Archive for the 'macroeconomics' Category

Price Stickiness and Macroeconomics

Noah Smith has a classically snide rejoinder to Stephen Williamson’s outrage at Noah’s Bloomberg paean to price stickiness and to the classic Ball and Maniw article on the subject, an article that provoked an embarrassingly outraged response from Robert Lucas when published over 20 years ago. I don’t know if Lucas ever got over it, but evidently Williamson hasn’t.

Now to be fair, Lucas’s outrage, though misplaced, was understandable, at least if one understands that Lucas was so offended by the ironic tone in which Ball and Mankiw cast themselves as defenders of traditional macroeconomics – including both Keynesians and Monetarists – against the onslaught of “heretics” like Lucas, Sargent, Kydland and Prescott that he just stopped reading after the first few pages and then, in a fit of righteous indignation, wrote a diatribe attacking Ball and Mankiw as religious fanatics trying to halt the progress of science as if that was the real message of the paper – not, to say the least, a very sophisticated reading of what Ball and Mankiw wrote.

While I am not hostile to the idea of price stickiness — one of the most popular posts I have written being an attempt to provide a rationale for the stylized (though controversial) fact that wages are stickier than other input, and most output, prices — it does seem to me that there is something ad hoc and superficial about the idea of price stickiness and about many explanations, including those offered by Ball and Mankiw, for price stickiness. I think that the negative reactions that price stickiness elicits from a lot of economists — and not only from Lucas and Williamson — reflect a feeling that price stickiness is not well grounded in any economic theory.

Let me offer a slightly different criticism of price stickiness as a feature of macroeconomic models, which is simply that although price stickiness is a sufficient condition for inefficient macroeconomic fluctuations, it is not a necessary condition. It is entirely possible that even with highly flexible prices, there would still be inefficient macroeconomic fluctuations. And the reason why price flexibility, by itself, is no guarantee against macroeconomic contractions is that macroeconomic contractions are caused by disequilibrium prices, and disequilibrium prices can prevail regardless of how flexible prices are.

The usual argument is that if prices are free to adjust in response to market forces, they will adjust to balance supply and demand, and an equilibrium will be restored by the automatic adjustment of prices. That is what students are taught in Econ 1. And it is an important lesson, but it is also a “partial” lesson. It is partial, because it applies to a single market that is out of equilibrium. The implicit assumption in that exercise is that nothing else is changing, which means that all other markets — well, not quite all other markets, but I will ignore that nuance – are in equilibrium. That’s what I mean when I say (as I have done before) that just as macroeconomics needs microfoundations, microeconomics needs macrofoundations.

Now it’s pretty easy to show that in a single market with an upward-sloping supply curve and a downward-sloping demand curve, that a price-adjustment rule that raises price when there’s an excess demand and reduces price when there’s an excess supply will lead to an equilibrium market price. But that simple price-adjustment rule is hard to generalize when many markets — not just one — are in disequilibrium, because reducing disequilibrium in one market may actually exacerbate disequilibrium, or create a disequilibrium that wasn’t there before, in another market. Thus, even if there is an equilibrium price vector out there, which, if it were announced to all economic agents, would sustain a general equilibrium in all markets, there is no guarantee that following the standard price-adjustment rule of raising price in markets with an excess demand and reducing price in markets with an excess supply will ultimately lead to the equilibrium price vector. Even more disturbing, the standard price-adjustment rule may not, even under a tatonnement process in which no trading is allowed at disequilibrium prices, lead to the discovery of the equilibrium price vector. Of course, in the real world trading occurs routinely at disequilibrium prices, so that the “mechanical” forces tending an economy toward equilibrium are even weaker than the standard analysis of price-adjustment would suggest.

This doesn’t mean that an economy out of equilibrium has no stabilizing tendencies; it does mean that those stabilizing tendencies are not very well understood, and we have almost no formal theory with which to describe how such an adjustment process leading from disequilibrium to equilibrium actually works. We just assume that such a process exists. Franklin Fisher made this point 30 years ago in an important, but insufficiently appreciated, volume Disequilibrium Foundations of Equilibrium Economics. But the idea goes back even further: to Hayek’s important work on intertemporal equilibrium, especially his classic paper “Economics and Knowledge,” formalized by Hicks in the temporary-equilibrium model described in Value and Capital.

The key point made by Hayek in this context is that there can be an intertemporal equilibrium if and only if all agents formulate their individual plans on the basis of the same expectations of future prices. If their expectations for future prices are not the same, then any plans based on incorrect price expectations will have to be revised, or abandoned altogether, as price expectations are disappointed over time. For price adjustment to lead an economy back to equilibrium, the price adjustment must converge on an equilibrium price vector and on correct price expectations. But, as Hayek understood in 1937, and as Fisher explained in a dense treatise 30 years ago, we have no economic theory that explains how such a price vector, even if it exists, is arrived at, and even under a tannonement process, much less under decentralized price setting. Pinning the blame on this vague thing called price stickiness doesn’t address the deeper underlying theoretical issue.

Of course for Lucas et al. to scoff at price stickiness on these grounds is a bit rich, because Lucas and his followers seem entirely comfortable with assuming that the equilibrium price vector is rationally expected. Indeed, rational expectation of the equilibrium price vector is held up by Lucas as precisely the microfoundation that transformed the unruly field of macroeconomics into a real science.

Traffic Jams and Multipliers

Since my previous post which I closed by quoting the abstract of Brian Arthur’s paper “Complexity Economics: A Different Framework for Economic Thought,” I have been reading his paper and some of the papers he cites, especially Magda Fontana’s paper “The Santa Fe Perspective on Economics: Emerging Patterns in the Science of Complexity,” and Mark Blaug’s paper “The Formalist Revolution of the 1950s.” The papers bring together a number of themes that I have been emphasizing in previous posts on what I consider the misguided focus of modern macroeconomics on rational-expectations equilibrium as the organizing principle of macroeconomic theory. Among these themes are the importance of coordination failures in explaining macroeconomic fluctuations, the inappropriateness of the full general-equilibrium paradigm in macroeconomics, the mistaken transformation of microfoundations from a theoretical problem to be solved into an absolute methodological requirement to be insisted upon (almost exactly analogous to the absurd transformation of the mind-body problem into a dogmatic insistence that the mind is merely a figment of our own imagination), or, stated another way, a recognition that macrofoundations are just as necessary for economics as microfoundations.

Let me quote again from Arthur’s essay; this time a beautiful passage which captures the interdependence between the micro and macro perspectives

To look at the economy, or areas within the economy, from a complexity viewpoint then would mean asking how it evolves, and this means examining in detail how individual agents’ behaviors together form some outcome and how this might in turn alter their behavior as a result. Complexity in other words asks how individual behaviors might react to the pattern they together create, and how that pattern would alter itself as a result. This is often a difficult question; we are asking how a process is created from the purposed actions of multiple agents. And so economics early in its history took a simpler approach, one more amenable to mathematical analysis. It asked not how agents’ behaviors would react to the aggregate patterns these created, but what behaviors (actions, strategies, expectations) would be upheld by — would be consistent with — the aggregate patterns these caused. It asked in other words what patterns would call for no changes in microbehavior, and would therefore be in stasis, or equilibrium. (General equilibrium theory thus asked what prices and quantities of goods produced and consumed would be consistent with — would pose no incentives for change to — the overall pattern of prices and quantities in the economy’s markets. Classical game theory asked what strategies, moves, or allocations would be consistent with — would be the best course of action for an agent (under some criterion) — given the strategies, moves, allocations his rivals might choose. And rational expectations economics asked what expectations would be consistent with — would on average be validated by — the outcomes these expectations together created.)

This equilibrium shortcut was a natural way to examine patterns in the economy and render them open to mathematical analysis. It was an understandable — even proper — way to push economics forward. And it achieved a great deal. Its central construct, general equilibrium theory, is not just mathematically elegant; in modeling the economy it re-composes it in our minds, gives us a way to picture it, a way to comprehend the economy in its wholeness. This is extremely valuable, and the same can be said for other equilibrium modelings: of the theory of the firm, of international trade, of financial markets.

But there has been a price for this equilibrium finesse. Economists have objected to it — to the neoclassical construction it has brought about — on the grounds that it posits an idealized, rationalized world that distorts reality, one whose underlying assumptions are often chosen for analytical convenience. I share these objections. Like many economists, I admire the beauty of the neoclassical economy; but for me the construct is too pure, too brittle — too bled of reality. It lives in a Platonic world of order, stasis, knowableness, and perfection. Absent from it is the ambiguous, the messy, the real. (pp. 2-3)

Later in the essay, Arthur provides a simple example of a non-equilibrium complex process: traffic flow.

A typical model would acknowledge that at close separation from cars in front, cars lower their speed, and at wide separation they raise it. A given high density of traffic of N cars per mile would imply a certain average separation, and cars would slow or accelerate to a speed that corresponds. Trivially, an equilibrium speed emerges, and if we were restricting solutions to equilibrium that is all we would see. But in practice at high density, a nonequilibrium phenomenon occurs. Some car may slow down — its driver may lose concentration or get distracted — and this might cause cars behind to slow down. This immediately compresses the flow, which causes further slowing of the cars behind. The compression propagates backwards, traffic backs up, and a jam emerges. In due course the jam clears. But notice three things. The phenomenon’s onset is spontaneous; each instance of it is unique in time of appearance, length of propagation, and time of clearing. It is therefore not easily captured by closed-form solutions, but best studied by probabilistic or statistical methods. Second, the phenomenon is temporal, it emerges or happens within time, and cannot appear if we insist on equilibrium. And third, the phenomenon occurs neither at the micro-level (individual car level) nor at the macro-level (overall flow on the road) but at a level in between — the meso-level. (p. 9)

This simple example provides an excellent insight into why macroeconomic reasoning can be led badly astray by focusing on the purely equilibrium relationships characterizing what we now think of as microfounded models. In arguing against the Keynesian multiplier analysis supposedly justifying increased government spending as a countercyclical tool, Robert Barro wrote the following in an unfortunate Wall Street Journal op-ed piece, which I have previously commented on here and here.

Keynesian economics argues that incentives and other forces in regular economics are overwhelmed, at least in recessions, by effects involving “aggregate demand.” Recipients of food stamps use their transfers to consume more. Compared to this urge, the negative effects on consumption and investment by taxpayers are viewed as weaker in magnitude, particularly when the transfers are deficit-financed.

Thus, the aggregate demand for goods rises, and businesses respond by selling more goods and then by raising production and employment. The additional wage and profit income leads to further expansions of demand and, hence, to more production and employment. As per Mr. Vilsack, the administration believes that the cumulative effect is a multiplier around two.

If valid, this result would be truly miraculous. The recipients of food stamps get, say, $1 billion but they are not the only ones who benefit. Another $1 billion appears that can make the rest of society better off. Unlike the trade-off in regular economics, that extra $1 billion is the ultimate free lunch.

How can it be right? Where was the market failure that allowed the government to improve things just by borrowing money and giving it to people? Keynes, in his “General Theory” (1936), was not so good at explaining why this worked, and subsequent generations of Keynesian economists (including my own youthful efforts) have not been more successful.

In the disequilibrium environment of a recession, it is at least possible that injecting additional spending into the economy could produce effects that a similar injection of spending, under “normal” macro conditions, would not produce, just as somehow withdrawing a few cars from a congested road could increase the average speed of all the remaining cars on the road, by a much greater amount than would withdrawing a few cars from an uncongested road. In other words, microresponses may be sensitive to macroconditions.

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.


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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