Economists as Scientists

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This is the third entry in a series of loosely connected posts on economics. The first entry is here and the second entry is here. (Related posts by me are noted parenthetically throughout this one.)

Science is something that some people “do” some of the time. There are full-time human beings and part-time scientists. And the part-timers are truly scientists only when they think and act in accordance with the scientific method.*

Acting in accordance with the scientific method is a matter of attitude and application. The proper attitude is one of indifference about the correctness of a hypothesis or theory. The proper application rejects a hypothesis if it can’t be tested, and rejects a theory if it’s refuted (falsified) by relevant and reliable observations.

Regarding attitude, I turn to the most famous person who was sometimes a scientist: Albert Einstein. This is from the Wikipedia article about the Bohr-Einstein debate:

The quantum revolution of the mid-1920s occurred under the direction of both Einstein and [Niels] Bohr, and their post-revolutionary debates were about making sense of the change. The shocks for Einstein began in 1925 when Werner Heisenberg introduced matrix equations that removed the Newtonian elements of space and time from any underlying reality. The next shock came in 1926 when Max Born proposed that mechanics were to be understood as a probability without any causal explanation.

Einstein rejected this interpretation. In a 1926 letter to Max Born, Einstein wrote: “I, at any rate, am convinced that He [God] does not throw dice.” [Apparently, Einstein also used the line in Bohr’s presence, and Bohr replied, “Einstein, stop telling God what to do.” — TEA]

At the Fifth Solvay Conference held in October 1927 Heisenberg and Born concluded that the revolution was over and nothing further was needed. It was at that last stage that Einstein’s skepticism turned to dismay. He believed that much had been accomplished, but the reasons for the mechanics still needed to be understood.

Einstein’s refusal to accept the revolution as complete reflected his desire to see developed a model for the underlying causes from which these apparent random statistical methods resulted. He did not reject the idea that positions in space-time could never be completely known but did not want to allow the uncertainty principle to necessitate a seemingly random, non-deterministic mechanism by which the laws of physics operated.

It’s true that quantum mechanics was inchoate in the mid-1920s, and that it took a couple of decades to mature into quantum field theory. But there’s more than a trace of “attitude” in Einstein’s refusal to accept quantum mechanics, to stay abreast of developments in the theory, and to search quixotically for his own theory of everything, which he hoped would obviate the need for a non-deterministic explanation of quantum phenomena.

Improper application of the scientific method is rife. See, for example the Wikipedia article about the replication crisis, John Ioannidis’s article, “Why Most Published Research Findings Are False.” (See also “Ty Cobb and the State of Science” and “Is Science Self-Correcting?“) For a thorough analysis of the roots of the crisis, read Michael Hart’s book, Hubris: The Troubling Science, Economics, and Politics of Climate Change.

A bad attitude and improper application are both found among the so-called scientists who declare that the “science” of global warming is “settled,” and that human-generated CO2 emissions are the primary cause of the apparent rise in global temperatures during the last quarter of the 20th century. The bad attitude is the declaration of “settled science.” In “The Science Is Never Settled” I give many prominent examples of the folly of declaring it to be “settled.”

The improper application of the scientific method with respect to global warming began with the hypothesis that the “culprit” is CO2 emissions generated by the activities of human beings — thus anthropogenic global warming (AGW). There’s no end of evidence to the contrary, some of which is summarized in these posts and many of the links found therein. There’s enough evidence, in my view, to have rejected the CO2 hypothesis many times over. But there’s a great deal of money and peer-approval at stake, so the rush to judgment became a stampede. And attitude rears its ugly head when pro-AGW “scientists” shun the real scientists who are properly skeptical about the CO2 hypothesis, or at least about the degree to which CO2 supposedly influences temperatures. (For a depressingly thorough account of the AGW scam, read Michael Hart’s Hubris: The Troubling Science, Economics, and Politics of Climate Change.)

I turn now to economists, as I have come to know them in more than fifty years of being taught by them, working with them, and reading their works. Scratch an economist and you’re likely to find a moralist or reformer just beneath a thin veneer of rationality. Economists like to believe that they’re objective. But they aren’t; no one is. Everyone brings to the table a large serving of biases that are incubated in temperament, upbringing, education, and culture.

Economists bring to the table a heaping helping of tunnel vision. “Hard scientists” do, too, but their tunnel vision is generally a good thing, because it’s actually aimed at a deeper understanding of the inanimate and subhuman world rather than the advancement of a social or economic agenda. (I make a large exception for “hard scientists” who contribute to global-warming hysteria, as discussed above.)

Some economists, especially behavioralists, view the world through the lens of wealth-and-utility-maximization. Their great crusade is to force everyone to make rational decisions (by their lights), through “nudging.” It almost goes without saying that government should be the nudger-in-chief. (See “The Perpetual Nudger” and the many posts linked to therein.)

Other economists — though far fewer than in the past — have a thing about monopoly and oligopoly (the domination of a market by one or a few sellers). They’re heirs to the trust-busting of the late 1800s and early 1900s, a movement led by non-economists who sought to blame the woes of working-class Americans on the “plutocrats” (Rockefeller, Carnegie, Ford, etc.) who had merely made life better and more affordable for Americans, while also creating jobs for millions of them and reaping rewards for the great financial risks that they took. (See “Monopoly and the General Welfare” and “Monopoly: Private Is Better than Public.”) As it turns out, the biggest and most destructive monopoly of all is the federal government, so beloved and trusted by trust-busters — and too many others. (See “The Rahn Curve Revisited.”)

Nowadays, a lot of economists are preoccupied by income inequality, as if it were something evil and not mainly an artifact of differences in intelligence, ambition, and education, etc. And inequality — the prospect of earning rather grand sums of money — is what drives a lot of economic endeavor, to good of workers and consumers. (See “Mass (Economic) Hysteria: Income Inequality and Related Themes” and the many posts linked to therein.) Remove inequality and what do you get? The Soviet Union and Communist China, in which everyone is equal except party operatives and their families, friends, and favorites.

When the inequality-preoccupied economists are confronted by the facts of life, they usually turn their attention from inequality as a general problem to the (inescapable) fact that an income distribution has a top one-percent and top one-tenth of one-percent — as if there were something especially loathsome about people in those categories. (Paul Krugman shifted his focus to the top one-tenth of one percent when he realized that he’s in the top one percent, so perhaps he knows that’s he’s loathsome and wishes to deny it, to himself.)

Crony capitalism is trotted out as a major cause of very high incomes. But that’s hardly a universal cause, given that a lot of very high incomes are earned by athletes and film stars beside whom most investment bankers and CEOs are making peanuts. Moreover, as I’ve said on several occasions, crony capitalists are bright and driven enough to be in the stratosphere of any income distribution. Further, the fertile soil of crony capitalism is the regulatory power of government that makes it possible.

Many economists became such, it would seem, in order to promote big government and its supposed good works — income redistribution being one of them. Joseph Stiglitz and Paul Krugman are two leading exemplars of what I call the New Deal school of economic thought, which amounts to throwing government and taxpayers’ money at every perceived problem, that is, every economic outcome that is deemed unacceptable by accountants of the soul. (See “Accountants of the Soul.”)

Stiglitz and Krugman — both Nobel laureates in economics — are typical “public intellectuals” whose intelligence breeds in them a kind of arrogance. (See “Intellectuals and Society: A Review.”) It’s the kind of arrogance that I mentioned in the preceding post in this series: a penchant for deciding what’s best for others.

New Deal economists like Stiglitz and Krugman carry it a few steps further. They ascribe to government an impeccable character, an intelligence to match their own, and a monolithic will. They then assume that this infallible and wise automaton can and will do precisely what they would do: Create the best of all possible worlds. (See the many posts in which I discuss the nirvana fallacy.)

New Deal economists, in other words, live their intellectual lives  in a dream-world populated by the likes of Jiminy Cricket (“When You Wish Upon a Star”), Dorothy (“Somewhere Over the Rainbow”), and Mary Jane of a long-forgotten comic book (“First I shut my eyes real tight, then I wish with all my might! Magic words of poof, poof, piffles, make me just as small as [my mouse] Sniffles!”).

I could go on, but you should by now have grasped the point: What too many economists want to do is change human nature, channel it in directions deemed “good” (by the economist), or simply impose their view of “good” on everyone. To do such things, they must rely on government.

It’s true that government can order people about, but it can’t change human nature, which has an uncanny knack for thwarting Utopian schemes. (Obamacare, whose chief architect was economist Jonathan Gruber, is exhibit A this year.) And government (inconveniently for Utopians) really consists of fallible, often unwise, contentious human beings. So government is likely to march off in a direction unsought by Utopian economists.

Nevertheless, it’s hard to thwart the tax collector. The regulator can and does make things so hard for business that if one gets off the ground it can’t create as much prosperity and as many jobs as it would in the absence of regulation. And the redistributor only makes things worse by penalizing success. Tax, regulate, and redistribute should have been the mantra of the New Deal and most presidential “deals” since.

I hold economists of the New Deal stripe partly responsible for the swamp of stagnation into which the nation’s economy has descended. (See “Economic Growth Since World War II.”) Largely responsible, of course, are opportunistic if not economically illiterate politicians who pander to rent-seeking, economically illiterate constituencies. (Yes, I’m thinking of old folks and the various “disadvantaged” groups with which they have struck up an alliance of convenience.)

The distinction between normative economics and positive economics is of no particular use in sorting economists between advocates and scientists. A lot of normative economics masquerades as positive economics. The work of Thomas Piketty and his comrades-in-arms comes to mind, for example. (See “McCloskey on Piketty.”) Almost everything done to quantify and defend the Keynesian multiplier counts as normative economics, inasmuch as the work is intended (wittingly or not) to defend an intellectual scam of 80 years’ standing. (See “The Keynesian Multiplier: Phony Math,” “The True Multiplier,” and “Further Thoughts about the Keynesian Multiplier.”)

Enough said. If you want to see scientific economics in action, read Regulation. Not every article in it exemplifies scientific inquiry, but a good many of them do. It’s replete with articles about microeconomics, in which the authors uses real-world statistics to validate and quantify the many axioms of economics.

A final thought is sparked by Arnold Kling’s post, “Ed Glaeser on Science and Economics.” Kling writes:

I think that the public has a sort of binary classification. If it’s “science,” then an expert knows more than the average Joe. If it’s not a science, then anyone’s opinion is as good as anyone else’s. I strongly favor an in-between category, called a discipline. Think of economics as a discipline, where it is possible for avid students to know more than ordinary individuals, but without the full use of the scientific method.

On this rare occasion I disagree with Kling. The accumulation of knowledge about economic variables, or pseudo-knowledge such as estimates of GDP (see “Macroeconomics and Microeconomics“), either leads to well-tested, verified, and reproducible theories of economic behavior or it leads to conjectures, of which there are so many opposing ones that it’s “take your pick.” If that’s what makes a discipline, give me the binary choice between science and story-telling. Most of economics seems to be story-telling. “Discipline” is just a fancy word for it.

Collecting baseball cards and memorizing the statistics printed on them is a discipline. Most of economics is less useful than collecting baseball cards — and a lot more destructive.

Here’s my hypothesis about economists: There are proportionally as many of them who act like scientists as there are baseball players who have career batting averages of at least .300.
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* Richard Feynman, a physicist and real scientist, had a different view of the scientific method than Karl Popper’s standard taxonomy. I see Feynman’s view as complementary to Popper’s, not at odds with it. What is “constructive skepticism” (Feynman’s term) but a gentler way of saying that a hypothesis or theory might be falsified and that the act of falsification may point to a better hypothesis or theory?

Economics and Science

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This is the second entry in what I expect to be a series of loosely connected posts on economics. The first entry is here.

Science is unnecessarily daunting to the uninitiated, which is to say, the vast majority of the populace. Because scientific illiteracy is rampant, advocates of policy positions — scientists and non-scientists alike — are able to invoke “science” wantonly, thus lending unwarranted authority to their positions.

Here I will dissect science, then turn to economics and begin a discussion of its scientific and non-scientific aspects. It has both, though at least one non-scientific aspect (the Keynesian multiplier) draws an inordinate amount of attention, and has many true believers within the profession.

Science is knowledge, but not all knowledge is science. A scientific body of knowledge is systematic; that is, the granular facts or phenomena which comprise the body of knowledge must be connected in patterned ways. The purported facts or phenomena of a science must represent reality, things that can be observed and measured in some way. Scientists may hypothesize the existence of an unobserved thing (e.g., the ether, dark matter), in an effort to explain observed phenomena. But the unobserved thing stands outside scientific knowledge until its existence is confirmed by observation, or because it remains standing as the only plausible explanation of observable phenomena. Hypothesized things may remain outside the realm of scientific knowledge for a very long time, if not forever. The Higgs boson, for example, was hypothesized in 1964 and has been tentatively (but not conclusively) confirmed since its “discovery” in 2011.

Science has other key characteristics. Facts and patterns must be capable of validation and replication by persons other than those who claim to have found them initially. Patterns should have predictive power; thus, for example, if the sun fails to rise in the east, the model of Earth’s movements which says that it will rise in the east is presumably invalid and must be rejected or modified so that it correctly predicts future sunrises or the lack thereof. Creating a model or tweaking an existing model just to account for a past event (e.g., the failure of the Sun to rise, the apparent increase in global temperatures from the 1970s to the 1990s) proves nothing other than an ability to “predict” the past with accuracy.

Models are usually clothed in the language of mathematics and statistics. But those aren’t scientific disciplines in themselves; they are tools of science. Expressing a theory in mathematical terms may lend the theory a scientific aura, but a theory couched in mathematical terms is not a scientific one unless (a) it can be tested against facts yet to be ascertained and events yet to occur, and (b) it is found to accord with those facts and events consistently, by rigorous statistical tests.

A science may be descriptive rather than mathematical. In a descriptive science (e.g., plant taxonomy), particular phenomena sometimes are described numerically (e.g., the number of leaves on the stem of a species), but the relations among various phenomena are not reducible to mathematics. Nevertheless, a predominantly descriptive discipline will be scientific if the phenomena within its compass are connected in patterned ways, can be validated, and are applicable to newly discovered entities.

Non-scientific disciplines can be useful, whereas some purportedly scientific disciplines verge on charlatanism. Thus, for example:

  • History, by my reckoning, is not a science because its account of events and their relationships is inescapably subjective and incomplete. But a knowledge of history is valuable, nevertheless, for the insights it offers into the influence of human nature on the outcomes of economic and political processes.
  • Physics is a science in most of its sub-disciplines, but there are some (e.g., cosmology) where it descends into the realm of speculation. It is informed, fascinating speculation to be sure, but speculation all the same. The idea of multiverses, for example, can’t be tested, inasmuch as human beings and their tools are bound to the known universe.
  • Economics is a science only to the extent that it yields empirically valid insights about  specific economic phenomena (e.g., the effects of laws and regulations on the prices and outputs of specific goods and services). Then there are concepts like the Keynesian multiplier, about which I’ll say more in this series. It’s a hypothesis that rests on a simplistic, hydraulic view of the economic system. (Other examples of pseudo-scientific economic theories are the labor theory of value and historical determinism.)

In sum, there is no such thing as “science,” writ large; that is, no one may appeal, legitimately, to “science” in the abstract. A particular discipline may be a science, but it is a science only to the extent that it comprises a factual and replicable body of patterned knowledge. Patterned knowledge includes theories with predictive power.

A scientific theory is a hypothesis that has thus far been confirmed by observation. Every scientific theory rests eventually on axioms: self-evident principles that are accepted as true without proof. The principle of uniformity (which can be traced to Galileo) is an example of such an axiom:

Uniformitarianism is the assumption that the same natural laws and processes that operate in the universe now have always operated in the universe in the past and apply everywhere in the universe. It refers to invariance in the metaphysical principles underpinning science, such as the constancy of causal structure throughout space-time, but has also been used to describe spatiotemporal invariance of physical laws. Though an unprovable postulate that cannot be verified using the scientific method, uniformitarianism has been a key first principle of virtually all fields of science

Thus, for example, if observer B is moving away from observer A at a certain speed, observer A will perceive that he is moving away from observer B at that speed. It follows that an observer cannot determine either his absolute velocity or direction of travel in space. The principle of uniformity is a fundamental axiom of modern physics, most notably of Einstein’s special and general theories of relativity.

There’s a fine line between an axiom and a theory. Was the idea of a geocentric universe an axiom or a theory? If it was taken as axiomatic — as it surely was by many scientists for about 2,000 years — then it’s fair to say that an axiom can give way under the pressure of observational evidence. (Such an event is what Thomas Kuhn calls a paradigm shift.) But no matter how far scientists push the boundaries of knowledge, they must at some point rely on untestable axioms, such as the principle of uniformity. There are simply deep and (probably) unsolvable mysteries that science is unlikely to fathom.

This brings me to economics, which — in my view — rests on these self-evident axioms:

1. Each person strives to maximize his or her sense of satisfaction, which may also be called well-being, happiness, or utility (an ugly word favored by economists). Striving isn’t the same as achieving, of course, because of lack of information, emotional decision-making, buyer’s remorse, etc

2. Happiness can and often does include an empathic concern for the well-being of others; that is, one’s happiness may be served by what is usually labelled altruism or self-sacrifice.

3. Happiness can be and often is served by the attainment of non-material ends. Not all persons (perhaps not even most of them) are interested in the maximization of wealth, that is, claims on the output of goods and services. In sum, not everyone is a wealth maximizer. (But see axiom number 12.)

4. The feeling of satisfaction that an individual derives from a particular product or service is situational — unique to the individual and to the time and place in which the individual undertakes to acquire or enjoy the product or service. Generally, however, there is a (situationally unique) point at which the acquisition or enjoyment of additional units of a particular product or service during a given period of time tends to offer less satisfaction than would the acquisition or enjoyment of units of other products or services that could be obtained at the same cost.

5. The value that a person places on a product or service is subjective. Products and services don’t have intrinsic values that apply to all persons at a given time or period of time.

6. The ability of a person to acquire products and services, and to accumulate wealth, depends (in the absence of third-party interventions) on the valuation of the products and services that are produced in part or whole by the person’s labor (mental or physical), or by the assets that he owns (e.g., a factory building, a software patent). That valuation is partly subjective (e.g., consumers’ valuation of the products and services, an employer’s qualitative evaluation of the person’s contributions to output) and partly objective (e.g., an employer’s knowledge of the price commanded by a product or service, an employer’s measurement of an employees’ contribution to the quantity of output).

7. The persons and firms from which products and services flow are motivated by the acquisition of income, with which they can acquire other products and services, and accumulate wealth for personal purposes (e.g., to pass to heirs) or business purposes (e.g., to expand the business and earn more income). So-called profit maximization (seeking to maximize the difference between the cost of production and revenue from sales) is a key determinant of business decisions but far from the only one. Others include, but aren’t limited to, being a “good neighbor,” providing employment opportunities for local residents, and underwriting philanthropic efforts.

8. The cost of production necessarily influences the price at which a good or and service will be offered for sale, but doesn’t solely determine the price at which it will be sold. Selling price depends on the subjective valuation of the products or service, prospective buyers’ incomes, and the prices of other products and services, including those that are direct or close substitutes and those to which users may switch, depending on relative prices.

9. The feeling of satisfaction that a person derives from the acquisition and enjoyment of the “basket” of products and services that he is able to buy, given his income, etc., doesn’t necessarily diminish, as long as the person has access to a great variety of products and services. (This axiom and axiom 12 put paid to the myth of diminishing marginal utility of income.)

10. Work may be a source of satisfaction in itself or it may simply be a means of acquiring and enjoying products and services, or acquiring claims to them by accumulating wealth. Even when work is satisfying in itself, it is subject to the “law” of diminishing marginal satisfaction.

11. Work, for many (but not all) persons, is no longer be worth the effort if they become able to subsist comfortably enough by virtue of the wealth that they have accumulated, the availability of redistributive schemes (e.g., Social Security and Medicare), or both. In such cases the accumulation of wealth often ceases and reverses course, as it is “cashed in” to defray the cost of subsistence (which may be far more than minimal).

12. However, there are not a few persons whose “work” is such a great source of satisfaction that they continue doing it until they are no longer capable of doing so. And there are some persons whose “work” is the accumulation of wealth, without limit. Such persons may want to accumulate wealth in order to “do good” or to leave their heirs well off or simply for the satisfaction of running up the score. The justification matters not. There is no theoretical limit to the satisfaction that a particular person may derive from the accumulation of wealth. Moreover, many of the persons (discussed in axiom 11) who aren’t able to accumulate wealth endlessly would do so if they had the ability and the means to take the required risks.

13. Individual degrees of satisfaction (happiness, etc.) are ephemeral, nonquantifiable, and incommensurable. There is no such thing as a social welfare function that a third party (e.g., government) can maximize by taking from A to give to B. If there were such a thing, its value would increase if, for example, A were to punch B in the nose and derive a degree of pleasure that somehow more than offsets the degree of pain incurred by B. (The absurdity of a social-welfare function that allows As to punch Bs in their noses ought to be enough shame inveterate social engineers into quietude — but it won’t. They derive great satisfaction from meddling.) Moreover, one of the primary excuses for meddling is that income (and thus wealth) has a  diminishing marginal utility, so it makes sense to redistribute from those with higher incomes (or more wealth) to those who have less of either. Marginal utility is, however, unknowable (see axioms 4 and 5), and may not always be negative (see axioms 9 and 12).

14. Whenever a third party (government, do-gooders, etc.) intervene in the affairs of others, that third party is merely imposing its preferences on those others. The third party sometimes claims to know what’s best for “society as a whole,” etc., but no third party can know such a thing. (See axiom 13.)

15. It follows from axiom 13 that the welfare of “society as a whole” can’t be aggregated or measured. An estimate of the monetary value of the economic output of a nation’s economy (Gross Domestic Product) is by no means an estimate of the welfare of “society as a whole.” (Again, see axiom 13.)

That may seem like a lot of axioms, which might give you pause about my claim that some aspects of economics are scientific. But economics is inescapably grounded in axioms such as the ones that I propound. This aligns me (mainly) with the Austrian economists, whose leading light was Ludwig von Mises. Gene Callahan writes about him at the website of the Ludwig von Mises Institute:

As I understand [Mises], by categorizing the fundamental principles of economics as a priori truths and not contingent facts open to empirical discovery or refutation, Mises was not claiming that economic law is revealed to us by divine action, like the ten commandments were to Moses. Nor was he proposing that economic principles are hard-wired into our brains by evolution, nor even that we could articulate or comprehend them prior to gaining familiarity with economic behavior through participating in and observing it in our own lives. In fact, it is quite possible for someone to have had a good deal of real experience with economic activity and yet never to have wondered about what basic principles, if any, it exhibits.

Nevertheless, Mises was justified in describing those principles as a priori, because they are logically prior to any empirical study of economic phenomena. Without them it is impossible even to recognize that there is a distinct class of events amenable to economic explanation. It is only by pre-supposing that concepts like intention, purpose, means, ends, satisfaction, and dissatisfaction are characteristic of a certain kind of happening in the world that we can conceive of a subject matter for economics to investigate. Those concepts are the logical prerequisites for distinguishing a domain of economic events from all of the non-economic aspects of our experience, such as the weather, the course of a planet across the night sky, the growth of plants, the breaking of waves on the shore, animal digestion, volcanoes, earthquakes, and so on.

Unless we first postulate that people deliberately undertake previously planned activities with the goal of making their situations, as they subjectively see them, better than they otherwise would be, there would be no grounds for differentiating the exchange that takes place in human society from the exchange of molecules that occurs between two liquids separated by a permeable membrane. And the features which characterize the members of the class of phenomena singled out as the subject matter of a special science must have an axiomatic status for practitioners of that science, for if they reject them then they also reject the rationale for that science’s existence.

Economics is not unique in requiring the adoption of certain assumptions as a pre-condition for using the mode of understanding it offers. Every science is founded on propositions that form the basis rather than the outcome of its investigations. For example, physics takes for granted the reality of the physical world it examines. Any piece of physical evidence it might offer has weight only if it is already assumed that the physical world is real. Nor can physicists demonstrate their assumption that the members of a sequence of similar physical measurements will bear some meaningful and consistent relationship to each other. Any test of a particular type of measurement must pre-suppose the validity of some other way of measuring against which the form under examination is to be judged.

Why do we accept that when we place a yardstick alongside one object, finding that the object stretches across half the length of the yardstick, and then place it alongside another object, which only stretches to a quarter its length, that this means the first object is longer than the second? Certainly not by empirical testing, for any such tests would be meaningless unless we already grant the principle in question. In mathematics we don’t come to know that 2 + 2 always equals 4 by repeatedly grouping two items with two others and counting the resulting collection. That would only show that our answer was correct in the instances we examined — given the assumption that counting works! — but we believe it is universally true. [And it is universally true by the conventions of mathematics. If what we call “5” were instead called “4,” 2 + 2 would always equal 5. — TEA] Biology pre-supposes that there is a significant difference between living things and inert matter, and if it denied that difference it would also be denying its own validity as a special science. . . .

The great fecundity from such analysis in economics is due to the fact that, as acting humans ourselves, we have a direct understanding of human action, something we lack in pondering the behavior of electrons or stars. The contemplative mode of theorizing is made even more important in economics because the creative nature of human choice inherently fails to exhibit the quantitative, empirical regularities, the discovery of which characterizes the modern, physical sciences. (Biology presents us with an interesting intermediate case, as many of its findings are qualitative.) . . .

[A] person can be presented with scores of experiments supporting a particular scientific theory is sound, but no possible experiment ever can demonstrate to him that experimentation is a reasonable means by which to evaluate a scientific theory. Only his intuitive grasp of its plausibility can bring him to accept that proposition. (Unless, of course, he simply adopts it on the authority of others.) He can be led through hundreds of rigorous proofs for various mathematical theorems and be taught the criteria by which they are judged to be sound, but there can be no such proof for the validity of the method itself. (Kurt Gödel famously demonstrated that a formal system of mathematical deduction that is complex enough to model even so basic a topic as arithmetic might avoid either incompleteness or inconsistency, but always must suffer at least one of those flaws.) . . .

This ultimate, inescapable reliance on judgment is illustrated by Lewis Carroll in Alice Through the Looking Glass. He has Alice tell Humpty Dumpty that 365 minus one is 364. Humpty is skeptical, and asks to see the problem done on paper. Alice dutifully writes down:

365 – 1 = 364

Humpty Dumpty studies her work for a moment before declaring that it seems to be right. The serious moral of Carroll’s comic vignette is that formal tools of thinking are useless in convincing someone of their conclusions if he hasn’t already intuitively grasped the basic principles on which they are built.

All of our knowledge ultimately is grounded on our intuitive recognition of the truth when we see it. There is nothing magical or mysterious about the a priori foundations of economics, or at least nothing any more magical or mysterious than there is about our ability to comprehend any other aspect of reality.

(Callahan has more to say here. For a technical discussion of the science of human action, or praxeology, read this. Some glosses on Gödel’s incompleteness theorem are here.)

I omitted an important passage from the preceding quotation, in order to single it out. Callahan says also that

Mises’s protégé F.A. Hayek, while agreeing with his mentor on the a priori nature of the “logic of action” and its foundational status in economics, still came to regard investigating the empirical issues that the logic of action leaves open as a more important undertaking than further examination of that logic itself.

I agree with Hayek. It’s one thing to know axiomatically that the speed of light is constant; it is quite another (and useful) thing to know experimentally that the speed of light (in empty space) is about 671 million miles an hour. Similarly, it is one thing to deduce from the axioms of economics that demand curves generally slope downward; it is quite another (and useful) thing to estimate specific demand functions.

But one must always be mindful of the limitations of quantitative methods in economics. As James Sheehan writes at the website of the Mises Institute,

economists are prone to error when they ascribe excessive precision to advanced statistical techniques. They assume, falsely, that a voluminous amount of historical observations (sample data) can help them to make inferences about the future. They presume that probability distributions follow a bell-shaped pattern. They make no provision for the possibility that past correlations between economic variables and data were coincidences.

Nor do they account for the possibility, as economist Robert Lucas demonstrated, that people will incorporate predictable patterns into their expectations, thus canceling out the predictive value of such patterns. . . .

As [Nassim Nicholas] Taleb points out [in Fooled by Randomness], the popular Monte Carlo simulation “is more a way of thinking than a computational method.” Employing this way of thinking can enhance one’s understanding only if its weaknesses are properly understood and accounted for. . . .

Taleb’s critique of econometrics is quite compatible with Austrian economics, which holds that dynamic human actions are too subjective and variegated to be accurately modeled and predicted.

In some parts of Fooled by Randomness, Taleb almost sounds Austrian in his criticisms of economists who worship “the efficient market religion.” Such economists are misguided, he argues, because they begin with the flawed hypothesis that human beings act rationally and do what is mathematically “optimal.” . . .

As opposed to a Utopian Vision, in which human beings are rational and perfectible (by state action), Taleb adopts what he calls a Tragic Vision: “We are faulty and there is no need to bother trying to correct our flaws.” It is refreshing to see a highly successful practitioner of statistics and finance adopt a contrarian viewpoint towards economics.

Yet, as Arnold Kling explains, many (perhaps most) economists have lost sight of the axioms of economics in their misplaced zeal to emulate the methods of the physical sciences:

The most distinctive trend in economic research over the past hundred years has been the increased use of mathematics. In the wake of Paul Samuelson’s (Nobel 1970) Ph.D dissertation, published in 1948, calculus became a requirement for anyone wishing to obtain an economics degree. By 1980, every serious graduate student was expected to be able to understand the work of Kenneth Arrow (Nobel 1972) and Gerard Debreu (Nobel 1983), which required mathematics several semesters beyond first-year calculus.

Today, the “theory sequence” at most top-tier graduate schools in economics is controlled by math bigots. As a result, it is impossible to survive as an economics graduate student with a math background that is less than that of an undergraduate math major. In fact, I have heard that at this year’s American Economic Association meetings, at a seminar on graduate education one professor quite proudly said that he ignored prospective students’ grades in economics courses, because their math proficiency was the key predictor of their ability to pass the coursework required to obtain an advanced degree.

The raising of the mathematical bar in graduate schools over the past several decades has driven many intelligent men and women (perhaps women especially) to pursue other fields. The graduate training process filters out students who might contribute from a perspective of anthropology, biology, psychology, history, or even intense curiosity about economic issues. Instead, the top graduate schools behave as if their goal were to produce a sort of idiot-savant, capable of appreciating and adding to the mathematical contributions of other idiot-savants, but not necessarily possessed of any interest in or ability to comprehend the world to which an economist ought to pay attention.

. . . The basic question of What Causes Prosperity? is not a question of how trading opportunities play out among a given array of goods. Instead, it is a question of how innovation takes place or does not take place in the context of institutional factors that are still poorly understood.

Mathematics, as I have said, is a tool of science, it’s not science in itself. Dressing hypothetical relationships in the garb of mathematics doesn’t validate them.

Where, then, is the science in economics? And where is the nonsense? Stay tuned.

Is Science Self-Correcting?

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A long-time colleague, in response to a provocative article about the sins of scientists, characterized it as “garbage” and asserted that science is self-correcting.

I should note here that my colleague abhors “extreme” views, and would cross the street to avoid a controversy. As a quondam scientist, he thinks of a challenge to the integrity of science as “extreme.” Which strikes me as an unscientific attitude.

Science is only self-correcting on a time scale of decades, and even centuries. Wrong-headed theories can persist for a very long time. And it has become worse in the past six decades.

What has changed in the past six decades? Sputnik spurred a (relatively) massive increase in government-funded research. This created a new and compelling incentive: produce research that comports with the party line. The party line isn’t necessarily the line of the party then in power, but the line favored by the bureaucrats in charge of doling out money.

On top of that, politically incorrect research is generally frowned upon. And when it surfaces it is attacked en masse by academicians who are eager to prove their political correctness.

Thus it is that the mere coincidence of a rise in CO2 emissions and a rise in temperatures in the latter part of the 20th century became the basis for kludgey models which “prove” AGW — preferably of the “catastrophic” kind — while essentially ignoring eons of evidence to the contrary. Skeptics (i.e., scientists doing what scientists should do) are attacked viciously when they aren’t simply ignored. The attackers are, all too often, people who call themselves scientists.

And thus it is that research into the connection between race and intelligence has been discouraged and even suppressed at universities. This despite truckloads of evidence that there is such a connection.

Those two examples don’t represent all of science, to be sure, but they’re a sad commentary on the state of science — in some fields, at least.

There are many more examples in Politicizing Science: The Alchemy of Policy-Making, edited by Michael Gough. I haven’t read the book, but I’m familiar with most of the cases documented by the contributors. The cases are about scientists behaving badly, and about non-scientists misusing science and advocating policies that lack firm scientific backing.

Scientists have been behaved badly since the dawn of science, though — as discussed above — there are now more (or different) incentives to behave badly than there were in the past. But non-scientists (especially politicians) will behave badly regardless of and contrary to scientific knowledge. So I won’t blame science or scientists for that behavior, except to the extent that scientists are actively abetting the bad behavior of non-scientists.

Which brings me to the matter of science being self-correcting. I am an avid (perhaps rabid) anti-reificationist. So I must say here that there is no such thing as “science.” There’s only what scientists “do” and claim to know.

It’s possible, though not certain, that future scientists will correct the errors of their predecessors — whether those errors arose from honest mistakes or bias. But, in the meantime, the errors persist and are used to abet policies that have costly, harmful, and even fatal consequences for multitudes of people. And most of that damage can’t be undone.

So, in this age of weaponized science, I take no solace in the idea that the errors of its practitioners and abusers might, someday, be recognized. The errors of knowledge might be corrected, but the errors of application are (mostly) beyond remedy.

Here’s an analogy: The errors of the builders, owners, captain, and crew of RMS Titanic seem to have been corrected, in that there hasn’t been a repetition of the conditions and events that led to the ship’s sinking. But that doesn’t make up for the loss of 1,514 lives, the physical and emotional suffering of the 710 survivors, the loss of a majestic ship, the loss of much valuable property, or the grief of the families and friends of those who were lost.

In sum, the claim that science is self-correcting amounts to a fatuous excuse for the irreparable damage that is often done in the name of science.

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Related posts:

Demystifying Science
Scientism, Evolution, and the Meaning of Life
The Fallacy of Human Progress
Pinker Commits Scientism
AGW: The Death Knell (with many links to related readings and earlier posts)
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists
Not-So-Random Thoughts (XIV) (second item)
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?
Understanding Probability: Pascal’s Wager and Catastrophic Global Warming
The Technocratic Illusion
The Precautionary Principle and Pascal’s Wager
Further Pretensions of Knowledge
“And the Truth Shall Set You Free”
AGW in Austin? (II)

Ty Cobb and the State of Science

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This post was inspired by “Layman’s Guide to Understanding Scientific Research” at bluebird of bitterness.

The thing about history is that it’s chock full of lies. Well, a lot of the lies are just incomplete statements of the truth. Think of history as an artificially smooth surface, where gaps in knowledge have been filled by assumptions and guesses, and where facts that don’t match the surrounding terrain have been sanded down. Charles Leershen offers an excellent example of the lies that became “history” in his essay “Who Was Ty Cobb? The History We Know That’s Wrong.” (I’m now reading the book on which the essay is based, and it tells the same tale, at length.)

Science is much like history in its illusory certainty. Stand back from things far enough and you see a smooth, mathematical relationship. Look closer, however, and you find rough patches. A classic example is found in physics, where the big picture of general relativity doesn’t mesh with the small picture of quantum mechanics.

Science is based on guesses, also known as hypotheses. The guesses are usually informed by observation, but they are guesses nonetheless. Even when a guess has been lent credence by tests and observations, it only becomes a theory — a working model of a limited aspect of physical reality. A theory is never proven; it can only be disproved.

Science, in other words, is never “settled.” Napoleon is supposed to have said “What is history but a fable agreed upon?” It seems, increasingly, that so-called scientific facts are nothing but a fable that some agree upon because they wish to use those “facts” as a weapon with which to advance their careers and political agendas. Or they simply wish to align themselves with the majority, just as Barack Obama’s popularity soared (for a few months) after he was re-elected.

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Related reading:

Wikipedia, “Replication Crisis

John P.A. Ionnidis, “Why Most Published Research Findings Are False,” PLOS Medicine, August 30, 2005

Liberty Corner, “Science’s Anti-Scientific Bent,” April 12, 2006

Politics & Prosperity, “Modeling Is Not Science,” April 8, 2009

Politics & Prosperity, “Physics Envy,” May 26, 2010

Politics & Prosperity, “Demystifying Science,” October 5, 2011 (also see the long list of related posts at the bottom)

Politics & Prosperity, “The Science Is Settled,” May 25, 2014

Politics & Prosperity, “The Limits of Science, Illustrated by Scientists,” July 28, 2014

Steven E. Koonin, “Climate Science Is Not Settled,” WSJ.com, September 19, 2014

Joel Achenbach, “No, Science’s Reproducibility Problem Is Not Limited to Psychology,” The Washington Post, August 28, 2015

William A. Wilson, “Scientific Regress,” First Things, May 2016

Jonah Goldberg, “Who Are the Real Deniers of Science?AEI.org, May 20, 2016

Steven Hayward, “The Crisis of Scientific Credibility,” Power Line, May 25, 2016

There’s a lot more here.