Archive for the 'microfoundations' Category

Dr. Popper: Or How I Learned to Stop Worrying and Love Metaphysics

Introduction to Falsificationism

Although his reputation among philosophers was never quite as exalted as it was among non-philosophers, Karl Popper was a pre-eminent figure in 20th century philosophy. As a non-philosopher, I won’t attempt to adjudicate which take on Popper is the more astute, but I think I can at least sympathize, if not fully agree, with philosophers who believe that Popper is overrated by non-philosophers. In an excellent blog post, Phillipe Lemoine gives a good explanation of why philosophers look askance at falsificationism, Popper’s most important contribution to philosophy.

According to Popper, what distinguishes or demarcates a scientific statement from a non-scientific (metaphysical) statement is whether the statement can, or could be, disproved or refuted – falsified (in the sense of being shown to be false not in the sense of being forged, misrepresented or fraudulently changed) – by an actual or potential observation. Vulnerability to potentially contradictory empirical evidence, according to Popper, is what makes science special, allowing it to progress through a kind of dialectical process of conjecture (hypothesis) and refutation (empirical testing) leading to further conjecture and refutation and so on.

Theories purporting to explain anything and everything are thus non-scientific or metaphysical. Claiming to be able to explain too much is a vice, not a virtue, in science. Science advances by risk-taking, not by playing it safe. Trying to explain too much is actually playing it safe. If you’re not willing to take the chance of putting your theory at risk, by saying that this and not that will happen — rather than saying that this or that will happen — you’re playing it safe. This view of science, portrayed by Popper in modestly heroic terms, was not unappealing to scientists, and in part accounts for the positive reception of Popper’s work among scientists.

But this heroic view of science, as Lemoine nicely explains, was just a bit oversimplified. Theories never exist in a vacuum, there is always implicit or explicit background knowledge that informs and provides context for the application of any theory from which a prediction is deduced. To deduce a prediction from any theory, background knowledge, including complementary theories that are presumed to be valid for purposes of making a prediction, is necessary. Any prediction relies not just on a single theory but on a system of related theories and auxiliary assumptions.

So when a prediction is deduced from a theory, and the predicted event is not observed, it is never unambiguously clear which of the multiple assumptions underlying the prediction is responsible for the failure of the predicted event to be observed. The one-to-one logical dependence between a theory and a prediction upon which Popper’s heroic view of science depends doesn’t exist. Because the heroic view of science is too simplified, Lemoine considers it false, at least in the naïve and heroic form in which it is often portrayed by its proponents.

But, as Lemoine himself acknowledges, Popper was not unaware of these issues and actually dealt with some if not all of them. Popper therefore dismissed those criticisms pointing to his various acknowledgments and even anticipations of and responses to the criticisms. Nevertheless, his rhetorical style was generally not to qualify his position but to present it in stark terms, thereby reinforcing the view of his critics that he actually did espouse the naïve version of falsificationism that, only under duress, would be toned down to meet the objections raised to the usual unqualified version of his argument. Popper after all believed in making bold conjectures and framing a theory in the strongest possible terms and characteristically adopted an argumentative and polemical stance in staking out his positions.

Toned-Down Falsificationism

In his tone-downed version of falsificationism, Popper acknowledged that one can never know if a prediction fails because the underlying theory is false or because one of the auxiliary assumptions required to make the prediction is false, or even because of an error in measurement. But that acknowledgment, Popper insisted, does not refute falsificationism, because falsificationism is not a scientific theory about how scientists do science; it is a normative theory about how scientists ought to do science. The normative implication of falsificationism is that scientists should not try to shield their theories by making just-so adjustments in their theories through ad hoc auxiliary assumptions, e.g., ceteris paribus assumptions, to shield their theories from empirical disproof. Rather they should accept the falsification of their theories when confronted by observations that conflict with the implications of their theories and then formulate new and better theories to replace the old ones.

But a strict methodological rule against adjusting auxiliary assumptions or making further assumptions of an ad hoc nature would have ruled out many fruitful theoretical developments resulting from attempts to account for failed predictions. For example, the planet Neptune was discovered in 1846 by scientists who posited (ad hoc) the existence of another planet to explain why the planet Uranus did not follow its predicted path. Rather than conclude that the Newtonian theory was falsified by the failure of Uranus to follow the orbital path predicted by Newtonian theory, the French astronomer Urbain Le Verrier posited the existence of another planet that would account for the path actually followed by Uranus. Now in this case, it was possible to observe the predicted position of the new planet, and its discovery in the predicted location turned out to be a sensational confirmation of Newtonian theory.

Popper therefore admitted that making an ad hoc assumption in order to save a theory from refutation was permissible under his version of normative faslisificationism, but only if the ad hoc assumption was independently testable. But suppose that, under the circumstances, it would have been impossible to observe the existence of the predicted planet, at least with the observational tools then available, making the ad hoc assumption testable only in principle, but not in practice. Strictly adhering to Popper’s methodological requirement of being able to test independently any ad hoc assumption would have meant accepting the refutation of the Newtonian theory rather than positing the untestable — but true — ad hoc other-planet hypothesis to account for the failed prediction of the orbital path of Uranus.

My point is not that ad hoc assumptions to save a theory from falsification are ok, but to point out that a strict methodological rules requiring rejection of any theory once it appears to be contradicted by empirical evidence and prohibiting the use of any ad hoc assumption to save the theory unless the ad hoc assumption is independently testable might well lead to the wrong conclusion given the nuances and special circumstances associated with every case in which a theory seems to be contradicted by observed evidence. Such contradictions are rarely so blatant that theory cannot be reconciled with the evidence. Indeed, as Popper himself recognized, all observations are themselves understood and interpreted in the light of theoretical presumptions. It is only in extreme cases that evidence cannot be interpreted in a way that more or less conforms to the theory under consideration. At first blush, the Copernican heliocentric view of the world seemed obviously contradicted by direct sensory observation that earth seems flat and the sun rise and sets. Empirical refutation could be avoided only by providing an alternative interpretation of the sensory data that could be reconciled with the apparent — and obvious — flatness and stationarity of the earth and the movement of the sun and moon in the heavens.

So the problem with falsificationism as a normative theory is that it’s not obvious why a moderately good, but less than perfect, theory should be abandoned simply because it’s not perfect and suffers from occasional predictive failures. To be sure, if a better theory than the one under consideration is available, predicting correctly whenever the one under consideration predicts correctly and predicting more accurately than the one under consideration when the latter fails to predict correctly, the alternative theory is surely preferable, but that simply underscores the point that evaluating any theory in isolation is not very important. After all, every theory, being a simplification, is an imperfect representation of reality. It is only when two or more theories are available that scientists must try to determine which of them is preferable.

Oakeshott and the Poverty of Falsificationism

These problems with falsificationism were brought into clearer focus by Michael Oakeshott in his famous essay “Rationalism in Politics,” which though not directed at Popper himself (whose colleague at the London School of Economics he was) can be read as a critique of Popper’s attempt to prescribe methodological rules for scientists to follow in carrying out their research. Methodological rules of the kind propounded by Popper are precisely the sort of supposedly rational rules of practice intended to ensure the successful outcome of an undertaking that Oakeshott believed to be ill-advised and hopelessly naïve. The rationalist conceit in Oakesott’s view is that there are demonstrably correct answers to practical questions and that practical activity is rational only when it is based on demonstrably true moral or causal rules.

The entry on Michael Oakeshott in the Stanford Encyclopedia of Philosophy summarizes Oakeshott’s position as follows:

The error of Rationalism is to think that making decisions simply requires skill in the technique of applying rules or calculating consequences. In an early essay on this theme, Oakeshott distinguishes between “technical” and “traditional” knowledge. Technical knowledge is of facts or rules that can be easily learned and applied, even by those who are without experience or lack the relevant skills. Traditional knowledge, in contrast, means “knowing how” rather than “knowing that” (Ryle 1949). It is acquired by engaging in an activity and involves judgment in handling facts or rules (RP 12–17). The point is not that rules cannot be “applied” but rather that using them skillfully or prudently means going beyond the instructions they provide.

The idea that a scientist’s decision about when to abandon one theory and replace it with another can be reduced to the application of a Popperian falsificationist maxim ignores all the special circumstances and all the accumulated theoretical and practical knowledge that a truly expert scientist will bring to bear in studying and addressing such a problem. Here is how Oakeshott addresses the problem in his famous essay.

These two sorts of knowledge, then, distinguishable but inseparable, are the twin components of the knowledge involved in every human activity. In a practical art such as cookery, nobody supposes that the knowledge that belongs to the good cook is confined to what is or what may be written down in the cookery book: technique and what I have called practical knowledge combine to make skill in cookery wherever it exists. And the same is true of the fine arts, of painting, of music, of poetry: a high degree of technical knowledge, even where it is both subtle and ready, is one thing; the ability to create a work of art, the ability to compose something with real musical qualities, the ability to write a great sonnet, is another, and requires in addition to technique, this other sort of knowledge. Again these two sorts of knowledge are involved in any genuinely scientific activity. The natural scientist will certainly make use of observation and verification that belong to his technique, but these rules remain only one of the components of his knowledge; advances in scientific knowledge were never achieved merely by following the rules. . . .

Technical knowledge . . . is susceptible of formulation in rules, principles, directions, maxims – comprehensively, in propositions. It is possible to write down technical knowledge in a book. Consequently, it does not surprise us that when an artist writes about his art, he writes only about the technique of his art. This is so, not because he is ignorant of what may be called asesthetic element, or thinks it unimportant, but because what he has to say about that he has said already (if he is a painter) in his pictures, and he knows no other way of saying it. . . . And it may be observed that this character of being susceptible of precise formulation gives to technical knowledge at least the appearance of certainty: it appears to be possible to be certain about a technique. On the other hand, it is characteristic of practical knowledge that it is not susceptible of formulation of that kind. Its normal expression is in a customary or traditional way of doing things, or, simply, in practice. And this gives it the appearance of imprecision and consequently of uncertainty, of being a matter of opinion, of probability rather than truth. It is indeed knowledge that is expressed in taste or connoisseurship, lacking rigidity and ready for the impress of the mind of the learner. . . .

Technical knowledge, in short, an be both taught and learned in the simplest meanings of these words. On the other hand, practical knowledge can neither be taught nor learned, but only imparted and acquired. It exists only in practice, and the only way to acquire it is by apprenticeship to a master – not because the master can teach it (he cannot), but because it can be acquired only by continuous contact with one who is perpetually practicing it. In the arts and in natural science what normally happens is that the pupil, in being taught and in learning the technique from his master, discovers himself to have acquired also another sort of knowledge than merely technical knowledge, without it ever having been precisely imparted and often without being able to say precisely what it is. Thus a pianist acquires artistry as well as technique, a chess-player style and insight into the game as well as knowledge of the moves, and a scientist acquires (among other things) the sort of judgement which tells him when his technique is leading him astray and the connoisseurship which enables him to distinguish the profitable from the unprofitable directions to explore.

Now, as I understand it, Rationalism is the assertion that what I have called practical knowledge is not knowledge at all, the assertion that, properly speaking, there is no knowledge which is not technical knowledge. The Rationalist holds that the only element of knowledge involved in any human activity is technical knowledge and that what I have called practical knowledge is really only a sort of nescience which would be negligible if it were not positively mischievous. (Rationalism in Politics and Other Essays, pp. 12-16)

Almost three years ago, I attended the History of Economics Society meeting at Duke University at which Jeff Biddle of Michigan State University delivered his Presidential Address, “Statistical Inference in Economics 1920-1965: Changes in Meaning and Practice, published in the June 2017 issue of the Journal of the History of Economic Thought. The paper is a remarkable survey of the differing attitudes towards using formal probability theory as the basis for making empirical inferences from the data. The underlying assumptions of probability theory about the nature of the data were widely viewed as being too extreme to make probability theory an acceptable basis for empirical inferences from the data. However, the early negative attitudes toward accepting probability theory as the basis for making statistical inferences from data were gradually overcome (or disregarded). But as late as the 1960s, even though econometric techniques were becoming more widely accepted, a great deal of empirical work, including by some of the leading empirical economists of the time, avoided using the techniques of statistical inference to assess empirical data using regression analysis. Only in the 1970s was there a rapid sea-change in professional opinion that made statistical inference based on explicit probabilisitic assumptions about underlying data distributions the requisite technique for drawing empirical inferences from the analysis of economic data. In the final section of his paper, Biddle offers an explanation for this rapid change in professional attitude toward the use of probabilistic assumptions about data distributions as the required method of the empirical assessment of economic data.

By the 1970s, there was a broad consensus in the profession that inferential methods justified by probability theory—methods of producing estimates, of assessing the reliability of those estimates, and of testing hypotheses—were not only applicable to economic data, but were a necessary part of almost any attempt to generalize on the basis of economic data. . . .

This paper has been concerned with beliefs and practices of economists who wanted to use samples of statistical data as a basis for drawing conclusions about what was true, or probably true, in the world beyond the sample. In this setting, “mechanical objectivity” means employing a set of explicit and detailed rules and procedures to produce conclusions that are objective in the sense that if many different people took the same statistical information, and followed the same rules, they would come to exactly the same conclusions. The trustworthiness of the conclusion depends on the quality of the method. The classical theory of inference is a prime example of this sort of mechanical objectivity.

Porter [Trust in Numbers: The Pursuit of Objectivity in Science and Public Life] contrasts mechanical objectivity with an objectivity based on the “expert judgment” of those who analyze data. Expertise is acquired through a sanctioned training process, enhanced by experience, and displayed through a record of work meeting the approval of other experts. One’s faith in the analyst’s conclusions depends on one’s assessment of the quality of his disciplinary expertise and his commitment to the ideal of scientific objectivity. Elmer Working’s method of determining whether measured correlations represented true cause-and-effect relationships involved a good amount of expert judgment. So, too, did Gregg Lewis’s adjustments of the various estimates of the union/non-union wage gap, in light of problems with the data and peculiarities of the times and markets from which they came. Keynes and Persons pushed for a definition of statistical inference that incorporated space for the exercise of expert judgment; what Arthur Goldberger and Lawrence Klein referred to as ‘statistical inference’ had no explicit place for expert judgment.

Speaking in these terms, I would say that in the 1920s and 1930s, empirical economists explicitly acknowledged the need for expert judgment in making statistical inferences. At the same time, mechanical objectivity was valued—there are many examples of economists of that period employing rule-oriented, replicable procedures for drawing conclusions from economic data. The rejection of the classical theory of inference during this period was simply a rejection of one particular means for achieving mechanical objectivity. By the 1970s, however, this one type of mechanical objectivity had become an almost required part of the process of drawing conclusions from economic data, and was taught to every economics graduate student.

Porter emphasizes the tension between the desire for mechanically objective methods and the belief in the importance of expert judgment in interpreting statistical evidence. This tension can certainly be seen in economists’ writings on statistical inference throughout the twentieth century. However, it would be wrong to characterize what happened to statistical inference between the 1940s and the 1970s as a displace-ment of procedures requiring expert judgment by mechanically objective procedures. In the econometric textbooks published after 1960, explicit instruction on statistical inference was largely limited to instruction in the mechanically objective procedures of the classical theory of inference. It was understood, however, that expert judgment was still an important part of empirical economic analysis, particularly in the specification of the models to be estimated. But the disciplinary knowledge needed for this task was to be taught in other classes, using other textbooks.

And in practice, even after the statistical model had been chosen, the estimates and standard errors calculated, and the hypothesis tests conducted, there was still room to exercise a fair amount of judgment before drawing conclusions from the statistical results. Indeed, as Marcel Boumans (2015, pp. 84–85) emphasizes, no procedure for drawing conclusions from data, no matter how algorithmic or rule bound, can dispense entirely with the need for expert judgment. This fact, though largely unacknowledged in the post-1960s econometrics textbooks, would not be denied or decried by empirical economists of the 1970s or today.

This does not mean, however, that the widespread embrace of the classical theory of inference was simply a change in rhetoric. When application of classical inferential procedures became a necessary part of economists’ analyses of statistical data, the results of applying those procedures came to act as constraints on the set of claims that a researcher could credibly make to his peers on the basis of that data. For example, if a regression analysis of sample data yielded a large and positive partial correlation, but the correlation was not “statistically significant,” it would simply not be accepted as evidence that the “population” correlation was positive. If estimation of a statistical model produced a significant estimate of a relationship between two variables, but a statistical test led to rejection of an assumption required for the model to produce unbiased estimates, the evidence of a relationship would be heavily discounted.

So, as we consider the emergence of the post-1970s consensus on how to draw conclusions from samples of statistical data, there are arguably two things to be explained. First, how did it come about that using a mechanically objective procedure to generalize on the basis of statistical measures went from being a choice determined by the preferences of the analyst to a professional requirement, one that had real con-sequences for what economists would and would not assert on the basis of a body of statistical evidence? Second, why was it the classical theory of inference that became the required form of mechanical objectivity? . . .

Perhaps searching for an explanation that focuses on the classical theory of inference as a means of achieving mechanical objectivity emphasizes the wrong characteristic of that theory. In contrast to earlier forms of mechanical objectivity used by economists, such as standardized methods of time series decomposition employed since the 1920s, the classical theory of inference is derived from, and justified by, a body of formal mathematics with impeccable credentials: modern probability theory. During a period when the value placed on mathematical expression in economics was increasing, it may have been this feature of the classical theory of inference that increased its perceived value enough to overwhelm long-standing concerns that it was not applicable to economic data. In other words, maybe the chief causes of the profession’s embrace of the classical theory of inference are those that drove the broader mathematization of economics, and one should simply look to the literature that explores possible explanations for that phenomenon rather than seeking a special explanation of the embrace of the classical theory of inference.

I would suggest one more factor that might have made the classical theory of inference more attractive to economists in the 1950s and 1960s: the changing needs of pedagogy in graduate economics programs. As I have just argued, since the 1920s, economists have employed both judgment based on expertise and mechanically objective data-processing procedures when generalizing from economic data. One important difference between these two modes of analysis is how they are taught and learned. The classical theory of inference as used by economists can be taught to many students simultaneously as a set of rules and procedures, recorded in a textbook and applicable to “data” in general. This is in contrast to the judgment-based reasoning that combines knowledge of statistical methods with knowledge of the circumstances under which the particular data being analyzed were generated. This form of reasoning is harder to teach in a classroom or codify in a textbook, and is probably best taught using an apprenticeship model, such as that which ideally exists when an aspiring economist writes a thesis under the supervision of an experienced empirical researcher.

During the 1950s and 1960s, the ratio of PhD candidates to senior faculty in PhD-granting programs was increasing rapidly. One consequence of this, I suspect, was that experienced empirical economists had less time to devote to providing each interested student with individualized feedback on his attempts to analyze data, so that relatively more of a student’s training in empirical economics came in an econometrics classroom, using a book that taught statistical inference as the application of classical inference procedures. As training in empirical economics came more and more to be classroom training, competence in empirical economics came more and more to mean mastery of the mechanically objective techniques taught in the econometrics classroom, a competence displayed to others by application of those techniques. Less time in the training process being spent on judgment-based procedures for interpreting statistical results meant fewer researchers using such procedures, or looking for them when evaluating the work of others.

This process, if indeed it happened, would not explain why the classical theory of inference was the particular mechanically objective method that came to dominate classroom training in econometrics; for that, I would again point to the classical theory’s link to a general and mathematically formalistic theory. But it does help to explain why the application of mechanically objective procedures came to be regarded as a necessary means of determining the reliability of a set of statistical measures and the extent to which they provided evidence for assertions about reality. This conjecture fits in with a larger possibility that I believe is worth further exploration: that is, that the changing nature of graduate education in economics might sometimes be a cause as well as a consequence of changing research practices in economics. (pp. 167-70)

The correspondence between Biddle’s discussion of the change in the attitude of the economics profession about how inferences should be drawn from data about empirical relationships is strikingly similar to Oakeshott’s discussion and depressing in its implications for the decline of expert judgment by economics, expert judgment having been replaced by mechanical and technical knowledge that can be objectively summarized in the form of rules or tests for statistical significance, itself an entirely arbitrary convention lacking any logical, or self-evident, justification.

But my point is not to condemn using rules derived from classical probability theory to assess the significance of relationships statistically estimated from historical data, but to challenge the methodological prohibition against the kinds of expert judgments that many statistically knowledgeable economists like Nobel Prize winners such as Simon Kuznets, Milton Friedman, Theodore Schultz and Gary Becker routinely used to make in their empirical studies. As Biddle notes:

In 1957, Milton Friedman published his theory of the consumption function. Friedman certainly understood statistical theory and probability theory as well as anyone in the profession in the 1950s, and he used statistical theory to derive testable hypotheses from his economic model: hypotheses about the relationships between estimates of the marginal propensity to consume for different groups and from different types of data. But one will search his book almost in vain for applications of the classical methods of inference. Six years later, Friedman and Anna Schwartz published their Monetary History of the United States, a work packed with graphs and tables of statistical data, as well as numerous generalizations based on that data. But the book contains no classical hypothesis tests, no confidence intervals, no reports of statistical significance or insignificance, and only a handful of regressions. (p. 164)

Friedman’s work on the Monetary History is still regarded as authoritative. My own view is that much of the Monetary History was either wrong or misleading. But my quarrel with the Monetary History mainly pertains to the era in which the US was on the gold standard, inasmuch as Friedman simply did not understand how the gold standard worked, either in theory or in practice, as McCloskey and Zecher showed in two important papers (here and here). Also see my posts about the empirical mistakes in the Monetary History (here and here). But Friedman’s problem was bad monetary theory, not bad empirical technique.

Friedman’s theoretical misunderstandings have no relationship to the misguided prohibition against doing quantitative empirical research without obeying the arbitrary methodological requirement that statistical be derived in a way that measures the statistical significance of the estimated relationships. These methodological requirements have been adopted to support a self-defeating pretense to scientific rigor, necessitating the use of relatively advanced mathematical techniques to perform quantitative empirical research. The methodological requirements for measuring statistical relationships were never actually shown to be generate more accurate or reliable statistical results than those derived from the less technically advanced, but in some respects more economically sophisticated, techniques that have almost totally been displaced. One more example of the fallacy that there is but one technique of research that ensures the discovery of truth, a mistake even Popper was never guilty of.

Methodological Prescriptions Go from Bad to Worse

The methodological requirement for the use of formal tests of statistical significance before any quantitative statistical estimate could be credited was a prelude, though it would be a stretch to link them causally, to another and more insidious form of methodological tyrannizing: the insistence that any macroeconomic model be derived from explicit micro-foundations based on the solution of an intertemporal-optimization exercise. Of course, the idea that such a model was in any way micro-founded was a pretense, the solution being derived only through the fiction of a single representative agent, rendering the entire optimization exercise fundamentally illegitimate and the exact opposite of micro-founded model. Having already explained in previous posts why transforming microfoundations from a legitimate theoretical goal into methodological necessity has taken a generation of macroeconomists down a blind alley (here, here, here, and here) I will only make the further comment that this is yet another example of the danger of elevating technique over practice and substance.

Popper’s More Important Contribution

This post has largely concurred with the negative assessment of Popper’s work registered by Lemoine. But I wish to end on a positive note, because I have learned a great deal from Popper, and even if he is overrated as a philosopher of science, he undoubtedly deserves great credit for suggesting falsifiability as the criterion by which to distinguish between science and metaphysics. Even if that criterion does not hold up, or holds up only when qualified to a greater extent than Popper admitted, Popper made a hugely important contribution by demolishing the startling claim of the Logical Positivists who in the 1920s and 1930s argued that only statements that can be empirically verified through direct or indirect observation have meaning, all other statements being meaningless or nonsensical. That position itself now seems to verge on the nonsensical. But at the time many of the world’s leading philosophers, including Ludwig Wittgenstein, no less, seemed to accept that remarkable view.

Thus, Popper’s demarcation between science and metaphysics had a two-fold significance. First, that it is not verifiability, but falsifiability, that distinguishes science from metaphysics. That’s the contribution for which Popper is usually remembered now. But it was really the other aspect of his contribution that was more significant: that even metaphysical, non-scientific, statements can be meaningful. According to the Logical Positivists, unless you are talking about something that can be empirically verified, you are talking nonsense. In other words they were deliberately hoisting themselves on their petard, because their discussions about what is and what is not meaningful, being discussions about concepts, not empirically verifiable objects, were themselves – on the Positivists’ own criterion of meaning — meaningless and nonsensical.

Popper made the world safe for metaphysics, and the world is a better place as a result. Science is a wonderful enterprise, rewarding for its own sake and because it contributes to the well-being of many millions of human beings, though like many other human endeavors, it can also have unintended and unfortunate consequences. But metaphysics, because it was used as a term of abuse by the Positivists, is still, too often, used as an epithet. It shouldn’t be.

Certainly economists should aspire to tease out whatever empirical implications they can from their theories. But that doesn’t mean that an economic theory with no falsifiable implications is useless, a judgment whereby Mark Blaug declared general equilibrium theory to be unscientific and useless, a judgment that I don’t think has stood the test of time. And even if general equilibrium theory is simply metaphysical, my response would be: so what? It could still serve as a source of inspiration and insight to us in framing other theories that may have falsifiable implications. And even if, in its current form, a theory has no empirical content, there is always the possibility that, through further discussion, critical analysis and creative thought, empirically falsifiable implications may yet become apparent.

Falsifiability is certainly a good quality for a theory to have, but even an unfalsifiable theory may be worth paying attention to and worth thinking about.

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More on Sticky Wages

It’s been over four and a half years since I wrote my second most popular post on this blog (“Why are Wages Sticky?”). Although the post was linked to and discussed by Paul Krugman (which is almost always a guarantee of getting a lot of traffic) and by other econoblogosphere standbys like Mark Thoma and Barry Ritholz, unlike most of my other popular posts, it has continued ever since to attract a steady stream of readers. It’s the posts that keep attracting readers long after their original expiration date that I am generally most proud of.

I made a few preliminary points about wage stickiness before getting to my point. First, although Keynes is often supposed to have used sticky wages as the basis for his claim that market forces, unaided by stimulus to aggregate demand, cannot automatically eliminate cyclical unemployment within the short or even medium term, he actually devoted a lot of effort and space in the General Theory to arguing that nominal wage reductions would not increase employment, and to criticizing economists who blamed unemployment on nominal wages fixed by collective bargaining at levels too high to allow all workers to be employed. So, the idea that wage stickiness is a Keynesian explanation for unemployment doesn’t seem to me to be historically accurate.

I also discussed the search theories of unemployment that in some ways have improved our understanding of why some level of unemployment is a normal phenomenon even when people are able to find jobs fairly easily and why search and unemployment can actually be productive, enabling workers and employers to improve the matches between the skills and aptitudes that workers have and the skills and aptitudes that employers are looking for. But search theories also have trouble accounting for some basic facts about unemployment.

First, a lot of job search takes place when workers have jobs while search theories assume that workers can’t or don’t search while they are employed. Second, when unemployment rises in recessions, it’s not because workers mistakenly expect more favorable wage offers than employers are offering and mistakenly turn down job offers that they later regret not having accepted, which is a very skewed way of interpreting what happens in recessions; it’s because workers are laid off by employers who are cutting back output and idling production lines.

I then suggested the following alternative explanation for wage stickiness:

Consider the incentive to cut price of a firm that can’t sell as much as it wants [to sell] at the current price. The firm is off its supply curve. The firm is a price taker in the sense that, if it charges a higher price than its competitors, it won’t sell anything, losing all its sales to competitors. Would the firm have any incentive to cut its price? Presumably, yes. But let’s think about that incentive. Suppose the firm has a maximum output capacity of one unit, and can produce either zero or one units in any time period. Suppose that demand has gone down, so that the firm is not sure if it will be able to sell the unit of output that it produces (assume also that the firm only produces if it has an order in hand). Would such a firm have an incentive to cut price? Only if it felt that, by doing so, it would increase the probability of getting an order sufficiently to compensate for the reduced profit margin at the lower price. Of course, the firm does not want to set a price higher than its competitors, so it will set a price no higher than the price that it expects its competitors to set.

Now consider a different sort of firm, a firm that can easily expand its output. Faced with the prospect of losing its current sales, this type of firm, unlike the first type, could offer to sell an increased amount at a reduced price. How could it sell an increased amount when demand is falling? By undercutting its competitors. A firm willing to cut its price could, by taking share away from its competitors, actually expand its output despite overall falling demand. That is the essence of competitive rivalry. Obviously, not every firm could succeed in such a strategy, but some firms, presumably those with a cost advantage, or a willingness to accept a reduced profit margin, could expand, thereby forcing marginal firms out of the market.

Workers seem to me to have the characteristics of type-one firms, while most actual businesses seem to resemble type-two firms. So what I am suggesting is that the inability of workers to take over the jobs of co-workers (the analog of output expansion by a firm) when faced with the prospect of a layoff means that a powerful incentive operating in non-labor markets for price cutting in response to reduced demand is not present in labor markets. A firm faced with the prospect of being terminated by a customer whose demand for the firm’s product has fallen may offer significant concessions to retain the customer’s business, especially if it can, in the process, gain an increased share of the customer’s business. A worker facing the prospect of a layoff cannot offer his employer a similar deal. And requiring a workforce of many workers, the employer cannot generally avoid the morale-damaging effects of a wage cut on his workforce by replacing current workers with another set of workers at a lower wage than the old workers were getting.

I think that what I wrote four years ago is clearly right, identifying an important reason for wage stickiness. But there’s also another reason that I didn’t mention then, but whose importance has since come to appear increasingly significant to me, especially as a result of writing and rewriting my paper “Hayek, Hicks, Radner and three concepts of intertemporal equilibrium.”

If you are unemployed because the demand for your employer’s product has gone down, and your employer, planning to reduce output, is laying off workers no longer needed, how could you, as an individual worker, unconstrained by a union collective-bargaining agreement or by a minimum-wage law, persuade your employer not to lay you off? Could you really keep your job by offering to accept a wage cut — no matter how big? If you are being laid off because your employer is reducing output, would your offer to work at a lower wage cause your employer to keep output unchanged, despite a reduction in demand? If not, how would your offer to take a pay cut help you keep your job? Unless enough workers are willing to accept a big enough wage cut for your employer to find it profitable to maintain current output instead of cutting output, how would your own willingness to accept a wage cut enable you to keep your job?

Now, if all workers were to accept a sufficiently large wage cut, it might make sense for an employer not to carry out a planned reduction in output, but the offer by any single worker to accept a wage cut certainly would not cause the employer to change its output plans. So, if you are making an independent decision whether to offer to accept a wage cut, and other workers are making their own independent decisions about whether to accept a wage cut, would it be rational for you or any of them to accept a wage cut? Whether it would or wouldn’t might depend on what each worker was expecting other workers to do. But certainly given the expectation that other workers are not offering to accept a wage cut, why would it make any sense for any worker to be the one to offer to accept a wage cut? Would offering to accept a wage cut, increase the likelihood that a worker would be one of the lucky ones chosen not to be laid off? Why would offering to accept a wage cut that no one else was offering to accept, make the worker willing to work for less appear more desirable to the employer than the others that wouldn’t accept a wage cut? One reaction by the employer might be: what’s this guy’s problem?

Combining this way of looking at the incentives workers have to offer to accept wage reductions to keep their jobs with my argument in my post of four years ago, I now am inclined to suggest that unemployment as such provides very little incentive for workers and employers to cut wages. Price cutting in periods of excess supply is often driven by aggressive price cutting by suppliers with large unsold inventories. There may be lots of unemployment, but no one is holding a large stock of unemployed workers, and no is in a position to offer low wages to undercut the position of those currently employed at  nominal wages that, arguably, are too high.

That’s not how labor markets operate. Labor markets involve matching individual workers and individual employers more or less one at a time. If nominal wages fall, it’s not because of an overhang of unsold labor flooding the market; it’s because something is changing the expectations of workers and employers about what wage will be offered by employers, and accepted by workers, for a particular kind of work. If the expected wage is too high, not all workers willing to work at that wage will find employment; if it’s too low, employers will not be able to find as many workers as they would like to hire, but the situation will not change until wage expectations change. And the reason that wage expectations change is not because the excess demand for workers causes any immediate pressure for nominal wages to rise.

The further point I would make is that the optimal responses of workers and the optimal responses of their employers to a recessionary reduction in demand, in which the employers, given current input and output prices, are planning to cut output and lay off workers, are mutually interdependent. While it is, I suppose, theoretically possible that if enough workers decided to immediately offer to accept sufficiently large wage cuts, some employers might forego plans to lay off their workers, there are no obvious market signals that would lead to such a response, because such a response would be contingent on a level of coordination between workers and employers and a convergence of expectations about future outcomes that is almost unimaginable.

One can’t simply assume that it is in the independent self-interest of every worker to accept a wage cut as soon as an employer perceives a reduced demand for its product, making the current level of output unprofitable. But unless all, or enough, workers decide to accept a wage cut, the optimal response of the employer is still likely to be to cut output and lay off workers. There is no automatic mechanism by which the market adjusts to demand shocks to achieve the set of mutually consistent optimal decisions that characterizes a full-employment market-clearing equilibrium. Market-clearing equilibrium requires not merely isolated price and wage cuts by individual suppliers of inputs and final outputs, but a convergence of expectations about the prices of inputs and outputs that will be consistent with market clearing. And there is no market mechanism that achieves that convergence of expectations.

So, this brings me back to Keynes and the idea of sticky wages as the key to explaining cyclical fluctuations in output and employment. Keynes writes at the beginning of chapter 19 of the General Theory.

For the classical theory has been accustomed to rest the supposedly self-adjusting character of the economic system on an assumed fluidity of money-wages; and, when there is rigidity, to lay on this rigidity the blame of maladjustment.

A reduction in money-wages is quite capable in certain circumstances of affording a stimulus to output, as the classical theory supposes. My difference from this theory is primarily a difference of analysis. . . .

The generally accept explanation is . . . quite a simple one. It does not depend on roundabout repercussions, such as we shall discuss below. The argument simply is that a reduction in money wages will, cet. par. Stimulate demand by diminishing the price of the finished product, and will therefore increase output, and will therefore increase output and employment up to the point where  the reduction which labour has agreed to accept in its money wages is just offset by the diminishing marginal efficiency of labour as output . . . is increased. . . .

It is from this type of analysis that I fundamentally differ.

[T]his way of thinking is probably reached as follows. In any given industry we have a demand schedule for the product relating the quantities which can be sold to the prices asked; we have a series of supply schedules relating the prices which will be asked for the sale of different quantities. .  . and these schedules between them lead up to a further schedule which, on the assumption that other costs are unchanged . . . gives us the demand schedule for labour in the industry relating the quantity of employment to different levels of wages . . . This conception is then transferred . . . to industry as a whole; and it is supposed, by a parity of reasoning, that we have a demand schedule for labour in industry as a whole relating the quantity of employment to different levels of wages. It is held that it makes no material difference to this argument whether it is in terms of money-wages or of real wages. If we are thinking of real wages, we must, of course, correct for changes in the value of money; but this leaves the general tendency of the argument unchanged, since prices certainly do not change in exact proportion to changes in money wages.

If this is the groundwork of the argument . . ., surely it is fallacious. For the demand schedules for particular industries can only be constructed on some fixed assumption as to the nature of the demand and supply schedules of other industries and as to the amount of aggregate effective demand. It is invalid, therefore, to transfer the argument to industry as a whole unless we also transfer our assumption that the aggregate effective demand is fixed. Yet this assumption amount to an ignoratio elenchi. For whilst no one would wish to deny the proposition that a reduction in money-wages accompanied by the same aggregate demand as before will be associated with an increase in employment, the precise question at issue is whether the reduction in money wages will or will not be accompanied by the same aggregate effective demand as before measured in money, or, at any rate, measured by an aggregate effective demand which is not reduced in full proportion to the reduction in money-wages. . . But if the classical theory is not allowed to extend by analogy its conclusions in respect of a particular industry to industry as a whole, it is wholly unable to answer the question what effect on employment a reduction in money-wages will have. For it has no method of analysis wherewith to tackle the problem. (General Theory, pp. 257-60)

Keynes’s criticism here is entirely correct. But I would restate slightly differently. Standard microeconomic reasoning about preferences, demand, cost and supply is partial-equilbriium analysis. The focus is on how equilibrium in a single market is achieved by the adjustment of the price in a single market to equate the amount demanded in that market with amount supplied in that market.

Supply and demand is a wonderful analytical tool that can illuminate and clarify many economic problems, providing the key to important empirical insights and knowledge. But supply-demand analysis explicitly – but too often without realizing its limiting implications – assumes that other prices and incomes in other markets are held constant. That assumption essentially means that the market – i.e., the demand, cost and supply curves used to represent the behavioral characteristics of the market being analyzed – is small relative to the rest of the economy, so that changes in that single market can be assumed to have a de minimus effect on the equilibrium of all other markets. (The conditions under which such an assumption could be justified are themselves not unproblematic, but I am now assuming that those problems can in fact be assumed away at least in many applications. And a good empirical economist will have a good instinctual sense for when it’s OK to make the assumption and when it’s not OK to make the assumption.)

So, the underlying assumption of microeconomics is that the individual markets under analysis are very small relative to the whole economy. Why? Because if those markets are not small, we can’t assume that the demand curves, cost curves, and supply curves end up where they started. Because a high price in one market may have effects on other markets and those effects will have further repercussions that move the very demand, cost and supply curves that were drawn to represent the market of interest. If the curves themselves are unstable, the ability to predict the final outcome is greatly impaired if not completely compromised.

The working assumption of the bread and butter partial-equilibrium analysis that constitutes econ 101 is that markets have closed borders. And that assumption is not always valid. If markets have open borders so that there is a lot of spillover between and across markets, the markets can only be analyzed in terms of broader systems of simultaneous equations, not the simplified solutions that we like to draw in two-dimensional space corresponding to intersections of stable supply curves with stable supply curves.

What Keynes was saying is that it makes no sense to draw a curve representing the demand of an entire economy for labor or a curve representing the supply of labor of an entire economy, because the underlying assumption of such curves that all other prices are constant cannot possibly be satisfied when you are drawing a demand curve and a supply curve for an input that generates more than half the income earned in an economy.

But the problem is even deeper than just the inability to draw a curve that meaningfully represents the demand of an entire economy for labor. The assumption that you can model a transition from one point on the curve to another point on the curve is simply untenable, because not only is the assumption that other variables are being held constant untenable and self-contradictory, the underlying assumption that you are starting from an equilibrium state is never satisfied when you are trying to analyze a situation of unemployment – at least if you have enough sense not to assume that economy is starting from, and is not always in, a state of general equilibrium.

So, Keynes was certainly correct to reject the naïve transfer of partial equilibrium theorizing from its legitimate field of applicability in analyzing the effects of small parameter changes on outcomes in individual markets – what later came to be known as comparative statics – to macroeconomic theorizing about economy-wide disturbances in which the assumptions underlying the comparative-statics analysis used in microeconomics are clearly not satisfied. That illegitimate transfer of one kind of theorizing to another has come to be known as the demand for microfoundations in macroeconomic models that is the foundational methodological principle of modern macroeconomics.

The principle, as I have been arguing for some time, is illegitimate for a variety of reasons. And one of those reasons is that microeconomics itself is based on the macroeconomic foundational assumption of a pre-existing general equilibrium, in which all plans in the entire economy are, and will remain, perfectly coordinated throughout the analysis of a particular parameter change in a single market. Once you relax the assumption that all, but one, markets are in equilibrium, the discipline imposed by the assumption of the rationality of general equilibrium and comparative statics is shattered, and a different kind of theorizing must be adopted to replace it.

The search for that different kind of theorizing is the challenge that has always faced macroeconomics. Despite heroic attempts to avoid facing that challenge and pretend that macroeconomics can be built as if it were microeconomics, the search for a different kind of theorizing will continue; it must continue. But it would certainly help if more smart and creative people would join in that search.

The Standard Narrative on the History of Macroeconomics: An Exercise in Self-Serving Apologetics

During my recent hiatus from blogging, I have been pondering an important paper presented in June at the History of Economics Society meeting in Toronto, “The Standard Narrative on History of Macroeconomics: Central Banks and DSGE Models” by Francesco Sergi of the University of Bristol, which was selected by the History of Economics Society as the best conference paper by a young scholar in 2017.

Here is the abstract of Sergi’s paper:

How do macroeconomists write the history of their own discipline? This article provides a careful reconstruction of the history of macroeconomics told by the practitioners working today in the dynamic stochastic general equilibrium (DSGE) approach.

Such a tale is a “standard narrative”: a widespread and “standardizing” view of macroeconomics as a field evolving toward “scientific progress”. The standard narrative explains scientific progress as resulting from two factors: “consensus” about theory and “technical change” in econometric tools and computational power. This interpretation is a distinctive feature of central banks’ technical reports about their DSGE models.

Furthermore, such a view on “consensus” and “technical change” is a significantly different view with respect to similar tales told by macroeconomists in the past — which rather emphasized the role of “scientific revolutions” and struggles among competing “schools of thought”. Thus, this difference raises some new questions for historians of macroeconomics.

Sergi’s paper is too long and too rich in content to easily summarize in this post, so what I will do is reproduce and comment on some of the many quotations provided by Sergi, taken mostly from central-bank reports, but also from some leading macroeconomic textbooks and historical survey papers, about the “progress” of modern macroeconomics, and especially about the critical role played by “microfoundations” in achieving that progress. The general tenor of the standard narrative is captured well by the following quotations from V. V. Chari

[A]ny interesting model must be a dynamic stochastic general equilibrium model. From this perspective, there is no other game in town. […] A useful aphorism in macroeconomics is: “If you have an interesting and coherent story to tell, you can tell it in a DSGE model.  (Chari 2010, 2)

I could elaborate on this quotation at length, but I will just leave it out there for readers to ponder with a link to an earlier post of mine about methodological arrogance. Instead I will focus on two other sections of Sergi’s paper “the five steps of theoretical progress” and “microfoundations as theoretical progress.” Here is how Sergi explains the role of the five steps:

The standard narrative provides a detailed account of the progressive evolution toward the synthesis. Following a teleological perspective, each step of this evolution is an incremental, linear improvement of the theoretical tool box for model building. The standard narrative identifies five steps . . . .  Each step corresponds to the emergence of a school of thought. Therefore, in the standard narrative, there are not such things as competing schools of thought and revolutions. Firstly, because schools of thought are represented as a sequence; one school (one step) is always leading to another school (the following step), hence different schools are not coexisting for a long period of time. Secondly, there are no revolutions because, while emerging, new schools of thought [do] not overthrow the previous ones; instead, they suggest improvements and amendments, that are accepted as an improvement by pre-existing schools therefore, accumulation of knowledge takes place thanks to consensus. (pp. 17-18)

The first step in the standard narrative is the family of Keynesian macroeconometric models of the 1950s and 1960s, the primitive ancestors of the modern DSGE models. The second step was the emergence of New Classical macroeconomics which introduced the ideas of rational expectations and dynamic optimization into theoretical macroeconomic discourse in the 1970s. The third step was the development, inspired by New Classical ideas, of Real-Business-Cycle models of the 1980s, and the fourth step was introduction of New Keynesian models in the late 1980s and 1990s that tweaked the Real-Business-Cycle models in ways that rationalized the use of counter-cyclical macroeconomic policy within the theoretical framework of the Real-Business-Cycle approach. The final step, the DSGE model, emerged more or less naturally as a synthesis of the converging Real-Business-Cycle and New Keynesian approaches.

After detailing the five steps of theoretical progress, Sergi focuses attention on “the crucial improvement” that allowed the tool box of macroeconomic modelling to be extended in such a theoretically fruitful way: the insistence on providing explicit microfoundations for macroeconomic models. He writes:

Abiding [by] the Lucasian microfoundational program is put forward by DSGE modellers as the very fundamental essence of theoretical progress allowed by [the] consensus. As Sanajay K. Chugh (University of Pennsylvania) explains in the historical chapter of his textbook, microfoundations is all what modern macroeconomics is about: (p. 20)

Modern macroeconomics begin by explicitly studying the microeconomic principles of utility maximization, profit maximization and market-clearing. [. . . ] This modern macroeconomics quickly captured the attention of the profession through the 1980s [because] it actually begins with microeconomic principles, which was a rather attractive idea. Rather than building a framework of economy-wide events from the top down [. . .] one could build this framework using microeconomic discipline from the bottom up. (Chugh 2015, 170)

Chugh’s rationale for microfoundations is a naïve expression of reductionist bias dressed up as simple homespun common-sense. Everyone knows that you should build from the bottom up, not from the top down, right? But things are not always quite as simple as they seem. Here is an attempt to present microfoundations as being cutting-edge and sophisticated offered in a 2009 technical report written by Cuche-Curti et al. for the Swiss National Bank.

The key property of DSGE models is that they rely on explicit micro-foundations and a rational treatment of expectations in a general equilibrium context. They thus provide a coherent and compelling theoretical framework for macroeconomic analysis. (Cuche-Curti et al. 2009, 6)

A similar statement is made by Gomes et al in a 2010 technical report for the European Central Bank:

The microfoundations of the model together with its rich structure allow [us] to conduct a quantitative analysis in a theoretically coherent and fully consistent model setup, clearly spelling out all the policy implications. (Gomes et al. 2010, 5)

These laudatory descriptions of the DSGE model stress its “coherence” as a primary virtue. What is meant by “coherence” is spelled out more explicitly in a 2006 technical report describing NEMO, a macromodel of the Norwegian economy, by Brubakk et al. for the Norges Bank.

Various agents’ behavior is modelled explicitly in NEMO, based on microeconomic theory. A consistent theoretical framework makes it easier to interpret relationships and mechanisms in the model in the light of economic theory. One advantage is that we can analyse the economic effects of changes of a more structural nature […] [making it] possible to provide a consistent and detailed economic rationale for Norges Bank’s projections for the Norwegian economy. This distinguishes NEMO from purely statistical models, which to a limited extent provide scope for economic interpretations. (Brubakk and Sveen 2009, 39)

By creating microfounded models, in which all agents are optimizers making choices consistent with the postulates of microeconomic theory, DSGE model-builders, in effect, create “laboratories” from which to predict the consequences of alternative monetary policies, enabling policy makers to make informed policy choices. I pause merely to note and draw attention to the tendentious and misleading misappropriation of the language of empirical science by these characteristically self-aggrandizing references to DSGE models as “laboratories” as if what was going on in such models was determined by an actual physical process, as is routinely the case in the laboratories of physical and natural scientists, rather than speculative exercises in high-level calculations derived from the manipulation of DSGE models.

As a result of recent advances in macroeconomic theory and computational techniques, it has become feasible to construct richly structured dynamic stochastic general equilibrium models and use them as laboratories for the study of business cycles and for the formulation and analysis of monetary policy. (Cuche-Curri et al. 2009, 39)

Policy makers can be confident that the conditional predictions corresponding to the policy alternative under consideration, which are derived from their “laboratory” DSGE models, because those models, having been constructed on the basis of the postulates of economic theory, are therefore microfounded, embodying deep structural parameters that are invariant to policy changes. Microfounded models are thus immune to the Lucas Critique of macroeconomic policy evaluation, under which the empirically estimated coefficients of traditional Keynesian macroeconometric models cannot be assumed to remain constant under policy changes, because those coefficient estimates are themselves conditional to policy choices.

Here is how the point is made in three different central bank technical reports: by Argov et al. in a 2012 technical report about MOISE, a DSGE model for the Israeli economy, by Cuche-Curti et al. and by Medina and Soto in a 2006 technical report about a new DSGE model for the Chilean economy for the Central Bank of Chile.

Being micro-founded, the model enables the central bank to assess the effect of its alternative policy choices on the future paths of the economy’s endogenous variables, in a way that is immune to the Lucas critique. (Argov et al. 2012, 5)

[The DSGE] approach has three distinct advantages in comparison to other modelling strategies. First and foremost, its microfoundations should allow it to escape the Lucas critique. (Cuche-Curti et al. 2009, 6)

The main advantage of this type of model, over more traditional reduce-form macro models, is that the structural interpretation of their parameters allows [it] to overcome the Lucas Critique. This is clearly an advantage for policy analysis. (Medina and Soto, 2006, 2)

These quotations show clearly that escaping, immunizing, or overcoming the Lucas Critique is viewed by DSGE modelers as the holy grail of macroeconomic model building and macroeconomic policy analysis. If the Lucas Critique cannot be neutralized, the coefficient estimates derived from reduced-form macroeconometric models cannot be treated as invariant to policy and therefore cannot provide a secure basis for predicting the effects of alternative policies. But DSGE models allow deep structural relationships, reflecting the axioms underlying microeconomic theory, to be estimated. Because they reflect the deep, and presumably stable, microeconomic structure of the economy, estimates of deep parameters derived from DSGE models, DSGE modelers claim that these estimates provide policy makers with a reliable basis for conditional forecasting of the effects of macroeconomic policy.

Because of the consistently poor track record of DSGE models in actual forecasting (for evidence of that poor track record see the paper by Carlaw and Lipsey and my post about their paper) comparing the predictive performance of DSGE models with more traditional macroeconometric models), the emphasis placed on the Lucas Critique by DSGE modelers has an apologetic character, DSGE modelers having to account for the relatively poor comparative predictive power of DSGE models by relentlessly invoking the Lucas Critique in trying to account for, and explain away, the poor predictive performance of the DSGE models. But if DSGE models really are better than traditional macro models why are their unconditional predictions not at least as good as those of traditional macroeconometric models? Obviously estimates of the deep structural relationships provided by microfounded models are not as reliable as DSGE apologetics tries to suggest.

And the reason that the estimates of deep structural relationships derived from DSGE models are not reliable is that those models, no less than traditional macroeconometric models, are subject to the Lucas Critique, the deep microeconomic structural relationships embodied in DSGE models being conditional on the existence of a unique equilibrium solution that persists long enough for the structural relationships characterizing that equilibrium to be inferred from the data-generating mechanism whereby those models are estimated. (I have made this point previously here.) But if the data-generating mechanism does not conform to the unique general equilibrium upon whose existence the presumed deep structural relationships of microeconomic theory embodied in DSGE models are conditioned, the econometric estimates derived from DSGE models cannot capture the desired deep structural relationships, and the resulting structural estimates are therefore incapable of providing a reliable basis for macroeconomic-policy analysis or for conditional forecasts of the effects of alternative policies, much less unconditional forecasts of endogenous macroeconomic variables.

Of course, the problem is even more intractable than the discussion above implies, because there is no reason why the deep structural relationships corresponding to a particular equilibrium should be invariant to changes in the equilibrium. So any change in economic policy that displaces a pre-existing equilibrium, let alone any other unforeseen technological change or change in tastes or resource endowments that displaces a pre-existing equilibrium will necessarily cause all the deep structural relationships to change correspondingly. So the deep structural parameters upon whose invariance the supposedly unique capacity of DSGE models to provide policy analysis upon which policy makers can rely simply don’t exist. Policy making based on DSGE models is as much an uncertain art requiring the exercise of finely developed judgment and intuition as policy making based on any other kind of economic modeling. DSGE models provide no uniquely reliable basis for making macroeconomic policy.

References

Argov, E., Barnea, E., Binyamini, A., Borenstein, E., Elkayam, D., and Rozenshtrom, I. (2012). MOISE: A DSGE Model for the Israeli Economy. Technical Report 2012.06, Bank of Israel.
Brubakk, L.,Husebø, T. A., Maih, J., Olsen, K., and Østnor, M. (2006). Finding NEMO: Documentation of the Norwegian economy model. Technical Report 2006/6, Norges Bank, Staff Memo.
Carlaw, K. I., and Lipsey, R. G. (2012). “Does History Matter?: Empirical Analysis of Evolutionary versus Stationary Equilibrium Views of the Economy.” Journal of Evolutionary Economics. 22(4):735-66.
Chari, V. V. (2010). Testimony before the committee on Science and Technology, Subcommittee on Investigations and Oversight, US House of Representatives. In Building a Science of Economics for the Real World.
Chugh, S. K. (2015). Modern Macroeconomics. MIT Press, Cambridge (MA).
Cuche-Curti, N. A., Dellas, H., and Natal, J.-M. (2009). DSGE-CH. A Dynamic Stochastic General Equilibrium Model for Switzerland. Technical Report 5, Swiss National Bank.
Gomes, S., Jacquinot, P., and Pisani, M. (2010). The EAGLE. A Model for Policy Analysis of Macroeconomic Interdependence in the Euro Area. Technical Report 1195, European Central Bank.
Medina, J. P. and Soto, C. (2006). Model for Analysis and Simulations (MAS): A New DSGE Model for the Chilean Economy. Technical report, Central Bank of Chile.

Paul Romer on Modern Macroeconomics, Or, the “All Models Are False” Dodge

Paul Romer has been engaged for some time in a worthy campaign against the travesty of modern macroeconomics. A little over a year ago I commented favorably about Romer’s takedown of Robert Lucas, but I also defended George Stigler against what I thought was an unfair attempt by Romer to identify George Stigler as an inspiration and role model for Lucas’s transgressions. Now just a week ago, a paper based on Romer’s Commons Memorial Lecture to the Omicron Delta Epsilon Society, has become just about the hottest item in the econ-blogosophere, even drawing the attention of Daniel Drezner in the Washington Post.

I have already written critically about modern macroeconomics in my five years of blogging, and here are some links to previous posts (link, link, link, link). It’s good to see that Romer is continuing to voice his criticisms, and that they are gaining a lot of attention. But the macroeconomic hierarchy is used to criticism, and has its standard responses to criticism, which are being dutifully deployed by defenders of the powers that be.

Romer’s most effective rhetorical strategy is to point out that the RBC core of modern DSGE models posit unobservable taste and technology shocks to account for fluctuations in the economic time series, but that these taste and technology shocks are themselves simply inferred from the fluctuations in the times-series data, so that the entire structure of modern macroeconometrics is little more than an elaborate and sophisticated exercise in question-begging.

In this post, I just want to highlight one of the favorite catch-phrases of modern macroeconomics which serves as a kind of default excuse and self-justification for the rampant empirical failures of modern macroeconomics (documented by Lipsey and Carlaw as I showed in this post). When confronted by evidence that the predictions of their models are wrong, the standard and almost comically self-confident response of the modern macroeconomists is: All models are false. By which the modern macroeconomists apparently mean something like: “And if they are all false anyway, you can’t hold us accountable, because any model can be proven wrong. What really matters is that our models, being microfounded, are not subject to the Lucas Critique, and since all other models than ours are not micro-founded, and, therefore, being subject to the Lucas Critique, they are simply unworthy of consideration. This is what I have called methodological arrogance. That response is simply not true, because the Lucas Critique applies even to micro-founded models, those models being strictly valid only in equilibrium settings and being unable to predict the adjustment of economies in the transition between equilibrium states. All models are subject to the Lucas Critique.

Here is Romer’s take:

In response to the observation that the shocks are imaginary, a standard defense invokes Milton Friedman’s (1953) methodological assertion from unnamed authority that “the more significant the theory, the more unrealistic the assumptions (p.14).” More recently, “all models are false” seems to have become the universal hand-wave for dismissing any fact that does not conform to the model that is the current favorite.

Friedman’s methodological assertion would have been correct had Friedman substituted “simple” for “unrealistic.” Sometimes simplifications are unrealistic, but they don’t have to be. A simplification is a generalization of something complicated. By simplifying, we can transform a problem that had been too complex to handle into a problem more easily analyzed. But such simplifications aren’t necessarily unrealistic. To say that all models are false is simply a dodge to avoid having to account for failure. The excuse of course is that all those other models are subject to the Lucas Critique, so my model wins. But your model is subject to the Lucas Critique even though you claim it’s not, so even according to the rules you have arbitrarily laid down, you don’t win.

So I was just curious about where the little phrase “all models are false” came from. I was expecting that Karl Popper might have said it, in which case to use the phrase as a defense mechanism against empirical refutation would have been a particularly fraudulent tactic, because it would have been a perversion of Popper’s methodological stance, which was to force our theoretical constructs to face up to, not to insulate it from, empirical testing. But when I googled “all theories are false” what I found was not Popper, but the British statistician, G. E. P. Box who wrote in his paper “Science and Statistics” based on his R. A. Fisher Memorial Lecture to the American Statistical Association: “All models are wrong.” Here’s the exact quote:

Since all models are wrong the scientist cannot obtain a “correct” one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity.

Since all models are wrong the scientist must be alert to what is importantly wrong. It is inappropriate to be concerned about mice when there are tigers abroad. Pure mathematics is concerned with propositions like “given that A is true, does B necessarily follow?” Since the statement is a conditional one, it has nothing whatsoever to do with the truth of A nor of the consequences B in relation to real life. The pure mathematician, acting in that capacity, need not, and perhaps should not, have any contact with practical matters at all.

In applying mathematics to subjects such as physics or statistics we make tentative assumptions about the real world which we know are false but which we believe may be useful nonetheless. The physicist knows that particles have mass and yet certain results, approximating what really happens, may be derived from the assumption that they do not. Equally, the statistician knows, for example, that in nature there never was a normal distribution, there never was a straight line, yet with normal and linear assumptions, known to be false, he can often derive results which match, to a useful approximation, those found in the real world. It follows that, although rigorous derivation of logical consequences is of great importance to statistics, such derivations are necessarily encapsulated in the knowledge that premise, and hence consequence, do not describe natural truth.

It follows that we cannot know that any statistical technique we develop is useful unless we use it. Major advances in science and in the science of statistics in particular, usually occur, therefore, as the result of the theory-practice iteration.

One of the most annoying conceits of modern macroeconomists is the constant self-congratulatory references to themselves as scientists because of their ostentatious use of axiomatic reasoning, formal proofs, and higher mathematical techniques. The tiresome self-congratulation might get toned down ever so slightly if they bothered to read and take to heart Box’s lecture.

There Is No Intertemporal Budget Constraint

Last week Nick Rowe posted a link to a just published article in a special issue of the Review of Keynesian Economics commemorating the 80th anniversary of the General Theory. Nick’s article discusses the confusion in the General Theory between saving and hoarding, and Nick invited readers to weigh in with comments about his article. The ROKE issue also features an article by Simon Wren-Lewis explaining the eclipse of Keynesian theory as a result of the New Classical Counter-Revolution, correctly identified by Wren-Lewis as a revolution inspired not by empirical success but by a methodological obsession with reductive micro-foundationalism. While deploring the New Classical methodological authoritarianism, Wren-Lewis takes solace from the ability of New Keynesians to survive under the New Classical methodological regime, salvaging a role for activist counter-cyclical policy by, in effect, negotiating a safe haven for the sticky-price assumption despite its shaky methodological credentials. The methodological fiction that sticky prices qualify as micro-founded allowed New Keynesianism to survive despite the ascendancy of micro-foundationalist methodology, thereby enabling the core Keynesian policy message to survive.

I mention the Wren-Lewis article in this context because of an exchange between two of the commenters on Nick’s article: the presumably pseudonymous Avon Barksdale and blogger Jason Smith about microfoundations and Keynesian economics. Avon began by chastising Nick for wasting time discussing Keynes’s 80-year old ideas, something Avon thinks would never happen in a discussion about a true science like physics, the 100-year-old ideas of Einstein being of no interest except insofar as they have been incorporated into the theoretical corpus of modern physics. Of course, this is simply vulgar scientism, as if the only legitimate way to do economics is to mimic how physicists do physics. This methodological scolding is typically charming New Classical arrogance. Sort of reminds one of how Friedrich Engels described Marxian theory as scientific socialism. I mean who, other than a religious fanatic, would be stupid enough to argue with the assertions of science?

Avon continues with a quotation from David Levine, a fine economist who has done a lot of good work, but who is also enthralled by the New Classical methodology. Avon’s scientism provoked the following comment from Jason Smith, a Ph. D. in physics with a deep interest in and understanding of economics.

You quote from Levine: “Keynesianism as argued by people such as Paul Krugman and Brad DeLong is a theory without people either rational or irrational”

This is false. The L in ISLM means liquidity preference and e.g. here …

http://krugman.blogs.nytimes.com/2013/11/18/the-new-keynesian-case-for-fiscal-policy-wonkish/

… Krugman mentions an Euler equation. The Euler equation essentially says that an agent must be indifferent between consuming one more unit today on the one hand and saving that unit and consuming in the future on the other if utility is maximized.

So there are agents in both formulations preferring one state of the world relative to others.

Avon replied:

Jason,

“This is false. The L in ISLM means liquidity preference and e.g. here”

I know what ISLM is. It’s not recursive so it really doesn’t have people in it. The dynamics are not set by any micro-foundation. If you’d like to see models with people in them, try Ljungqvist and Sargent, Recursive Macroeconomic Theory.

To which Jason retorted:

Avon,

So the definition of “people” is restricted to agents making multi-period optimizations over time, solving a dynamic programming problem?

Well then any such theory is obviously wrong because people don’t behave that way. For example, humans don’t optimize the dictator game. How can you add up optimizing agents and get a result that is true for non-optimizing agents … coincident with the details of the optimizing agents mattering.

Your microfoundation requirement is like saying the ideal gas law doesn’t have any atoms in it. And it doesn’t! It is an aggregate property of individual “agents” that don’t have properties like temperature or pressure (or even volume in a meaningful sense). Atoms optimize entropy, but not out of any preferences.

So how do you know for a fact that macro properties like inflation or interest rates are directly related to agent optimizations? Maybe inflation is like temperature — it doesn’t exist for individuals and is only a property of economics in aggregate.

These questions are not answered definitively, and they’d have to be to enforce a requirement for microfoundations … or a particular way of solving the problem.

Are quarks important to nuclear physics? Not really — it’s all pions and nucleons. Emergent degrees of freedom. Sure, you can calculate pion scattering from QCD lattice calculations (quark and gluon DoF), but it doesn’t give an empirically better result than chiral perturbation theory (pion DoF) that ignores the microfoundations (QCD).

Assuming quarks are required to solve nuclear physics problems would have been a giant step backwards.

To which Avon rejoined:

Jason

The microfoundation of nuclear physics and quarks is quantum mechanics and quantum field theory. How the degrees of freedom reorganize under the renormalization group flow, what effective field theory results is an empirical question. Keynesian economics is worse tha[n] useless. It’s wrong empirically, it has no theoretical foundation, it has no laws. It has no microfoundation. No serious grad school has taught Keynesian economics in nearly 40 years.

To which Jason answered:

Avon,

RG flow is irrelevant to chiral perturbation theory which is based on the approximate chiral symmetry of QCD. And chiral perturbation theory could exist without QCD as the “microfoundation”.

Quantum field theory is not a ‘microfoundation’, but rather a framework for building theories that may or may not have microfoundations. As Weinberg (1979) said:

” … quantum field theory itself has no content beyond analyticity, unitarity,
cluster decomposition, and symmetry.”

If I put together an NJL model, there is no requirement that the scalar field condensate be composed of quark-antiquark pairs. In fact, the basic idea was used for Cooper pairs as a model of superconductivity. Same macro theory; different microfoundations. And that is a general problem with microfoundations — different microfoundations can lead to the same macro theory, so which one is right?

And the IS-LM model is actually pretty empirically accurate (for economics):

http://informationtransfereconomics.blogspot.com/2014/03/the-islm-model-again.html

To which Avon responded:

First, ISLM analysis does not hold empirically. It just doesn’t work. That’s why we ended up with the macro revolution of the 70s and 80s. Keynesian economics ignores intertemporal budget constraints, it violates Ricardian equivalence. It’s just not the way the world works. People might not solve dynamic programs to set their consumption path, but at least these models include a future which people plan over. These models work far better than Keynesian ISLM reasoning.

As for chiral perturbation theory and the approximate chiral symmetries of QCD, I am not making the case that NJL models requires QCD. NJL is an effective field theory so it comes from something else. That something else happens to be QCD. It could have been something else, that’s an empirical question. The microfoundation I’m talking about with theories like NJL is QFT and the symmetries of the vacuum, not the short distance physics that might be responsible for it. The microfoundation here is about the basic laws, the principles.

ISLM and Keynesian economics has none of this. There is no principle. The microfoundation of modern macro is not about increasing the degrees of freedom to model every person in the economy on some short distance scale, it is about building the basic principles from consistent economic laws that we find in microeconomics.

Well, I totally agree that IS-LM is a flawed macroeconomic model, and, in its original form, it was borderline-incoherent, being a single-period model with an interest rate, a concept without meaning except as an intertemporal price relationship. These deficiencies of IS-LM became obvious in the 1970s, so the model was extended to include a future period, with an expected future price level, making it possible to speak meaningfully about real and nominal interest rates, inflation and an equilibrium rate of spending. So the failure of IS-LM to explain stagflation, cited by Avon as the justification for rejecting IS-LM in favor of New Classical macro, was not that hard to fix, at least enough to make it serviceable. And comparisons of the empirical success of augmented IS-LM and the New Classical models have shown that IS-LM models consistently outperform New Classical models.

What Avon fails to see is that the microfoundations that he considers essential for macroeconomics are themselves derived from the assumption that the economy is operating in macroeconomic equilibrium. Thus, insisting on microfoundations – at least in the formalist sense that Avon and New Classical macroeconomists understand the term – does not provide a foundation for macroeconomics; it is just question begging aka circular reasoning or petitio principia.

The circularity is obvious from even a cursory reading of Samuelson’s Foundations of Economic Analysis, Robert Lucas’s model for doing economics. What Samuelson called meaningful theorems – thereby betraying his misguided acceptance of the now discredited logical positivist dogma that only potentially empirically verifiable statements have meaning – are derived using the comparative-statics method, which involves finding the sign of the derivative of an endogenous economic variable with respect to a change in some parameter. But the comparative-statics method is premised on the assumption that before and after the parameter change the system is in full equilibrium or at an optimum, and that the equilibrium, if not unique, is at least locally stable and the parameter change is sufficiently small not to displace the system so far that it does not revert back to a new equilibrium close to the original one. So the microeconomic laws invoked by Avon are valid only in the neighborhood of a stable equilibrium, and the macroeconomics that Avon’s New Classical mentors have imposed on the economics profession is a macroeconomics that, by methodological fiat, is operative only in the neighborhood of a locally stable equilibrium.

Avon dismisses Keynesian economics because it ignores intertemporal budget constraints. But the intertemporal budget constraint doesn’t exist in any objective sense. Certainly macroeconomics has to take into account intertemporal choice, but the idea of an intertemporal budget constraint analogous to the microeconomic budget constraint underlying the basic theory of consumer choice is totally misguided. In the static theory of consumer choice, the consumer has a given resource endowment and known prices at which consumers can transact at will, so the utility-maximizing vector of purchases and sales can be determined as the solution of a constrained-maximization problem.

In the intertemporal context, consumers have a given resource endowment, but prices are not known. So consumers have to make current transactions based on their expectations about future prices and a variety of other circumstances about which consumers can only guess. Their budget constraints are thus not real but totally conjectural based on their expectations of future prices. The optimizing Euler equations are therefore entirely conjectural as well, and subject to continual revision in response to changing expectations. The idea that the microeconomic theory of consumer choice is straightforwardly applicable to the intertemporal choice problem in a setting in which consumers don’t know what future prices will be and agents’ expectations of future prices are a) likely to be very different from each other and thus b) likely to be different from their ultimate realizations is a huge stretch. The intertemporal budget constraint has a completely different role in macroeconomics from the role it has in microeconomics.

If I expect that the demand for my services will be such that my disposable income next year would be $500k, my consumption choices would be very different from what they would have been if I were expecting a disposable income of $100k next year. If I expect a disposable income of $500k next year, and it turns out that next year’s income is only $100k, I may find myself in considerable difficulty, because my planned expenditure and the future payments I have obligated myself to make may exceed my disposable income or my capacity to borrow. So if there are a lot of people who overestimate their future incomes, the repercussions of their over-optimism may reverberate throughout the economy, leading to bankruptcies and unemployment and other bad stuff.

A large enough initial shock of mistaken expectations can become self-amplifying, at least for a time, possibly resembling the way a large initial displacement of water can generate a tsunami. A financial crisis, which is hard to model as an equilibrium phenomenon, may rather be an emergent phenomenon with microeconomic sources, but whose propagation can’t be described in microeconomic terms. New Classical macroeconomics simply excludes such possibilities on methodological grounds by imposing a rational-expectations general-equilibrium structure on all macroeconomic models.

This is not to say that the rational expectations assumption does not have a useful analytical role in macroeconomics. But the most interesting and most important problems in macroeconomics arise when the rational expectations assumption does not hold, because it is when individual expectations are very different and very unstable – say, like now, for instance — that macroeconomies become vulnerable to really scary instability.

Simon Wren-Lewis makes a similar point in his paper in the Review of Keynesian Economics.

Much discussion of current divisions within macroeconomics focuses on the ‘saltwater/freshwater’ divide. This understates the importance of the New Classical Counter Revolution (hereafter NCCR). It may be more helpful to think about the NCCR as involving two strands. The one most commonly talked about involves Keynesian monetary and fiscal policy. That is of course very important, and plays a role in the policy reaction to the recent Great Recession. However I want to suggest that in some ways the second strand, which was methodological, is more important. The NCCR helped completely change the way academic macroeconomics is done.

Before the NCCR, macroeconomics was an intensely empirical discipline: something made possible by the developments in statistics and econometrics inspired by The General Theory. After the NCCR and its emphasis on microfoundations, it became much more deductive. As Hoover (2001, p. 72) writes, ‘[t]he conviction that macroeconomics must possess microfoundations has changed the face of the discipline in the last quarter century’. In terms of this second strand, the NCCR was triumphant and remains largely unchallenged within mainstream academic macroeconomics.

Perhaps I will have some more to say about Wren-Lewis’s article in a future post. And perhaps also about Nick Rowe’s article.

HT: Tom Brown

Update (02/11/16):

On his blog Jason Smith provides some further commentary on his exchange with Avon on Nick Rowe’s blog, explaining at greater length how irrelevant microfoundations are to doing real empirically relevant physics. He also expands on and puts into a broader meta-theoretical context my point about the extremely narrow range of applicability of the rational-expectations equilibrium assumptions of New Classical macroeconomics.

David Glasner found a back-and-forth between me and a commenter (with the pseudonym “Avon Barksdale” after [a] character on The Wire who [didn’t end] up taking an economics class [per Tom below]) on Nick Rowe’s blog who expressed the (widely held) view that the only scientific way to proceed in economics is with rigorous microfoundations. “Avon” held physics up as a purported shining example of this approach.
I couldn’t let it go: even physics isn’t that reductionist. I gave several examples of cases where the microfoundations were actually known, but not used to figure things out: thermodynamics, nuclear physics. Even modern physics is supposedly built on string theory. However physicists do not require every pion scattering amplitude be calculated from QCD. Some people do do so-called lattice calculations. But many resort to the “effective” chiral perturbation theory. In a sense, that was what my thesis was about — an effective theory that bridges the gap between lattice QCD and chiral perturbation theory. That effective theory even gave up on one of the basic principles of QCD — confinement. It would be like an economist giving up opportunity cost (a basic principle of the micro theory). But no physicist ever said to me “your model is flawed because it doesn’t have true microfoundations”. That’s because the kind of hard core reductionism that surrounds the microfoundations paradigm doesn’t exist in physics — the most hard core reductionist natural science!
In his post, Glasner repeated something that he had before and — probably because it was in the context of a bunch of quotes about physics — I thought of another analogy.

Glasner says:

But the comparative-statics method is premised on the assumption that before and after the parameter change the system is in full equilibrium or at an optimum, and that the equilibrium, if not unique, is at least locally stable and the parameter change is sufficiently small not to displace the system so far that it does not revert back to a new equilibrium close to the original one. So the microeconomic laws invoked by Avon are valid only in the neighborhood of a stable equilibrium, and the macroeconomics that Avon’s New Classical mentors have imposed on the economics profession is a macroeconomics that, by methodological fiat, is operative only in the neighborhood of a locally stable equilibrium.

 

This hits on a basic principle of physics: any theory radically simplifies near an equilibrium.

Go to Jason’s blog to read the rest of his important and insightful post.

Representative Agents, Homunculi and Faith-Based Macroeconomics

After my previous post comparing the neoclassical synthesis in its various versions to the mind-body problem, there was an interesting Twitter exchange between Steve Randy Waldman and David Andolfatto in which Andolfatto queried whether Waldman and I are aware that there are representative-agent models in which the equilibrium is not Pareto-optimal. Andalfatto raised an interesting point, but what I found interesting about it might be different from what Andalfatto was trying to show, which, I am guessing, was that a representative-agent modeling strategy doesn’t necessarily commit the theorist to the conclusion that the world is optimal and that the solutions of the model can never be improved upon by a monetary/fiscal-policy intervention. I concede the point. It is well-known I think that, given the appropriate assumptions, a general-equilibrium model can have a sub-optimal solution. Given those assumptions, the corresponding representative-agent will also choose a sub-optimal solution. So I think I get that, but perhaps there’s a more subtle point  that I’m missing. If so, please set me straight.

But what I was trying to argue was not that representative-agent models are necessarily optimal, but that representative-agent models suffer from an inherent, and, in my view, fatal, flaw: they can’t explain any real macroeconomic phenomenon, because a macroeconomic phenomenon has to encompass something more than the decision of a single agent, even an omniscient central planner. At best, the representative agent is just a device for solving an otherwise intractable general-equilibrium model, which is how I think Lucas originally justified the assumption.

Yet just because a general-equilibrium model can be formulated so that it can be solved as the solution of an optimizing agent does not explain the economic mechanism or process that generates the solution. The mathematical solution of a model does not necessarily provide any insight into the adjustment process or mechanism by which the solution actually is, or could be, achieved in the real world. Your ability to find a solution for a mathematical problem does not mean that you understand the real-world mechanism to which the solution of your model corresponds. The correspondence between your model may be a strictly mathematical correspondence which may not really be in any way descriptive of how any real-world mechanism or process actually operates.

Here’s an example of what I am talking about. Consider a traffic-flow model explaining how congestion affects vehicle speed and the flow of traffic. It seems obvious that traffic congestion is caused by interactions between the different vehicles traversing a thoroughfare, just as it seems obvious that market exchange arises as the result of interactions between the different agents seeking to advance their own interests. OK, can you imagine building a useful traffic-flow model based on solving for the optimal plan of a representative vehicle?

I don’t think so. Once you frame the model in terms of a representative vehicle, you have abstracted from the phenomenon to be explained. The entire exercise would be pointless – unless, that is, you assumed that interactions between vehicles are so minimal that they can be ignored. But then why would you be interested in congestion effects? If you want to claim that your model has any relevance to the effect of congestion on traffic flow, you can’t base the claim on an assumption that there is no congestion.

Or to take another example, suppose you want to explain the phenomenon that, at sporting events, all, or almost all, the spectators sit in their seats but occasionally get up simultaneously from their seats to watch the play on the field or court. Would anyone ever think that an explanation in terms of a representative spectator could explain that phenomenon?

In just the same way, a representative-agent macroeconomic model necessarily abstracts from the interactions between actual agents. Obviously, by abstracting from the interactions, the model can’t demonstrate that there are no interactions between agents in the real world or that their interactions are too insignificant to matter. I would be shocked if anyone really believed that the interactions between agents are unimportant, much less, negligible; nor have I seen an argument that interactions between agents are unimportant, the concept of network effects, to give just one example, being an important topic in microeconomics.

It’s no answer to say that all the interactions are accounted for within the general-equilibrium model. That is just a form of question-begging. The representative agent is being assumed because without him the problem of finding a general-equilibrium solution of the model is very difficult or intractable. Taking into account interactions makes the model too complicated to work with analytically, so it is much easier — but still hard enough to allow the theorist to perform some fancy mathematical techniques — to ignore those pesky interactions. On top of that, the process by which the real world arrives at outcomes to which a general-equilibrium model supposedly bears at least some vague resemblance can’t even be described by conventional modeling techniques.

The modeling approach seems like that of a neuroscientist saying that, because he could simulate the functions, electrical impulses, chemical reactions, and neural connections in the brain – which he can’t do and isn’t even close to doing, even though a neuroscientist’s understanding of the brain far surpasses any economist’s understanding of the economy – he can explain consciousness. Simulating the operation of a brain would not explain consciousness, because the computer on which the neuroscientist performed the simulation would not become conscious in the course of the simulation.

Many neuroscientists and other materialists like to claim that consciousness is not real, that it’s just an epiphenomenon. But we all have the subjective experience of consciousness, so whatever it is that someone wants to call it, consciousness — indeed the entire world of mental phenomena denoted by that term — remains an unexplained phenomenon, a phenomenon that can only be dismissed as unreal on the basis of a metaphysical dogma that denies the existence of anything that can’t be explained as the result of material and physical causes.

I call that metaphysical belief a dogma not because it’s false — I have no way of proving that it’s false — but because materialism is just as much a metaphysical belief as deism or monotheism. It graduates from belief to dogma when people assert not only that the belief is true but that there’s something wrong with you if you are unwilling to believe it as well. The most that I would say against the belief in materialism is that I can’t understand how it could possibly be true. But I admit that there are a lot of things that I just don’t understand, and I will even admit to believing in some of those things.

New Classical macroeconomists, like, say, Robert Lucas and, perhaps, Thomas Sargent, like to claim that unless a macroeconomic model is microfounded — by which they mean derived from an explicit intertemporal optimization exercise typically involving a representative agent or possibly a small number of different representative agents — it’s not an economic model, because the model, being vulnerable to the Lucas critique, is theoretically superficial and vacuous. But only models of intertemporal equilibrium — a set of one or more mutually consistent optimal plans — are immune to the Lucas critique, so insisting on immunity to the Lucas critique as a prerequisite for a macroeconomic model is a guarantee of failure if your aim to explain anything other than an intertemporal equilibrium.

Unless, that is, you believe that real world is in fact the realization of a general equilibrium model, which is what real-business-cycle theorists, like Edward Prescott, at least claim to believe. Like materialist believers that all mental states are epiphenomenous, and that consciousness is an (unexplained) illusion, real-business-cycle theorists purport to deny that there is such a thing as a disequilibrium phenomenon, the so-called business cycle, in their view, being nothing but a manifestation of the intertemporal-equilibrium adjustment of an economy to random (unexplained) productivity shocks. According to real-business-cycle theorists, such characteristic phenomena of business cycles as surprise, regret, disappointed expectations, abandoned and failed plans, the inability to find work at wages comparable to wages that other similar workers are being paid are not real phenomena; they are (unexplained) illusions and misnomers. The real-business-cycle theorists don’t just fail to construct macroeconomic models; they deny the very existence of macroeconomics, just as strict materialists deny the existence of consciousness.

What is so preposterous about the New-Classical/real-business-cycle methodological position is not the belief that the business cycle can somehow be modeled as a purely equilibrium phenomenon, implausible as that idea seems, but the insistence that only micro-founded business-cycle models are methodologically acceptable. It is one thing to believe that ultimately macroeconomics and business-cycle theory will be reduced to the analysis of individual agents and their interactions. But current micro-founded models can’t provide explanations for what many of us think are basic features of macroeconomic and business-cycle phenomena. If non-micro-founded models can provide explanations for those phenomena, even if those explanations are not fully satisfactory, what basis is there for rejecting them just because of a methodological precept that disqualifies all non-micro-founded models?

According to Kevin Hoover, the basis for insisting that only micro-founded macroeconomic models are acceptable, even if the microfoundation consists in a single representative agent optimizing for an entire economy, is eschatological. In other words, because of a belief that economics will eventually develop analytical or computational techniques sufficiently advanced to model an entire economy in terms of individual interacting agents, an analysis based on a single representative agent, as the first step on this theoretical odyssey, is somehow methodologically privileged over alternative models that do not share that destiny. Hoover properly rejects the presumptuous notion that an avowed, but unrealized, theoretical destiny, can provide a privileged methodological status to an explanatory strategy. The reductionist microfoundationalism of New-Classical macroeconomics and real-business-cycle theory, with which New Keynesian economists have formed an alliance of convenience, is truly a faith-based macroeconomics.

The remarkable similarity between the reductionist microfoundational methodology of New-Classical macroeconomics and the reductionist materialist approach to the concept of mind suggests to me that there is also a close analogy between the representative agent and what philosophers of mind call a homunculus. The Cartesian materialist theory of mind maintains that, at some place or places inside the brain, there resides information corresponding to our conscious experience. The question then arises: how does our conscious experience access the latent information inside the brain? And the answer is that there is a homunculus (or little man) that processes the information for us so that we can perceive it through him. For example, the homunculus (see the attached picture of the little guy) views the image cast by light on the retina as if he were watching a movie projected onto a screen.

homunculus

But there is an obvious fallacy, because the follow-up question is: how does our little friend see anything? Well, the answer must be that there’s another, smaller, homunculus inside his brain. You can probably already tell that this argument is going to take us on an infinite regress. So what purports to be an explanation turns out to be just a form of question-begging. Sound familiar? The only difference between the representative agent and the homunculus is that the representative agent begs the question immediately without having to go on an infinite regress.

PS I have been sidetracked by other responsibilities, so I have not been blogging much, if at all, for the last few weeks. I hope to post more frequently, but I am afraid that my posting and replies to comments are likely to remain infrequent for the next couple of months.

Romer v. Lucas

A couple of months ago, Paul Romer created a stir by publishing a paper in the American Economic Review “Mathiness in the Theory of Economic Growth,” an attack on two papers, one by McGrattan and Prescott and the other by Lucas and Moll on aspects of growth theory. He accused the authors of those papers of using mathematical modeling as a cover behind which to hide assumptions guaranteeing results by which the authors could promote their research agendas. In subsequent blog posts, Romer has sharpened his attack, focusing it more directly on Lucas, whom he accuses of a non-scientific attachment to ideological predispositions that have led him to violate what he calls Feynman integrity, a concept eloquently described by Feynman himself in a 1974 commencement address at Caltech.

It’s a kind of scientific integrity, a principle of scientific thought that corresponds to a kind of utter honesty–a kind of leaning over backwards. For example, if you’re doing an experiment, you should report everything that you think might make it invalid–not only what you think is right about it: other causes that could possibly explain your results; and things you thought of that you’ve eliminated by some other experiment, and how they worked–to make sure the other fellow can tell they have been eliminated.

Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can–if you know anything at all wrong, or possibly wrong–to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition.

Romer contrasts this admirable statement of what scientific integrity means with another by George Stigler, seemingly justifying, or at least excusing, a kind of special pleading on behalf of one’s own theory. And the institutional and perhaps ideological association between Stigler and Lucas seems to suggest that Lucas is inclined to follow the permissive and flexible Stiglerian ethic rather than rigorous Feynman standard of scientific integrity. Romer regards this as a breach of the scientific method and a step backward for economics as a science.

I am not going to comment on the specific infraction that Romer accuses Lucas of having committed; I am not familiar with the mathematical question in dispute. Certainly if Lucas was aware that his argument in the paper Romer criticizes depended on the particular mathematical assumption in question, Lucas should have acknowledged that to be the case. And even if, as Lucas asserted in responding to a direct question by Romer, he could have derived the result in a more roundabout way, then he should have pointed that out, too. However, I don’t regard the infraction alleged by Romer to be more than a misdemeanor, hardly a scandalous breach of the scientific method.

Why did Lucas, who as far as I can tell was originally guided by Feynman integrity, switch to the mode of Stigler conviction? Market clearing did not have to evolve from auxiliary hypothesis to dogma that could not be questioned.

My conjecture is economists let small accidents of intellectual history matter too much. If we had behaved like scientists, things could have turned out very differently. It is worth paying attention to these accidents because doing so might let us take more control over the process of scientific inquiry that we are engaged in. At the very least, we should try to reduce the odds that that personal frictions and simple misunderstandings could once again cause us to veer off on some damaging trajectory.

I suspect that it was personal friction and a misunderstanding that encouraged a turn toward isolation (or if you prefer, epistemic closure) by Lucas and colleagues. They circled the wagons because they thought that this was the only way to keep the rational expectations revolution alive. The misunderstanding is that Lucas and his colleagues interpreted the hostile reaction they received from such economists as Robert Solow to mean that they were facing implacable, unreasoning resistance from such departments as MIT. In fact, in a remarkably short period of time, rational expectations completely conquered the PhD program at MIT.

More recently Romer, having done graduate work both at MIT and Chicago in the late 1970s, has elaborated on the personal friction between Solow and Lucas and how that friction may have affected Lucas, causing him to disengage from the professional mainstream. Paul Krugman, who was at MIT when this nastiness was happening, is skeptical of Romer’s interpretation.

My own view is that being personally and emotionally attached to one’s own theories, whether for religious or ideological or other non-scientific reasons, is not necessarily a bad thing as long as there are social mechanisms allowing scientists with different scientific viewpoints an opportunity to make themselves heard. If there are such mechanisms, the need for Feynman integrity is minimized, because individual lapses of integrity will be exposed and remedied by criticism from other scientists; scientific progress is possible even if scientists don’t live up to the Feynman standards, and maintain their faith in their theories despite contradictory evidence. But, as I am going to suggest below, there are reasons to doubt that social mechanisms have been operating to discipline – not suppress, just discipline – dubious economic theorizing.

My favorite example of the importance of personal belief in, and commitment to the truth of, one’s own theories is Galileo. As discussed by T. S. Kuhn in The Structure of Scientific Revolutions. Galileo was arguing for a paradigm change in how to think about the universe, despite being confronted by empirical evidence that appeared to refute the Copernican worldview he believed in: the observations that the sun revolves around the earth, and that the earth, as we directly perceive it, is, apart from the occasional earthquake, totally stationary — good old terra firma. Despite that apparently contradictory evidence, Galileo had an alternative vision of the universe in which the obvious movement of the sun in the heavens was explained by the spinning of the earth on its axis, and the stationarity of the earth by the assumption that all our surroundings move along with the earth, rendering its motion imperceptible, our perception of motion being relative to a specific frame of reference.

At bottom, this was an almost metaphysical world view not directly refutable by any simple empirical test. But Galileo adopted this worldview or paradigm, because he deeply believed it to be true, and was therefore willing to defend it at great personal cost, refusing to recant his Copernican view when he could have easily appeased the Church by describing the Copernican theory as just a tool for predicting planetary motion rather than an actual representation of reality. Early empirical tests did not support heliocentrism over geocentrism, but Galileo had faith that theoretical advancements and improved measurements would eventually vindicate the Copernican theory. He was right of course, but strict empiricism would have led to a premature rejection of heliocentrism. Without a deep personal commitment to the Copernican worldview, Galileo might not have articulated the case for heliocentrism as persuasively as he did, and acceptance of heliocentrism might have been delayed for a long time.

Imre Lakatos called such deeply-held views underlying a scientific theory the hard core of the theory (aka scientific research program), a set of beliefs that are maintained despite apparent empirical refutation. The response to any empirical refutation is not to abandon or change the hard core but to adjust what Lakatos called the protective belt of the theory. Eventually, as refutations or empirical anomalies accumulate, the research program may undergo a crisis, leading to its abandonment, or it may simply degenerate if it fails to solve new problems or discover any new empirical facts or regularities. So Romer’s criticism of Lucas’s dogmatic attachment to market clearing – Lucas frequently makes use of ad hoc price stickiness assumptions; I don’t know why Romer identifies market-clearing as a Lucasian dogma — may be no more justified from a history of science perspective than would criticism of Galileo’s dogmatic attachment to heliocentrism.

So while I have many problems with Lucas, lack of Feynman integrity is not really one of them, certainly not in the top ten. What I find more disturbing is his narrow conception of what economics is. As he himself wrote in an autobiographical sketch for Lives of the Laureates, he was bewitched by the beauty and power of Samuelson’s Foundations of Economic Analysis when he read it the summer before starting his training as a graduate student at Chicago in 1960. Although it did not have the transformative effect on me that it had on Lucas, I greatly admire the Foundations, but regardless of whether Samuelson himself meant to suggest such an idea (which I doubt), it is absurd to draw this conclusion from it:

I loved the Foundations. Like so many others in my cohort, I internalized its view that if I couldn’t formulate a problem in economic theory mathematically, I didn’t know what I was doing. I came to the position that mathematical analysis is not one of many ways of doing economic theory: It is the only way. Economic theory is mathematical analysis. Everything else is just pictures and talk.

Oh, come on. Would anyone ever think that unless you can formulate the problem of whether the earth revolves around the sun or the sun around the earth mathematically, you don’t know what you are doing? And, yet, remarkably, on the page following that silly assertion, one finds a totally brilliant description of what it was like to take graduate price theory from Milton Friedman.

Friedman rarely lectured. His class discussions were often structured as debates, with student opinions or newspaper quotes serving to introduce a problem and some loosely stated opinions about it. Then Friedman would lead us into a clear statement of the problem, considering alternative formulations as thoroughly as anyone in the class wanted to. Once formulated, the problem was quickly analyzed—usually diagrammatically—on the board. So we learned how to formulate a model, to think about and decide which features of a problem we could safely abstract from and which he needed to put at the center of the analysis. Here “model” is my term: It was not a term that Friedman liked or used. I think that for him talking about modeling would have detracted from the substantive seriousness of the inquiry we were engaged in, would divert us away from the attempt to discover “what can be done” into a merely mathematical exercise. [my emphasis].

Despite his respect for Friedman, it’s clear that Lucas did not adopt and internalize Friedman’s approach to economic problem solving, but instead internalized the caricature he extracted from Samuelson’s Foundations: that mathematical analysis is the only legitimate way of doing economic theory, and that, in particular, the essence of macroeconomics consists in a combination of axiomatic formalism and philosophical reductionism (microfoundationalism). For Lucas, the only scientifically legitimate macroeconomic models are those that can be deduced from the axiomatized Arrow-Debreu-McKenzie general equilibrium model, with solutions that can be computed and simulated in such a way that the simulations can be matched up against the available macroeconomics time series on output, investment and consumption.

This was both bad methodology and bad science, restricting the formulation of economic problems to those for which mathematical techniques are available to be deployed in finding solutions. On the one hand, the rational-expectations assumption made finding solutions to certain intertemporal models tractable; on the other, the assumption was justified as being required by the rationality assumptions of neoclassical price theory.

In a recent review of Lucas’s Collected Papers on Monetary Theory, Thomas Sargent makes a fascinating reference to Kenneth Arrow’s 1967 review of the first two volumes of Paul Samuelson’s Collected Works in which Arrow referred to the problematic nature of the neoclassical synthesis of which Samuelson was a chief exponent.

Samuelson has not addressed himself to one of the major scandals of current price theory, the relation between microeconomics and macroeconomics. Neoclassical microeconomic equilibrium with fully flexible prices presents a beautiful picture of the mutual articulations of a complex structure, full employment being one of its major elements. What is the relation between this world and either the real world with its recurrent tendencies to unemployment of labor, and indeed of capital goods, or the Keynesian world of underemployment equilibrium? The most explicit statement of Samuelson’s position that I can find is the following: “Neoclassical analysis permits of fully stable underemployment equilibrium only on the assumption of either friction or a peculiar concatenation of wealth-liquidity-interest elasticities. . . . [The neoclassical analysis] goes far beyond the primitive notion that, by definition of a Walrasian system, equilibrium must be at full employment.” . . .

In view of the Phillips curve concept in which Samuelson has elsewhere shown such interest, I take the second sentence in the above quotation to mean that wages are stationary whenever unemployment is X percent, with X positive; thus stationary unemployment is possible. In general, one can have a neoclassical model modified by some elements of price rigidity which will yield Keynesian-type implications. But such a model has yet to be constructed in full detail, and the question of why certain prices remain rigid becomes of first importance. . . . Certainly, as Keynes emphasized the rigidity of prices has something to do with the properties of money; and the integration of the demand and supply of money with general competitive equilibrium theory remains incomplete despite attempts beginning with Walras himself.

If the neoclassical model with full price flexibility were sufficiently unrealistic that stable unemployment equilibrium be possible, then in all likelihood the bulk of the theorems derived by Samuelson, myself, and everyone else from the neoclassical assumptions are also contrafactual. The problem is not resolved by what Samuelson has called “the neoclassical synthesis,” in which it is held that the achievement of full employment requires Keynesian intervention but that neoclassical theory is valid when full employment is reached. . . .

Obviously, I believe firmly that the mutual adjustment of prices and quantities represented by the neoclassical model is an important aspect of economic reality worthy of the serious analysis that has been bestowed on it; and certain dramatic historical episodes – most recently the reconversion of the United States from World War II and the postwar European recovery – suggest that an economic mechanism exists which is capable of adaptation to radical shifts in demand and supply conditions. On the other hand, the Great Depression and the problems of developing countries remind us dramatically that something beyond, but including, neoclassical theory is needed.

Perhaps in a future post, I may discuss this passage, including a few sentences that I have omitted here, in greater detail. For now I will just say that Arrow’s reference to a “neoclassical microeconomic equilibrium with fully flexible prices” seems very strange inasmuch as price flexibility has absolutely no role in the proofs of the existence of a competitive general equilibrium for which Arrow and Debreu and McKenzie are justly famous. All the theorems Arrow et al. proved about the neoclassical equilibrium were related to existence, uniqueness and optimaiity of an equilibrium supported by an equilibrium set of prices. Price flexibility was not involved in those theorems, because the theorems had nothing to do with how prices adjust in response to a disequilibrium situation. What makes this juxtaposition of neoclassical microeconomic equilibrium with fully flexible prices even more remarkable is that about eight years earlier Arrow wrote a paper (“Toward a Theory of Price Adjustment”) whose main concern was the lack of any theory of price adjustment in competitive equilibrium, about which I will have more to say below.

Sargent also quotes from two lectures in which Lucas referred to Don Patinkin’s treatise Money, Interest and Prices which provided perhaps the definitive statement of the neoclassical synthesis Samuelson espoused. In one lecture (“My Keynesian Education” presented to the History of Economics Society in 2003) Lucas explains why he thinks Patinkin’s book did not succeed in its goal of integrating value theory and monetary theory:

I think Patinkin was absolutely right to try and use general equilibrium theory to think about macroeconomic problems. Patinkin and I are both Walrasians, whatever that means. I don’t see how anybody can not be. It’s pure hindsight, but now I think that Patinkin’s problem was that he was a student of Lange’s, and Lange’s version of the Walrasian model was already archaic by the end of the 1950s. Arrow and Debreu and McKenzie had redone the whole theory in a clearer, more rigorous, and more flexible way. Patinkin’s book was a reworking of his Chicago thesis from the middle 1940s and had not benefited from this more recent work.

In the other lecture, his 2003 Presidential address to the American Economic Association, Lucas commented further on why Patinkin fell short in his quest to unify monetary and value theory:

When Don Patinkin gave his Money, Interest, and Prices the subtitle “An Integration of Monetary and Value Theory,” value theory meant, to him, a purely static theory of general equilibrium. Fluctuations in production and employment, due to monetary disturbances or to shocks of any other kind, were viewed as inducing disequilibrium adjustments, unrelated to anyone’s purposeful behavior, modeled with vast numbers of free parameters. For us, today, value theory refers to models of dynamic economies subject to unpredictable shocks, populated by agents who are good at processing information and making choices over time. The macroeconomic research I have discussed today makes essential use of value theory in this modern sense: formulating explicit models, computing solutions, comparing their behavior quantitatively to observed time series and other data sets. As a result, we are able to form a much sharper quantitative view of the potential of changes in policy to improve peoples’ lives than was possible a generation ago.

So, as Sargent observes, Lucas recreated an updated neoclassical synthesis of his own based on the intertemporal Arrow-Debreu-McKenzie version of the Walrasian model, augmented by a rationale for the holding of money and perhaps some form of monetary policy, via the assumption of credit-market frictions and sticky prices. Despite the repudiation of the updated neoclassical synthesis by his friend Edward Prescott, for whom monetary policy is irrelevant, Lucas clings to neoclassical synthesis 2.0. Sargent quotes this passage from Lucas’s 1994 retrospective review of A Monetary History of the US by Friedman and Schwartz to show how tightly Lucas clings to neoclassical synthesis 2.0 :

In Kydland and Prescott’s original model, and in many (though not all) of its descendants, the equilibrium allocation coincides with the optimal allocation: Fluctuations generated by the model represent an efficient response to unavoidable shocks to productivity. One may thus think of the model not as a positive theory suited to all historical time periods but as a normative benchmark providing a good approximation to events when monetary policy is conducted well and a bad approximation when it is not. Viewed in this way, the theory’s relative success in accounting for postwar experience can be interpreted as evidence that postwar monetary policy has resulted in near-efficient behavior, not as evidence that money doesn’t matter.

Indeed, the discipline of real business cycle theory has made it more difficult to defend real alternaltives to a monetary account of the 1930s than it was 30 years ago. It would be a term-paper-size exercise, for example, to work out the possible effects of the 1930 Smoot-Hawley Tariff in a suitably adapted real business cycle model. By now, we have accumulated enough quantitative experience with such models to be sure that the aggregate effects of such a policy (in an economy with a 5% foreign trade sector before the Act and perhaps a percentage point less after) would be trivial.

Nevertheless, in the absence of some catastrophic error in monetary policy, Lucas evidently believes that the key features of the Arrow-Debreu-McKenzie model are closely approximated in the real world. That may well be true. But if it is, Lucas has no real theory to explain why.

In his 1959 paper (“Towards a Theory of Price Adjustment”) I just mentioned, Arrow noted that the theory of competitive equilibrium has no explanation of how equilibrium prices are actually set. Indeed, the idea of competitive price adjustment is beset by a paradox: all agents in a general equilibrium being assumed to be price takers, how is it that a new equilibrium price is ever arrived at following any disturbance to an initial equilibrium? Arrow had no answer to the question, but offered the suggestion that, out of equilibrium, agents are not price takers, but price searchers, possessing some measure of market power to set price in the transition between the old and new equilibrium. But the upshot of Arrow’s discussion was that the problem and the paradox awaited solution. Almost sixty years on, some of us are still waiting, but for Lucas and the Lucasians, there is neither problem nor paradox, because the actual price is the equilibrium price, and the equilibrium price is always the (rationally) expected price.

If the social functions of science were being efficiently discharged, this rather obvious replacement of problem solving by question begging would not have escaped effective challenge and opposition. But Lucas was able to provide cover for this substitution by persuading the profession to embrace his microfoundational methodology, while offering irresistible opportunities for professional advancement to younger economists who could master the new analytical techniques that Lucas and others were rapidly introducing, thereby neutralizing or coopting many of the natural opponents to what became modern macroeconomics. So while Romer considers the conquest of MIT by the rational-expectations revolution, despite the opposition of Robert Solow, to be evidence for the advance of economic science, I regard it as a sign of the social failure of science to discipline a regressive development driven by the elevation of technique over substance.

Krugman’s Second Best

A couple of days ago Paul Krugman discussed “Second-best Macroeconomics” on his blog. I have no real quarrel with anything he said, but I would like to amplify his discussion of what is sometimes called the problem of second-best, because I think the problem of second best has some really important implications for macroeconomics beyond the limited application of the problem that Krugman addressed. The basic idea underlying the problem of second best is not that complicated, but it has many applications, and what made the 1956 paper (“The General Theory of Second Best”) by R. G. Lipsey and Kelvin Lancaster a classic was that it showed how a number of seemingly disparate problems were really all applications of a single unifying principle. Here’s how Krugman frames his application of the second-best problem.

[T]he whole western world has spent years suffering from a severe shortfall of aggregate demand; in Europe a severe misalignment of national costs and prices has been overlaid on this aggregate problem. These aren’t hard problems to diagnose, and simple macroeconomic models — which have worked very well, although nobody believes it — tell us how to solve them. Conventional monetary policy is unavailable thanks to the zero lower bound, but fiscal policy is still on tap, as is the possibility of raising the inflation target. As for misaligned costs, that’s where exchange rate adjustments come in. So no worries: just hit the big macroeconomic That Was Easy button, and soon the troubles will be over.

Except that all the natural answers to our problems have been ruled out politically. Austerians not only block the use of fiscal policy, they drive it in the wrong direction; a rise in the inflation target is impossible given both central-banker prejudices and the power of the goldbug right. Exchange rate adjustment is blocked by the disappearance of European national currencies, plus extreme fear over technical difficulties in reintroducing them.

As a result, we’re stuck with highly problematic second-best policies like quantitative easing and internal devaluation.

I might quibble with Krugman about the quality of the available macroeconomic models, by which I am less impressed than he, but that’s really beside the point of this post, so I won’t even go there. But I can’t let the comment about the inflation target pass without observing that it’s not just “central-banker prejudices” and the “goldbug right” that are to blame for the failure to raise the inflation target; for reasons that I don’t claim to understand myself, the political consensus in both Europe and the US in favor of perpetually low or zero inflation has been supported with scarcely any less fervor by the left than the right. It’s only some eccentric economists – from diverse positions on the political spectrum – that have been making the case for inflation as a recovery strategy. So the political failure has been uniform across the political spectrum.

OK, having registered my factual disagreement with Krugman about the source of our anti-inflationary intransigence, I can now get to the main point. Here’s Krugman:

“[S]econd best” is an economic term of art. It comes from a classic 1956 paper by Lipsey and Lancaster, which showed that policies which might seem to distort markets may nonetheless help the economy if markets are already distorted by other factors. For example, suppose that a developing country’s poorly functioning capital markets are failing to channel savings into manufacturing, even though it’s a highly profitable sector. Then tariffs that protect manufacturing from foreign competition, raise profits, and therefore make more investment possible can improve economic welfare.

The problems with second best as a policy rationale are familiar. For one thing, it’s always better to address existing distortions directly, if you can — second best policies generally have undesirable side effects (e.g., protecting manufacturing from foreign competition discourages consumption of industrial goods, may reduce effective domestic competition, and so on). . . .

But here we are, with anything resembling first-best macroeconomic policy ruled out by political prejudice, and the distortions we’re trying to correct are huge — one global depression can ruin your whole day. So we have quantitative easing, which is of uncertain effectiveness, probably distorts financial markets at least a bit, and gets trashed all the time by people stressing its real or presumed faults; someone like me is then put in the position of having to defend a policy I would never have chosen if there seemed to be a viable alternative.

In a deep sense, I think the same thing is involved in trying to come up with less terrible policies in the euro area. The deal that Greece and its creditors should have reached — large-scale debt relief, primary surpluses kept small and not ramped up over time — is a far cry from what Greece should and probably would have done if it still had the drachma: big devaluation now. The only way to defend the kind of thing that was actually on the table was as the least-worst option given that the right response was ruled out.

That’s one example of a second-best problem, but it’s only one of a variety of problems, and not, it seems to me, the most macroeconomically interesting. So here’s the second-best problem that I want to discuss: given one distortion (i.e., a departure from one of the conditions for Pareto-optimality), reaching a second-best sub-optimum requires violating other – likely all the other – conditions for reaching the first-best (Pareto) optimum. The strategy for getting to the second-best suboptimum cannot be to achieve as many of the conditions for reaching the first-best optimum as possible; the conditions for reaching the second-best optimum are in general totally different from the conditions for reaching the first-best optimum.

So what’s the deeper macroeconomic significance of the second-best principle?

I would put it this way. Suppose there’s a pre-existing macroeconomic equilibrium, all necessary optimality conditions between marginal rates of substitution in production and consumption and relative prices being satisfied. Let the initial equilibrium be subjected to a macoreconomic disturbance. The disturbance will immediately affect a range — possibly all — of the individual markets, and all optimality conditions will change, so that no market will be unaffected when a new optimum is realized. But while optimality for the system as a whole requires that prices adjust in such a way that the optimality conditions are satisfied in all markets simultaneously, each price adjustment that actually occurs is a response to the conditions in a single market – the relationship between amounts demanded and supplied at the existing price. Each price adjustment being a response to a supply-demand imbalance in an individual market, there is no theory to explain how a process of price adjustment in real time will ever restore an equilibrium in which all optimality conditions are simultaneously satisfied.

Invoking a general Smithian invisible-hand theorem won’t work, because, in this context, the invisible-hand theorem tells us only that if an equilibrium price vector were reached, the system would be in an optimal state of rest with no tendency to change. The invisible-hand theorem provides no account of how the equilibrium price vector is discovered by any price-adjustment process in real time. (And even tatonnement, a non-real-time process, is not guaranteed to work as shown by the Sonnenschein-Mantel-Debreu Theorem). With price adjustment in each market entirely governed by the demand-supply imbalance in that market, market prices determined in individual markets need not ensure that all markets clear simultaneously or satisfy the optimality conditions.

Now it’s true that we have a simple theory of price adjustment for single markets: prices rise if there’s an excess demand and fall if there’s an excess supply. If demand and supply curves have normal slopes, the simple price adjustment rule moves the price toward equilibrium. But that partial-equilibriuim story is contingent on the implicit assumption that all other markets are in equilibrium. When all markets are in disequilibrium, moving toward equilibrium in one market will have repercussions on other markets, and the simple story of how price adjustment in response to a disequilibrium restores equilibrium breaks down, because market conditions in every market depend on market conditions in every other market. So unless all markets arrive at equilibrium simultaneously, there’s no guarantee that equilibrium will obtain in any of the markets. Disequilibrium in any market can mean disequilibrium in every market. And if a single market is out of kilter, the second-best, suboptimal solution for the system is totally different from the first-best solution for all markets.

In the standard microeconomics we are taught in econ 1 and econ 101, all these complications are assumed away by restricting the analysis of price adjustment to a single market. In other words, as I have pointed out in a number of previous posts (here and here), standard microeconomics is built on macroeconomic foundations, and the currently fashionable demand for macroeconomics to be microfounded turns out to be based on question-begging circular reasoning. Partial equilibrium is a wonderful pedagogical device, and it is an essential tool in applied microeconomics, but its limitations are often misunderstood or ignored.

An early macroeconomic application of the theory of second is the statement by the quintessentially orthodox pre-Keynesian Cambridge economist Frederick Lavington who wrote in his book The Trade Cycle “the inactivity of all is the cause of the inactivity of each.” Each successive departure from the conditions for second-, third-, fourth-, and eventually nth-best sub-optima has additional negative feedback effects on the rest of the economy, moving it further and further away from a Pareto-optimal equilibrium with maximum output and full employment. The fewer people that are employed, the more difficult it becomes for anyone to find employment.

This insight was actually admirably, if inexactly, expressed by Say’s Law: supply creates its own demand. The cause of the cumulative contraction of output in a depression is not, as was often suggested, that too much output had been produced, but a breakdown of coordination in which disequilibrium spreads in epidemic fashion from market to market, leaving individual transactors unable to compensate by altering the terms on which they are prepared to supply goods and services. The idea that a partial-equilibrium response, a fall in money wages, can by itself remedy a general-disequilibrium disorder is untenable. Keynes and the Keynesians were therefore completely wrong to accuse Say of committing a fallacy in diagnosing the cause of depressions. The only fallacy lay in the assumption that market adjustments would automatically ensure the restoration of something resembling full-employment equilibrium.

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.


About Me

David Glasner
Washington, DC

I am an economist in the Washington DC area. My research and writing has been mostly on monetary economics and policy and the history of economics. 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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