The Pretense of Knowledge

In which I team up with Friedrich Hayek to explain what the heck’s gone wrong with Economics (Part 1)

• “I confess that I prefer true but imperfect knowledge to a pretense of exact knowledge that is likely to be false.” . . . . . . . Friedrich Hayek

• Any similarity between this essay and Friedrich Hayek’s 1974 Nobel Prize acceptance address is entirely intentional.

• Below, I attempt to “translate” his address into the vernacular from Hayek’s somewhat abstruse English original.

• Hayek’s original text follows my “translation.”

The other day I was watching CNBC as two respected economists bickered over what had caused our post-COVID inflation problem.  One was pretty sure the cause was an exogenous supply-chain shock.  The other thought that government stimulus may have played a role.  Then, last night I heard MMT goddess Stephanie Kelton pronounce with 100% certainty that, no, inflation had resulted from the Fed’s interest rate hikes. None of them mentioned the true cause that should be obvious to everyone: the government goosed M2 by 40% in two years.  (See "Ain't Nothin' but a Party" ).

Way back in early 2021, no economist was forecasting inflation (except, maybe, Larry Summers.)  That is perhaps forgivable: the future is a very difficult thing to forecast.  But for economists today, several years after the fact, to be unable to account for inflation makes one question whether they have any clue what the actual cause of inflation might be. It seems to me that if economics were really a science (as all economists contend), it would be able to explain as fundamental a phenomenon as inflation in retrospect even if it could not be predicted.

Similarly, a decade ago, Western economies were hammered and nearly destroyed by the 2007-2008 Financial Crisis.  Economists were completely blindsided by the crisis.   Worse, as with today’s inflation problem, even today no economist understands what actually caused it.  (But I do: see  "Basel: Faulty"  )

All of this made me ask myself the following question: “Charlie, what the heck is wrong with economics?”  I resolved to spend some time trying to answer this question.

My initial (prior) view is that there are at least four fundamental problems with economics today:

1. The dream of economists to advance economics into the ranks of the true sciences has led to a fetish for mathematical models and an obsession with quantitative data.  Frequently this means that less measurable, but more relevant, variables are studiously avoided.  If this is true, then economics started going off the rails 80 years ago, as Keynes’ heirs took charge. This is the main issue that Hayek addresses in his essay.

2. The Keynesian legacy bequeathed to economics a blind faith in government’s ability to effectively correct Capitalism’s flaws.  Skeptics of government competence and good intentions have been written out of economic textbooks.  This cohort includes Ludwig von Mises, Friedrich Hayek, Milton Friedman, James Buchanan, and Joseph Schumpeter.  (To me, it is an open question whether Keynes himself would have sided with them or the neo-Keynesians.)

   This wrongheaded faith in government intervention stems importantly from the experience in WW II of a group of influential post-war economists: Samuelson, Tobin, Galbraith and Solow among them.  Because war spending extracted us from the Great Depression and defeated the Axis, these economists became convinced that government micromanagement could effectively manage the economy and vanquish the business cycle.

3. Like most academic disciplines, economics today has a distinctly left-leaning bias (to say the least.)  This militates against the dispassionate analysis of economic problems.  In particular, many liberal economists seem to reject such fundamental economic tenets as: resources are limited, inequality is both inevitable and desirable, and just about everybody wants a free lunch.  But guess what? There ain’t no free lunch.

4. In his paradigm-shifting 1962 masterpiece “The Structure of Scientific Revolutions” Thomas Kuhn explained how status quo institutions tend to throw up obstacles to scientific progress and suppress new ideas.  Tenured professors are protective of the ideas that built their careers.  Younger professors who want tenure are unwilling to rock the boat.  Doctoral candidates will not cross their advisors.  Peer reviewed journals, whose “peers” consist of those same tenured professors, will decline to publish unconventional ideas.  The result is a welter of scientists simply tinkering around the edges in a desperate effort to publish work that glorifies their bosses’ achievements.  “Groupthink” is another word for this phenomenon. Today, this has resulted in a “replicability crisis” and sometimes outright fraud driven by P-hacking and other kinds of data manipulation.

If all of this is true in the natural sciences, it is doubly, maybe triply true of the social sciences - prominently economics.  Because most economic theories typically are not testable, they are seldom questioned, let alone falsified, even in the face of compelling qualitative evidence that they are wrong.  I am convinced that nowadays the “status quo” doesn’t just repress disruptive ideas, it forbids any consideration of views (notably the Austrian school) that might challenge the neo-Keynesian orthodoxy .  Political bias makes this much worse than it otherwise would be.  Bias of all kinds has led economics down the wrong path for at least the past several decades.

(Caution: a respected Karl Popper scholar tells me that I am at least somewhat misreading Kuhn. He says “Kuhn didn’t really offer a philosophy along the lines that you present. Rather, he offered a philosophy that said everything scientists think they know is a product of their paradigm so that “rationality” simply means consistency with the ‘paradigm.’ A shift between paradigms is a fundamentally irrational phenomenon. He said a paradigm shift was like a gestalt switch or a religious conversion -  suddenly you see the world in a different way. Popperian philosophers usually think of all this simply as epistemological relativism.”

This particular fellow is a lot smarter than me, so I’m sure he’s right about Kuhn. Even so, I’m going to stick with what I wrote because it’s what Kuhn should have said.

Friedrich Hayek saw all this coming

To get a handle on what is wrong with economics today, an excellent place to start is Friedrich Hayek’s 1974 Nobel Prize acceptance speech entitled “The Pretense of Knowledge.”   In it, he focuses on my first concern: economists’ cult-like faith in arcane quantitative models founded on unrealistic assumptions.  He argues that economics will never achieve the holy grail of full recognition as a science in the same company as physics and chemistry.  Economics, indeed all the social sciences, are simply too complex; too many of the critical factors are inherently unquantifiable and constantly changing.  Results are often unfalsifiable and not amenable to experimentation. Our knowledge of economic phenomena must always be provisional.  Therefore, he says, we must have deep humility about the economic theories that underpin our economic policies.

Hayek was a native German speaking scholar.  Not surprisingly, his prose style is often not crystal clear, to say the least, and is sometimes downright convoluted.  This essay reflects my best attempt to “translate” Hayek’s prose into vernacular English.  My prime objective is to present my understanding of Hayek’s meaning as clearly as possible.  In selecting words and sentences, his own text was always the default choice. I emphasize that this is my reading of Hayek’s intended meanings.  I don’t pretend to have privileged access to his ideas.  I would love to hear alternative views.  In the interest of clarity, I have taken just a few liberties which are enumerated in footnotes at the end of the essay..

Hayek’s original text appears after my revision so you can check my work and see if I may have misread any of his points.

The Pretense of Knowledge

Friedrich Hayek: A translation of his 1974 Nobel Prize acceptance address

These are challenging times for economists.  There is good news and bad news. The good news is that these days the general public concedes to economics some of the prestige and credibility of the natural sciences. The bad news is that economists now confront the serious threat of accelerating inflation which was largely brought about by policies they themselves recommended and even urged governments to pursue.  We have little cause for pride; as a profession we have made a mess of things.

Why haven’t economists been more effective in shaping policy?  One key reason is economists’ propensity to mimic as closely as possible the methods of the physical sciences.  For a social science like economics, the attempt to pursue this objective can lead to outright error.  The discipline of economics is not scientific in the true sense of the word.  It might be better described as “scientistic”.  That is, it mechanically and uncritically imposes on economics methods that were developed for the physical sciences.  In this address, I want to begin by explaining how some of the gravest errors of recent economic policy are a direct consequence of this scientistic error.

One example of scientism is the conviction among most economists that, because there is a positive correlation between total employment and aggregate demand, that one causes the other.  This, they believe, implies that we can permanently assure full employment by applying government policies that maintain total monetary expenditure at an appropriate level.  While this conviction is supported by strong quantitative evidence, I regard it as fundamentally false, and to have acted upon it has been very harmful.

Unlike problems in the physical sciences, economic problems are so complex that the data available to analyze them are necessarily limited and constantly in flux. ^[1] The most important information our models require may elude quantification. In the physical sciences, for the most part, any important factors which determine observed phenomena will themselves be observable and measurable.  But to analyze phenomena as complex as the market, we can hardly ever know, let alone measure, all the causal factors that we wish to analyze.  In the physical sciences we can typically measure those things that, based on our prima facie theory, we have determined to be important.  But in the social sciences, far too often we measure what can be measured and pronounce that important.  At the extreme, this means that only quantitative factors may be considered, to the exclusion of perhaps more important factors which cannot be quantified.

The insistence among economists that all data be quantitative arbitrarily limits the data that we can admit as possible causes of events in the real world.  This view, which is often naively seen as required by scientific procedure, has some paradoxical consequences.  When we study the market and similar social structures, we know that there are many facts^[2] that we can measure only imprecisely or not at all.  Often, economists simply disregard these inconvenient facts and happily proceed on the fiction that the factors which they can measure are the only relevant ones.

Take, for example, the challenge of explaining unemployment.  Most consensus economists believe that employment is above all a function of aggregate demand. The problem is that even the correlation between aggregate demand and total employment is weak.  It is, however, the only variable on which we have quantitative data.  Therefore, it is assumed to be the only causal connection that counts.   This obsession with ostensibly “scientific” evidence implies that a false theory may be regarded as true simply because there exists quantifiable data to support it, while a valid theory will be rejected because it has none.  We may be led to pursue misguided policies simply because they seem to have “scientific” underpinnings.

I believe that serious unemployment cannot be cured with the now fashionable inflationary policies that advise stimulating aggregate demand.  I am convinced that the true cause of unemployment is the existence of discrepancies between the distribution of demand in the economy and the allocation of labor and other resources. While we do not possess incontrovertible data to “prove” my theory, I understand “qualitatively” what causes this discrepancy. Furthermore, we have a fairly good idea how a better balance between demand and supply can be achieved.  That is, the structure of relative prices in the economy has been distorted and the demand for and supply of labor must be brought back in line.

Unfortunately, it is difficult, if not impossible, to obtain a precise “quantitative” measure of the set of prices and wages that will produce employment equilibrium.   We know the general conditions under which an equilibrium can be achieved, but we can never know the precise level of prices and wages that will bring about such an equilibrium. Therefore, we cannot produce statistical evidence to show how much the prevailing prices and wages deviate from those which would produce equilibrium.  The theory is highly useful and may be considered “scientific” in the sense that it can be “falsified”, even if it is not founded on quantitative data.

Why must economists plead ignorance of the sort of facts about which a physical scientist would certainly be expected to give precise information?  The reason is that the social sciences, like much of biology but unlike most fields of the physical sciences, must deal with structures of essential complexity.  That is, they must deal with structures whose properties can be exhibited only by models made up of a multitude of variables. Competition, for instance, will be effective only if there are a large number of actors.

In some of the physical sciences and some other fields, these difficulties can be overcome by using probabilities.  But this is true only where we are dealing with “phenomena of unorganized complexity,” ^[3] in contrast to “phenomena of organized complexity” which characterize the social sciences.  In the former case, each individual observation is independent of every other one.  “Organized complexity”, in contrast describes structures that depend not only on the properties of its individual elements, but also on the correlation of these individual elements with each other.  

To explain “structures of organized complexity”, we cannot replace the information about the individual elements with statistical information.  Rather, they require full information about each element if we are to derive specific predictions about individual events from our theory. Without such information, we shall be confined to what on another occasion I have called mere pattern predictions.  These can predict some of the general attributes of the structures observed, but do not contain specific statements about the individual elements of which these structures are built.^[4]

This is particularly true of our theories concerning how systems of relative prices and wages produce a well-functioning market.  The market is generated by specific information possessed by each market participant – a quantity of facts which no single mind can comprehend.   This is what makes the market so powerful; it draws on a near infinity of wants, preferences and knowledge that are dispersed among uncounted individual actors. 

We, the economists, can never know all the determinants of such an order.  Thus it follows that we also cannot know such things as the specific structure of prices and wages at which demand will equal supply.  Nor can we statistically test our theory, which is that it is deviations from that “equilibrium” structure which make it impossible to sell some of the products and services at the prices at which they are offered.

It is important that I define the inherent limitations of numerical knowledge that are so often overlooked.   I want to do this to avoid giving the impression that I reject the application of the mathematical methods to economics. Mathematical analysis has great advantages.  One of these is that it allows us to model^[5] the general character of a pattern even when we may not be able to quantify or understand what is driving its constituent parts.

But mathematical methods come at a price. They have led to the illusion that we can use these techniques to determine and predict the numerical values of those magnitudes.  This has led to a vain search for quantitative or numerical constants.^[6]

Ironically, the founders of mathematical economics had no illusions about the applicability of their models.   Certainly, their equations were highly useful in describing the general pattern of market equilibria.   They are framed so that that if we were able to fill in all the blanks of the abstract formulae (that is, if we knew all the parameters of these equations), we could calculate the actual prices and quantities of all commodities and services sold at any point in time.   Unfortunately, many of these factors are impervious to quantification.

Vilfredo Pareto was one of the first to apply the discipline of mathematics to economics.   As he clearly stated, its purpose cannot be “to arrive at a numerical calculation of prices”, because, as he said, it would be “absurd” to assume that we could ascertain all the data.  

All this means that we must be skeptical of the conclusions that we draw from these models.   We must always be humble about the degree of certainty that our models can bestow on us. Mathematical models present at best an approximation of what is really going on in the economy.  They rely critically on their underlying assumptions.

I sometimes wish that our mathematical economists would take this to heart. I must confess that I doubt whether their search for measurable magnitudes has made significant contributions to our theoretical understanding of the economy – as distinct from their value as a description of particular situations. Nor am I prepared to accept the excuse that this branch of research is still very young: Sir William Petty, the founder of econometrics, was after all a somewhat senior colleague of Sir Isaac Newton in the Royal Society!

Granted, I know of few past instances in which the math obsession has done outright harm to economic practice, but today there are two serious ones: our inflation problem and our unemployment problem.  Scientistic-minded economists have disregarded what is probably the true cause of unemployment because its operation cannot be confirmed quantitatively.  In fact, by focusing myopically on factors that can be measured empirically, they have made matters worse.

To be sure, the true explanation of unemployment is a theory that is perhaps more general in nature than one would prefer.   It allows us to make only imprecise predictions of the kind of events we must expect in any particular situation. But the results of policy based on scientistic models have not just been imprecise, they have been downright damaging.  I confess that I prefer true but imperfect knowledge to a pretense of exact knowledge that is likely to be false.  To pursue policies simply because they conform to some pie-in-the-sky scientific standards can have grave consequences.

Today’s dominant “macro-economic” theories that recommend increasing aggregate demand to fix unemployment have resulted in an extensive misallocation of resources that makes future large-scale unemployment inevitable. Policies that continuously inject money into the economy will only create temporary demand.  Together with rising price expectations, this will misallocate labor and other resources into those sectors that benefit, but this can last only so long as the increase of the quantity of money continues at the same rate – or maybe only so long as the flow of money continues to accelerate.

Thus, easy money policies have produced a distribution of employment that is unsustainable in the long term and can only be sustained by inflation in the short term.  Worst case, this will lead to a rate of inflation high enough to unbalance all economic activity.  The fact is that by applying a misguided “scientistic” theoretical program, we have been led into the precarious position in which we cannot prevent serious unemployment from re-appearing.  This is not because unemployment has been deliberately inflicted to combat inflation, but because it is now bound to occur as an inescapable consequence of the mistaken policies of the past as soon as inflation ceases to accelerate.

So now we see how attempts to apply abstract “scientistic” theories to the real world can produce momentous unintended consequences.  We must be vigilant to the long run dangers posed by the uncritical acceptance of policy prescriptions that have the mere appearance of being scientific.  In economics, and I suspect in many other disciplines as well, what often looks like the most scientific procedure is really the most unscientific. In these disciplines, there are sharp limits to what we can expect an ostensibly “scientific” approach to achieve. To blindly entrust to science more than the scientific method can achieve may have deplorable effects.

The progress of the natural sciences in modern times has of course exceeded expectations so dramatically that any suggestion that it has limits is bound to arouse suspicion. Those who will most stubbornly resist such an insight are those who may have had hoped that increased use of scientific methods would lead to an improved power of prediction and control of social processes, ultimately enabling us to mold society entirely to our liking.  (Also, those who hoped to advance their own careers.)

In contrast to the exhilarating discoveries that often arise from the physical sciences, attempts to apply scientific methods to the study of society tend to be disappointing.  Unsurprisingly, many economists are unwilling to accept this inconvenient fact.  Confidence in the unlimited power of science is too often based on imitating the form rather than the substance of scientific procedure.  It almost seems as if the quantitative techniques of science were more easily learnt than the critical thinking skills that might identify truly important problems and invent ways to solve them in the real world.

There is a conflict between what the public at large expects science to achieve and what science actually can achieve.  This is a serious matter.  Even if true scientists were to recognize the limitations of their methods as tools with which to study society, the public might expect more.  Unfortunately, there will always be some “scientists” who are willing to pretend, and may perhaps honestly believe, that science can do more to fulfill this popular belief than is really within its power. It is difficult enough for the expert, and often impossible for the layman, to distinguish between legitimate and illegitimate claims advanced in the name of science.

It is by no means only in economics that far-reaching claims are made in favor of a more scientific direction for all human activities and the desirability of replacing spontaneous processes with “conscious human control”. If I am not mistaken, psychology, psychiatry, and some branches of sociology, as well as the so-called philosophy of history, are even more biased by the “scientistic prejudice,” and by specious claims of what science can achieve.

If we are to safeguard the reputation of science, and to prevent the arrogation of knowledge based on superficial similarity of procedure with that of the physical sciences, we must strive to debunk such arrogations.  Sadly, many of these have by now become the vested interests of established university departments. We cannot be grateful enough to such modern philosophers of science as Sir Karl Popper for giving us a test by which we can distinguish between what we may accept as scientific and what we may not – a test which I am sure some doctrines now widely accepted as scientific would not pass.

But there are some special challenges with essentially complex phenomena such as social structures.   In these fields not only are there absolute obstacles to the prediction of specific events, but to act as if we possessed the scientific knowledge that might enable us to transcend them may pose an obstacle to the advance of human knowledge.

The great and rapid advance of the physical sciences have proven that explanation and prediction could be based on laws which accounted for the observed phenomena as functions of comparatively few variables – either particular facts or relative frequencies of events. This may be the reason why we single out these realms as “physical” in contrast to those more highly organized structures which I have here called “essentially complex phenomena” which tend to characterize the social sciences.  

There is no reason why the theories and methods that apply in the social sciences must be the same as those that apply in the natural sciences.  The difficulties that we encounter in economics are not, as one might at first suspect, obstacles to formulating theories to explain observed events.   Rather, these difficulties center on challenges in testing proposed explanations and therefore about eliminating bad theories. A theory of essentially complex phenomena will refer to a myriad of particular facts. To derive a prediction from these data, or to test it, we must ascertain all of the individual facts. (It will prove virtually impossible to hold constant most of these.)  Once we have done this, it should not be difficult to derive testable predictions using modern computers.  The real difficulty, which is sometimes insoluble, consists in ascertaining the particular facts that are difficult to measure.  Science has little to say about how to do this.

A simple example will show the nature of this difficulty. Consider some ball game played by a few people of approximately equal skill. If we knew a few particular facts in addition to our general knowledge of the ability of the individual players, such as their state of attention, their perceptions and the state of their hearts, lungs, muscles etc. at each moment of the game, we could probably predict the outcome. Indeed, if we were familiar both with the game and the teams, we should probably have a fairly shrewd idea on what the outcome will depend. But we shall of course not be able to ascertain those facts and in consequence the result of the game will be outside the range of the scientifically predictable, however well we may know what effects particular events would have on the result of the game. This does not mean that we can make no predictions at all about the course of such a game. If we know the rules of the different games we shall, in watching one, very soon know which game is being played and what kinds of actions we can expect and what kind not. But our capacity to predict will be confined to such general characteristics of the events to be expected and not include the capacity of predicting particular individual events. ^[7]

This example corresponds to what I earlier referred to as the mere pattern predictions to which we are increasingly confined as we move from the realm of relatively simple laws into the realm in which organized complexity rules.  As we advance, we increasingly find that we can in fact ascertain only some but not all the particular circumstances which determine the outcome of a given process.  Consequently, we can predict only some but not all the properties of the result we expect. Often all that we shall be able to predict will be some abstract characteristic of the pattern that will appear – relationships between kinds of elements about which individually we know very little. Yet, as I am anxious to repeat, we will still achieve predictions which can be falsified, and which therefore are of empirical significance.

Of course, compared with the precise predictions we have come to expect of the physical sciences, mere pattern prediction is a distinctly second-best result.  Yet I dispute the belief that to have a claim accepted as scientific it is necessary to achieve better than second-best. This way lies charlatanism and worse.  To act on the mistaken belief that we possess the knowledge and the power which enable us to shape the processes of society entirely to our liking is likely to do much harm.

In the physical sciences there may be little objection to trying to do the impossible; one might even feel that one ought not to discourage the over-confident because their experiments may after all produce some new insights. But in the social field, enacting a policy in the belief that it will have beneficial consequences is just as likely to backfire and accomplish little more than install a new authority that will coerce other citizens. Even if such power is not inherently bad, its exercise is likely to impede the functioning of those spontaneous ordering forces by which, without understanding them, man is in fact so largely assisted in the pursuit of his aims. We are only beginning to understand the subtlety of the communication system underlying an advanced industrial society.  We call this communications system “the market”.  Prices are the synapses that make the market run efficiently.   With all its imperfections, the market turns out to be a far more efficient mechanism for digesting dispersed information than any mechanism that man has ever designed.

If humanity is not to do more harm than good in its efforts to improve the social order, it will have to learn that in all fields where essential complexity of an organized kind prevails, he cannot acquire the full knowledge which would grant mastery of events. Therefore, he must use what limited knowledge he can achieve not to shape the results as the craftsman shapes his handiwork, but rather to cultivate growth by providing the appropriate environment, as the gardener nurtures his plants.

There is much danger in the exuberant feeling of ever-growing power which the advance of the physical sciences has engendered.   It tempts man to try - “dizzy with success”, to use a trope of early communism - to subject not only our natural but also our human environment to the control of human will. If we are to avoid becoming accomplices in men’s fatal striving to control society, we must learn a lesson in humility by acknowledging the insuperable limits to our knowledge.   With luck, this might mitigate the striving which makes man not only a tyrant over his fellows but may well make him the destroyer of a civilization which no brain has designed but which has emerged over time from the free efforts of millions of individuals.

^[1] Hayek does not say “flux.”  It was Schumpeter who criticized economic models for ignoring market dynamism.

^[2] Hayek often uses the word “facts.”  Sometimes this appears to mean “variables” and sometimes actual facts that we know with certainty.

^[3][3]  I think I understand the distinction Hayek draws between “phenomena of unorganized complexity” and those of “organized complexity.”  I believe that the latter is typical of the social sciences in which the inputs to a model may be highly correlated while the former is typical of the physical sciences, in which inputs can be assumed to be random.  But I’m not 100% sure. 

^[4] I think he is simply saying that economic models can be no better than more or less imperfect representations of reality.

^[5]  I think “model” is an appropriate word.

^[6] This is somewhat opaque to me, especially “quantitative and numerical constraints.”  I think his main point is that we should be careful not to assume that our models can do more than they are capable of. 

^[7] I always object to sports analogies, and this one is no different. This paragraph is included verbatim from Hayeks’ address. It seems labored to me and I’m not sure I fully get it. I think he means that we can’t get the detailed information we need to make a “scientific” prediction, but we can get enough to make an informed bet.  But if I’m betting on the outcome of a game, even a tiny piece of information can be a huge advantage. I wish he had come up with a better example or worked on this one a little harder. If readers can explain it better, I’d be indebted.

The Pretense of Knowledge

Friedrich Hayek’s original address

The particular occasion of this lecture, combined with the chief practical problem which economists have to face today, have made the choice of its topic almost inevitable. On the one hand the still recent establishment of the Nobel Memorial Prize in Economic Science marks a significant step in the process by which, in the opinion of the general public, economics has been conceded some of the dignity and prestige of the physical sciences. On the other hand, the economists are at this moment called upon to say how to extricate the free world from the serious threat of accelerating inflation which, it must be admitted, has been brought about by policies which the majority of economists recommended and even urged governments to pursue. We have indeed at the moment little cause for pride: as a profession we have made a mess of things.

It seems to me that this failure of the economists to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences - an attempt which in our field may lead to outright error. It is an approach which has come to be described as the "scientistic" attitude - an attitude which, as I defined it some thirty years ago, "is decidedly unscientific in the true sense of the word, since it involves a mechanical and uncritical application of habits of thought to fields different from those in which they have been formed."1 I want today to begin by explaining how some of the gravest errors of recent economic policy are a direct consequence of this scientistic error.

The theory which has been guiding monetary and financial policy during the last thirty years, and which I contend is largely the product of such a mistaken conception of the proper scientific procedure, consists in the assertion that there exists a simple positive correlation between total employment and the size of the aggregate demand for goods and services; it leads to the belief that we can permanently assure full employment by maintaining total money expenditure at an appropriate level. Among the various theories advanced to account for extensive unemployment, this is probably the only one in support of which strong quantitative evidence can be adduced. I nevertheless regard it as fundamentally false, and to act upon it, as we now experience, as very harmful.

This brings me to the crucial issue. Unlike the position that exists in the physical sciences, in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited and may not include the important ones. While in the physical sciences it is generally assumed, probably with good reason, that any important factor which determines the observed events will itself be directly observable and measurable, in the study of such complex phenomena as the market, which depend on the actions of many individuals, all the circumstances which will determine the outcome of a process, for reasons which I shall explain later, will hardly ever be fully known or measurable. And while in the physical sciences the investigator will be able to measure what, on the basis of a prima facie theory, he thinks important, in the social sciences often that is treated as important which happens to be accessible to measurement. This is sometimes carried to the point where it is demanded that our theories must be formulated in such terms that they refer only to measurable magnitudes.

It can hardly be denied that such a demand quite arbitrarily limits the facts which are to be admitted as possible causes of the events which occur in the real world. This view, which is often quite naively accepted as required by scientific procedure, has some rather paradoxical consequences. We know: of course, with regard to the market and similar social structures, a great many facts which we cannot measure and on which indeed we have only some very imprecise and general information. And because the effects of these facts in any particular instance cannot be confirmed by quantitative evidence, they are simply disregarded by those sworn to admit only what they regard as scientific evidence: they thereupon happily proceed on the fiction that the factors which they can measure are the only ones that are relevant.

The correlation between aggregate demand and total employment, for instance, may only be approximate, but as it is the only one on which we have quantitative data, it is accepted as the only causal connection that counts. On this standard there may thus well exist better "scientific" evidence for a false theory, which will be accepted because it is more "scientific", than for a valid explanation, which is rejected because there is no sufficient quantitative evidence for it.

Let me illustrate this by a brief sketch of what I regard as the chief actual cause of extensive unemployment - an account which will also explain why such unemployment cannot be lastingly cured by the inflationary policies recommended by the now fashionable theory. This correct explanation appears to me to be the existence of discrepancies between the distribution of demand among the different goods and services and the allocation of labour and other resources among the production of those outputs. We possess a fairly good "qualitative" knowledge of the forces by which a correspondence between demand and supply in the different sectors of the economic system is brought about, of the conditions under which it will be achieved, and of the factors likely to prevent such an adjustment. The separate steps in the account of this process rely on facts of everyday experience, and few who take the trouble to follow the argument will question the validity of the factual assumptions, or the logical correctness of the conclusions drawn from them. We have indeed good reason to believe that unemployment indicates that the structure of relative prices and wages has been distorted (usually by monopolistic or governmental price fixing), and that to restore equality between the demand and the supply of labour in all sectors changes of relative prices and some transfers of labour will be necessary.

But when we are asked for quantitative evidence for the particular structure of prices and wages that would be required in order to assure a smooth continuous sale of the products and services offered, we must admit that we have no such information. We know, in other words, the general conditions in which what we call, somewhat misleadingly, an equilibrium will establish itself: but we never know what the particular prices or wages are which would exist if the market were to bring about such an equilibrium. We can merely say what the conditions are in which we can expect the market to establish prices and wages at which demand will equal supply. But we can never produce statistical information which would show how much the prevailing prices and wages deviate from those which would secure a continuous sale of the current supply of labour. Though this account of the causes of unemployment is an empirical theory, in the sense that it might be proved false, e.g. if, with a constant money supply, a general increase of wages did not lead to unemployment, it is certainly not the kind of theory which we could use to obtain specific numerical predictions concerning the rates of wages, or the distribution of labour, to be expected.

Why should we, however, in economics, have to plead ignorance of the sort of facts on which, in the case of a physical theory, a scientist would certainly be expected to give precise information? It is probably not surprising that those impressed by the example of the physical sciences should find this position very unsatisfactory and should insist on the standards of proof which they find there. The reason for this state of affairs is the fact, to which I have already briefly referred, that the social sciences, like much of biology but unlike most fields of the physical sciences, have to deal with structures of essential complexity, i.e. with structures whose characteristic properties can be exhibited only by models made up of relatively large numbers of variables. Competition, for instance, is a process which will produce certain results only if it proceeds among a fairly large number of acting persons.

In some fields, particularly where problems of a similar kind arise in the physical sciences, the difficulties can be overcome by using, instead of specific information about the individual elements, data about the relative frequency, or the probability, of the occurrence of the various distinctive properties of the elements. But this is true only where we have to deal with what has been called by Dr. Warren Weaver (formerly of the Rockefeller Foundation), with a distinction which ought to be much more widely understood, "phenomena of unorganized complexity," in contrast to those "phenomena of organized complexity" with which we have to deal in the social sciences.2 Organized complexity here means that the character of the structures showing it depends not only on the properties of the individual elements of which they are composed, and the relative frequency with which they occur, but also on the manner in which the individual elements are connected with each other. In the explanation of the working of such structures we can for this reason not replace the information about the individual elements by statistical information, but require full information about each element if from our theory we are to derive specific predictions about individual events. Without such specific information about the individual elements we shall be confined to what on another occasion I have called mere pattern predictions - predictions of some of the general attributes of the structures that will form themselves, but not containing specific statements about the individual elements of which the structures will be made up.3

This is particularly true of our theories accounting for the determination of the systems of relative prices and wages that will form themselves on a wellfunctioning market. Into the determination of these prices and wages there will enter the effects of particular information possessed by every one of the participants in the market process - a sum of facts which in their totality cannot be known to the scientific observer, or to any other single brain. It is indeed the source of the superiority of the market order, and the reason why, when it is not suppressed by the powers of government, it regularly displaces other types of order, that in the resulting allocation of resources more of the knowledge of particular facts will be utilized which exists only dispersed among uncounted persons, than any one person can possess. But because we, the observing scientists, can thus never know all the determinants of such an order, and in consequence also cannot know at which particular structure of prices and wages demand would everywhere equal supply, we also cannot measure the deviations from that order; nor can we statistically test our theory that it is the deviations from that "equilibrium" system of prices and wages which make it impossible to sell some of the products and services at the prices at which they are offered.

Before I continue with my immediate concern, the effects of all this on the employment policies currently pursued, allow me to define more specifically the inherent limitations of our numerical knowledge which are so often overlooked. I want to do this to avoid giving the impression that I generally reject the mathematical method in economics. I regard it in fact as the great advantage of the mathematical technique that it allows us to describe, by means of algebraic equations, the general character of a pattern even where we are ignorant of the numerical values which will determine its particular manifestation. We could scarcely have achieved that comprehensive picture of the mutual interdependencies of the different events in a market without this algebraic technique. It has led to the illusion, however, that we can use this technique for the determination and prediction of the numerical values of those magnitudes; and this has led to a vain search for quantitative or numerical constants. This happened in spite of the fact that the modern founders of mathematical economics had no such illusions. It is true that their systems of equations describing the pattern of a market equilibrium are so framed that if we were able to fill in all the blanks of the abstract formulae, i.e. if we knew all the parameters of these equations, we could calculate the prices and quantities of all commodities and services sold. But, as Vilfredo Pareto, one of the founders of this theory, clearly stated, its purpose cannot be "to arrive at a numerical calculation of prices", because, as he said, it would be "absurd" to assume that we could ascertain all the data.4 Indeed, the chief point was already seen by those remarkable anticipators of modern economics, the Spanish schoolmen of the sixteenth century, who emphasized that what they called pretium mathematicum, the mathematical price, depended on so many particular circumstances that it could never be known to man but was known only to God.5 I sometimes wish that our mathematical economists would take this to heart. I must confess that I still doubt whether their search for measurable magnitudes has made significant contributions to our theoretical understanding of economic phenomena - as distinct from their value as a description of particular situations. Nor am I prepared to accept the excuse that this branch of research is still very young: Sir William Petty, the founder of econometrics, was after all a somewhat senior colleague of Sir Isaac Newton in the Royal Society!

There may be few instances in which the superstition that only measurable magnitudes can be important has done positive harm in the economic field: but the present inflation and employment problems are a very serious one. Its effect has been that what is probably the true cause of extensive unemployment has been disregarded by the scientistically minded majority of economists, because its operation could not be confirmed by directly observable relations between measurable magnitudes, and that an almost exclusive concentration on quantitatively measurable surface phenomena has produced a policy which has made matters worse.

It has, of course, to be readily admitted that the kind of theory which I regard as the true explanation of unemployment is a theory of somewhat limited content because it allows us to make only very general predictions of the kindof events which we must expect in a given situation. But the effects on policy of the more ambitious constructions have not been very fortunate and I confess that I prefer true but imperfect knowledge, even if it leaves much indetermined and unpredictable, to a pretence of exact knowledge that is likely to be false. The credit which the apparent conformity with recognized scientific standards can gain for seemingly simple but false theories may, as the present instance shows, have grave consequences.

In fact, in the case discussed, the very measures which the dominant "macro-economic" theory has recommended as a remedy for unemployment, namely the increase of aggregate demand, have become a cause of a very extensive misallocation of resources which is likely to make later large-scale unemployment inevitable. The continuous injection of additional amounts of money at points of the economic system where it creates a temporary demand which must cease when the increase of the quantity of money stops or slows down, together with the expectation of a continuing rise of prices, draws labour and other resources into employments which can last only so long as the increase of the quantity of money continues at the same rate - or perhaps even only so long as it continues to accelerate at a given rate. What this policy has produced is not so much a level of employment that could not have been brought about in other ways, as a distribution of employment which cannot be indefinitely maintained and which after some time can be maintained only by a rate of inflation which would rapidly lead to a disorganisation of all economic activity. The fact is that by a mistaken theoretical view we have been led into a precarious position in which we cannot prevent substantial unemployment from re-appearing; not because, as this view is sometimes misrepresented, this unemployment is deliberately brought about as a means to combat inflation, but because it is now bound to occur as a deeply regrettable but inescapable consequence of the mistaken policies of the past as soon as inflation ceases to accelerate.

I must, however, now leave these problems of immediate practical importance which I have introduced chiefly as an illustration of the momentous consequences that may follow from errors concerning abstract problems of the philosophy of science. There is as much reason to be apprehensive about the long run dangers created in a much wider field by the uncritical acceptance of assertions which have the appearance of being scientific as there is with regard to the problems I have just discussed. What I mainly wanted to bring out by the topical illustration is that certainly in my field, but I believe also generally in the sciences of man, what looks superficially like the most scientific procedure is often the most unscientific, and, beyond this, that in these fields there are definite limits to what we can expect science to achieve. This means that to entrust to science - or to deliberate control according to scientific principles - more than scientific method can achieve may have deplorable effects. The progress of the natural sciences in modern times has of course so much exceeded all expectations that any suggestion that there may be some limits to it is bound to arouse suspicion. Especially all those will resist such an insight who have hoped that our increasing power of prediction and control, generally regarded as the characteristic result of scientific advance, applied to the processes of society, would soon enable us to mould society entirely to our liking. It is indeed true that, in contrast to the exhilaration which the discoveries of the physical sciences tend to produce, the insights which we gain from the study of society more often have a dampening effect on our aspirations; and it is perhaps not surprising that the more impetuous younger members of our profession are not always prepared to accept this. Yet the confidence in the unlimited power of science is only too often based on a false belief that the scientific method consists in the application of a ready-made technique, or in imitating the form rather than the substance of scientific procedure, as if one needed only to follow some cooking recipes to solve all social problems. It sometimes almost seems as if the techniques of science were more easily learnt than the thinking that shows us what the problems are and how to approach them.

The conflict between what in its present mood the public expects science to achieve in satisfaction of popular hopes and what is really in its power is a serious matter because, even if the true scientists should all recognize the limitations of what they can do in the field of human affairs, so long as the public expects more there will always be some who will pretend, and perhaps honestly believe, that they can do more to meet popular demands than is really in their power. It is often difficult enough for the expert, and certainly in many instances impossible for the layman, to distinguish between legitimate and illegitimate claims advanced in the name of science. The enormous publicity recently given by the media to a report pronouncing in the name of science on The Limits to Growth, and the silence of the same media about the devastating criticism this report has received from the competent experts6, must make one feel somewhat apprehensive about the use to which the prestige of science can be put. But it is by no means only in the field of economics that far-reaching claims are made on behalf of a more scientific direction of all human activities and the desirability of replacing spontaneous processes by "conscious human control". If I am not mistaken, psychology, psychiatry and some branches of sociology, not to speak about the so-called philosophy of history, are even more affected by what I have called the scientistic prejudice, and by specious claims of what science can achieve.7

If we are to safeguard the reputation of science, and to prevent the arrogation of knowledge based on a superficial similarity of procedure with that of the physical sciences, much effort will have to be directed toward debunking such arrogations, some of which have by now become the vested interests of established university departments. We cannot be grateful enough to such modern philosophers of science as Sir Karl Popper for giving us a test by which we can distinguish between what we may accept as scientific and what not - a test which I am sure some doctrines now widely accepted as scientific would not pass. There are some special problems, however, in connection with those essentially complex phenomena of which social structures are so important an instance, which make me wish to restate in conclusion in more general terms the reasons why in these fields not only are there only absolute obstacles to the prediction of specific events, but why to act as if we possessed scientific knowledge enabling us to transcend them may itself become a serious obstacle to the advance of the human intellect.

The chief point we must remember is that the great and rapid advance of the physical sciences took place in fields where it proved that explanation and prediction could be based on laws which accounted for the observed phenomena as functions of comparatively few variables - either particular facts or relative frequencies of events. This may even be the ultimate reason why we single out these realms as "physical" in contrast to those more highly organized structures which I have here called essentially complex phenomena. There is no reason why the position must be the same in the latter as in the former fields. The difficulties which we encounter in the latter are not, as one might at first suspect, difficulties about formulating theories for the explanation of the observed events - although they cause also special difficulties about testing proposed explanations and therefore about eliminating bad theories. They are due to the chief problem which arises when we apply our theories to any particular situation in the real world. A theory of essentially complex phenomena must refer to a large number of particular facts; and to derive a prediction from it, or to test it, we have to ascertain all these particular facts. Once we succeeded in this there should be no particular difficulty about deriving testable predictions - with the help of modern computers it should be easy enough to insert these data into the appropriate blanks of the theoretical formulae and to derive a prediction. The real difficulty, to the solution of which science has little to contribute, and which is sometimes indeed insoluble, consists in the ascertainment of the particular facts.

A simple example will show the nature of this difficulty. Consider some ball game played by a few people of approximately equal skill. If we knew a few particular facts in addition to our general knowledge of the ability of the individual players, such as their state of attention, their perceptions and the state of their hearts, lungs, muscles etc. at each moment of the game, we could probably predict the outcome. Indeed, if we were familiar both with the game and the teams we should probably have a fairly shrewd idea on what the outcome will depend. But we shall of course not be able to ascertain those facts and in consequence the result of the game will be outside the range of the scientifically predictable, however well we may know what effects particular events would have on the result of the game. This does not mean that we can make no predictions at all about the course of such a game. If we know the rules of the different games we shall, in watching one, very soon know which game is being played and what kinds of actions we can expect and what kind not. But our capacity to predict will be confined to such general characteristics of the events to be expected and not include the capacity of predicting particular individual events.

This corresponds to what I have called earlier the mere pattern predictions to which we are increasingly confined as we penetrate from the realm in which relatively simple laws prevail into the range of phenomena where organized complexity rules. As we advance we find more and more frequently that we can in fact ascertain only some but not all the particular circumstances which determine the outcome of a given process; and in consequence we are able to predict only some but not all the properties of the result we have to expect. Often all that we shall be able to predict will be some abstract characteristic of the pattern that will appear - relations between kinds of elements about which individually we know very little. Yet, as I am anxious to repeat, we will still achieve predictions which can be falsified and which therefore are of empirical significance.

Of course, compared with the precise predictions we have learnt to expect in the physical sciences, this sort of mere pattern predictions is a second best with which one does not like to have to be content. Yet the danger of which I want to warn is precisely the belief that in order to have a claim to be accepted as scientific it is necessary to achieve more. This way lies charlatanism and worse. To act on the belief that we possess the knowledge and the power which enable us to shape the processes of society entirely to our liking, knowledge which in fact we do not possess, is likely to make us do much harm. In the physical sciences there may be little objection to trying to do the impossible; one might even feel that one ought not to discourage the over-confident because their experiments may after all produce some new insights. But in the social field the erroneous belief that the exercise of some power would have beneficial consequences is likely to lead to a new power to coerce other men being conferred on some authority. Even if such power is not in itself bad, its exercise is likely to impede the functioning of those spontaneous ordering forces by which, without understanding them, man is in fact so largely assisted in the pursuit of his aims. We are only beginning to understand on how subtle a communication system the functioning of an advanced industrial society is based - a communications system which we call the market and which turns out to be a more efficient mechanism for digesting dispersed information than any that man has deliberately designed.

If man is not to do more harm than good in his efforts to improve the social order, he will have to learn that in this, as in all other fields where essential complexity of an organized kind prevails, he cannot acquire the full knowledge which would make mastery of the events possible. He will therefore have to use what knowledge he can achieve, not to shape the results as the craftsman shapes his handiwork, but rather to cultivate a growth by providing the appropriate environment, in the manner in which the gardener does this for his plants. There is danger in the exuberant feeling of ever growing power which the advance of the physical sciences has engendered and which tempts man to try, "dizzy with success", to use a characteristic phrase of early communism, to subject not only our natural but also our human environment to the control of a human will. The recognition of the insuperable limits to his knowledge ought indeed to teach the student of society a lesson of humility which should guard him against becoming an accomplice in men's fatal striving to control society - a striving which makes him not only a tyrant over his fellows, but which may well make him the destroyer of a civilization which no brain has designed but which has grown from the free efforts of millions of individuals.

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1. "Scientism and the Study of Society", Economica, vol. IX, no. 35, August 1942, reprinted in The Counter-Revolution of Science, Glencoe, Ill., 1952, p. 15 of this reprint.

2. Warren Weaver, "A Quarter Century in the Natural Sciences", The Rockefeller Foundation Annual Report 1958, chapter I, "Science and Complexity".

3. See my essay "The Theory of Complex Phenomena" in The Critical Approach to Science and Philosophy. Essays in Honor of K.R. Popper, ed. M. Bunge, New York 1964, and reprinted (with additions) in my Studies in Philosophy, Politics and Economics, London and Chicago 1967.

4. V. Pareto, Manuel d'économie politique, 2nd. ed., Paris 1927, pp. 223-4.

5. See, e.g., Luis Molina, De iustitia et iure, Cologne 1596-1600, tom. II, disp. 347, no. 3, and particularly Johannes de Lugo, Disputationum de iustitia et iure tomus secundus, Lyon 1642, disp. 26, sect. 4, no. 40.

6. See The Limits to Growth: A Report of the Club of Rome's Project on the Predicament of Mankind, New York 1972; for a systematic examination of this by a competent economist cf. Wilfred Beckerman, In Defence of Economic Growth, London 1974, and, for a list of earlier criticisms by experts, Gottfried Haberler, Economic Growth and Stability, Los Angeles 1974, who rightly calls their effect "devastating".

7. I have given some illustrations of these tendencies in other fields in my inaugural lecture as Visiting Professor at the University of Salzburg, Die Irrtümer des Konstruktivismus und die Grundlagen legitimer Kritik gesellschaftlicher Gebilde, Munich 1970, now reissued for the Walter Eucken Institute, at Freiburg i.Brg. by J.C.B. Mohr, Tübingen 1975.

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^[1] Hayek does not say “flux.”  It was Schumpeter who criticized economic models for ignoring market dynamism.

^[2] Hayek often uses the word “facts.”  Sometimes this appears to mean “variables” and sometimes actual facts that we know with certainty.

^[3][3]  I think I understand the distinction Hayek draws between “phenomena of unorganized complexity” and those of “organized complexity.”  I believe that the former is typical of the social sciences in which the inputs to a model may be highly correlated while the latter is typical of the physical sciences, in which inputs can be assumed to be random.  But I’m not 100% sure. 

^[4] I think he is simply saying that economic models can be no better than more or less imperfect representations of reality.

^[5]  I think “model” is an appropriate word.

^[6] This is somewhat opaque to me, especially “quantitative and numerical constraints.”  I think his main point is that we should be careful to assume that our models can do more than they are capable of.  I expand on this in the paragraph below.

^[7] This analogy is included word for word from Hayeks’ address It seems labored to me. I think he means that we can’t get the detailed information we need to make a “scientific” prediction, but we can get enough to make an informed bet.  I wish he had come up with a better example or worked on this one a little harder.