Not-So-Random Thoughts (XV)

Links to the other posts in this occasional series may be found at “Favorite Posts,” just below the list of topics.

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Victor Davis Hanson writes:

This descent into the Dark Ages will not end well. It never has in the past. [“Building the New Dark-Age Mind,” Works and Days, June 8, 2015]

Hamson’s chronicle of political correctness and doublespeak echoes one theme of my post, “1963: The Year Zero.”

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Timothy Taylor does the two-handed economist act:

It may be that the question of “does inequality slow down economic growth” is too broad and diffuse to be useful. Instead, those of us who care about both the rise in inequality and the slowdown in economic growth should be looking for policies to address both goals, without presuming that substantial overlap will always occur between them. [“Does Inequality Reduce Economic Growth: A Skeptical View,” The Conversible Economist, May 29, 2015]

The short answer to the question “Does inequality reduce growth?” is no. See my post “Income Inequality and Economic Growth.” Further, even if inequality does reduce growth, the idea of reducing inequality (through income redistribution, say) to foster growth is utilitarian and therefore morally egregious. (See “Utilitarianism vs. Liberty.”)

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In “Diminishing Marginal Utility and the Redistributive Urge” I write:

[L]eftists who deign to offer an economic justification for redistribution usually fall back on the assumption of the diminishing marginal utility (DMU) of income and wealth. In doing so, they commit (at least) four errors.

The first error is the fallacy of misplaced concreteness which is found in the notion of utility. Have you ever been able to measure your own state of happiness? I mean measure it, not just say that you’re feeling happier today than you were when your pet dog died. It’s an impossible task, isn’t it? If you can’t measure your own happiness, how can you (or anyone) presume to measure and aggregate the happiness of millions or billions of individual human beings? It can’t be done.

Which brings me to the second error, which is an error of arrogance. Given the impossibility of measuring one person’s happiness, and the consequent impossibility of measuring and comparing the happiness of many persons, it is pure arrogance to insist that “society” would be better off if X amount of income or wealth were transferred from Group A to Group B….

The third error lies in the implicit assumption embedded in the idea of DMU. The assumption is that as one’s income or wealth rises one continues to consume the same goods and services, but more of them….

All of that notwithstanding, the committed believer in DMU will shrug and say that at some point DMU must set in. Which leads me to the fourth error, which is an error of introspection….  [If over the years] your real income has risen by a factor of two or three or more — and if you haven’t messed up your personal life (which is another matter) — you’re probably incalculably happier than when you were just able to pay your bills. And you’re especially happy if you put aside a good chunk of money for your retirement, the anticipation and enjoyment of which adds a degree of utility (such a prosaic word) that was probably beyond imagining when you were in your twenties, thirties, and forties.

Robert Murphy agrees:

[T]he problem comes in when people sometimes try to use the concept of DMU to justify government income redistribution. Specifically, the argument is that (say) the billionth dollar to Bill Gates has hardly any marginal utility, while the 10th dollar to a homeless man carries enormous marginal utility. So clearly–the argument goes–taking a dollar from Bill Gates and giving it to a homeless man raises “total social utility.”

There are several serious problems with this type of claim. Most obvious, even if we thought it made sense to attribute units of utility to individuals, there is no reason to suppose we could compare them across individuals. For example, even if we thought a rich man had units of utility–akin to the units of his body temperature–and that the units declined with more money, and likewise for a poor person, nonetheless we have no way of placing the two types of units on the same scale….

In any event, this is all a moot point regarding the original question of interpersonal utility comparisons. Even if we thought individuals had cardinal utilities, it wouldn’t follow that redistribution would raise total social utility.

Even if we retreat to the everyday usage of terms, it still doesn’t follow as a general rule that rich people get less happiness from a marginal dollar than a poor person. There are many people, especially in the financial sector, whose self-esteem is directly tied to their earnings. And as the photo indicates, Scrooge McDuck really seems to enjoy money. Taking gold coins from Scrooge and giving them to a poor monk would not necessarily increase happiness, even in the everyday psychological sense. [“Can We Compare People’s Utilities?,” Mises Canada, May 22, 2015]

See also David Henderson’s “Murphy on Interpersonal Utility Comparisons” (EconLog, May 22, 2015) and Henderson’s earlier posts on the subject, to which he links. Finally, see my comment on an earlier post by Henderson, in which he touches on the related issue of cost-benefit analysis.

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Here’s a slice of what Robert Tracinski has to say about “reform conservatism”:

The key premise of this non-reforming “reform conservatism” is the idea that it’s impossible to really touch the welfare state. We might be able to alter its incentives and improve its clanking machinery, but only if we loudly assure everyone that we love it and want to keep it forever.

And there’s the problem. Not only is this defeatist at its core, abandoning the cause of small government at the outset, but it fails to address the most important problem facing the country.

“Reform conservatism” is an answer to the question: how can we promote the goal of freedom and small government—without posing any outright challenge to the welfare state? The answer: you can’t. All you can do is tinker around the edges of Leviathan. And ultimately, it won’t make much difference, because it will all be overwelmed in the coming disaster. [“Reform Conservatism Is an Answer to the Wrong Question,” The Federalist, May 22, 2015]

Further, as I observe in “How to Eradicate the Welfare State, and How Not to Do It,” the offerings of “reform conservatives”

may seem like reasonable compromises with the left’s radical positions. But they are reasonable compromises only if you believe that the left wouldn’t strive vigorously to undo them and continue the nation’s march toward full-blown state socialism. That’s the way leftists work. They take what they’re given and then come back for more, lying and worse all the way.

See also Arnold Kling’s “Reason Roundtable on Reform Conservatism” (askblog, May 22, 2015) and follow the links therein.

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I’ll end this installment with a look at science and the anti-scientific belief in catastrophic anthropogenic global warming.

Here’s Philip Ball in “The Trouble With Scientists“:

It’s likely that some researchers are consciously cherry-picking data to get their work published. And some of the problems surely lie with journal publication policies. But the problems of false findings often begin with researchers unwittingly fooling themselves: they fall prey to cognitive biases, common modes of thinking that lure us toward wrong but convenient or attractive conclusions. “Seeing the reproducibility rates in psychology and other empirical science, we can safely say that something is not working out the way it should,” says Susann Fiedler, a behavioral economist at the Max Planck Institute for Research on Collective Goods in Bonn, Germany. “Cognitive biases might be one reason for that.”

Psychologist Brian Nosek of the University of Virginia says that the most common and problematic bias in science is “motivated reasoning”: We interpret observations to fit a particular idea. Psychologists have shown that “most of our reasoning is in fact rationalization,” he says. In other words, we have already made the decision about what to do or to think, and our “explanation” of our reasoning is really a justification for doing what we wanted to do—or to believe—anyway. Science is of course meant to be more objective and skeptical than everyday thought—but how much is it, really?

Whereas the falsification model of the scientific method championed by philosopher Karl Popper posits that the scientist looks for ways to test and falsify her theories—to ask “How am I wrong?”—Nosek says that scientists usually ask instead “How am I right?” (or equally, to ask “How are you wrong?”). When facts come up that suggest we might, in fact, not be right after all, we are inclined to dismiss them as irrelevant, if not indeed mistaken….

Given that science has uncovered a dizzying variety of cognitive biases, the relative neglect of their consequences within science itself is peculiar. “I was aware of biases in humans at large,” says [Chris] Hartgerink [of Tilburg University in the Netherlands], “but when I first ‘learned’ that they also apply to scientists, I was somewhat amazed, even though it is so obvious.”…

One of the reasons the science literature gets skewed is that journals are much more likely to publish positive than negative results: It’s easier to say something is true than to say it’s wrong. Journal referees might be inclined to reject negative results as too boring, and researchers currently get little credit or status, from funders or departments, from such findings. “If you do 20 experiments, one of them is likely to have a publishable result,” [Ivan] Oransky and [Adam] Marcus [who run the service Retraction Watch] write. “But only publishing that result doesn’t make your findings valid. In fact it’s quite the opposite.”9 [Nautilus, May 14, 2015]

Zoom to AGW. Robert Tracinski assesses the most recent bit of confirmation bias:

A lot of us having been pointing out one of the big problems with the global warming theory: a long plateau in global temperatures since about 1998. Most significantly, this leveling off was not predicted by the theory, and observed temperatures have been below the lowest end of the range predicted by all of the computerized climate models….

Why, change the data, of course!

Hence a blockbuster new report: a new analysis of temperature data since 1998 “adjusts” the numbers and magically finds that there was no plateau after all. The warming just continued….

How convenient.

It’s so convenient that they’re signaling for everyone else to get on board….

This is going to be the new party line. “Hiatus”? What hiatus? Who are you going to believe, our adjustments or your lying thermometers?…

The new adjustments are suspiciously convenient, of course. Anyone who is touting a theory that isn’t being borne out by the evidence and suddenly tells you he’s analyzed the data and by golly, what do you know, suddenly it does support his theory—well, he should be met with more than a little skepticism.

If we look, we find some big problems. The most important data adjustments by far are in ocean temperature measurements. But anyone who has been following this debate will notice something about the time period for which the adjustments were made. This is a time in which the measurement of ocean temperatures has vastly improved in coverage and accuracy as a whole new set of scientific buoys has come online. So why would this data need such drastic “correcting”?

As climatologist Judith Curry puts it:

The greatest changes in the new NOAA surface temperature analysis is to the ocean temperatures since 1998. This seems rather ironic, since this is the period where there is the greatest coverage of data with the highest quality of measurements–ARGO buoys and satellites don’t show a warming trend. Nevertheless, the NOAA team finds a substantial increase in the ocean surface temperature anomaly trend since 1998.


I realize the warmists are desperate, but they might not have thought through the overall effect of this new “adjustment” push. We’ve been told to take very, very seriously the objective data showing global warming is real and is happening—and then they announce that the data has been totally changed post hoc. This is meant to shore up the theory, but it actually calls the data into question….

All of this fits into a wider pattern: the global warming theory has been awful at making predictions about the data ahead of time. But it has been great at going backward, retroactively reinterpreting the data and retrofitting the theory to mesh with it. A line I saw from one commenter, I can’t remember where, has been rattling around in my head: “once again, the theory that predicts nothing explains everything.” [“Global Warming: The Theory That Predicts Nothing and Explains Everything,” The Federalist, June 8, 2015]

Howard Hyde also weighs in with “Climate Change: Where Is the Science?” (American Thinker, June 11, 2015).

Bill Nye, the so-called Science Guy, seems to epitomize the influence of ideology on “scientific knowledge.”  I defer to John Derbyshire:

Bill Nye the Science Guy gave a commencement speech at Rutgers on Sunday. Reading the speech left me thinking that if this is America’s designated Science Guy, I can be the nation’s designated swimsuit model….

What did the Science Guy have to say to the Rutgers graduates? Well, he warned them of the horrors of climate change, which he linked to global inequality.

We’re going to find a means to enable poor people to advance in their societies in countries around the world. Otherwise, the imbalance of wealth will lead to conflict and inefficiency in energy production, which will lead to more carbon pollution and a no-way-out overheated globe.

Uh, given that advanced countries use far more energy per capita than backward ones—the U.S.A. figure is thirty-four times Bangladesh’s—wouldn’t a better strategy be to keep poor countries poor? We could, for example, encourage all their smartest and most entrepreneurial people to emigrate to the First World … Oh, wait: we already do that.

The whole climate change business is now a zone of hysteria, generating far more noise—mostly of a shrieking kind—than its importance justifies. Opinions about climate change are, as Greg Cochran said, “a mark of tribal membership.” It is also the case, as Greg also said, that “the world is never going to do much about in any event, regardless of the facts.”…

When Ma Nature means business, stuff happens on a stupendously colossal scale.  And Bill Nye the Science Guy wants Rutgers graduates to worry about a 0.4ºC warming over thirty years? Feugh.

The Science Guy then passed on from the dubiously alarmist to the batshit barmy.

There really is no such thing as race. We are one species … We all come from Africa.

Where does one start with that? Perhaps by asserting that: “There is no such thing as states. We are one country.”

The climatological equivalent of saying there is no such thing as race would be saying that there is no such thing as weather. Of course there is such a thing as race. We can perceive race with at least three of our five senses, and read it off from the genome. We tick boxes for it on government forms: I ticked such a box for the ATF just this morning when buying a gun.

This is the Science Guy? The foundational text of modern biology bears the title On the Origin of Species by Means of Natural Selection, or the Preservation of Favored Races in the Struggle for Life. Is biology not a science?

Darwin said that populations of a species long separated from each other will diverge in their biological characteristics, forming races. If the separation goes on long enough, any surviving races will diverge all the way to separate species. Was Ol’ Chuck wrong about that, Mr. Science Guy?

“We are one species”? Rottweilers and toy poodles are races within one species, a species much newer than ours; yet they differ mightily, not only in appearance but also—gasp!—in behavior, intelligence, and personality. [“Nye Lied, I Sighed,” Taki’s Magazine, May 21, 2015]

This has gone on long enough. Instead of quoting myself, I merely refer you to several related posts:

Demystifying Science
AGW: The Death Knell
Evolution and Race
The Limits of Science (II)
The Pretence of Knowledge
“The Science Is Settled”
The Limits of Science, Illustrated by Scientists
Rationalism, Empiricism, and Scientific Knowledge
AGW in Austin?