Archive for the 'macroeconomics' Category

The Trouble with IS-LM (and its Successors)

Lately, I have been reading a paper by Roger Backhouse and David Laidler, “What Was Lost with IS-LM” (an earlier version is available here) which was part of a very interesting symposium of 11 papers on the IS-LM model published as a supplement to the 2004 volume of History of Political Economy. The main thesis of the paper is that the IS-LM model, like the General Theory of which it is a partial and imperfect distillation, aborted a number of promising developments in the rapidly developing, but still nascent, field of macroeconomics in the 1920 and 1930s, developments that just might, had they not been elbowed aside by the IS-LM model, have evolved into a more useful and relevant theory of macroeconomic fluctuations and policy than we now possess. Even though I have occasionally sparred with Scott Sumner about IS-LM – with me pushing back a bit at Scott’s attacks on IS-LM — I have a lot of sympathy for the Backhouse-Laidler thesis.

The Backhouse-Laidler paper is too long to summarize, but I will just note that there are four types of loss that they attribute to IS-LM, which are all, more or less, derivative of the static equilibrium character of Keynes’s analytic method in both the General Theory and the IS-LM construction.

1 The loss of dynamic analysis. IS-LM is a single-period model.

2 The loss of intertemporal choice and expectations. Intertemporal choice and expectations are excluded a priori in a single-period model.

3 The loss of policy regimes. In a single-period model, policy is a one-time affair. The problem of setting up a regime that leads to optimal results over time doesn’t arise.

4 The loss of intertemporal coordination failures. Another concept that is irrelevant in a one-period model.

There was one particular passage that I found especially impressive. Commenting on the lack of any systematic dynamic analysis in the GT, Backhouse and Laidler observe,

[A]lthough [Keynes] made many remarks that could be (and in some cases were later) turned into dynamic models, the emphasis of the General Theory was nevertheless on unemployment as an equilibrium phenomenon.

Dynamic accounts of how money wages might affect employment were only a little more integrated into Keynes’s formal analysis than they were later into IS-LM. Far more significant for the development in Keynes’s thought is how Keynes himself systematically neglected dynamic factors that had been discussed in previous explanations of unemployment. This was a feature of the General Theory remarked on by Bertil Ohlin (1937, 235-36):

Keynes’s theoretical system . . . is equally “old-fashioned” in the second respect which characterizes recent economic theory – namely, the attempt to break away from an explanation of economic events by means of orthodox equilibrium constructions. No other analysis of trade fluctuations in recent years – with the possible exception of the Mises-Hayek school – follows such conservative lines in this respect. In fact, Keynes is much more of an “equilibrium theorist” than such economists as Cassel and, I think, Marshall.

Backhouse and Laidler go on to cite the Stockholm School (of which Ohlin was a leading figure) as an example of explicitly dynamic analysis.

As Bjorn Hansson (1982) has shown, this group developed an explicit method, using the idea of a succession of “unit periods,” in which each period began with agents having plans based on newly formed expectations about the outcome of executing them, and ended with the economy in some new situation that was the outcome of executing them, and ended with the economy in some new situation that was the outcome of market processes set in motion by the incompatibility of those plans, and in which expectations had been reformulated, too, in the light of experience. They applied this method to the construction of a wide variety of what they called “model sequences,” many of which involved downward spirals in economic activity at whose very heart lay rising unemployment. This is not the place to discuss the vexed question of the extent to which some of this work anticipated the Keynesian multiplier process, but it should be noted that, in IS-LM, it is the limit to which such processes move, rather than the time path they follow to get there, that is emphasized.

The Stockholm method seems to me exactly the right way to explain business-cycle downturns. In normal times, there is a rough – certainly not perfect, but good enough — correspondence of expectations among agents. That correspondence of expectations implies that the individual plans contingent on those expectations will be more or less compatible with one another. Surprises happen; here and there people are disappointed and regret past decisions, but, on the whole, they are able to adjust as needed to muddle through. There is usually enough flexibility in a system to allow most people to adjust their plans in response to unforeseen circumstances, so that the disappointment of some expectations doesn’t become contagious, causing a systemic crisis.

But when there is some sort of major shock – and it can only be a shock if it is unforeseen – the system may not be able to adjust. Instead, the disappointment of expectations becomes contagious. If my customers aren’t able to sell their products, I may not be able to sell mine. Expectations are like networks. If there is a breakdown at some point in the network, the whole network may collapse or malfunction. Because expectations and plans fit together in interlocking networks, it is possible that even a disturbance at one point in the network can cascade over an increasingly wide group of agents, leading to something like a system-wide breakdown, a financial crisis or a depression.

But the “problem” with the Stockholm method was that it was open-ended. It could offer only “a wide variety” of “model sequences,” without specifying a determinate solution. It was just this gap in the Stockholm approach that Keynes was able to fill. He provided a determinate equilibrium, “the limit to which the Stockholm model sequences would move, rather than the time path they follow to get there.” A messy, but insightful, approach to explaining the phenomenon of downward spirals in economic activity coupled with rising unemployment was cast aside in favor of the neater, simpler approach of Keynes. No wonder Ohlin sounds annoyed in his comment, quoted by Backhouse and Laidler, about Keynes. Tractability trumped insight.

Unfortunately, that is still the case today. Open-ended models of the sort that the Stockholm School tried to develop still cannot compete with the RBC and DSGE models that have displaced IS-LM and now dominate modern macroeconomics. The basic idea that modern economies form networks, and that networks have properties that are not reducible to just the nodes forming them has yet to penetrate the trained intuition of modern macroeconomists. Otherwise, how would it have been possible to imagine that a macroeconomic model could consist of a single representative agent? And just because modern macroeconomists have expanded their models to include more than a single representative agent doesn’t mean that the intellectual gap evidenced by the introduction of representative-agent models into macroeconomic discourse has been closed.

Another Complaint about Modern Macroeconomics

In discussing modern macroeconomics, I’ve have often mentioned my discomfort with a narrow view of microfoundations, but I haven’t commented very much on another disturbing feature of modern macro: the requirement that theoretical models be spelled out fully in axiomatic form. The rhetoric of axiomatization has had sweeping success in economics, making axiomatization a pre-requisite for almost any theoretical paper to be taken seriously, and even considered for publication in a reputable economics journal.

The idea that a good scientific theory must be derived from a formal axiomatic system has little if any foundation in the methodology or history of science. Nevertheless, it has become almost an article of faith in modern economics. I am not aware, but would be interested to know, whether, and if so how widely, this misunderstanding has been propagated in other (purportedly) empirical disciplines. The requirement of the axiomatic method in economics betrays a kind of snobbishness and (I use this word advisedly, see below) pedantry, resulting, it seems, from a misunderstanding of good scientific practice.

Before discussing the situation in economics, I would note that axiomatization did not become a major issue for mathematicians until late in the nineteenth century (though demands – luckily ignored for the most part — for logical precision followed immediately upon the invention of the calculus by Newton and Leibniz) and led ultimately to the publication of the great work of Russell and Whitehead, Principia Mathematica whose goal was to show that all of mathematics could be derived from the axioms of pure logic. This is yet another example of an unsuccessful reductionist attempt, though it seemed for a while that the Principia paved the way for the desired reduction. But 20 years after the Principia was published, Kurt Godel proved his famous incompleteness theorem, showing that, as a matter of pure logic, not even all the valid propositions of arithmetic, much less all of mathematics, could be derived from any system of axioms. This doesn’t mean that trying to achieve a reduction of a higher-level discipline to another, deeper discipline is not a worthy objective, but it certainly does mean that one cannot just dismiss, out of hand, a discipline simply because all of its propositions are not deducible from some set of fundamental propositions. Insisting on reduction as a prerequisite for scientific legitimacy is not a scientific attitude; it is merely a form of obscurantism.

As far as I know, which admittedly is not all that far, the only empirical science which has been axiomatized to any significant extent is theoretical physics. In his famous list of 23 unsolved mathematical problems, the great mathematician David Hilbert included the following (number 6).

Mathematical Treatment of the Axioms of Physics. The investigations on the foundations of geometry suggest the problem: To treat in the same manner, by means of axioms, those physical sciences in which already today mathematics plays an important part, in the first rank are the theory of probabilities and mechanics.

As to the axioms of the theory of probabilities, it seems to me desirable that their logical investigation should be accompanied by a rigorous and satisfactory development of the method of mean values in mathematical physics, and in particular in the kinetic theory of gasses. . . . Boltzman’s work on the principles of mechanics suggests the problem of developing mathematically the limiting processes, there merely indicated, which lead from the atomistic view to the laws of motion of continua.

The point that I want to underscore here is that axiomatization was supposed to ensure that there was an adequate logical underpinning for theories (i.e., probability and the kinetic theory of gasses) that had already been largely worked out. Thus, Hilbert proposed axiomatization not as a method of scientific discovery, but as a method of checking for hidden errors and problems. Error checking is certainly important for science, but it is clearly subordinate to the creation and empirical testing of new and improved scientific theories.

The fetish for axiomitization in economics can largely be traced to Gerard Debreu’s great work, The Theory of Value: An Axiomatic Analysis of Economic Equilibrium, in which Debreu, building on his own work and that of Kenneth Arrow, presented a formal description of a decentralized competitive economy with both households and business firms, and proved that, under the standard assumptions of neoclassical theory (notably diminishing marginal rates of substitution in consumption and production and perfect competition) such an economy would have at least one, and possibly more than one, equilibrium.

A lot of effort subsequently went into gaining a better understanding of the necessary and sufficient conditions under which an equilibrium exists, and when that equilibrium would be unique and Pareto optimal. The subsequent work was then brilliantly summarized and extended in another great work, General Competitive Analysis by Arrow and Frank Hahn. Unfortunately, those two books, paragons of the axiomatic method, set a bad example for the future development of economic theory, which embarked on a needless and counterproductive quest for increasing logical rigor instead of empirical relevance.

A few months ago, I wrote a review of Kartik Athreya’s book Big Ideas in Macroeconomics. One of the arguments of Athreya’s book that I didn’t address was his defense of modern macroeconomics against the complaint that modern macroeconomics is too mathematical. Athreya is not responsible for the reductionist and axiomatic fetishes of modern macroeconomics, but he faithfully defends them against criticism. So I want to comment on a few paragraphs in which Athreya dismisses criticism of formalism and axiomatization.

Natural science has made significant progress by proceeding axiomatically and mathematically, and whether or not we [economists] will achieve this level of precision for any unit of observation in macroeconomics, it is likely to be the only rational alternative.

First, let me observe that axiomatization is not the same as using mathematics to solve problems. Many problems in economics cannot easily be solved without using mathematics, and sometimes it is useful to solve a problem in a few different ways, each way potentially providing some further insight into the problem not provided by the others. So I am not at all opposed to the use of mathematics in economics. However, the choice of tools to solve a problem should bear some reasonable relationship to the problem at hand. A good economist will understand what tools are appropriate to the solution of a particular problem. While mathematics has clearly been enormously useful to the natural sciences and to economics in solving problems, there are very few scientific advances that can be ascribed to axiomatization. Axiomatization was vital in proving the existence of equilibrium, but substantive refutable propositions about real economies, e.g., the Heckscher-Ohlin Theorem, or the Factor-Price Equalization Theorem, or the law of comparative advantage, were not discovered or empirically tested by way of axiomatization. Arthreya talks about economics achieving the “level of precision” achieved by natural science, but the concept of precision is itself hopelessly imprecise, and to set precision up as an independent goal makes no sense. Arthreya continues:

In addition to these benefits from the systematic [i.e. axiomatic] approach, there is the issue of clarity. Lowering mathematical content in economics represents a retreat from unambiguous language. Once mathematized, words in any given model cannot ever mean more than one thing. The unwillingness to couch things in such narrow terms (usually for fear of “losing something more intelligible”) has, in the past, led to a great deal of essentially useless discussion.

Arthreya writes as if the only source of ambiguity is imprecise language. That just isn’t so. Is unemployment voluntary or involuntary? Arthreya actually discusses the question intelligently on p. 283, in the context of search models of unemployment, but I don’t think that he could have provided any insight into that question with a purely formal, symbolic treatment. Again back to Arthreya:

The plaintive expressions of “fear of losing something intangible” are concessions to the forces of muddled thinking. The way modern economics gets done, you cannot possibly not know exactly what the author is assuming – and to boot, you’ll have a foolproof way of checking whether their claims of what follows from these premises is actually true or not.

So let me juxtapose this brief passage from Arthreya with a rather longer passage from Karl Popper in which he effectively punctures the fallacies underlying the specious claims made on behalf of formalism and against ordinary language. The extended quotations are from an addendum titled “Critical Remarks on Meaning Analysis” (pp. 261-77) to chapter IV of Realism and the Aim of Science (volume 1 of the Postscript to the Logic of Scientific Discovery). In this addendum, Popper begins by making the following three claims:

1 What-is? questions, such as What is Justice? . . . are always pointless – without philosophical or scientific interest; and so are all answers to what-is? questions, such as definitions. It must be admitted that some definitions may sometimes be of help in answering other questions: urgent questions which cannot be dismissed: genuine difficulties which may have arisen in science or in philosophy. But what-is? questions as such do not raise this kind of difficulty.

2 It makes no difference whether a what-is question is raised in order to inquire into the essence or into the nature of a thing, or whether it is raised in order to inquire into the essential meaning or into the proper use of an expression. These kinds of what-is questions are fundamentally the same. Again, it must be admitted that an answer to a what-is question – for example, an answer pointing out distinctions between two meanings of a word which have often been confused – may not be without point, provided the confusion led to serious difficulties. But in this case, it is not the what-is question which we are trying to solve; we hope rather to resolve certain contradictions that arise from our reliance upon somewhat naïve intuitive ideas. (The . . . example discussed below – that of the ideas of a derivative and of an integral – will furnish an illustration of this case.) The solution may well be the elimination (rather than the clarification) of the naïve idea. But an answer to . . . a what-is question is never fruitful. . . .

3 The problem, more especially, of replacing an “inexact” term by an “exact” one – for example, the problem of giving a definition in “exact” or “precise” terms – is a pseudo-problem. It depends essentially upon the inexact and imprecise terms “exact” and “precise.” These are most misleading, not only because they strongly suggest that there exists what does not exist – absolute exactness or precision – but also because they are emotionally highly charged: under the guise of scientific character and of scientific objectivity, they suggest that precision or exactness is something superior, a kind of ultimate value, and that it is wrong, or unscientific, or muddle-headed, to use inexact terms (as it is indeed wrong not to speak as lucidly and simply as possible). But there is no such thing as an “exact” term, or terms made “precise” by “precise definitions.” Also, a definition must always use undefined terms in its definiens (since otherwise we should get involved in an infinite regress or in a circle); and if we have to operate with a number of undefined terms, it hardly matters whether we use a few more. Of course, if a definition helps to solve a genuine problem, the situation is different; and some problems cannot be solved without an increase of precision. Indeed, this is the only way in which we can reasonably speak of precision: the demand for precision is empty, unless it is raised relative to some requirements that arise from our attempts to solve a definite problem. (pp. 261-63)

Later in his addendum Popper provides an enlightening discussion of the historical development of calculus despite its lack of solid logical axiomatic foundation. The meaning of an infinitesimal or a derivative was anything but precise. It was, to use Arthreya’s aptly chosen term, a muddle. Mathematicians even came up with a symbol for the derivative. But they literally had no precise idea of what they were talking about. When mathematicians eventually came up with a definition for the derivative, the definition did not clarify what they were talking about; it just provided a particular method of calculating what the derivative would be. However, the absence of a rigorous and precise definition of the derivative did not prevent mathematicians from solving some enormously important practical problems, thereby helping to change the world and our understanding of it.

The modern history of the problem of the foundations of mathematics is largely, it has been asserted, the history of the “clarification” of the fundamental ideas of the differential and integral calculus. The concept of a derivative (the slope of a curve of the rate of increase of a function) has been made “exact” or “precise” by defining it as the limit of the quotient of differences (given a differentiable function); and the concept of an integral (the area or “quadrature” of a region enclosed by a curve) has likewise been “exactly defined”. . . . Attempts to eliminate the contradictions in this field constitute not only one of the main motives of the development of mathematics during the last hundred or even two hundred years, but they have also motivated modern research into the “foundations” of the various sciences and, more particularly, the modern quest for precision or exactness. “Thus mathematicians,” Bertrand Russell says, writing about one of the most important phases of this development, “were only awakened from their “dogmatic slumbers” when Weierstrass and his followers showed that many of their most cherished propositions are in general false. Macaulay, contrasting the certainty of mathematics with the uncertainty of philosophy, asks who ever heard of a reaction against Taylor’s theorem. If he had lived now, he himself might have heard of such a reaction, for his is precisely one of the theorems which modern investigations have overthrown. Such rude shocks to mathematical faith have produced that love of formalism which appears, to those who are ignorant of its motive, to be mere outrageous pedantry.”

It would perhaps be too much to read into this passage of Russell’s his agreement with a view which I hold to be true: that without “such rude shocks” – that is to say, without the urgent need to remove contradictions – the love of formalism is indeed “mere outrageous pedantry.” But I think that Russell does convey his view that without an urgent need, an urgent problem to be solved, the mere demand for precision is indefensible.

But this is only a minor point. My main point is this. Most people, including mathematicians, look upon the definition of the derivative, in terms of limits of sequences, as if it were a definition in the sense that it analyses or makes precise, or “explicates,” the intuitive meaning of the definiendum – of the derivative. But this widespread belief is mistaken. . . .

Newton and Leibniz and their successors did not deny that a derivative, or an integral, could be calculated as a limit of certain sequences . . . . But they would not have regarded these limits as possible definitions, because they do not give the meaning, the idea, of a derivative or an integral.

For the derivative is a measure of a velocity, or a slope of a curve. Now the velocity of a body at a certain instant is something real – a concrete (relational) attribute of that body at that instant. By contrast the limit of a sequence of average velocities is something highly abstract – something that exists only in our thoughts. The average velocities themselves are unreal. Their unending sequence is even more so; and the limit of this unending sequence is a purely mathematical construction out of these unreal entities. Now it is intuitively quite obvious that this limit must numerically coincide with the velocity, and that, if the limit can be calculated, we can thereby calculate the velocity. But according to the views of Newton and his contemporaries, it would be putting the cart before the horse were we to define the velocity as being identical with this limit, rather than as a real state of the body at a certain instant, or at a certain point, of its track – to be calculated by any mathematical contrivance we may be able to think of.

The same holds of course for the slope of a curve in a given point. Its measure will be equal to the limit of a sequence of measures of certain other average slopes (rather than actual slopes) of this curve. But it is not, in its proper meaning or essence, a limit of a sequence: the slope is something we can sometimes actually draw on paper, and construct with a compasses and rulers, while a limit is in essence something abstract, rarely actually reached or realized, but only approached, nearer and nearer, by a sequence of numbers. . . .

Or as Berkeley put it “. . . however expedient such analogies or such expressions may be found for facilitating the modern quadratures, yet we shall not find any light given us thereby into the original real nature of fluxions considered in themselves.” Thus mere means for facilitating our calculations cannot be considered as explications or definitions.

This was the view of all mathematicians of the period, including Newton and Leibniz. If we now look at the modern point of view, then we see that we have completely given up the idea of definition in the sense in which it was understood by the founders of the calculus, as well as by Berkeley. We have given up the idea of a definition which explains the meaning (for example of the derivative). This fact is veiled by our retaining the old symbol of “definition” for some equivalences which we use, not to explain the idea or the essence of a derivative, but to eliminate it. And it is veiled by our retention of the name “differential quotient” or “derivative,” and the old symbol dy/dx which once denoted an idea which we have now discarded. For the name, and the symbol, now have no function other than to serve as labels for the defiens – the limit of a sequence.

Thus we have given up “explication” as a bad job. The intuitive idea, we found, led to contradictions. But we can solve our problems without it, retaining the bulk of the technique of calculation which originally was based upon the intuitive idea. Or more precisely we retain only this technique, as far as it was sound, and eliminate the idea its help. The derivative and the integral are both eliminated; they are replaced, in effect, by certain standard methods of calculating limits. (oo. 266-70)

Not only have the original ideas of the founders of calculus been eliminated, because they ultimately could not withstand logical scrutiny, but a premature insistence on logical precision would have had disastrous consequences for the ultimate development of calculus.

It is fascinating to consider that this whole admirable development might have been nipped in the bud (as in the days of Archimedes) had the mathematicians of the day been more sensitive to Berkeley’s demand – in itself quite reasonable – that we should strictly adhere to the rules of logic, and to the rule of always speaking sense.

We now know that Berkeley was right when, in The Analyst, he blamed Newton . . . for obtaining . . . mathematical results in the theory of fluxions or “in the calculus differentialis” by illegitimate reasoning. And he was completely right when he indicated that [his] symbols were without meaning. “Nothing is easier,” he wrote, “than to devise expressions and notations, for fluxions and infinitesimals of the first, second, third, fourth, and subsequent orders. . . . These expressions indeed are clear and distinct, and the mind finds no difficulty in conceiving them to be continued beyond any assignable bounds. But if . . . we look underneath, if, laying aside the expressions, we set ourselves attentively to consider the things themselves which are supposed to be expressed or marked thereby, we shall discover much emptiness, darkness, and confusion . . . , direct impossibilities, and contradictions.”

But the mathematicians of his day did not listen to Berkeley. They got their results, and they were not afraid of contradictions as long as they felt that they could dodge them with a little skill. For the attempt to “analyse the meaning” or to “explicate” their concepts would, as we know now, have led to nothing. Berkeley was right: all these concept were meaningless, in his sense and in the traditional sense of the word “meaning:” they were empty, for they denoted nothing, they stood for nothing. Had this fact been realized at the time, the development of the calculus might have been stopped again, as it had been stopped before. It was the neglect of precision, the almost instinctive neglect of all meaning analysis or explication, which made the wonderful development of the calculus possible.

The problem underlying the whole development was, of course, to retain the powerful instrument of the calculus without the contradictions which had been found in it. There is no doubt that our present methods are more exact than the earlier ones. But this is not due to the fact that they use “exactly defined” terms. Nor does it mean that they are exact: the main point of the definition by way of limits is always an existential assertion, and the meaning of the little phrase “there exists a number” has become the centre of disturbance in contemporary mathematics. . . . This illustrates my point that the attribute of exactness is not absolute, and that it is inexact and highly misleading to use the terms “exact” and “precise” as if they had any exact or precise meaning. (pp. 270-71)

Popper sums up his discussion as follows:

My examples [I quoted only the first of the four examples as it seemed most relevant to Arthreya's discussion] may help to emphasize a lesson taught by the whole history of science: that absolute exactness does not exist, not even in logic and mathematics (as illustrated by the example of the still unfinished history of the calculus); that we should never try to be more exact than is necessary for the solution of the problem in hand; and that the demand for “something more exact” cannot in itself constitute a genuine problem (except, of course, when improved exactness may improve the testability of some theory). (p. 277)

I apologize for stringing together this long series of quotes from Popper, but I think that it is important to understand that there is simply no scientific justification for the highly formalistic manner in which much modern economics is now carried out. Of course, other far more authoritative critics than I, like Mark Blaug and Richard Lipsey (also here) have complained about the insistence of modern macroeconomics on microfounded, axiomatized models regardless of whether those models generate better predictions than competing models. Their complaints have regrettably been ignored for the most part. I simply want to point out that a recent, and in many ways admirable, introduction to modern macroeconomics failed to provide a coherent justification for insisting on axiomatized models. It really wasn’t the author’s fault; a coherent justification doesn’t exist.

John Cochrane on the Failure of Macroeconomics

The state of modern macroeconomics is not good; John Cochrane, professor of finance at the University of Chicago, senior fellow of the Hoover Institution, and adjunct scholar of the Cato Institute, writing in Thursday’s Wall Street Journal, thinks macroeconomics is a failure. Perhaps so, but he has trouble explaining why.

The problem that Cochrane is chiefly focused on is slow growth.

Output per capita fell almost 10 percentage points below trend in the 2008 recession. It has since grown at less than 1.5%, and lost more ground relative to trend. Cumulative losses are many trillions of dollars, and growing. And the latest GDP report disappoints again, declining in the first quarter.

Sclerotic growth trumps every other economic problem. Without strong growth, our children and grandchildren will not see the great rise in health and living standards that we enjoy relative to our parents and grandparents. Without growth, our government’s already questionable ability to pay for health care, retirement and its debt evaporate. Without growth, the lot of the unfortunate will not improve. Without growth, U.S. military strength and our influence abroad must fade.

Macroeconomists offer two possible explanations for slow growth: a) too little demand — correctable through monetary or fiscal stimulus — and b) structural rigidities and impediments to growth, for which stimulus is no remedy. Cochrane is not a fan of the demand explanation.

The “demand” side initially cited New Keynesian macroeconomic models. In this view, the economy requires a sharply negative real (after inflation) rate of interest. But inflation is only 2%, and the Federal Reserve cannot lower interest rates below zero. Thus the current negative 2% real rate is too high, inducing people to save too much and spend too little.

New Keynesian models have also produced attractively magical policy predictions. Government spending, even if financed by taxes, and even if completely wasted, raises GDP. Larry Summers and Berkeley’s Brad DeLong write of a multiplier so large that spending generates enough taxes to pay for itself. Paul Krugman writes that even the “broken windows fallacy ceases to be a fallacy,” because replacing windows “can stimulate spending and raise employment.”

If you look hard at New-Keynesian models, however, this diagnosis and these policy predictions are fragile. There are many ways to generate the models’ predictions for GDP, employment and inflation from their underlying assumptions about how people behave. Some predict outsize multipliers and revive the broken-window fallacy. Others generate normal policy predictions—small multipliers and costly broken windows. None produces our steady low-inflation slump as a “demand” failure.

Cochrane’s characterization of what’s wrong with New Keynesian models is remarkably superficial. Slow growth, according to the New Keynesian model, is caused by the real interest rate being insufficiently negative, with the nominal rate at zero and inflation at (less than) 2%. So what is the problem? True, the nominal rate can’t go below zero, but where is it written that the upper bound on inflation is (or must be) 2%? Cochrane doesn’t say. Not only doesn’t he say, he doesn’t even seem interested. It might be that something really terrible would happen if the rate of inflation rose about 2%, but if so, Cochrane or somebody needs to explain why terrible calamities did not befall us during all those comparatively glorious bygone years when the rate of inflation consistently exceeded 2% while real economic growth was at least a percentage point higher than it is now. Perhaps, like Fischer Black, Cochrane believes that the rate of inflation has nothing to do with monetary or fiscal policy. But that is certainly not the standard interpretation of the New Keynesian model that he is using as the archetype for modern demand-management macroeconomic theories. And if Cochrane does believe that the rate of inflation is not determined by either monetary policy or fiscal policy, he ought to come out and say so.

Cochrane thinks that persistent low inflation and low growth together pose a problem for New Keynesian theories. Indeed it does, but it doesn’t seem that a radical revision of New Keynesian theory would be required to cope with that state of affairs. Cochrane thinks otherwise.

These problems [i.e., a steady low-inflation slump, aka "secular stagnation"] are recognized, and now academics such as Brown University’s Gauti Eggertsson and Neil Mehrotra are busy tweaking the models to address them. Good. But models that someone might get to work in the future are not ready to drive trillions of dollars of public expenditure.

In other words, unless the economic model has already been worked out before a particular economic problem arises, no economic policy conclusions may be deduced from that economic model. May I call  this Cochrane’s rule?

Cochrane the proceeds to accuse those who look to traditional Keynesian ideas of rejecting science.

The reaction in policy circles to these problems is instead a full-on retreat, not just from the admirable rigor of New Keynesian modeling, but from the attempt to make economics scientific at all.

Messrs. DeLong and Summers and Johns Hopkins’s Laurence Ball capture this feeling well, writing in a recent paper that “the appropriate new thinking is largely old thinking: traditional Keynesian ideas of the 1930s to 1960s.” That is, from before the 1960s when Keynesian thinking was quantified, fed into computers and checked against data; and before the 1970s, when that check failed, and other economists built new and more coherent models. Paul Krugman likewise rails against “generations of economists” who are “viewing the world through a haze of equations.”

Well, maybe they’re right. Social sciences can go off the rails for 50 years. I think Keynesian economics did just that. But if economics is as ephemeral as philosophy or literature, then it cannot don the mantle of scientific expertise to demand trillions of public expenditure.

This is political rhetoric wrapped in a cloak of scientific objectivity. We don’t have the luxury of knowing in advance what the consequences of our actions will be. The United States has spent trillions of dollars on all kinds of stuff over the past dozen years or so. A lot of it has not worked out well at all. So it is altogether fitting and proper for us to be skeptical about whether we will get our money’s worth for whatever the government proposes to spend on our behalf. But Cochrane’s implicit demand that money only be spent if there is some sort of scientific certainty that the money will be well spent can never be met. However, as Larry Summers has pointed out, there are certainly many worthwhile infrastructure projects that could be undertaken, so the risk of committing the “broken windows fallacy” is small. With the government able to borrow at negative real interest rates, the present value of funding such projects is almost certainly positive. So one wonders what is the scientific basis for not funding those projects?

Cochrane compares macroeconomics to climate science:

The climate policy establishment also wants to spend trillions of dollars, and cites scientific literature, imperfect and contentious as that literature may be. Imagine how much less persuasive they would be if they instead denied published climate science since 1975 and bemoaned climate models’ “haze of equations”; if they told us to go back to the complex writings of a weather guru from the 1930s Dustbowl, as they interpret his writings. That’s the current argument for fiscal stimulus.

Cochrane writes as if there were some important scientific breakthrough made by modern macroeconomics — “the new and more coherent models,” either the New Keynesian version of New Classical macroeconomics or Real Business Cycle Theory — that rendered traditional Keynesian economics obsolete or outdated. I have never been a devote of Keynesian economics, but the fact is that modern macroeconomics has achieved its ascendancy in academic circles almost entirely by way of a misguided methodological preference for axiomatized intertemporal optimization models for which a unique equilibrium solution can be found by imposing the empirically risible assumption of rational expectations. These models, whether in their New Keynesian or Real Business Cycle versions, do not generate better empirical predictions than the old fashioned Keynesian models, and, as Noah Smith has usefully pointed out, these models have been consistently rejected by private forecasters in favor of the traditional Keynesian models. It is only the dominant clique of ivory-tower intellectuals that cultivate and nurture these models. The notion that such models are entitled to any special authority or scientific status is based on nothing but the exaggerated self-esteem that is characteristic of almost every intellectual clique, particularly dominant ones.

Having rejected inadequate demand as a cause of slow growth, Cochrane, relying on no model and no evidence, makes a pitch for uncertainty as the source of slow growth.

Where, instead, are the problems? John Taylor, Stanford’s Nick Bloom and Chicago Booth’s Steve Davis see the uncertainty induced by seat-of-the-pants policy at fault. Who wants to hire, lend or invest when the next stroke of the presidential pen or Justice Department witch hunt can undo all the hard work? Ed Prescott emphasizes large distorting taxes and intrusive regulations. The University of Chicago’s Casey Mulligan deconstructs the unintended disincentives of social programs. And so forth. These problems did not cause the recession. But they are worse now, and they can impede recovery and retard growth.

Where, one wonders, is the science on which this sort of seat-of-the-pants speculation is based? Is there any evidence, for example, that the tax burden on businesses or individuals is greater now than it was let us say in 1983-85 when, under President Reagan, the economy, despite annual tax increases partially reversing the 1981 cuts enacted in Reagan’s first year, began recovering rapidly from the 1981-82 recession?

Methodological Arrogance

A few weeks ago, I posted a somewhat critical review of Kartik Athreya’s new book Big Ideas in Macroeconomics. In quoting a passage from chapter 4 in which Kartik defended the rational-expectations axiom on the grounds that it protects the public from economists who, if left unconstrained by the discipline of rational expectations, could use expectational assumptions to generate whatever results they wanted, I suggested that this sort of reasoning in defense of the rational-expectations axiom betrayed what I called the “methodological arrogance” of modern macroeconomics which has, to a large extent, succeeded in imposing that axiom on all macroeconomic models. In his comment responding to my criticisms, Kartik made good-natured reference in passing to my charge of “methodological arrogance,” without substantively engaging with the charge. And in a post about the early reviews of Kartik’s book, Steve Williamson, while crediting me for at least reading the book before commenting on it, registered puzzlement at what I meant by “methodological arrogance.”

Actually, I realized when writing that post that I was not being entirely clear about what “methodological arrogance” meant, but I thought that my somewhat tongue-in-cheek reference to the duty of modern macroeconomists “to ban such models from polite discourse — certainly from the leading economics journals — lest the public be tainted by economists who might otherwise dare to abuse their models by making illicit assumptions about expectations formation and equilibrium concepts” was sufficiently suggestive not to require elaboration, especially after having devoted several earlier posts to criticisms of the methodology of modern macroeconomics (e.g., here, here, and here). That was a misjudgment.

So let me try to explain what I mean by methodological arrogance, which is not the quite the same as, but is closely related to, methodological authoritarianism. I will do so by referring to the long introductory essay (“A Realist View of Logic, Physics, and History”) that Karl Popper contributed to a book The Self and Its Brain co-authored with neuroscientist John Eccles. The chief aim of the essay was to argue that the universe is not fully determined, but evolves, producing new, emergent, phenomena not originally extant in the universe, such as the higher elements, life, consciousness, language, science and all other products of human creativity, which in turn interact with the universe, in fundamentally unpredictable ways. Popper regards consciousness as a real phenomenon that cannot be reduced to or explained by purely physical causes. Though he makes only brief passing reference to the social sciences, Popper’s criticisms of reductionism are directly applicable to the microfoundations program of modern macroeconomics, and so I think it will be useful to quote what he wrote at some length.

Against the acceptance of the view of emergent evolution there is a strong intuitive prejudice. It is the intuition that, if the universe consists of atoms or elementary particles, so that all things are structures of such particles, then every event in the universe ought to be explicable, and in principle predictable, in terms of particle structure and of particle interaction.

Notice how easy it would be rephrase this statement as a statement about microfoundations:

Against the acceptance of the view that there are macroeconomic phenomena, there is a strong intuitive prejudice. It is the intuition that, if the macroeconomy consists of independent agents, so that all macroeconomic phenomena are the result of decisions made by independent agents, then every macreconomic event ought to be explicable, and in principle predictable, in terms of the decisions of individual agents and their interactions.

Popper continues:

Thus we are led to what has been called the programme of reductionism [microfoundations]. In order to discuss it I shall make use of the following Table

(12) Level of ecosystems

(11) Level of populations of metazoan and plants

(10) Level of metezoa and multicellular plants

(9) Level of tissues and organs (and of sponges?)

(8) Level of populations of unicellular organisms

(7) Level of cells and of unicellular organisms

(6) Level of organelles (and perhaps of viruses)

(5) Liquids and solids (crystals)

(4) Molecules

(3) Atoms

(2) Elementary particles

(1) Sub-elementary particles

(0) Unknown sub-sub-elementary particles?

The reductionist idea behind this table is that the events or things on each level should be explained in terms of the lower levels. . . .

This reductionist idea is interesting and important; and whenever we can explain entities and events on a higher level by those of a lower level, we can speak of a great scientific success, and can say that we have added much to our understanding of the higher level. As a research programme, reductionism is not only important, but it is part of the programme of science whose aim is to explain and to understand.

So far so good. Reductionism certainly has its place. So do microfoundations. Whenever we can take an observation and explain it in terms of its constituent elements, we have accomplished something important. We have made scientific progress.

But Popper goes on to voice a cautionary note. There may be, and probably are, strict, perhaps insuperable, limits to how far higher-level phenomena can be reduced to (explained by) lower-level phenomena.

[E]ven the often referred to reduction of chemistry to physics, important as it is, is far from complete, and very possibly incompletable. . . . [W]e are far removed indeed from being able to claim that all, or most, properties of chemical compounds can be reduced to atomic theory. . . . In fact, the five lower levels of [our] Table . . . can be used to show that we have reason to regard this kind of intuitive reduction programme as clashing with some results of modern physics.

For what [our] Table suggests may be characterized as the principle of “upward causation.” This is the principle that causation can be traced in our Table . . . . from a lower level to a higher level, but not vice versa; that what happens on a higher level can be explained in terms of the next lower level, and ultimately in terms of elementary particles and the relevant physical laws. It appears at first that the higher levels cannot act on the lower ones.

But the idea of particle-to-particle or atom-to-atom interaction has been superseded by physics itself. A diffraction grating or a crystal (belonging to level (5) of our Table . . .) is a spatially very extended complex (and periodic) structure of billions of molecules; but it interacts as a whole extended periodic structure with the photons or the particles of a beam of photons or particles. Thus we have here an important example of “downward causation“. . . . That is to say, the whole, the macro structure, may, qua whole, act upon a photon or an elementary particle or an atom. . . .

Other physical examples of downward causation – of macroscopic structures on level (5) acting upon elementary particles or photons on level (1) – are lasers, masers, and holograms. And there are also many other macro structures which are examples of downward causation: every simple arrangement of negative feedback, such as a steam engine governor, is a macroscopic structure that regulates lower level events, such as the flow of the molecules that constitute the steam. Downward causation is of course important in all tools and machines which are designed for sompe purpose. When we use a wedge, for example, we do not arrange for the action of its elementary particles, but we use a structure, relying on it ot guide the actions of its constituent elementary particles to act, in concert, so as to achieve the desired result.

Stars are undersigned, but one may look at them as undersigned “machines” for putting the atoms and elementary particles in their central region under terrific gravitational pressure, with the (undersigned) result that some atomic nuclei fuse and form the nuclei of heavier elements; an excellent example of downward causation,of the action of the whole structure upon its constituent particles.

(Stars, incidentally, are good examples of the general rule that things are processes. Also, they illustrate the mistake of distinguishing between “wholes” – which are “more than the sums of their parts” – and “mere heaps”: a star is, in a sense, a “mere” accumulation, a “mere heap” of its constituent atoms. Yet it is a process – a dynamic structure. Its stability depends upon the dynamic equilibrium between its gravitational pressure, due to its sheer bulk, and the repulsive forces between its closely packed elementary particles. If the latter are excessive, the star explodes, If they are smaller than the gravitational pressure, it collapses into a “black hole.”

The most interesting examples of downward causation are to be found in organisms and in their ecological systems, and in societies of organisms [my emphasis]. A society may continue to function even though many of its members die; but a strike in an essential industry, such as the supply of electricity, may cause great suffering to many individual people. .. . I believe that these examples make the existence of downward causation obvious; and they make the complete success of any reductionist programme at least problematic.

I was very glad when I recently found this discussion of reductionism by Popper in a book that I had not opened for maybe 40 years, because it supports an argument that I have been making on this blog against the microfoundations program in macroeconomics: that as much as macroeconomics requires microfoundations, microeconomics also requires macrofoundations. Here is how I put a little over a year ago:

In fact, the standard comparative-statics propositions of microeconomics are also based on the assumption of the existence of a unique stable general equilibrium. Those comparative-statics propositions about the signs of the derivatives of various endogenous variables (price, quantity demanded, quantity supplied, etc.) with respect to various parameters of a microeconomic model involve comparisons between equilibrium values of the relevant variables before and after the posited parametric changes. All such comparative-statics results involve a ceteris-paribus assumption, conditional on the existence of a unique stable general equilibrium which serves as the starting and ending point (after adjustment to the parameter change) of the exercise, thereby isolating the purely hypothetical effect of a parameter change. Thus, as much as macroeconomics may require microfoundations, microeconomics is no less in need of macrofoundations, i.e., the existence of a unique stable general equilibrium, absent which a comparative-statics exercise would be meaningless, because the ceteris-paribus assumption could not otherwise be maintained. To assert that macroeconomics is impossible without microfoundations is therefore to reason in a circle, the empirically relevant propositions of microeconomics being predicated on the existence of a unique stable general equilibrium. But it is precisely the putative failure of a unique stable intertemporal general equilibrium to be attained, or to serve as a powerful attractor to economic variables, that provides the rationale for the existence of a field called macroeconomics.

And more recently, I put it this way:

The microeconomic theory of price adjustment is a theory of price adjustment in a single market. It is a theory in which, implicitly, all prices and quantities, but a single price-quantity pair are in equilibrium. Equilibrium in that single market is rapidly restored by price and quantity adjustment in that single market. That is why I have said that microeconomics rests on a macroeconomic foundation, and that is why it is illusory to imagine that macroeconomics can be logically derived from microfoundations. Microfoundations, insofar as they explain how prices adjust, are themselves founded on the existence of a macroeconomic equilibrium. Founding macroeconomics on microfoundations is just a form of bootstrapping.

So I think that my criticism of the microfoundations project exactly captures the gist of Popper’s criticism of reductionism. Popper extended his criticism of a certain form of reductionism, which he called “radical materialism or radical physicalism” in later passage in the same essay that is also worth quoting:

Radical materialism or radical physicalism is certainly a selfconsistent position. Fir it is a view of the universe which, as far as we know, was adequate once; that is, before the emergence of life and consciousness. . . .

What speaks in favour of radical materialism or radical physicalism is, of course, that it offers us a simple vision of a simple universe, and this looks attractive just because, in science, we search for simple theories. However, I think that it is important that we note that there are two different ways by which we can search for simplicity. They may be called, briefly, philosophical reduction and scientific reduction. The former is characterized by an attempt to provide bold and testable theories of high explanatory power. I believe that the latter is an extremely valuable and worthwhile method; while the former is of value only if we have good reasons to assume that it corresponds to the facts about the universe.

Indeed, the demand for simplicity in the sense of philosophical rather than scientific reduction may actually be damaging. For even in order to attempt scientific reduction, it is necessary for us to get a full grasp of the problem to be solved, and it is therefore vitally important that interesting problems are not “explained away” by philosophical analysis. If, say, more than one factor is responsible for some effect, it is important that we do not pre-empt the scientific judgment: there is always the danger that we might refuse to admit any ideas other than the ones we appear to have at hand: explaining away, or belittling the problem. The danger is increased if we try to settle the matter in advance by philosophical reduction. Philosophical reduction also makes us blind to the significance of scientific reduction.

Popper adds the following footnote about the difference between philosophic and scientific reduction.

Consider, for example, what a dogmatic philosophical reductionist of a mechanistic disposition (or even a quantum-mechanistic disposition) might have done in the face of the problem of the chemical bond. The actual reduction, so far as it goes, of the theory of the hydrogen bond to quantum mechanics is far more interesting than the philosophical assertion that such a reduction will one be achieved.

What modern macroeconomics now offers is largely an array of models simplified sufficiently so that they are solvable using the techniques of dynamic optimization. Dynamic optimization by individual agents — the microfoundations of modern macro — makes sense only in the context of an intertemporal equilibrium. But it is just the possibility that intertemporal equilibrium may not obtain that, to some of us at least, makes macroeconomics interesting and relevant. As the great Cambridge economist, Frederick Lavington, anticipating Popper in grasping the possibility of downward causation, put it so well, “the inactivity of all is the cause of the inactivity of each.”

So what do I mean by methodological arrogance? I mean an attitude that invokes microfoundations as a methodological principle — philosophical reductionism in Popper’s terminology — while dismissing non-microfounded macromodels as unscientific. To be sure, the progress of science may enable us to reformulate (and perhaps improve) explanations of certain higher-level phenomena by expressing those relationships in terms of lower-level concepts. That is what Popper calls scientific reduction. But scientific reduction is very different from rejecting, on methodological principle, any explanation not expressed in terms of more basic concepts.

And whenever macrotheory seems inconsistent with microtheory, the inconsistency poses a problem to be solved. Solving the problem will advance our understanding. But simply to reject the macrotheory on methodological principle without evidence that the microfounded theory gives a better explanation of the observed phenomena than the non-microfounded macrotheory (and especially when the evidence strongly indicates the opposite) is arrogant. Microfoundations for macroeconomics should result from progress in economic theory, not from a dubious methodological precept.

Let me quote Popper again (this time from his book Objective Knowledge) about the difference between scientific and philosophical reduction, addressing the denial by physicalists that that there is such a thing as consciousness, a denial based on their belief that all supposedly mental phenomena can and will ultimately be reduced to purely physical phenomena

[P]hilosophical speculations of a materialistic or physicalistic character are very interesting, and may even be able to point the way to a successful scientific reduction. But they should be frankly tentative theories. . . . Some physicalists do not, however, consider their theories as tentative, but as proposals to express everything in physicalist language; and they think these proposals have much in their favour because they are undoubtedly convenient: inconvenient problems such as the body-mind problem do indeed, most conveniently, disappear. So these physicalists think that there can be no doubt that these problems should be eliminated as pseudo-problems. (p. 293)

One could easily substitute “methodological speculations about macroeconomics” for “philosophical speculations of a materialistic or physicalistic character” in the first sentence. And in the third sentence one could substitute “advocates of microfounding all macroeconomic theories” for “physicalists,” “microeconomic” for “physicalist,” and “Phillips Curve” or “involuntary unemployment” for “body-mind problem.”

So, yes, I think it is arrogant to think that you can settle an argument by forcing the other side to use only those terms that you approve of.

What Does “Keynesian” Mean?

Last week Simon Wren-Lewis wrote a really interesting post on his blog trying to find the right labels with which to identify macroeconomists. Simon, rather disarmingly, starts by admitting the ultimate futility of assigning people labels; reality is just too complicated to conform to the labels that we invent to help ourselves make sense of reality. A good label can provide us with a handle with which to gain a better grasp on a messy set of observations, but it is not the reality. And if you come up with one label, I may counter with a different one. Who’s to say which label is better?

At any rate, as I read through Simon’s post I found myself alternately nodding my head in agreement and shaking my head in disagreement. So staying in the spirit of fun in which Simon wrote his post, I will provide a commentary on his labels and other pronouncements. If the comments are weighted on the side of disagreement, well, that’s what makes blogging fun, n’est-ce pas?

Simon divides academic researchers into two groups (mainstream and heterodox) and macroeconomic policy into two approaches (Keynesian and anti-Keynesian). He then offers the following comment on the meaning of the label Keynesian.

Just think about the label Keynesian. Any sensible definition would involve the words sticky prices and aggregate demand. Yet there are still some economists (generally not academics) who think Keynesian means believing fiscal rather than monetary policy should be used to stabilise demand. Fifty years ago maybe, but no longer. Even worse are non-economists who think being a Keynesian means believing in market imperfections, government intervention in general and a mixed economy. (If you do not believe this happens, look at the definition in Wikipedia.)

Well, as I pointed out in a recent post, there is nothing peculiarly Keynesian about the assumption of sticky prices, especially not as a necessary condition for an output gap and involuntary unemployment. So if Simon is going to have to work harder to justify his distinction between Keynesian and anti-Keynesian. In a comment on Simon’s blog, Nick Rowe pointed out just this problem, asking in particular why Simon could not substitute a Monetarist/anti-Monetarist dichotomy for the Keynesian/anti-Keynesian one.

The story gets more complicated in Simon’s next paragraph in which he describes his dichotomy of academic research into mainstream and heterodox.

Thanks to the microfoundations revolution in macro, mainstream macroeconomists speak the same language. I can go to a seminar that involves an RBC model with flexible prices and no involuntary unemployment and still contribute and possibly learn something. Equally an economist like John Cochrane can and does engage in meaningful discussions of New Keynesian theory (pdf).

In other words, the range of acceptable macroeconomic models has been drastically narrowed. Unless it is microfounded in a dynamic stochastic general equilibrium model, a model does not qualify as “mainstream.” This notion of microfoundation is certainly not what Edmund Phelps meant by “microeconomic foundations” when he edited his famous volume Microeconomic Foundations of Employment and Inflation Theory, which contained, among others, Alchian’s classic paper on search costs and unemployment and a paper by the then not so well-known Robert Lucas and his early collaborator Leonard Rapping. Nevertheless, in the current consensus, it is apparently the New Classicals that determine what kind of model is acceptable, while New Keynesians are allowed to make whatever adjustments, mainly sticky wages, they need to derive Keynesian policy recommendations. Anyone who doesn’t go along with this bargain is excluded from the mainstream. Simon may not be happy with this state of affairs, but he seems to have made peace with it without undue discomfort.

Now many mainstream macroeconomists, myself included, can be pretty critical of the limitations that this programme can place on economic thinking, particularly if it is taken too literally by microfoundations purists. But like it or not, that is how most macro research is done nowadays in the mainstream, and I see no sign of this changing anytime soon. (Paul Krugman discusses some reasons why here.) My own view is that I would like to see more tolerance and a greater variety of modelling approaches, but a pragmatic microfoundations macro will and should remain the major academic research paradigm.

Thus, within the mainstream, there is no basic difference in how to create a macroeconomic model. The difference is just in how to tweak the model in order to derive the desired policy implication.

When it comes to macroeconomic policy, and keeping to the different language idea, the only significant division I see is between the mainstream macro practiced by most economists, including those in most central banks, and anti-Keynesians. By anti-Keynesian I mean those who deny the potential for aggregate demand to influence output and unemployment in the short term.

So, even though New Keynesians have learned how to speak the language of New Classicals, New Keynesians can console themselves in retaining the upper hand in policy discussions. Which is why in policy terms, Simon chooses a label that is at least suggestive of a certain Keynesian primacy, the other side being defined in terms of their opposition to Keynesian policy. Half apologetically, Simon then asks: “Why do I use the term anti-Keynesian rather than, say, New Classical?” After all, it’s the New Classical model that’s being tweaked. Simon responds:

Partly because New Keynesian economics essentially just augments New Classical macroeconomics with sticky prices. But also because as far as I can see what holds anti-Keynesians together isn’t some coherent and realistic view of the world, but instead a dislike of what taking aggregate demand seriously implies.

This explanation really annoyed Steve Williamson who commented on Simon’s blog as follows:

Part of what defines a Keynesian (new or old), is that a Keynesian thinks that his or her views are “mainstream,” and that the rest of macroeconomic thought is defined relative to what Keynesians think – Keynesians reside at the center of the universe, and everything else revolves around them.

Simon goes on to explain what he means by the incoherence of the anti-Keynesian view of the world, pointing out that the Pigou Effect, which supposedly invalidated Keynes’s argument that perfect wage and price flexibility would not eventually restore full employment to an economy operating at less than full employment, has itself been shown not to be valid. And then Simon invokes that old standby Say’s Law.

Second, the evidence that prices are not flexible is so overwhelming that you need something else to drive you to ignore this evidence. Or to put it another way, you need something pretty strong for politicians or economists to make the ‘schoolboy error’ that is Says Law, which is why I think the basis of the anti-Keynesian view is essentially ideological.

Here, I think, Simon is missing something important. It was a mistake on Keynes’s part to focus on Say’s Law as the epitome of everything wrong with “classical economics.” Actually Say’s Law is a description of what happens in an economy when trading takes place at disequilibrium prices. At disequilibrium prices, potential gains from trade are left on the table. Not only are they left on the table, but the effects can be cumulative, because the failure to supply implies a further failure to demand. The Keynesian spending multiplier is the other side of the coin of the supply-side contraction envisioned by Say. Even infinite wage and price flexibility may not help an economy in which a lot of trade is occurring at disequilibrium prices.

The microeconomic theory of price adjustment is a theory of price adjustment in a single market. It is a theory in which, implicitly, all prices and quantities, but a single price-quantity pair are in equilibrium. Equilibrium in that single market is rapidly restored by price and quantity adjustment in that single market. That is why I have said that microeconomics rests on a macroeconomic foundation, and that is why it is illusory to imagine that macroeconomics can be logically derived from microfoundations. Microfoundations, insofar as they explain how prices adjust, are themselves founded on the existence of a macroeconomic equilibrium. Founding macroeconomics on microfoundations is just a form of bootstrapping.

If there is widespread unemployment, it may indeed be that wages are too high, and that a reduction in wages would restore equilibrium. But there is no general presumption that unemployment will be cured by a reduction in wages. Unemployment may be the result of a more general dysfunction in which all prices are away from their equilibrium levels, in which case no adjustment of the wage would solve the problem, so that there is no presumption that the current wage exceeds the full-equilibrium wage. This, by the way, seems to me to be nothing more than a straightforward implication of the Lipsey-Lancaster theory of second best.

Big Ideas in Macroeconomics: A Review

Steve Williamson recently plugged a new book by Kartik Athreya (Big Ideas in Macroeconomics), an economist at the Federal Reserve Bank of Richmond, which tries to explain in relatively non-technical terms what modern macroeconomics is all about. I will acknowledge that my graduate training in macroeconomics predated the rise of modern macro, and I am not fluent in the language of modern macro, though I am trying to fill in the gaps. And this book is a good place to start. I found Athreya’s book a good overview of the field, explaining the fundamental ideas and how they fit together.

Big Ideas in Macroeconomics is a moderately big book, 415 pages, covering a very wide range of topics. It is noteworthy, I think, that despite its size, there is so little overlap between the topics covered in this book, and those covered in more traditional, perhaps old-fashioned, books on macroeconomics. The index contains not a single entry on the price level, inflation, deflation, money, interest, total output, employment or unemployment. Which is not to say that none of those concepts are ever mentioned or discussed, just that they are not treated, as they are in traditional macroeconomics books, as the principal objects of macroeconomic inquiry. The conduct of monetary or fiscal policy to achieve some explicit macroeconomic objective is never discussed. In contrast, there are repeated references to Walrasian equilibrium, the Arrow-Debreu-McKenzie model, the Radner model, Nash-equilibria, Pareto optimality, the first and second Welfare theorems. It’s a new world.

The first two chapters present a fairly detailed description of the idea of Walrasian general equilibrium and its modern incarnation in the canonical Arrow-Debreu-McKenzie (ADM) model.The ADM model describes an economy of utility-maximizing households and profit-maximizing firms engaged in the production and consumption of commodities through time and space. There are markets for commodities dated by time period, specified by location and classified by foreseeable contingent states of the world, so that the same physical commodity corresponds to many separate commodities, each corresponding to different time periods and locations and to contingent states of the world. Prices for such physically identical commodities are not necessarily uniform across times, locations or contingent states.The demand for road salt to de-ice roads depends on whether conditions, which depend on time and location and on states of the world. For each different possible weather contingency, there would be a distinct market for road salt for each location and time period.

The ADM model is solved once for all time periods and all states of the world. Under appropriate conditions, there is one (and possibly more than one) intertemporal equilibrium, all trades being executed in advance, with all deliveries subsequently being carried out, as time an contingencies unfold, in accordance with the terms of the original contracts.

Given the existence of an equilibrium, i.e., a set of prices subject to which all agents are individually optimizing, and all markets are clearing, there are two classical welfare theorems stating that any such equilibrium involves a Pareto-optimal allocation and any Pareto-optimal allocation could be supported by an equilibrium set of prices corresponding to a suitably chosen set of initial endowments. For these optimality results to obtain, it is necessary that markets be complete in the sense that there is a market for each commodity in each time period and contingent state of the world. Without a complete set of markets in this sense, the Pareto-optimality of the Walrasian equilibrium cannot be proved.

Readers may wonder about the process by which an equilibrium price vector would actually be found through some trading process. Athreya invokes the fiction of a Walrasian clearinghouse in which all agents (truthfully) register their notional demands and supplies at alternative price vectors. Based on these responses the clearinghouse is able to determine, by a process of trial and error, the equilibrium price vector. Since the Walrasian clearinghouse presumes that no trading occurs except at an equilibrium price vector, there can be no assurance that an equilibrium price vector would ever be arrived at under an actual trading process in which trading occurs at disequilibrium prices. Moreover, as Clower and Leijonhufvud showed over 40 years ago (“Say’s Principle: What it Means and What it Doesn’t Mean”), trading at disequilibrium prices may cause cumulative contractions of aggregate demand because the total volume of trade at a disequilibrium price will always be less than the volume of trade at an equilibrium price, the volume of trade being constrained by the lesser of quantity supplied and quantity demanded.

In the view of modern macroeconomics, then, Walrasian general equilibrium, as characterized by the ADM model, is the basic and overarching paradigm of macroeconomic analysis. To be sure, modern macroeconomics tries to go beyond the highly restrictive assumptions of the ADM model, but it is not clear whether the concessions made by modern macroeconomics to the real world go very far in enhancing the realism of the basic model.

Chapter 3, contains some interesting reflections on the importance of efficiency (Pareto-optimality) as a policy objective and on the trade-offs between efficiency and equity and between ex-ante and ex-post efficiency. But these topics are on the periphery of macroeconomics, so I will offer no comment here.

In chapter 4, Athreya turns to some common criticisms of modern macroeconomics: that it is too highly aggregated, too wedded to the rationality assumption, too focused on equilibrium steady states, and too highly mathematical. Athreya correctly points out that older macroeconomic models were also highly aggregated, so that if aggregation is a problem it is not unique to modern macroeconomics. That’s a fair point, but skirts some thorny issues. As Athreya acknowledges in chapter 5, an important issue separating certain older macroeconomic traditions (both Keynesian and Austrian among others) is the idea that macroeconomic dysfunction is a manifestation of coordination failure. It is a property – a remarkable property – of Walrasian general equilibrium that it achieves perfect (i.e., Pareto-optimal) coordination of disparate, self-interested, competitive individual agents, fully reconciling their plans in a way that might have been achieved by an omniscient and benevolent central planner. Walrasian general equilibrium fully solves the coordination problem. Insofar as important results of modern macroeconomics depend on the assumption that a real-life economy can be realistically characterized as a Walrasian equilibrium, modern macroeconomics is assuming that coordination failures are irrelevant to macroeconomics. It is only after coordination failures have been excluded from the purview of macroeconomics that it became legitimate (for the sake of mathematical tractability) to deploy representative-agent models in macroeconomics, a coordination failure being tantamount, in the context of a representative agent model, to a form of irrationality on the part of the representative agent. Athreya characterizes choices about the level of aggregation as a trade-off between realism and tractability, but it seems to me that, rather than making a trade-off between realism and tractability, modern macroeconomics has simply made an a priori decision that coordination problems are not a relevant macroeconomic concern.

A similar argument applies to Athreya’s defense of rational expectations and the use of equilibrium in modern macroeconomic models. I would not deny that there are good reasons to adopt rational expectations and full equilibrium in some modeling situations, depending on the problem that theorist is trying to address. The question is whether it can be appropriate to deviate from the assumption of a full rational-expectations equilibrium for the purposes of modeling fluctuations over the course of a business cycle, especially a deep cyclical downturn. In particular, the idea of a Hicksian temporary equilibrium in which agents hold divergent expectations about future prices, but markets clear period by period given those divergent expectations, seems to offer (as in, e.g., Thompson’s “Reformulation of Macroeconomic Theory“) more realism and richer empirical content than modern macromodels of rational expectations.

Athreya offers the following explanation and defense of rational expectations:

[Rational expectations] purports to explain the expectations people actually have about the relevant items in their own futures. It does so by asking that their expectations lead to economy-wide outcomes that do not contradict their views. By imposing the requirement that expectations not be systematically contradicted by outcomes, economists keep an unobservable object from becoming a source of “free parameters” through which we can cheaply claim to have “explained” some phenomenon. In other words, in rational-expectations models, expectations are part of what is solved for, and so they are not left to the discretion of the modeler to impose willy-nilly. In so doing, the assumption of rational expectations protects the public from economists.

This defense of rational expectations plainly belies betrays the methodological arrogance of modern macroeconomics. I am all in favor of solving a model for equilibrium expectations, but solving for equilibrium expectations is certainly not the same as insisting that the only interesting or relevant result of a model is the one generated by the assumption of full equilibrium under rational expectations. (Again see Thompson’s “Reformulation of Macroeconomic Theory” as well as the classic paper by Foley and Sidrauski, and this post by Rajiv Sethi on his blog.) It may be relevant and useful to look at a model and examine its properties in a state in which agents hold inconsistent expectations about future prices; the temporary equilibrium existing at a point in time does not correspond to a steady state. Why is such an equilibrium uninteresting and uninformative about what happens in a business cycle? But evidently modern macroeconomists such as Athreya consider it their duty to ban such models from polite discourse — certainly from the leading economics journals — lest the public be tainted by economists who might otherwise dare to abuse their models by making illicit assumptions about expectations formation and equilibrium concepts.

Chapter 5 is the most important chapter of the book. It is in this chapter that Athreya examines in more detail the kinds of adjustments that modern macroeconomists make in the Walrasian/ADM paradigm to accommodate the incompleteness of markets and the imperfections of expectation formation that limit the empirical relevance of the full ADM model as a macroeconomic paradigm. To do so, Athreya starts by explaining how the Radner model in which a less than the full complement of Arrow-Debreu contingent-laims markets is available. In the Radner model, unlike the ADM model, trading takes place through time for those markets that actually exist, so that the full Walrasian equilibrium exists only if agents are able to form correct expectations about future prices. And even if the full Walrasian equilibrium exists, in the absence of a complete set of Arrow-Debreu markets, the classical welfare theorems may not obtain.

To Athreya, these limitations on the Radner version of the Walrasian model seem manageable. After all, if no one really knows how to improve on the equilibrium of the Radner model, the potential existence of Pareto improvements to the Radner equilibrium is not necessarily that big a deal. Athreya expands on the discussion of the Radner model by introducing the neoclassical growth model in both its deterministic and stochastic versions, all the elements of the dynamic stochastic general equilibrium (DSGE) model that characterizes modern macroeconomics now being in place. Athreya closes out the chapter with additional discussions of the role of further modifications to the basic Walrasian paradigm, particularly search models and overlapping-generations models.

I found the discussion in chapter 5 highly informative and useful, but it doesn’t seem to me that Athreya faces up to the limitations of the Radner model or to the implied disconnect between the Walraisan paradigm and macroeconomic analysis. A full Walrasian equilibrium exists in the Radner model only if all agents correctly anticipate future prices. If they don’t correctly anticipate future prices, then we are in the world of Hicksian temporary equilibrium. But in that world, the kind of coordination failures that Athreya so casually dismisses seem all too likely to occur. In a world of temporary equilibrium, there is no guarantee that intertemporal budget constraints will be effective, because those budget constraint reflect expected, not actual, future prices, and, in temporary equilibrium, expected prices are not the same for all transactors. Budget constraints are not binding in a world in which trading takes place through time based on possibly incorrect expectations of future prices. Not only does this mean that all the standard equilibrium and optimality conditions of Walrasian theory are violated, but that defaults on IOUs and, thus, financial-market breakdowns, are entirely possible.

In a key passage in chapter 5, Athreya dismisses coordination-failure explanations, invidiously characterized as Keynesian, for inefficient declines in output and employment. While acknowledging that such fluctuations could, in theory, be caused by “self-fulfilling pessimism or fear,” Athreya invokes the benchmark Radner trading arrangement of the ADM model. “In the Radner economy, Athreya writes, “households and firms have correct expectations for the spot market prices one period hence.” The justification for that expectational assumption, which seems indistinguishable from the assumption of a full, rational-expectations equilibrium, is left unstated. Athreya continues:

Granting that they indeed have such expectations, we can now ask about the extent to which, in a modern economy, we can have outcomes that are extremely sensitive to them. In particular, is it the case that under fairly plausible conditions, “optimism” and “pessimism” can be self-fulfilling in ways that make everyone (or nearly everyone) better off in the former than the latter?

Athreya argues that this is possible only if the aggregate production function of the economy is characterized by increasing returns to scale, so that productivity increases as output rises.

[W]hat I have in mind is that the structure of the economy must be such that when, for example, all households suddenly defer consumption spending (and save instead), interest rates do not adjust rapidly to forestall such a fall in spending by encouraging firms to invest.

Notice that Athreya makes no distinction between a reduction in consumption in which people shift into long-term real or financial assets and one in which people shift into holding cash. The two cases are hardly identical, but Athreya has nothing to say about the demand for money and its role in macroeconomics.

If they did, under what I will later describe as a “standard” production side for the economy, wages would, barring any countervailing forces, promptly rise (as the capital stock rises and makes workers more productive). In turn, output would not fall in response to pessimism.

What Athreya is saying is that if we assume that there is a reduction in the time preference of households, causing them to defer present consumption in order to increase their future consumption, the shift in time preference should be reflected in a rise in asset prices, causing an increase in the production of durable assets, and leading to an increase in wages insofar as the increase in the stock of fixed capital implies an increase in the marginal product of labor. Thus, if all the consequences of increased thrift are foreseen at the moment that current demand for output falls, there would be a smooth transition from the previous steady state corresponding to a high rate of time preference to the new steady state corresponding to a low rate of time preference.

Fine. If you assume that the economy always remains in full equilibrium, even in the transition from one steady state to another, because everyone has rational expectations, you will avoid a lot of unpleasantness. But what if entrepreneurial expectations do not change instantaneously, and the reduction in current demand for output corresponding to reduced spending on consumption causes entrepreneurs to reduce, not increase, their demand for capital equipment? If, after the shift in time preference, total spending actually falls, there may be a chain of disappointments in expectations, and a series of defaults on IOUs, culminating in a financial crisis. Pessimism may indeed be self-fulfilling. But Athreya has a just-so story to tell, and he seems satisfied that there is no other story to be told. Others may not be so easily satisfied, especially when his just-so story depends on a) the rational expectations assumption that many smart people have a hard time accepting as even remotely plausible, and b) the assumption that no trading takes place at disequilibrium prices. Athreya continues:

Thus, at least within the context of models in which households and firms are not routinely incorrect about the future, multiple self-fulfilling outcomes require particular features of the production side of the economy to prevail.

Actually what Athreya should have said is: “within the context of models in which households and firms always predict future prices correctly.”

In chapter 6, Athreya discusses how modern macroeconomics can and has contributed to the understanding of the financial crisis of 2007-08 and the subsequent downturn and anemic recovery. There is a lot of very useful information and discussion of various issues, especially in connection with banking and financial markets. But further comment at this point would be largely repetitive.

Anyway, despite my obvious and strong disagreements with much of what I read, I learned a lot from Athreya’s well-written and stimulating book, and I actually enjoyed reading it.

G. L. S. Shackle and the Indeterminacy of Economics

A post by Greg Hill, which inspired a recent post of my own, and Greg’s comment on that post, have reminded me of the importance of the undeservedly neglected English economist, G. L. S. Shackle, many of whose works I read and profited from as a young economist, but which I have hardly looked at for many years. A student of Hayek’s at the London School of Economics in the 1930s, Shackle renounced his early Hayekian views and the doctoral dissertation on capital theory that he had already started writing under Hayek’s supervision, after hearing a lecture by Joan Robinson in 1935 about the new theory of income and employment that Keynes was then in the final stages of writing up to be published the following year as The General Theory of Employment, Interest and Money. When Shackle, with considerable embarrassment, had to face Hayek to inform him that he could not finish the dissertation that he had started, no longer believing in what he had written, and having been converted to Keynes’s new theory. After hearing that Shackle was planning to find a new advisor under whom to write a new dissertation on another topic, Hayek, in a gesture of extraordinary magnanimity, responded that of course Shackle was free to write on whatever topic he desired, and that he would be happy to continue to serve as Shackle’s advisor regardless of the topic Shackle chose.

Although Shackle became a Keynesian, he retained and developed a number of characteristic Hayekian ideas (possibly extending them even further than Hayek would have), especially the notion that economic fluctuations result from the incompatibility between the plans that individuals are trying to implement, an incompatibility stemming from the imperfect and inconsistent expectations about the future that individuals hold, at least some plans therefore being doomed to failure. For Shackle the conception of a general equilibrium in which all individual plans are perfectly reconciled was a purely mental construct that might be useful in specifying the necessary conditions for the harmonization of individually formulated plans, but lacking descriptive or empirical content. Not only is a general equilibrium never in fact achieved, the very conception of such a state is at odds with the nature of reality. For example, the phenomenon of surprise (and, I would add, regret) is, in Shackle’s view, a characteristic feature of economic life, but under the assumption of most economists (though not of Knight, Keynes or Hayek) that all events can be at least be forecasted in terms of their underlying probability distributions, the phenomenon of surprise cannot be understood. There are some observed events – black swans in Taleb’s terminology – that we can’t incorporate into the standard probability calculus, and are completely inconsistent with the general equilibrium paradigm.

A rational-expectations model allows for stochastic variables (e.g., will it be rainy or sunny two weeks from tomorrow), but those variables are assumed to be drawn from distributions known by the agents, who can also correctly anticipate the future prices conditional on any realization (at a precisely known future moment in time) of a random variable. Thus, all outcomes correspond to expectations conditional on all future realizations of random variables; there are no surprises and no regrets. For a model to be correct and determinate in this sense, it must have accounted fully for all the non-random factors that could affect outcomes. If any important variable(s) were left out, the predictions of the model could not be correct. In other words, unless the model is properly specified, all causal factors having been identified and accounted for, the model will not generate correct predictions for all future states and all possible realizations of random variables. And unless the agents in the model can predict prices as accurately as the fully determined model can predict them, the model will not unfold through time on an equilibrium time path. This capability of forecasting future prices contingent on the realization of all random variables affecting the actual course of the model through time, is called rational expectations, which differs from perfect foresight only in being unable to predict in advance the realizations of the random variables. But all prices conditional on those realizations are correctly expected. Which is the more demanding assumption – rational expectations or perfect foresight — is actually not entirely clear to me.

Now there are two ways to think about rational expectations — one benign and one terribly misleading. The benign way is that the assumption of rational expectations is a means of checking the internal consistency of a model. In other words, if we are trying to figure out whether a model is coherent, we can suppose that the model is the true model; if we then posit that the expectations of the agents correspond to the solution of the model – i.e., the agents expect the equilibrium outcome – the solution of the model will confirm the expectations that have been plugged into the minds of the agents of the model. This is sometimes called a fixed-point property. If the model doesn’t have this fixed-point property, then there is something wrong with the model. So the assumption of rational expectations does not necessarily involve any empirical assertion about the real world, it does not necessarily assert anything about how expectations are formed or whether they ever are rational in the sense that agents can predict the outcome of the relevant model. The assumption merely allows the model to be tested for latent inconsistencies. Equilibrium expectations being a property of equilibrium, it makes no sense for equilibrium expectations not to generate an equilibrium.

But the other way of thinking about rational expectations is as an empirical assertion about what the expectations of people actually are or how those expectations are formed. If that is how we think about rational expectations, then we are saying people always anticipate the solution of the model. And if the model is internally consistent, then the empirical assumption that agents really do have rational expectations means that we are making an empirical assumption that the economy is in fact always in equilibrium, i.e., that is moving through time along an equilibrium path. If agents in the true model expect the equilibrium of the true model, the agents must be in equilibrium. To break out of that tight circle, either expectations have to be wrong (non-rational) or the model from which people derive their expectations must be wrong.

Of course, one way to finesse this problem is to say that the model is not actually true and expectations are not fully rational, but that the assumptions are close enough to being true for the model to be a decent approximation of reality. That is a defensible response, but one either has to take that assertion on faith, or there has to be strong evidence that the real world corresponds to the predictions of the model. Rational-expectations models do reasonably well in predicting the performance of economies near full employment, but not so well in periods like the Great Depression and the Little Depression. In other words, they work pretty well when we don’t need them, and not so well when we do need them.

The relevance of the rational-expectations assumption was discussed a year and a half ago by David Levine of Washington University. Levine was an undergraduate at UCLA after I had left, and went on to get his Ph.D. from MIT. He later returned to UCLA and held the Armen Alchian chair in economics from 1997 to 2006. Along with Michele Boldrin, Levine wrote a wonderful book Aginst Intellectual Monopoly. More recently he has written a little book (Is Behavioral Economics Doomed?) defending the rationality assumption in all its various guises, a book certainly worth reading even (or especially) if one doesn’t agree with all of its conclusions. So, although I have a high regard for Levine’s capabilities as an economist, I am afraid that I have to criticize what he has to say about rational expectations. I should also add that despite my criticism of Levine’s defense of rational expectations, I think the broader point that he makes that people do learn from experience, and that public policies should not be premised on the assumption that people will not eventually figure out how those policies are working, is valid.

In particular, let’s look at a post that Levine contributed to the Huffington Post blog defending the economics profession against the accusation that the economics profession is useless as demonstrated by their failure to predict the financial crisis of 2008. To counter this charge, Levine compared economics to physics — not necessarily the strategy I would have recommended for casting economics in a favorable light, but that’s merely an aside. Just as there is an uncertainty principle in physics, which says that you cannot identify simultaneously both the location and the speed of an electron, there’s an analogous uncertainty principle in economics, which says that the forecast affects the outcome.

The uncertainty principle in economics arises from a simple fact: we are all actors in the economy and the models we use determine how we behave. If a model is discovered to be correct, then we will change our behavior to reflect our new understanding of reality — and when enough of us do so, the original model stops being correct. In this sense future human behavior must necessarily be uncertain.

Levine is certainly right that insofar as the discovery of a new model changes expectations, the model itself can change outcomes. If the model predicts a crisis, the model, if it is believed, may be what causes the crisis. Fair enough, but Levine believes that this uncertainty principle entails the rationality of expectations.

The uncertainty principle in economics leads directly to the theory of rational expectations. Just as the uncertainty principle in physics is consistent with the probabilistic predictions of quantum mechanics (there is a 20% chance this particle will appear in this location with this speed) so the uncertainty principle in economics is consistent with the probabilistic predictions of rational expectations (there is a 3% chance of a stock market crash on October 28).

This claim, if I understand it, is shocking. The equations of quantum mechanics may be able to predict the probability that a particle will appear at given location with a given speed, I am unaware of any economic model that can provide even an approximately accurate prediction of the probability that a financial crisis will occur within a given time period.

Note what rational expectations are not: they are often confused with perfect foresight — meaning we perfectly anticipate what will happen in the future. While perfect foresight is widely used by economists for studying phenomena such as long-term growth where the focus is not on uncertainty — it is not the theory used by economists for studying recessions, crises or the business cycle. The most widely used theory is called DSGE for Dynamic Stochastic General Equilibrium. Notice the word stochastic — it means random — and this theory reflects the necessary randomness brought about by the uncertainty principle.

I have already observed that the introduction of random variables into a general equilibrium is not a significant relaxation of the predictive capacities of agents — and perhaps not even a relaxation, but an enhancement of the predictive capacities of the agents. The problem with this distinction between perfect foresight and stochastic disturbances is that there is no relaxation of the requirement that all agents share the same expectations of all future prices in all possible future states of the world. The world described is a world without surprise and without regret. From the standpoint of the informational requirements imposed on agents, the distinction between perfect foresight and rational expectations is not worth discussing.

In simple language what rational expectations means is “if people believe this forecast it will be true.”

Well, I don’t know about that. If the forecast is derived from a consistent, but empirically false, model, the assumption of rational expectations will ensure that the forecast of the model coincides with what people expect. But the real world may not cooperate, producing an outcome different from what was forecast and what was rationally expected. The expectation of a correct forecast does not guarantee the truth of the forecast unless the model generating the forecast is true. Is Levine convinced that the models used by economists are sufficiently close to being true to generate valid forecasts with a frequency approaching that of the Newtonian model in forecasting, say, solar eclipses? More generally, Levine seems to be confusing the substantive content of a theory — what motivates the agents populating theory and what constrains the choices of those agents in their interactions with other agents and with nature — with an assumption about how agents form expectations. This confusion becomes palpable in the next sentence.

By contrast if a theory is not one of rational expectations it means “if people believe this forecast it will not be true.”

I don’t what it means to say “a theory is not one of rational expectations.” Almost every economic theory depends in some way on the expectations of the agents populating the theory. There are many possible assumptions to make about how expectations are formed. Most of those assumptions about how expectations are formed allow, though they do not require, expectations to correspond to the predictions of the model. In other words, expectations can be viewed as an equilibrating variable of a model. To make a stronger assertion than that is to make an empirical claim about how closely the real world corresponds to the equilibrium state of the model. Levine goes on to make just such an assertion. Referring to a non-rational-expectations theory, he continues:

Obviously such a theory has limited usefulness. Or put differently: if there is a correct theory, eventually most people will believe it, so it must necessarily be rational expectations. Any other theory has the property that people must forever disbelieve the theory regardless of overwhelming evidence — for as soon as the theory is believed it is wrong.

It is hard to interpret what Levine is saying. What theory or class of theories is being dismissed as having limited usefulness? Presumably, all theories that are not “of rational expectations.” OK, but why is their usefulness limited? Is it that they are internally inconsistent, i.e., they lack the fixed-point property whose absence signals internal inconsistency, or is there some other deficiency? Levine seems to be conflating the two very different ways of understanding rational expectations (a test for internal inconsistency v. a substantive empirical hypothesis). Perhaps that’s why Levine feels compelled to paraphrase. But the paraphrase makes it clear that he is not distinguishing between the substantive theory and the specific expectational hypothesis. I also can’t tell whether his premise (“if there is a correct theory”) is meant to be a factual statement or a hypothetical? If it is the former, it would be nice if the correct theory were identified. If the correct theory can’t even be identified, how are people supposed to know which theory they are supposed to believe, so that they can form their expectations accordingly? Rather than an explanation for why the correct rational-expectations theory will eventually be recognized, this sounds like an explanation for why the correct theory is unknowable. Unless, of course, we assume that the rational expectations are a necessary feature of reality in which case, people have been forming expectations based on the one true model all along, and all economists are doing is trying to formalize a pre-existing process of expectations formation that already solves the problem. But the rest of his post (see part two here) makes it clear that Levine (properly) does not hold that extreme position about rational expectations.

So in the end , I find myself unable to make sense of rational expectations except as a test for the internal consistency of an economic model, and, perhaps also, as a tool for policy analysis. Just as one does not want to work with a model that is internally inconsistent, one does not want to formulate a policy based on the assumption that people will fail to understand the effects of the policy being proposed. But as a tool for understanding how economies actually work and what can go wrong, the rational-expectations assumption abstracts from precisely the key problem, the inconsistencies between the expectations held by different agents, which are an inevitable, though certainly not the only, cause of the surprise and regret that are so characteristic of real life.


About Me

David Glasner
Washington, DC

I am an economist at the Federal Trade Commission. Nothing that you read on this blog necessarily reflects the views of the FTC or the individual commissioners. Although I work at the FTC as an antitrust economist, most of my research and writing has been on monetary economics and policy and the history of monetary theory. In my book Free Banking and Monetary Reform, I argued for a non-Monetarist non-Keynesian approach to monetary policy, based on a theory of a competitive supply of money. Over the years, I have become increasingly impressed by the similarities between my approach and that of R. G. Hawtrey and hope to bring Hawtrey's unduly neglected contributions to the attention of a wider audience.

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