LARS P. SYLL

Disconfirming rational expectations

Empirical efforts at testing the correctness of the rational expectations hypothesis have resulted in a series of empirical studies that have more or less concluded that it is not consistent with the facts. In one of the more well-known and highly respected evaluation reviews made, Michael Lovell (1986) concluded:

it seems to me that the weight of empirical evidence is sufficiently strong to compel us to suspend belief in the hypothesis of rational expectations, pending the accumulation of additional empirical evidence.

And this is how Nikolay Gertchev summarizes studies on the empirical correctness of the hypothesis:

More recently, it even has been argued that the very conclusions of dynamic models assuming rational expectations are contrary to reality … If taken as an empirical behavioral assumption, the RE hypothesis is plainly false; if considered only as a theoretical tool, it is unfounded and selfcontradictory.

Those who want to build macroeconomics on microfoundations usually maintain that the only robust policies and institutions are those based on rational expectations and representative actors. As I have tried to show elsewhere — in On the use and misuse of theories and models in economics and Rational expectations: a fallacious foundation for macroeconomics in a non-ergodic world — there is really no support for this conviction at all. On the contrary. If we want to have anything of interest to say on real economies, financial crises and the decisions and choices real people make, it is high time to dump macroeconomic models building on representative actors and rational expectations microfoundations in the pseudo-science dustbin.

Wynne Godley on what it means for a nation not to have its own currency

If a government stops having its own currency, it doesn’t just give up “control over monetary policy” as normally understood; its spending powers also become constrained in an entirely new way. If a government does not have its own central bank on which it can draw cheques freely, its expenditures can be financed only by borrowing in the open market in competition with businesses, and this may prove excessively expensive or even impossible, particularly under “conditions of extreme emergency.”

If Europe is not to have a full-scale budget of its own under the new arrangements it will still have, by default, a fiscal stance of its own made up of the individual budgets of component states. The danger, then, is that the budgetary restraint to which governments are individually committed will impart a disinflationary bias that locks Europe as a whole into a depression it is powerless to lift.

Wynne Godley

Wynne Godley — the man who saw through the euro

If there were an economic and monetary union, in which the power to act independently had actually been abolished, ‘co-ordinated’ reflation of the kind which is so urgently needed now could only be undertaken by a federal European government. Without such an institution, EMU would prevent effective action by individual countries and put nothing in its place …

What happens if a whole country – a potential ‘region’ in a fully integrated community – suffers a structural setback? So long as it is a sovereign state, it can devalue its currency. It can then trade successfully at full employment provided its people accept the necessary cut in their real incomes. With an economic and monetary union, this recourse is obviously barred, and its prospect is grave indeed unless federal budgeting arrangements are made which fulfil a redistributive role … If a country or region has no power to devalue, and if it is not the beneficiary of a system of fiscal equalisation, then there is nothing to stop it suffering a process of cumulative and terminal decline leading, in the end, to emigration as the only alternative to poverty or starvation … What I find totally baffling is the position of those who are aiming for economic and monetary union without the creation of new political institutions (apart from a new central bank), and who raise their hands in horror at the words ‘federal’ or ‘federalism’. This is the position currently adopted by the Government and by most of those who take part in the public discussion.

Wynne Godley

The euro crisis is far from over. The tough austerity measures imposed in the eurozone has made economy after economy contract. And it has not only made things worse in the periphery countries, but also in countries like France and Germany. Alarming facts that should be taken seriously.

Europe may face a future with growing economic disparities where we will have​ to confront increasing hostility between nations and peoples. What we’ve seen lately in France shows that the protests against technocratic attempts to undermine democracy may go extremely violent.

The problems — created to a large extent by the euro — may not only endanger our economies, but also our democracy itself. How much whipping can democracy take? How many more are going to get seriously hurt and ruined before we end this madness and scrap the euro?

Your model is internally consistent? So what!

‘New Keynesian’ macroeconomist Simon Wren-Lewis has a post on his blog discussing how evidence is treated in modern macroeconomics (emphasis added):

The unique property that DSGE models have is internal consistency. Take a DSGE model, and alter a few equations so that they fit the data much better, and you have what could be called a structural econometric model. It is internally inconsistent, but because it fits the data better it may be a better guide for policy.

Being able to model a credible world, a world that somehow could be considered real or similar to the real world is not the same as investigating the real world. Even though all theories are false, since they simplify, they may still possibly serve our pursuit of truth. But then they cannot be unrealistic or false in any way. The falsehood or unrealisticness has to be qualified (in terms of resemblance, relevance, etc.). At the very least, the minimalist demand on models in terms of credibility has to give away to a stronger epistemic demand of appropriate similarity and plausibility. One could of course also ask for a sensitivity or robustness analysis, but the credible world, even after having tested it for sensitivity and robustness, can still be far away from reality – and unfortunately often in ways we know are important. Robustness of claims in a model does not per se give a warrant for exporting the claims to real world target systems.

Yours truly and people like Tony Lawson have for many years been urging economists to pay attention to the ontological foundations of their assumptions and models. Sad to say, economists have not paid much attention — and so modern economics has become increasingly irrelevant to the understanding of the real world.

Within mainstream economics, internal validity is still everything and external validity nothing. Why anyone should be interested in that kind of theories and models is beyond imagination. As long as mainstream economists do not come up with any export-licenses for their theories and models to the real world in which we live, they really should not be surprised if people say that this is not science, but autism!

To have valid evidence is not enough. Aiming only for validity is setting the economics aspirations level too low for developing a realist and relevant science.

DSGE — models built on shaky ground

In most aspects of their lives humans must plan forwards. They take decisions today that affect their future in complex interactions with the decisions of others. When taking such decisions, the available information is only ever a subset of the universe of past and present information, as no individual or group of individuals can be aware of all the relevant information. Hence, views or expectations about the future, relevant for their decisions, use a partial information set, formally expressed as a conditional expectation given the available information.

Moreover, all such views are predicated on there being no un-anticipated future changes in the environment pertinent to the decision. This is formally captured in the concept of ‘stationarity’. Without stationarity, good outcomes based on conditional expectations could not be achieved consistently. Fortunately, there are periods of stability when insights into the way that past events unfolded can assist in planning for the future.

The world, however, is far from completely stationary. Unanticipated events occur, and they cannot be dealt with using standard data-transformation techniques such as differencing, or by taking linear combinations, or ratios. In particular, ‘extrinsic unpredictability’ – unpredicted shifts of the distributions of economic variables at unanticipated times – is common. As we shall illustrate, extrinsic unpredictability has dramatic consequences for the standard macroeconomic forecasting models used by governments around the world – models known as ‘dynamic stochastic general equilibrium’ models – or DSGE models …

Many of the theoretical equations in DSGE models take a form in which a variable today, say incomes (denoted as yt) depends inter alia on its ‘expected future value’… For example, yt may be the log-difference between a de-trended level and its steady-state value. Implicitly, such a formulation assumes some form of stationarity is achieved by de-trending.

Unfortunately, in most economies, the underlying distributions can shift unexpectedly. This vitiates any assumption of stationarity. The consequences for DSGEs are profound. As we explain below, the mathematical basis of a DSGE model fails when distributions shift … This would be like a fire station automatically burning down at every outbreak of a fire. Economic agents are affected by, and notice such shifts. They consequently change their plans, and perhaps the way they form their expectations. When they do so, they violate the key assumptions on which DSGEs are built.

David Hendry & Grayham Mizon

A great article, not only showing on what shaky mathematical basis DSGE models are built but also confirming much of Keynes’s critique of econometrics, underlining that to understand real-world ‘non-routine’ decisions and unforeseeable changes in behaviour, stationary 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.

Advocates of DSGE modelling want to have deductively automated answers to fundamental causal questions. But to apply ‘thin’ methods we have to have ‘thick’ background knowledge of what’s going on in the real world, and not in idealized models. Conclusions can only be as certain as their premises — and that also applies to the quest for causality and forecasting predictability in DSGE models.

Economic crises and uncertainty

The financial crisis of 2007-08 hit most laymen and economists with surprise. What was it that went wrong with our macroeconomic models, since they obviously did not foresee the collapse or even make it conceivable?

There are many who have ventured to answer this question. And they have come up with a variety of answers, ranging from the exaggerated mathematization of economics to irrational and corrupt politicians.

But the root of our problem goes much deeper. It ultimately goes back to how we look upon the data we are handling. In ‘modern’ macroeconomics — Dynamic Stochastic General Equilibrium, New Synthesis, New Classical and New ‘Keynesian’ — variables are treated as if drawn from a known ‘data-generating process’ that unfolds over time and on which we, therefore, have access to heaps of historical time-series. If we do not assume that we know the ‘data-generating process’ – if we do not have the ‘true’ model – the whole edifice collapses. And of course, it has to. I mean, who really honestly believes that we should have access to this mythical Holy Grail, the data-generating process?

‘Modern’ macroeconomics obviously did not anticipate the enormity of the problems that unregulated ‘efficient’ financial markets created. Why? Because it builds on the myth of us knowing the ‘data-generating process’ and that we can describe the variables of our evolving economies as drawn from an urn containing stochastic probability functions with known means and variances.

This is like saying that you are going on a holiday-trip and that you know that the chance the weather being sunny is at least 30% and that this is enough for you to decide on bringing along your sunglasses or not. You are supposed to be able to calculate the expected utility based on the given probability of sunny weather and make a simple decision of either-or. Uncertainty is reduced to risk.

But as Keynes convincingly argued in his monumental Treatise on Probability (1921), this is not always possible. Often we simply do not know. According to one model the chance of sunny weather is perhaps somewhere around 10% and according to another – equally good – model the chance is perhaps somewhere around 40%. We cannot put exact numbers on these assessments. We cannot calculate means and variances. There are no given probability distributions that we can appeal to.

In the end, this is what it all boils down to. We all know that many activities, relations, processes and events are of the Keynesian uncertainty-type. The data do not unequivocally single out one decision as the only “rational” one. Neither the economist nor the deciding individual can fully pre-specify how people will decide when facing uncertainties and ambiguities that are ontological facts of the way the world works.

Some macroeconomists, however, still want to be able to use their hammer. So they decide to pretend that the world looks like a nail, and pretend that uncertainty can be reduced to risk. So they construct their mathematical models on that assumption. The result: financial crises and economic havoc.

How much better – how much bigger chance that we do not lull us into the comforting thought that we know everything and that everything is measurable and we have everything under control – if instead, we could just admit that we often simply do not know and that we have to live with that uncertainty as well as it goes.

Fooling people into believing that one can cope with an unknown economic future in a way similar to playing at the roulette wheels, is a sure recipe for only one thing – economic crisis!