Quote of the Day

Buck up. Irrational cheerfulness is hard to teach but good to have for any work .
-Deirdre N. McCloskey, Economical Writing, Second Edition, 2000, p. 21

Writing Reveals the Self

On and off the last months, I’ve been reading Strunk & White’s classical The Elements of Style. Most of the book is concerned with rules for good and elusive writing and usage of English. In the final chapter, they discuss style:

In this final chapter, we approach style in its broader meaning: style in the sense of what is distinguished and distinguishing. Here we leave solid ground. Who can confidently say what ignites a certain combination of words, causing them to explode in the mind? Who knows why certain notes in music are capable of stirring the listener deeply, though the same notes slightly rearranged are impotent? [...] There is no satisfactory explanation of style, no infallible guide to good writing, no assurance that a person who thinks clearly will be able to write clearly, no key that unlocks the door, no inflexible rule by which writers may shape their course. Writers will often find themselves steering by stars that are disturbingly in motion [p. 66, fourth edition, paperback].

Strunk & White seems to imply that clear thinking is required for clear writing. McCloskey states that explicitly in her Economical Writing, if I remember correctly. It’s hard to argue for anything else, I guess. What concerns me is that I seldom think clearly. I take forever to straighten out an argument or an idea. Perhaps writing is not something I should pursue?

Style is an increment in writing. When we speak of Fitzgerald’s style, we don’t mean his command of the relative pronoun, we mean the sound his words make on paper. All writers, by the way they use the language, reveal something of their spirits, their habits, their capacities, and their biases. This is inevitable, as well as enjoyable. All writing is communication; creative writing is communication through revelation it is the Self escaping into the open. No writer long remains incognito [pp. 66-67].

Writing reveals the Self!

Finally, some advice:

Young writers often suppose that style is a garnish for the meat of prose, a sauce by which a dull dish is made palatable. Style has no such separate entity; it is nondetachable, unfilterable. The beginner should approach style warily, realizing that it is an expression of self, and should turn resolutely away from all devices that are popularly believed to indicate style all mannerism, tricks, adornments. The approach to style is by way of plainness, simplicity, orderliness, sincerity.

Writing is, for most, laborious and slow. The mind travels faster than the pen; consequently, writing becomes a question of learning to make occasional wing shots, bringing down the bird of thought as it flashes by. A writer is a gunner, sometimes waiting in the blind for something to come in, sometimes roaming the countryside hoping to scare something up. Like other gunners, the writer must cultivate patience, working many covers to bring down one partridge [p. 69].

Truth Versus Precision in Economics by Thomas Mayer

My initial interest in Thomas Mayer’s Truth Versus Precision in Economics was spured when it was mentioned alongside McCloskey’s The Rhetoric of Economics in a footnote in a paper I read; the paper refered to it as a justification to accept unconventional p-values (probability of sampling error) in evaluating regression results.* Anyway, I picked it up at the library and was soon enthralled by Mayer’s sympathetic ideas.

The main claim in Truth Versus Precision is that economics is a victim of the principle of the strongest link, which leads to increased rigouization and decreased real-world relevance.

Mayer argues persuasively that economists has incentives to spend too much time on formalism, and that the formally explicit parts of arguments thus gets too much attention. Weaker parts of arguments are usually tended to by arm-waving. Strong, mathematically explicit arguments are subject to relatively much attention and are thus made stronger; weaker, implisit or verbal arguments receives less attention and remains weak. Further, the strength of a chain of arguments is often measured by the strength of the strongest argument, counter to the proverb that a chain is no stronger than its weakest link:

I call this procedure of focusing attention on the strongest part of an argument, and then attributing its strength to the entire argument, the ‘principle of the strongest link’ [p. 57**].

Mayer further suggests that economists preoccupation with formalism governs the prestige ranking of economics fields:

The prestige ranking of economics runs: first, formalist theory; second, empirical science theory; third, policy-advicing and data gathering, and fourth, history of economic thought and methodology [p. 46].

Mayer is a macroeconomist, and naturally parts of Truth Versus Precision discusses problems in macroeconomics. In particular, he argues that the foundations of new classical economics are questionable and concludes:

[N]ew classical theory is another example of the principle of the strongest link. Its advocates rightly take pride in the rigour of their deductive chains. But a rigorous deduction from a questionable premise, accompanied by no adequate tests of the conclusions, does not guarantee truth [p. 120].

Mayer also discusses the problems surrounding empirical testing in economics, for example that many focuses solely on Type I errors, that regressors with insignificant coefficients are excluded, problems with pre-testing of data, and confusions between statistical and substantive significance (see pp. 134 – 139). Finally, he discusses problems surrounding robustness tests (or rather, the lack thereof) (see pp. 142 – 147). He concludes the chapter on emprical testing accordingly:

[M]ost econometric testing is not rigorous. Combining such tests with formalized theoretical analysis or elaborate techniques is another instance of the principle of the strongest link. The car is sleek and elegant; too bad the wheels keep falling off [p. 149].

In the last chapter, Mayer discusses possible remedies. He calls for less abstraction and less formality; more replications and retests; proper use of statistical tests; care for data and awareness of anecdotal evidence; he wants journals to act as communication devices (not archives); critical evaluations of conflicting evidence; less focus on formal techniques in graduate training programmes; and more focus on writing skills.

All in all, I find many of Mayer’s arguments persuasive; they align with my feeling of unease when it comes to mathematical economics (note; I’m a mathematical economist myself). Some of Mayer’s critique also align with some of McCloskey’s critique. However, a professor at my school told me that Mayer was out-dated already in 1993 (the year of publication), and mentioned an article by Alexander Rosenberg from 1983 as evidence: Rosenberg discusses new classical economics. Notwithstanding, I still think there is something to Mayer’s critique, and as I said, it resonates with my own attitude towards economics. A more recent treatise discussing the very modern development of economics would be useful; have economics ridden itself of the principle of the strongest link? I need to find out.

* See p. 157; as far as I can see the only place in the text that actually argues for unconventional p-values, but not unconditionally.

** Page numbers refer to the paperback edition.

Related posts:

• Economics: A Science or Not?
• A Vertical Division of Economics
• Science vs. Pseudo-Science

Economics: A Science or Not?

I came across this truly interesting book, Truth Versus Precision in Economics (1993) by Thomas Mayer. I’m still only on p. 16, but endnote 1 in chapter one provided fodder for my thinking about economics and science:

I see no purpose in discussing whether economics actually is a science. Philosophers have not succeeded in finding a criterion that distinguishes science from non-science [...], and the question whether a field is an empirical science may even lack clear meansing [...]. Fortunately, nothing hinges on whether one calls economics a science or not, and the question can be left to lexicographers. Knowing whether economics is a science would not allow us to decide whether  it should use the same methods as the natural sciences, since not all sciences necessarily us the same methods. What methods economics should use can be decided better by looking at specific methods and specific problems than by talking in general about ‘scientific method’. Similarly, knowing whether economics is a science would not allow us to say whether it provides answers that deserve a high degree of credence. The science of weather forecasting does not, while the non-science of history does [p. 8, paperback edition].

I agree that nothing really important hinges on whether economics belong to the (hard) sciences or not (what matters is that it is scientific). But, Mayer doesn’t seem to recognize that the English science has lost it’s propper meaning (here’s McCloskey’s explanation): Science means ‘systematic inquiry’ in any other language.

Related posts:

• Economics IS a Science!
• What is Science?

Aris Spanos Reviews Ziliak & McCloskey

In the first issue of the new, free, and online journal Erasmus Journal for Philosophy and Economics, Aris Spanos reviews  Ziliak & McCloskey’s The Cult of Statistical Significance (pp. 154-164; see my rambling review for other reviews and Ziliak’s homepage for more reviews, comments, and much more).

The review is interesting for several reasons. First of all, Spanos is an expert on econometrics and is highly qualified to understand and relate to Ziliak and McCloskey’s critique. Second, the review is highly critical of the book; Spanos does not agree with Ziliak & McCloskey on most central issues, it seems, and he doesn’t like their lack of alternatives to classical, significance testing nor their rhetorics. Finally, the review is particularly interesting because Ziliak & McCloskey has been given the opportunity to reply to Spanos critique.

First, Spanos blows off some steam about Ziliak & McCloskey’s rhetorics:

[T]hey attempt to make their case using a variety of well-known rhetorical strategies and devices, including themes like battles between good vs. evil, and conceit vs. humility, frequent repetition of words and phrases like ‘oomph’, ‘testimation’, ‘sizeless stare’ and ‘size matters’, picturesque language, metaphor and symbolism, flashback, allusion, parody, sarcasm, and irony. Their discourse in persuasion also includes some ‘novel’ devices like cannibalizing quotations by inserting their own ‘explanatory’ comments to accommodate their preferred interpretation, ‘shaming’ notable academics who ‘should have known better’, and recalling private conversations as well as public events where notable adversaries demonstrated the depth of their ignorance [p. 155].

I’m particularly sympathetic to the above critique; I find the rhetoric in the book disturbing and, at times, simply bad. In parts, the use of visual effects is way overdone, which is strange given McCloskey’s warnings about exactly that in her little gem Economical Writing. However, exactly because of McCloskey’s demonstrated wisdom on writing and rhetoric, I’m suspecting that the overuse of visual effects, the insisting repetition, and the defamation of R.A. Fisher is intentional; readers (and professors in particular) are supposed to jump in their chairs, being offended.

Spanos comments rather shortly on much of the book, but his review still gives a good idea of what The Cult is onto and how it goes about it. Spanos’s review naturally focuses on what he’s most interested in; ‘various philosophical/methodological issues pertaining to the problem’ and what to do about it (p. 155).

Spanos is annoyed by the ‘nontechnical’ flavor of the book; he’d like to see alternative methods demonstrated to fix the ‘problem.’ Obviously, Spanos has worked extensively on related issues; he refers to his own work the whole time (so, either he is the world leading expert on the stuff, or he has a wrong idea of himself). Spanos claims that an important reason for the ‘confusion in the minds of practitioners concerning the appropriate use and interpretation of frequentist methods’ was that the philosophical foundations of the early development of the methods ‘left a lot to be desired’ (pp. 157-158). I’m not convinced. Ziliak & McCloskey argue that a mechanical test cannot substitute scientific judgment. ‘Philosophical foundations’ cannot change that.

Spanos continues:

In the absence of any guidance from the statistics literature, practitioners in different applied fields invented their own favored ways to deal with these issues which often amounted to misusing and/or misinterpreting the original frequentist procedures [...]. Such  misuses/misinterpretations include, not only the well-known ones relating to the p-value, but  also: (i) the observed confidence interval, (ii) the p-value curves, (iii) the effect sizes, (iv) the fallacy of the transposed conditional, (v) Rossi’s real type I error, (vi) Zellner’s random prior odds, and (vii) Leamer’s extreme bounds analysis [p. 158].

Spanos then claims that Ziliak & McCloskey too have misunderstood; they have misunderstood the methods they recommend to remedy the problem of significance testing. He goes on to shortly explain why the recommended methods won’t work. Unfortunately, some of his explanations are too short for me to understand. I’m convinced, however, that Spanos knows what he’s talking about and in particular that stuff like confidence intervals and p-value curves won’t help much; I was wondering myself how confidence intervals, based on standard errors, could help alleviate the misuse of significance testing (which is exactly to calculate standard errors and compare the distance between an estimate and a hypothesized value in terms of the standard error).

Spanos, too, misunderstands, however. As far as I can understand, on p. 160, where he writes

“A good and sensible rejection of the null is, among other things, a rejection with high power” (Ziliak and McCloskey 2008, 133). And “refutations of the null are easy to achieve if power is low or the sample is large enough” (p. 152).

No! No! You have it backwards. Rejection with high power is actually the main source of the problem of statistical vs. substantive significance, and ‘large enough sample sizes’ n go hand in hand with high power, not low.

Spanos misunderstands Ziliak & McCloskey when they write ‘if power is low or the sample is large enough’ (p. 152; my emphasis). They mean, as they write, or, not and, as Spanos seem to read.

Nonetheless, Spanos still claims that low power is desirable in a significance test. I presume he is correct; I was very confused about Ziliak & McCloskey’s discussion of power in statistical tests because my knowledge of it is limited and their explanations are not exactly text-book. Now, if I’m not wrong, Ziliak & McCloskey claimed that high power is necessary to avoid so-called Type II errors. Spanos doesn’t mention such errors when he claims they have misunderstood power; instead, he talks about Type I errors. Extremely unfortunate, Ziliak & McCloskey refrain from commenting on power in their reply to Spanos.

Spanos ends his review with a discussion of statistical adequacy, which, according to him is a more fundamental problem in applied statistics and which has been dealt with only recently and to a large degree by himself (p. 163). He continues:

Where does this leave the authors’ concern with the problem of statistical vs. substantive significance? Shouldn’t they have known that, even if one had a credible procedure to address the problem, one couldn’t make any progress on the basis of statistically misspecified models [p. 163]?

I don’t understand. Do more fundamental problems acquit researchers from misusing significance testing? I don’t think so.

I conclude that Ziliak & McCloskey’s are right in their critique of Fisher and his methods, but that their suggested methods aren’t exactly water tight either. Spanos is alien (hostile, even) to Bayesian methods, which he doesn’t even bother to discuss in detail; I may end up putting my faith there.

(For the record, my current understanding of the main difference between Fisherian and Bayesian methods is that Fisherian methods assume God [or whatever; Nature] put the truth out there [a parameter value, for example]; they assume the fixed, only truth exist and somehow treat observations as random. Bayesian methods, instead, treat the truth [the parameter value of interest] as random [or floating or whatever] and treat the observations as given. First, things change and stuff is not constant; the one and only truth don’t exist. Second, the observations are in fact the only given entity in a statistical problem, and I cannot help but find it funny to think of them as somehow random. Maybe I’m just not deep enough?)

Next, Ziliak & McCloskey’s reply (pp. 165 – 170). (Warning: A lot of cutting and pasting is about to hit you: The reply is so well-written that it best speaks for itself.) They start by repeating the gist of their book:

Over the past century the usual (and the conveniently mechanical) procedure devised by the great statistician, geneticist, and racial eugenicist R. A. Fisher has been shown to be scientifically silly again and again and again. Rarely has anyone actually defended NHST (null hypothesis significance testing). That is because it is logically indefensible. Statistical significance is neither necessary nor sufficient for substantive scientific significance. Everyone knows this, once they stop regressing for a minute and actually think [p. 165].

Obviously, they keep insisting on defaming Fisher; their rhetoric in the review, however, I find more balanced than that in the book.

Ziliak & McCloskey accuse Spanos of being angry and indignant. I find it peculiar: If anything else, what I read into Ziliak & McCloskey’s defamation of Fisher, it’s anger and indignation. I would also expect McCloskey to appreciate temperature in a debate. Furthermore, what do they expect when they do what they do to the icon Fisher in fact is? Again, I think Ziliak & McCloskey counted on stirring up feelings, and they use it for what it’s worth: they eloquently turn it against their attackers:

[T]he defenders [of significance testing] are always angry. Ignorant sneering, personal insult, and irrelevant indignation are judged acceptable when defending [significance testing]. We think the anger comes from a psychological tension. The defenders realize uneasily that it is strange to depend for scientific judgment on a sampling statistic without a persuasive context—failing to ask how big is big, which is the only scientific context relevant to a real scientific test. But they have been thoroughly indoctrinated in NHST, and belong to a professional club in which t > 2.0 or p < .05 or whatever is substituted for scientific judgment. The mechanical procedure of their profession is under attack. So they get angry. They have no reply. So they shout and bluster [pp. 165 - 166].

Next (p. 166) Ziliak & McCloskey sidesteps the main part of Spanos attack:

Spanos throws up a lot of technical smoke that has the effect of obscuring the plain fact that he agrees with us. (The mathematics in his piece is irrelevant to anything of importance. The reader may omit it.)

Omit it! They got some nerve. I still find it unfortunate that Ziliak & McCloskey avoid commenting on Spanos claims of errors and misunderstandings in The Cult. Anyway, they see differently on Spanos main criticism:

The main point of Spanos’s piece is that Ziliak and McCloskey do not offer guidance on how to address substantive scientific significance. Yet even if we had not, it would not be a fault. NHST is intellectually bankrupt, as Spanos agrees it is, and it should be abandoned. If you earn your living robbing banks, you should stop, right now, at once. You should not complain, “But how am I now to earn my living?” Go get honest work. And the honest work in the present case is the exercise of scientific judgment, quantified by relevant magnitudes that the best scientists find persuasive [p. 167].

Good point. And they find it appropriate to pound their main message in The Cult some more:

There is no discipline-independent criterion for importance, calculable from the numbers alone. Read that again. There is no discipline-independent criterion for importance, calculable from the numbers alone. Scientific judgment is scientific judgment, a human matter of the community of scientists. As vital as the statistical calculations are as an input into the judgment, the judgment cannot be made entirely by the statistical machinery [p. 168].

Cannot disagree to that. What is an expert if he cannot offer judgement? An expert is not merely an operator of a mathematical machinery; he knows best and should feel obliged to offer his judgment, he shouldn’t hide behind numbers.

Ziliak & McCloskey ends with a challenge (and their ‘prior’):

Here is our challenge. If you think, like Spanos, that you have a valid defense of NHST, offer it. Spanos, like Hoover/Siegler, and Anthony O’Brien (2004), have tried. They have failed. But at least they are serious about their intellectual commitments, and believe (given their Bayesian priors) that NHST is defensible. It is not [p. 169].

Hat-tip:  Homo Phileconomicus

Related post:

• The Cult of Statistical Significance by Ziliak & McCloskey

The Cult of Statistical Significance by Ziliak & McCloskey

Last year, Stephen T. Ziliak and Deirdre N. McCloskey published The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives. I finished it a while ago now (during my trip to Alaska, in fact; a lot of time available on those planes), and I want to discuss it here.

Before checking out my amateur opinions, however, it may be wise to check out some the reviews that Ziliak kindly has gathered on his homepage. I, for example, found the one from Science (by Theodore Porter) interesting. Only read the review in Journal of Economic Literature (by Saul Hymans) if you don’t plan to read the book itself. You may settle with the following, closing paragraph:

Despite my firm belief that most applied econometricians would benefit from adopting the methodological position presented by Ziliak and McCloskey and that economics as science would be improved significantly thereby, I can’t close without something of a rebuke. As often happens when someone is pushing what the mainstream considers an extreme or fringe position, the arguments become narrowly and harshly focused. This comes through too often in Ziliak and McCloskey. In its particularly narrow perspective, their treatment of the professional accomplishments of a number of exceptionally gifted economists is simply unjustified. Included among such economists are Gary Becker, Trygve Haavelmo, Harold Hotelling, Lawrence Klein, and Paul Samuelson. It is especially unfortunate, for example, that Ziliak and McCloskey misrepresent the significance of Haavelmo’s pathbreaking article of 1944 and never even mention his major contribution of 1947, a piece which Ziliak and McCloskey should find quite simpatico [p. 503].

The ‘review’ in the Journal of Economic Methodology (by Tom Engsted) is a full-length article discussing a debate surrounding the Ziliak & McCloskey book.

So, I hope you’re fed up already: Here are my (largely unqualified) opinions on and comments to this book. As (almost) always; first things first: The Cult of Statistical Significance carries some important messages (despite it’s terrible title; maybe they were inspired by the dreadful Andrew Keen). The Cult tells us that statistical significance is not the same thing as substantive significance, that statistical significance is often misused and appears to be misunderstood by many a scientist (and particularly economists), and that only by attending to quantitative, scientific magnitude and judgement will sciences like medicine (yes, medicine), economics, and other statistically confused fields be able to move ‘into the age of science and humanity’ (p. 251; all page references are to the paperback edition). Alright, maybe the last one there may be discussed (and the quote is slightly out of context); notwithstanding, Ziliak and McCloskey certainly feels that way, wants their readers to feel that way, and bring a lot of good arguments to the table.

A quick, non-technical update on statistical significance is found here, by the way. From the first paragraph:

In normal English, “significant” means important, while in Statistics “significant” means probably true (not due to chance). A research finding may be true without being important. When statisticians say a result is “highly significant” they [should] mean it is very probably true.

Everyone who understands statistical significance understands that substantial significance is something else and the more important of the two. The disagreement would be whether statistical significance is misused, misunderstood, or both. Perhaps, then, Ziliak and McCloskey’s crown argument is their study of the practice with statistical significance in the American Economic Review during the 1980s. (To those unaware; a publication in the AER is among the most prestigious and important things an economist can achieve, particularly in terms of their career.) Their findings, discussed in chapter 6 (pp. 74-78) and published in the Journal of Economic Literature in 1996, is discouraging. The best economists (that is, those publishing in the AER in the 1980s) misuse statistical significance to a large degree.

Next, Ziliak and McCloskey do something odd. Faced with arguments from colleagues that best practice had improved since the 1980s, perhaps partly because of their 1996 article, they go ahead and do another study of the practice in the AER in the 1990s:

We are very willing to believe that since the 1980s our colleagues have stopped making an elementary error and especially that we have changed their minds. But being readers of typical economics articles since that first decace of personal computers [the 1980s] we seriously doubted that fishing for significance had much abated. [...] And so in a second article, published in 2004, we [reapplied our study from 1996] to all the full-length empirical articles of the next decade of the AER, the 1990s [p. 79].

There’s a logical flaw here. If Ziliak and McCloskey caused the change with their 1996 article, it won’t show up in a study of the 1990s! And probably not of the first decade of the new millenium either; changes take a while, often a generation or so (just ask Thomas Kuhn, rephrased by Paul A. Samuelson in 1999: ‘Science advances funeral by funeral’). And indeed, Ziliak and McCloskey(or, McCloskey and Ziliak, as the reference will show) doesn’t find much of an improvement in the 1990s compared to the 1980s.

Of course, Ziliak and McCloskey have ideas on why scientific practice in the AER has not changed:

Significance unfortunately is a useful means toward personal ends in the advance of science – status and widely distributed publications, a big laboratory, a staff or research assistants, a reduction in teaching load, a better salary, the finer wines of Bordeaux. Precision, knowledge, and control. In a narrow and cynical sense statisitcal significance is the way to achieve these. Design experiment. Then calculate statistical significance. Publish articles showing “significant” results. Enjoy promotion.

But it is not science, and it will not last [p. 32].

They may be right. But, one cannot forget the position of the AER among economists. Because of it’s career generating potential, economists are likely to mimic it, both methodologically and rhetorically.

Still, Ziliak and McCloskey’s empirical evidence of the poor econometric practice in the AER is striking and convincing. I am now skeptic towards empirical economists. And not only economists: Ziliak and McCloskey summarizes evidence of bad practice in psychology, medicine, ecology and several other fields. One gets the impression that only the ‘hard’ sciences got it right (and I who used to think that medicine was a hard science).

In Ziliak and McCloskey’s view, one man is responsible for most of the statistical mess in economics and other fields: R. A. Fisher, whose Statistical Methods for Research Workers (1925), which went through no less than 14 editions, laid down the foundations for much of the later, statistical practice in many applied statistical fields. Ziliak and McCloskey attacks Fisher hard, in an almost distasteful way (they even accuse him of ‘outright, scientific fraud’ in an endnote somewhere, I’m sure, but I wasn’t able to find back to it), and large parts of the second half of the book they devote to attack Fisher in various ways and contrast him to (their hero, it appears) William Sealy Gosset, better know as ‘Student’ (look up Student-t). Maybe even more absurd is the blame put on the philosophical trends of the time:

One reason for the success of the Fisherian program against more logical alternatives [...] is that the Fisherian program emerged just as neopositivismand then falsificationism emerged in the philosophy of science. It would have fallen flat in philosophically more subtle times, such as those of Mill’s System of Logic Ratiocinative and Inductive (1843) or Imre Lakatos’s Proofs and Refutations (1976). No serious philosopher nowadays is a positivist, no seroius philosopher of science a simple falsificationist. But the philosophical atmosphere of 1922-62 was perfect for the fastening of Fisher’s grip on the [statistically confused] sciences [p. 149].

Toward the end, after the very interesting chapter 23 (pp. 238-244), Ziliak and McCloskey get almost out of hand. On pages 249-250, they propose a “Statement on the proprieties of Substantive Significance” which they want editors, administrators and scientists to sign. The language of their ‘statement’ is, however, to involved and won’t hold as a standalone statement. I don’t understand the purpose of the statement when it isn’t self-containted, and otherwise just repeats a message that has been pounded upon throughout the book. And they keep pounding it, increasing their volume:

The textbooks are wrong. The teaching is wrong. The seminar you just attended is wrong. The most prestigious journal in your scientific field is wrong [p. 250].

Got it.

I had high expectations for this book, particularly because McCloskey’s name was on the cover. I was sligthly disappointed, however. By close examination, I discovered that McCloskey’s name is put last and that they’ve ignored the alphabetical order of names: Ziliak is the main author. It is obvious in some places, Ziliak don’t have McCloskey’s Economical Writing under his skin (neither do I, of course, but I would expect McCloskey to). This is a minor issue, certainly, but I looked forward to some persuasive, well-written, and witful prose of the kind McCloskey promotes in her Economical Writing; most of the time, it didn’t happen.

UPDATE: I have a hundred things to say about this book, but I cannot say them all at once. My above review is bad, I know, and I apologize. I confused the important things I wanted to say with the unimportant ones. I may get back to the book in later posts, but for now, I suggest the reader rather reads my discussion of the debate between Spanos and Ziliak & McCloskey. It presumable gives a better idea of what’s important in the book and yields more enjoyable and interesting reading.

And, for the record, let me again point out that I agree with Ziliak & McCloskey on their main point in The Cult, as stated in their reply to Spanos:

Statistical significance is neither necessary nor sufficient for substantive scientific significance.

Wikipedia vs. Public Restrooms, and Social Knowledge

The user who visits Wikipedia to learn about some subject, to confirm some matter of fact, is rather in the position of a visitor to a public restroom. It may be obviously dirty, so that he knows to exercise great care, or it may seem fairly clean, so that he may be lulled into a false sense of security. What he certainly does not know is who has used the facilities before him.

The words belong to Robert McHenry, a former editor in chief of the Encyclopædia Britannica. I found the quote in David Weinberger’s book ‘Everything is Miscellaneous’ (p. 132). The quote is taken from an article McHenry wrote on TechCentralStation.com back in 2004. I’m sure it makes interesting reading. 2004 is five (5!) years ago, however, and a lot has happened since then.

Another skeptic towards Wikipedia is (or, was) Stephen J. Dubner of Freakonomics; he discovered himself on a list of well-known economists. That was 2005, however, and Dubner’s skepticism has faded (if my memory serves me right, that is; I’m sure he mentioned his newly won trust in Wikipedia somewhere, but I wasn’t able to find it; I need a backward-link seeking tool to find entries linking to the post I link to above, because it was when he mentioned his new view of Wikipedia he linked to the old post with his Wikipedia skepticism I found that; confusing I know, but it’s not important, so just forget about it).

Wikipedia may be great, but it also may be wrong from time to time. To know, you need to find out whether an entry is disputed or not. If it is, I’m sure the relevant discussion page suffices to make sure what is trustworthy and what is not, and eventually what side of the dispute you want to sympathize with. However, if the subject is a bit odd, Wikipedia may be wrong and still not disputed because so few people ever looks up the entry.

So, can Wikipedia be trusted on the big, important entries, but not the small ones? When is an entry big; when is it small? My conclusion is that Wikipedia may be a good starting point, but usually I rely on Wikipedia to take me somewhere else, to ‘real’ sources. Wikipedia doesn’t feel real to me, but it collects threads to a lot of real stuff.

The old rule of not relying on only one source remains. Paradoxically, Wikipedia, which is generated from innumerable sources, needs to be checked towards different sources before one can rely on it.

Weinberger concludes his section containing the McHenry quote with the following sentence:

Knowledge – its content and its organization – is becoming a social act [p.133].

I twisted when I read that. When was knowledge, its content and organization, not social? I’m certain dear Deirdre wrote somewhere (probably in ‘The Rhetoric of Economics’) that research is social; research is supposed to produce science, and if we’re strict about knowledge, it comes from science. Not all kinds of knowledge, for sure, but certainly the kind Weinberger is talking about. Research IS social. It’s not objective; it’s colored by the subjects involved and the social environment they do their research in. What Weinberger tries to tell us, I think, is that more people may take part in the process he calls knowledge (the social act). No initial requirements to participate are necessary, or rather, requirements (I’m thinking education; position; image) doesn’t matter, or matter less. Whether that is a good thing or not, I haven’t yet decided.

Related post:

• Four Characteristics of Knowledge

Mr Vertigo

Today, I finished ‘Mr Vertigo’; a novel by Paul Auster. I’m not going to discuss it at length (or at all), but the opening line is worth a whole post by itself:

I was twelve years old the first time I walked on water.

That’s a cracker. The opening line must be the hardest one. It’s like ligthening from a clear, blue sky. It must hook the reader, make him curious about what’s to follow. According to McCloskey’s ‘Economical Writing’, the opening statement should not be boring, but take the reader from his current standpoint to the issue at hand.

The rest of ‘Mr Vertigo’ is also great, by the way; go read it!

Economics Is Hard

In an old post on Freakonomics that discusses the Coase Theorem, Steven Levitt, the great economist, writes:

The basic idea of the Coase Theorem is that no matter who is assigned property rights, as long as transaction costs are not too high, the efficient outcome will be achieved.

That’s wrong, as far as I know. Well, at least, Deirdre McCloskey, who seem to know her stuff better than most, writes in her little gem Economical Writing:

“[T]he Coase Theorem” [that is] “the proposition that property rigths matter to allocation in the case of high transaction costs” (which, incidentally, is the correct statement of the theorem, widely misunderstood in economics) [p. 60, 2nd edition].

The quote is taken out of context, which is a discussion of the use of Capitalization, but that’s beside the point. Now, I looked the theorem up in the book I learned it from back in the days (‘Environmental Economics – In Theory and Practice’ by Hanley, Shogren, and White, 1997), and it was wrongly stated there as well:

The so-called Coase theorem posits that disputing parties will work out a private agreement that is Pareto efficient [that is, no-one can be made better off without making someone else worse off], regardless of the party to whom unilateral property rights to the non-market asset are assigned initially [p. 25].

Both Levitt and my text book are right, of course; property rights do not matter to efficiency when transaction costs are ignored. They are always present, however, and that’s were Coase put his emphasis, I think; when transaction costs are substantial, property rights matter. I should look up Coase’s original formulation and find out for myself, I know. I’m lazy, though, maybe some other time. I did google it, however, and every single explanation I found among the top hits got it the wrong way.

Economics is hard. Or confusing, maybe.

What is Science?

Despite my earlier efforts, the strange usage of ‘science’ in the English language still obstructs the discussion over on Climate Progress. John McCormick writes

Here is a definition of the word ‘science’

“1. the systematic observation of natural events and conditions in order to discover facts about them and to formulate laws and principles based on these facts. 2. the organized body of knowledge that is derived from such observations and that can be verified or tested by further investigation. 3. any specific branch of this general body of knowledge, such as biology, physics, geology, or astronomy.”

Academic Press Dictionary of Science & Technology [...]

Economics does nto [sic] fit the definition of science, in my opinion. So, scientific norms do not apply [when it comes to economics.]

McCloskey tracks the current use of ‘science’ back to 1867 (p. 20 in ‘The Rhetoric of Econmics,’ 2nd ed.). Earlier ‘science’ meant ‘studies,’  in line with its counterpart in other Indo-European languages. The weird thing is that today,  its counterpart in most languages hasn’t really changed meaning; it means ‘systematic inquiry’ and is not explicitly chained to ‘natural events.’ It is thus used to describe, e.g., philosphy and studies of poetry and language, as well as physics and chemistry. It is thus absurd that economics is a science in other languages, but not in English. What are we supposed to make of this? I let McCloskey explain (p. 21).

The point is that the foreigners have gotten it right. [...] “Economics is a science” should not be the fighting words they are in English. The fighting lacks point because, as our friends across the water could have told us, nothing important depends on its outcome. Economics in particular is merely a disciplined inquiry into the market for rice or the scarcity of love. Economics is a collection of literary forms, some of them expressed in mathematics, not a Science. Indeed, science is a collection of literary forms, not a Science. And literary forms are scientific. [...] The idea that science is a way of talking, not a separate realm of Truth, has become common among students of science since Thomas Kuhn.[*]

So, what’s important is that economics is scientific. Economics might not be a science in the U.S., but it is certainly scientific and scientific norms do apply.

* Thomas Kuhn (1922 – 1996) was maybe the most influental philosopher of science in the twentieth century. Anyone slightly interested in science, philosophy or generally should read his book ‘The Structure of Scientific Revolutions.’

Economics IS a Science!

In the comment section to Joe Romm’s third post on the evil of economists a very interesting comment surfaced. (My previous post links to Romm’s earlier attacks and some responses.) It is signed by ‘Asteroid Miner’ (comment no. 7):

Economists think that they are scientists. They are not. Science deals with NATURE, not man-made things like markets and money. Science requires and is based on public and replicable experiments. Computer simulations don’t count. Social sciences are suspect, but not as bad as economics. SCIENTIFIC EXPERIMENTS ARE NOT POSSIBLE IN ECONOMICS.

Economics presupposes the existence of a stable civilization and the invention of money. A stable civilization with money requires creatures that are at least marginally rational and intelligent and slightly knowledgeable. A stable civilization also requires an adequate food supply. The collapse of agriculture inevitably leads to the collapse of civilization and the collapse of money and economics. Economics is unable to go outside of its founding presuppositions. Global warming climatology MUST concern itself with the collapse of civilization and the possible extinction of the supposedly rational intelligent knowledgeable creatures. Climate change is therefore impossible for economists to imagine AS LONG AS THEY REMAIN ECONOMISTS.

Thus the problem of economists who speak on the subject of global warming. Being economists, they assume the impossible, which is that agriculture will not collapse, civilization will not collapse and Homo Sapiens will not go extinct. Being economists, they are unable to imagine anything outside of the basic presuppositions of economics. They have made those assumptions implicitly since long before their careers began. They cannot do otherwise. They are money oriented. It is a basic part of their personalities. They cannot change by themselves.

Our project, therefore, is to make economists quit being economists prior to the collapse of civilization. It is only by taking them outside of their economic world view that they can be shown how to imagine another world, a world without economics. We have to somehow show them the limitations of the boundaries of their world. We have to shock them into the realization that their world is a very small subset of reality.

My reply:

Asteroid: The English ’science’ has, since the late nineteenth century, been used in a new, weird, sense. Earlier, it meant ’studies.’ It’s counterpart in German (wissenschaft), French (science), and all other Indo-European languages mean ’systematic inquiry’ rather than something that deals with nature. Why the English term went off-track, I don’t know, but statements like ‘economics is not a science’ looks very weird to me (a foreigner). [...]

What I see as the misuse of ‘science’ in English has irritated me for a while (and is related to The English Problem). It was then heartening to read Deirdre McCloskey‘s ‘The Rhetoric of Economics.’ On page 20 (second edition) and onwards she discusses and compares the use of ‘science’ to its counterparts in ‘all Indo-European languages.’ She also quotes Lord Kelvin, who in 1883 obiously helped make ‘science’ absurd:

When you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind [...] It may be the beginning of knowledge, but you have scarcely in you thoughts advanced to the stage of science.

I conclude that economics is a science after all, only not in English.