A Teacher Writes to Students Series (20):Wrong-Headed, Lying Economists
By Annavajhula J C Bose, PhD
Department of Economics, SRCC, DU
William Stanley Jevons, an architect, in days of yore, of Marginal Revolution in economics, had commented on the Classical economist David Ricardo as “that able, but wrong-headed man” who put economics on the “wrong track”.
But this referral of his applies to his own types now in modern economics because, as John Kay points out, “A problem specific to economics is that students suspect the material they are taught is designed to offer intellectual cover for right-wing ideology…Economics teaching encourages students to think of a world of self-interested individuals and profit-oriented companies…They find themselves engaged in rote learning of models based on rational choice. They are fobbed off with assurances that acquisition of these skills is a necessary foundation for understanding of the great issues of the day; but somehow these great issues never make it into the curriculum”—great issues like unemployment, precarity, poverty, inequality, discrimination, inflation and financial crises.
“The proper scope of economics is any and all ideas that bear usefully on these topics: just as the proper scope of medicine is any and all therapies that help the patient”, adds John Kay, who sits on the advisory board of the Institute for New Economic Thinking, led by Professor Wendy Carlin of University College London.
According to libertarian McCloskey (2002), an inquiry into the world must think and it must look. Both ought to be done. That’s obvious and elementary. But typical economists don’t do this. They have indulged in two sins since long in terms of professing ‘qualitative theorems’ and ‘statistical significance’. The former is assumptions based pure thinking, mathematically expressed. Changing assumptions changes conclusions, though! “It is not disciplined by any simultaneous inquiry into How Much. It’s qualitative, not quantitative, and not organized to allow quantities into the story. It’s like stopping with the conclusion that forgetting your lover’s birthday will have some bad effect on one’s relationship—you still have no idea How Much, whether trivial or disastrous or somewhere in between. So the pure thinking is unbounded. It’s a game of imagining how your lover will react endlessly. True, if you had good ideas about what were plausible assumptions to make, derived from some inquiry into the actual state of the world, the situation might be rescued for science and other inquiries into the world, such as the inquiry into the probably quantitative effect of missing a birthday on your lover’s future commitment to you. But if not—and I’m telling you that such is the usual practice of “theoretical” pieces in economics—it’s “just” an intellectual game.”
And in doing empirical statistical research via estimated regressions, “statistical significance simply tells the researcher (in a very arbitrary way) that a particular finding probably would show up again if we were to examine another sample of the same underlying data. It does not tell us whether the finding is important or not. One constantly encounters this confusion. Suppose that in medical research we find that taking a particular drug reduces the likelihood of contracting lung cancer by one-half, and the relationship is “statistically significant.”
Suppose, however, that the probability of contracting lung cancer is only 0.00001 to begin with, so the drug reduces the probability by just 0.000005. Few of us would consider this risk reduction to be important (especially if the drug is very expensive). Statistical significance is not the same as importance. The point also applies in reverse. Important but statistically insignificant research findings sometimes are rejected unjustifiably. Again, suppose in a drug trial with eight lung cancer patients you found that two of the eight were cured of the disease. It is likely that, given this small sample size, a test of statistical significance would show the result to be statistically insignificant. But wait a minute. Two people—25 percent—were cured! Doesn’t it sound important to you?”
Owing to both these sins, which do not require any tiresome inquiry into How Much, How big is big, What is an important variable, and How Much exactly is its oomph, the progress of economic science has been seriously damaged. “You can’t believe anything that comes out of the Two Sins. Not a word. It is all nonsense, which future generations of economists are going to have to do all over again. Most of what appears in the best journals of economics is unscientific rubbish.”
Moosa (2019) supplements McCloskey with a shocker thus: “Because of the emphasis placed on econometric and quantitative analysis, modern economists cannot say anything useful about the real world, because they talk in a language that is incomprehensible to non-economists, let alone down-to-earth economists. Students and many employers feel that the typical economics graduate today receives training that is irrelevant to understanding real economies, incomprehensible to the target audiences for economic advice, and often just plain incorrect.
This situation can be dealt with by following a “back to the future” approach. Students need to learn more about the real world. They need to know about the current state of the world economy, as well as economic history and the history of economic thought. Students should be introduced to different approaches to economics rather than insisting that only the current mainstream approach is the right way to do good economics because it is amenable to quantification.
Unfortunately, the true believers are adamant that econometrics is contributing to human welfare…The contributions of econometricians is that they have provided tools that allow anyone to prove anything. Econometrics is not a science, perhaps it is junk science, but more accurately it is an art, a con art to be specific. It has no relevance whatsoever to real world economics.”
Finally, consider what the ecological economist Daly had said (Victor, 2022). Macroeconomists obsessed with economic growth tell you 11 lies:
- One can nearly always find something whose growth would be both desirable and possible;
- Since GDP is measured in value terms it is therefore not subject to physical limits;
- Benefits of growth outweigh the costs;
- There is no empirical evidence that the marginal cost of growth has become greater than the marginal benefit;
- The way we measure GDP automatically makes its growth a trustworthy guide to economic policy;
- As natural resources become scarce we can substitute capital for resources and continue to grow;
- Knowledge is the ultimate resource and since knowledge growth is infinite it can fuel economic growth without limit;
- Without growth we are condemned to unemployment;
- We live in a globalized economy and have no choice but to compete in the global growth race;
- Space, the high frontier, frees us from the finitude of the earth, and opens unlimited resources for growth; and
- Without economic growth all progress is at an end.
The terrible confusions and policy blunders emanating from these 11 fallacies need to be overcome.
Surely, these are very disturbing revelations for conventional economics students.
References
Deirdre McCloskey. 2002. The Secret Sins of Economics. Prickly Paradigm Press, LL. Chicago.
https://www.independent.org/publications/tir/article.asp?id=116
https://www.johnkay.com/2014/05/21/angry-economics-students-are-naive-and-mostly-right/
Imad Moosa. 2019. Is Econometrics Relevant to Real World Economics?, in Real World Economics Review. Issue No. 88. World Economics Association.
Peter Victor. 2022. Herman Daly’s Economics for a Full World. Earthscan for Routledge.
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