsistent with the evidence. Given that unions are weaker than they have been for a century or so, and that severe cuts to social welfare benefits have been imposed in most countries, the traditional rightwing explanation that labour market inflexibility [arising from minimum wage laws or unions], is the cause of unemployment, appeals only to ideologues (who are, unfortunately, plentiful) …

After the Global Financial Crisis, it became clear that the concessions made by the New Keynesians were ill-advised in both theoretical and political terms. In theoretical terms, the DSGE models developed during the spurious “Great Moderation” were entirely inconsistent with the experience of the New Depression. The problem was not just a failure of prediction: the models simply did not allow for depressions that permanently shift the economy from its previous long term growth path. In political terms, it turned out that the seeming convergence with the New Classical school was an illusion. Faced with the need to respond to the New Depression, most of the New Classical school retreated to pre-Keynesian positions based on versions of Say’s Law (supply creates its own demand) that Say himself would have rejected, and advocated austerity policies in the face of overwhelming evidence that they were not working …

Relative to DSGE, the key point is that there is no unique long-run equilibrium growth path, determined by technology and preferences, to which the economy is bound to return. In particular, the loss of productive capacity, skills and so on in the current depression is, for all practical purposes, permanent. But if there is no exogenously determined (though maybe still stochastic) growth path for the economy, economic agents (workers and firms) can’t make the kind of long-term plans required of them in standard life-cycle models. They have to rely on heuristics and rules of thumb … This is, in my view, the most important point made by post-Keynesians and ignored by Old Old Keynesians.

John Quiggin/Crooked Timber

Why Wall Street shorts economists and their DSGE models

Blogger Noah Smith recently did an informal survey to find out if financial firms actually use the “dynamic stochastic general equilibrium” models that encapsulate the dominant thinking about how the economy works. The result? Some do pay a little attention, because they want to predict the actions of central banks that use the models. In their investing, however, very few Wall Street firms find the DSGE models useful …

This should come as no surprise to anyone who has looked closely at the models. Can an economy of hundreds of millions of individuals and tens of thousands of different firms be distilled into just one household and one firm, which rationally optimize their risk-adjusted discounted expected returns over an infinite future? There is no empirical support for the idea. Indeed, research suggests that the models perform very poorly …

Why does the profession want so desperately to hang on to the models? I see two possibilities. Maybe they do capture some deep understanding about how the economy works … More likely, economists find the models useful not in explaining reality, but in telling nice stories that fit with established traditions and fulfill the crucial goal of getting their work published in leading academic journals …

Knowledge really is power. I know of at least one financial firm in London that has a team of meteorologists running a bank of supercomputers to gain a small edge over others in identifying emerging weather patterns. Their models help them make good profits in the commodities markets. If economists’ DSGE models offered any insight into how economies work, they would be used in the same way. That they are not speaks volumes.

Mark Buchanan/Bloomberg

[h/t Jan Milch]

Splendid article!

The unsellability of DSGE — private-sector firms do not pay lots of money to use DSGE models — is a strong argument against DSGE. But it is not the most damning critique of it.

In the basic DSGE models the labour market is always cleared – responding to a changing interest rate, expected life time incomes, or real wages, the representative agent maximizes the utility function by varying her labour supply, money holding and consumption over time. Most importantly – if the real wage somehow deviates from its “equilibrium value,” the representative agent adjust her labour supply, so that when the real wage is higher than its “equilibrium value,” labour supply is increased, and when the real wage is below its “equilibrium value,” labour supply is decreased.

In this model world, unemployment is always an optimal choice to changes in the labour market conditions. Hence, unemployment is totally voluntary. To be unemployed is something one optimally chooses to be.

Although this picture of unemployment as a kind of self-chosen optimality, strikes most people as utterly ridiculous, there are also, unfortunately, a lot of neoclassical economists out there who still think that price and wage rigidities are the prime movers behind unemployment. DSGE models basically explains variations in employment (and a fortiori output) with assuming nominal wages being more flexible than prices – disregarding the lack of empirical evidence for this rather counterintuitive assumption.

Lowering nominal wages would not  clear the labour market. Lowering wages – and possibly prices – could, perhaps, lower interest rates and increase investment. It would be much easier to achieve that effect by increasing the money supply. In any case, wage reductions was not seen as a general substitute for an expansionary monetary or fiscal policy. And even if potentially positive impacts of lowering wages exist, there are also more heavily weighing negative impacts – management-union relations deteriorating, expectations of on-going lowering of wages causing delay of investments, debt deflation et cetera.

The classical proposition that lowering wages would lower unemployment and ultimately take economies out of depressions, was ill-founded and basically wrong. Flexible wages would probably only make things worse by leading to erratic price-fluctuations. The basic explanation for unemployment is insufficient aggregate demand, and that is mostly determined outside the labour market.

Obviously it’s rather embarrassing that the kind of DSGE models “modern” macroeconomists use cannot incorporate such a basic fact of reality as involuntary unemployment. Of course, working with representative agent models, this should come as no surprise. The kind of unemployment that occurs is voluntary, since it is only adjustments of the hours of work that these optimizing agents make to maximize their utility.

To me, this — the inability to explain involuntary unemployment — is the most damning critique of DSGE.

Added 23:00 GMT: Paul Davidson writes in a lovely comment on this article:

In explaining why Samuelson’s “old” neoclassical synthesis Keynesianism and New Keynesianism theories have nothing to do with Keynes’s General Theory of Employment, I have continually quoted Keynes [from page 257 of The General Theory] who wrote “For the Classical Theory has been accustomed to rest the supposedly self-adjusting character of the economic system on the assumed fluidity of money-wages; and when there is rigidity, to lay on this rigidity the blame for maladjustment … My difference from this theory is primarily a difference of analysis”. This is in a chapter entitled “Changes in Money Wages” where Keynes explain why changes in money wages can not guarantee full employment.

When in a published debate with Milton Friedman in the JPKE – later published as a book entitled MILTON FRIEDMAN’S MONETARY FRAMEWORK: A DEBATE WITH HIS CRITICS I pointed out this chapter of the General Theory to Milton his response was that Davidson refers to many chapters in the back of the General Theory that have some interesting and relevant comments – but are not part of Keynes’s theory, while fixity of wages and prices are essential to understanding Keynes.

In a verbal discussion with Paul Samuelson many years ago, I pointed out this chapter to Samuelson. His response was he found the General Theory “unpalatable” but liked the policy implications and therefore he [Samuelson] merely assumed the General Theory was a Walrasian system with fixity of wages and prices!

Neoklassiska fantasifoster

Någon ses piska en dammig matta med en stor pinne.

Av detta drar man slutsatsen att stora pinnar lämpar sig väl för att rengöra dammiga ting, som säg, fönster. De flesta skulle uppfatta slutsatsen som galen.

Varför?

Rimligen för att vi vet tillräckligt om hur pinnar och fönster är beskaffade, för att dels se problemet med den specifika rengöringstekniken, dels kunna laborera med alternativa möjligheter att uppnå målet: ett rent fönster.

Liknelsen ovan presenteras av den brittiska ekonomen Tony Lawson. Han fortsätter: Låt oss nu se framför oss en situation där pinne-rengör-fönster-modellen testas upprepade gånger, med produktion av glasbitar som följd. Vad om slutsatsen då blir att man måste ”försöka lite hårdare”.

Kanske har det varit fel fönster man har prövat med, kanske är man snart i mål. Anhängare av en sådan teori skulle onekligen kunna benämnas dogmatiker.

De skulle i varje fall inte få tjänstgöra som vaktmästare särskilt länge. Men detta är, konstaterar Lawson, dessvärre en fungerande analogi för tillståndet inom den samtida, ortodoxa nationalekonomin. Ja, utom detta med den sparkade vaktmästaren då.

Lawson skrev det här i mitten av 1990-talet. Sedan dess har ganska lite hänt. Det vill säga, när det gäller utgångspunkterna för den ekonomivetenskap som undervisas på universiteten, som dominerar den akademiska disciplinens kommandohöjder och som levererar premisser till politiska och administrativa beslut.

I verkligheten har ganska mycket hänt. Bland annat återkommande finans- och valutakriser runt om i världen, spekulativa ”innovationer” som bidrog till att blåsa upp bubblor som spruckit och skvätt ned hundratals miljoner människor, pågående ”krishanteringar” som puttar hela samhällen ned i långvarig fattigdom och stagnation.

Allt detta medan ledande ekonomer har skrivit ut recept byggda på fantasier om självkorrigerande marknader. Pinne möter fönster. Hela institutioner diskuterar swing-tekniker.

Ali Esbati/Magasinet Arena