LARS P. SYLL

Simon Wren-Lewis on rational expectations — so wrong, so wrong

Oxford professor Simon Wren-Lewis tries — again — to defend the rational expectations hypothesis:

To put it simply, the media help cause changes in public opinion, rather than simply reflect that opinion. Yet, if you have a certain caricature of what a modern macroeconomist believes in your head, this is a strange argument for one to make. That caricature is that we all believe in rational expectations, where agents use all readily available information in an efficient way to make decisions …

Some who read my posts will also know that I am a fan of rational expectations. I tend to get irritated with those (e.g. some heterodox economists) that pan the idea by talking about superhuman agents that know everything. To engage constructively with how to model expectations, you have to talk about practical alternatives. If we want something simple (and, in particular, if we do not want to complicate by borrowing from the extensive recent literature on learning), we often seem to have to choose between assuming rationality or something naive, like adaptive expectations. I have argued that, for the kind of macroeconomic issues that I am interested in, rational expectations provides a more realistic starting point, although that should never stop us analysing the consequences of expectations errors.

It’s easy — and I think this also goes for those who are not “heterodox economists” — not to be exactly impressed by this kind of argumentation. If Wren-Lewis and other macroeconomic modellers don’t “believe in rational expectations,” then why use such a preposterous assumption? The only “caricature” here, is the view of science that the advocates of rational expectations give.

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 yours truly tried to show in a paper in Real-World Economics Review last year —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 crisis and the decisions and choices real people make, it is high time to place macroeconomic models building on representative actors and rational expectations-microfoundations where they belong – in the dustbin of history.

For if this microfounded macroeconomics has nothing to say about the real world and the economic problems out there, why should we care about it? The final court of appeal for macroeconomic models is the real world, and as long as no convincing justification is put forward for how the inferential bridging de facto is made, macroeconomic modelbuilding is little more than hand waving that give us rather little warrant for making inductive inferences from models to real world target systems. If substantive questions about the real world are being posed, it is the formalistic-mathematical representations utilized to analyze them that have to match reality, not the other way around.

“To engage constructively with how to model expectations, you have to talk about practical alternatives,” writes Wren-Lewis. And of course there are alternatives to neoclassical general equilibrium microfoundations. Behavioural economics and Roman Frydman and Michael Goldberg’s “imperfect knowledge” economics being two noteworthy examples that easily come to mind. In one of their recent books re rational expectations, Frydman and Goldberg write:

The belief in the scientific stature of fully predetermined models, and in the adequacy of the Rational Expectations Hypothesis to portray how rational individuals think about the future, extends well beyond asset markets. Some economists go as far as to argue that the logical consistency that obtains when this hypothesis is imposed in fully predetermined models is a precondition of the ability of economic analysis to portray rationality and truth.

For example, in a well-known article published in The New York Times Magazine in September 2009, Paul Krugman (2009, p. 36) argued that Chicago-school free-market theorists “mistook beauty . . . for truth.” One of the leading Chicago economists, John Cochrane (2009, p. 4), responded that “logical consistency and plausible foundations are indeed ‘beautiful’ but to me they are also basic preconditions for ‘truth.’” Of course, what Cochrane meant by plausible foundations were fully predetermined Rational Expectations models. But, given the fundamental flaws of fully predetermined models, focusing on their logical consistency or inconsistency, let alone that of the Rational Expectations Hypothesis itself, can hardly be considered relevant to a discussion of the basic preconditions for truth in economic analysis, whatever “truth” might mean.

There is an irony in the debate between Krugman and Cochrane. Although the New Keynesian and behavioral models, which Krugman favors, differ in terms of their specific assumptions, they are every bit as mechanical as those of the Chicago orthodoxy. Moreover, these approaches presume that the Rational Expectations Hypothesis provides the standard by which to define rationality and irrationality.

…

In fact, the Rational Expectations Hypothesis requires no assumptions about the intelligence of market participants whatsoever … Rather than imputing superhuman cognitive and computational abilities to individuals, the hypothesis presumes just the opposite: market participants forgo using whatever cognitive abilities they do have. The Rational Expectations Hypothesis supposes that individuals do not engage actively and creatively in revising the way they think about the future. Instead, they are presumed to adhere steadfastly to a single mechanical forecasting strategy at all times and in all circumstances. Thus, contrary to widespread belief, in the context of real-world markets, the Rational Expectations Hypothesis has no connection to how even minimally reasonable profit-seeking individuals forecast the future in real-world markets. When new relationships begin driving asset prices, they supposedly look the other way, and thus either abjure profit-seeking behavior altogether or forgo profit opportunities that are in plain sight.

Beyond Mechanical Markets

And in a more recent article the same authors write:

Contemporary economists’ reliance on mechanical rules to understand – and influence – economic outcomes extends to macroeconomic policy as well, and often draws on an authority, John Maynard Keynes, who would have rejected their approach. Keynes understood early on the fallacy of applying such mechanical rules. “We have involved ourselves in a colossal muddle,” he warned, “having blundered in the control of a delicate machine, the working of which we do not understand.”

In The General Theory of Employment, Interest, and Money, Keynes sought to provide the missing rationale for relying on expansionary fiscal policy to steer advanced capitalist economies out of the Great Depression. But, following World War II, his successors developed a much more ambitious agenda. Instead of pursuing measures to counter excessive fluctuations in economic activity, such as the deep contraction of the 1930’s, so-called stabilization policies focused on measures that aimed to maintain full employment. “New Keynesian” models underpinning these policies assumed that an economy’s “true” potential – and thus the so-called output gap that expansionary policy is supposed to fill to attain full employment – can be precisely measured.

But, to put it bluntly, the belief that an economist can fully specify in advance how aggregate outcomes – and thus the potential level of economic activity – unfold over time is bogus …

Roman Frydman & Michael Goldberg

The real macroeconomic challenge is to accept uncertainty and still try to explain why economic transactions take place – instead of simply conjuring the problem away by assuming rational expectations and treating uncertainty as if it was possible to reduce it to stochastic risk. That is scientific cheating. And it has been going on for too long now.