Scott Haufman has written a post on the variation in IQ over a person’s life. He writes:

In 1932, the entire population of Scottish 11-year-olds (87, 498 children) took an IQ test. Over 60 years later, psychologists Ian Deary and Lawrence Whalley tracked down about 500 of them and gave them the same test to take again.

Turns out, the correlation was strikingly high — .66, to be exact. Those who were at the top of the pack at age 11 also tended to be at the top of the pack at age 80, and those who were at the bottom also tended to stay at the bottom. Equally as interesting, the correlation was far from perfect. A few outliers could be found. One person had an IQ of over 100 at age 11, but scored just over 60 at age 80. There are many possible reasons for this outlier, including dementia. Other folks showed IQ increases as they aged. On average, people’s individual (or absolute) scores on the test taken again at age 80 was much higher (over one standard deviation) than their scores had been at age 11, even though the rank ordering among people stayed roughly the same.

These results are illustrative of what psychologists find over and over again. IQ tends to remain relatively stable over the lifespan. The key word here is relative. IQ researchers are interested in explaining differences. Developmentally speaking, an individual’s intelligence is not fixed at birth. Although rank ordering of scores tends to remain stable (relative change), scores within individuals fluctuate quite a bit (absolute change).

In his analysis, Haufman rightly points out that this is further evidence that IQ is not fixed. However, he hasn’t noted one element of the change in IQ – the heritability of IQ increases through childhood and adolescence. The idiosyncratic environmental influences wash out. Some of the variation is movement reflecting some fixed underlying factors.

If the experiment reported changes in IQ between the ages of 20 and 80, I expect the variation would be smaller.

Over at Wired, Jonah Lehrer has written a post in which he looks at a couple of lines of evidence about the innate response of humans to inequality. The first line, based on brain scans, is nicely discussed by Jeff at Cheap Talk.

The second involves an experiment with capuchin monkeys:

A similar lesson emerges from a classic experiment conducted by Franz de Waals and Sarah Brosnan. The primatologists trained brown capuchin monkeys to give them pebbles in exchange for cucumbers. Almost overnight, a capuchin economy developed, with hungry monkeys harvesting small stones. But the marketplace was disrupted when the scientists got mischievous: instead of giving every monkey a cucumber in exchange for pebbles, they started giving some monkeys a tasty grape instead. (Monkeys prefer grapes to cucumbers.) After witnessing this injustice, the monkeys earning cucumbers went on strike. Some started throwing their cucumbers at the scientists; the vast majority just stopped collecting pebbles. The capuchin economy ground to a halt. The monkeys were willing to forfeit cheap food simply to register their anger at the arbitrary pay scale.

This labor unrest among monkeys illuminates our innate sense of fairness. It’s not that the primates demanded equality — some capuchins collected many more pebbles than others, and that never created a problem — it’s that they couldn’t stand when the inequality was a result of injustice.

While this experiment shows that problems emerge following arbitrary outcomes, I would not describe the reaction as demonstrating an “innate sense of fairness”. The revolt was one-sided, and the monkeys who received grapes were not handing them back. It is more like an innate dislike of being on the bottom.

More importantly, I am not convinced that the experiment fully tested whether fair outcomes could generate unrest. As the stone gathering ability of monkeys is not likely to vary much, particularly when compared to the variation in human ability across different professions, the variation in opportunity for the monkeys was negligible. The variation in outcomes was also relatively small.

As a result, if a monkey was hungry, it is an easy task to get some stones. However, if a human needs money, the range of possibly courses of action are large, with the returns widely variable. A cleaner and a brain surgeon earn significantly different rates of return for an hour of effort.

What if the monkeys were paid on the basis that whoever collects the most stones gets the vast majority of the cucumbers or grapes? Or what if effort started to pay compound dividends, meaning that long-term focussed stone gathering delivered much higher returns. The rules might be clear and the victory fair, but I am not sure that the reaction to the significantly different outcomes would be benign.

Lehrer uses this experiment to draw the following conclusion:

When the rich do something to deserve their riches, nobody complains; that’s just the meritocracy at work. But when those at the bottom don’t understand the unequal distribution of wealth — when it seems as if the winners are getting rewarded for no reason — they get furious. They doubt the integrity of the system and become more sensitive to perceived inequities. They start camping out in parks. They reject the very premise of the game.

Even if the belief that nobody complains when the rich deserve their riches was true, do the majority of people understand the basis of the distribution of wealth in today’s economy? Has the economy reached a level of complexity that will always generate a certain level of distrust by those at the bottom?

I have been trying to find an electronic version of Thomas Malthus’s second edition of his An Essay on the Principle of Population. The second edition is significantly expanded and revised from the first, while later editions through to the sixth in 1826 are essentially minor revisions of the second (the sixth part one and part two are here). While I have, to now, been unable to find the text of the second edition, the Wikipedia page for the book notes an interesting paragraph that was included in the second edition, but was omitted from later editions:

A man who is born into a world already possessed, if he cannot get subsistence from his parents on whom he has a just demand, and if the society do not want his labour, has no claim of right to the smallest portion of food, and, in fact, has no business to be where he is. At nature’s mighty feast there is no vacant cover for him. She tells him to be gone, and will quickly execute her own orders, if he does not work upon the compassion of some of her guests. If these guests get up and make room for him, other intruders immediately appear demanding the same favour. The report of a provision for all that come, fills the hall with numerous claimants. The order and harmony of the feast is disturbed, the plenty that before reigned is changed into scarcity; and the happiness of the guests is destroyed by the spectacle of misery and dependence in every part of the hall, and by the clamorous importunity of those, who are justly enraged at not finding the provision which they had been taught to expect. The guests learn too late their error, in counter-acting those strict orders to all intruders, issued by the great mistress of the feast, who, wishing that all guests should have plenty, and knowing she could not provide for unlimited numbers, humanely refused to admit fresh comers when her table was already full.

Garrett Hardin, who I have posted about previously, wrote an essay which blames the general rejection of Malthus’s writings on this single paragraph:

The shocking Feast was spread before the public in 1803, in the second edition of the Essay. Malthus could hardly have chosen a worse time a sort of “compassion revolution” was then well under way. During the 19th century the English-speaking world made great progress in the humane treatment of animals, in getting rid of slavery, in curtailing child labor, and in (reluctantly) giving a modicum of freedom to women. Bonar has said that ‘for thirty years it rained refutations of Malthus.’ Before Malthus died in 1834, four more editions of the Essay had been published, the last in 1826; but in none of them did the Feast appear for a second time.

The remainder of Hardin’s essay is typical of many of his later writings on population, but one other passage in particular caught my eye:

Conscience, like other individual characteristics, varies. One woman may be satisfied with one child, while another craves four. Intended or not, with no community control of reproduction, a competition in breeding will develop. In all other species of animals there is a genetic component to fertility; but anyone who suggests that genes also influence fertility in the human animal kindles the ire of genophobes – individuals who are intellectually repelled by the idea of genetic differences in humans. Fortunately, in the dispute over population control, it is not necessary to raise the genetic issue. It is enough to assume that there may be a sort of cultural heredity – that the advice and examples set by parents have some influence on the behavior of their children. (Understandably, of course, parents usually crave more than merely ‘some’.) With either genetic heredity or cultural heredity, a variant of Gresham’s Law is set in play since high fertility tends to diminish the monetary wealth of a family, then (focusing only on economics) we must say that, over time, with uninhibited fertility, low living standards drive out high.

And if anyone knows where to find an electronic version of the second edition of An Essay on the Principle of Population, please let me know.

While IQ research seems to be be emerging from its taboo phase, Anneli Rufus has written an article in Alternet which asks why the study of human intelligence was off the agenda for so long.

The analysis points to the usual suspects – the shadow of eugenics and racial research – but the article does have a couple of interesting quotes from Stephen Murdoch and Dennis Garlick. First, in much of the literature on IQ, the focus is on finding ‘g’, a single measure of general intelligence. Murdoch is agnostic as to whether ‘g’ exists:

“The science underlying IQ tests isn’t like experiments in the life or hard sciences,” Murdoch insists. “IQ proponents believe in something they call general intelligence. That is, they believe there is one singular, measurable, inheritable kind of intelligence that we can all be ranked on. I have no idea if this is correct or not. Nor do I care.”

While many of the debates about how well IQ captures ‘g’, if it exists, don’t seem to bear much fruit, IQ is clearly an important variable and has significant predictive power. I find it hard to be agnostic about a measure with such important life implications. And alternatives to ‘g’ do not seem to have more promise:

“There is still little evidence to support many of the claims made by proponents of alternative intelligences,” Garlick says, “yet it is advocated that life-changing decisions should be made based upon them. One is tempted to say that the alternative intelligence industry is a reminder that snake-oil salesmen are alive and well in this day and age.”

Garlick points to the need for IQ research:

“”I find it ironical that so much research is devoted to disorders like autism that only affect less than 1 percent of the population, but little research is devoted to understanding differences in IQ. … If the deficits of autism can be improved through research, why not IQ?”

As low IQ can have such significant costs, IQ research is an important basis for any policy discussion. Even if differences in IQ are intractable (which to an extent they certainly are), we can’t be any worse off for that knowledge.

From the Journal of Personality and Social Psychology:

Much research shows that people are loss averse, meaning that they weigh losses more heavily than gains. Drawing on an evolutionary perspective, we propose that although loss aversion might have been adaptive for solving challenges in the domain of self-protection, this may not be true for men in the domain of mating. Three experiments examine how loss aversion is influenced by mating and self-protection motives. Findings reveal that mating motives selectively erased loss aversion in men. In contrast, self-protective motives led both men and women to become more loss averse. Overall, loss aversion appears to be sensitive to evolutionarily important motives, suggesting that it may be a domain-specific bias operating according to an adaptive logic of recurring threats and opportunities in different evolutionary domains.

Unfortunately, I cannot access the article beyond the abstract, but one of the article’s authors, Douglas Kenrick, has blogged about the paper at Psychology Today (HT: Åse). Kenrick writes:

[R]esearch by several members of our team shows that loss aversion waxes and wanes in flexible ways, depending of whether or not the person is experiencing different fundamental motivational states (such as self-protection or mating motivation). Research participants were asked how happy or unhappy it would make them to gain or lose $100, for example, or to experience a 30-percentile boost in their financial assets. As in the previous research, losses typically loomed slightly larger than gains. But all that changed for participants who answered the questions in a mating frame of mind (after imagining themselves having a romantic encounter with someone they found highly attractive). …

According to Jessica Li, who was the first author of the study: “For men in a mating frame of mind, loss aversion completely disappeared, so that they became more focused on wins than losses. For women, on the other hand, mating motivation led them to be even more loss averse.”

In another evolutionary scenario, where losses were clearly more costly than gains, participants become even more loss averse.

When we put participants in a self-protective frame of mind (by having them imagine being alone in the house on a dark night and hearing an intruder breaking in), both men and women became more loss averse in their judgments.

The way I prefer to think about loss aversion is to consider what the objective of the person is – and that is normally an evolutionary objective. Once the gains and losses are framed in evolutionary terms, what is loss aversion in one dimension is not loss aversion in the dimension that matters. For example, if a small cash win will not increase the number of mates but a small cash loss might cost them the mate that they have, a loss averse response to the potential cash pay-offs can be contrasted to the zero-gain potential in the mating dimension. It is not loss aversion to reject a bet with no upside.

Frances Wooley writes:

Economists’ policy recommendations – our ideas about which policies enhance economic efficiency and which ones detract from efficiency – are all based on the idea that individuals know what’s best for themselves. …

But if people’s demands are just a product of framing, salience, and the public prominence of hurty-elbow syndrome, how can we use them to infer the marginal benefits to consumers of consuming health care? How can we make statements like ‘the marginal benefits of health care are less than the marginal costs’? …

If people’s choices are not a reliable guide to their well-being, you have to turn to something else. Ask people how happy they are and measure well-being in terms of happiness. Evaluate health care spending by looking at objective measures of health, such as mortality, morbidity, or survival rates. Chuck out the entire elegant theoretical framework of welfare economics.

That idea has me, for one, reaching for the blue pill – after all, people aren’t stupid, so standard economic analysis isn’t a bad approximation of the real world, is it?

But I can’t find one. I can’t get all of that behavioural stuff outside of my head.

I want a purple pill – a merging of the red and the blue – that would allow me to merge behavioural insights into a coherent model of economic behaviour.

(Evolutionary economics – and other research programs that explain why humans behave the way they do – might have some promise as a purple pill).

Behavioural economics is going to continue to be attacked as a discipline until more of the results are placed in a conceptual framework. One of my favourite wikipedia pages is the list of cognitive biases – yet the nature of this list hints at the underlying failure to develop the framework in which they fit.

HT: Arnold Kling

From an interview of Steven Pinker on the Freakonomics blog:

There are many statistical predictors of violence that we choose not to use in our decision-making for moral and political reasons, because the ideal of fairness trumps the ideal of cost-effectiveness. A rational decision-maker using Bayes’ theorem would say, for example, that one should convict a black defendant with less evidence than one needs with a white defendant, because these days the base rates for violence among blacks is higher. Thankfully, this rational policy would be seen as a moral abomination. I suspect that the same sentiments would prevent any policy from pre-judging a child based on the behavior of his parents, whether one thinks the connection is due to genes or to parenting.

A review of the arguments against immigration would suggest that many people have no qualms using a similar Bayesian argument in shaping their immigration policy preferences.

Also from the same interview, which focuses on Pinker’s recently released book The Better Angels of Our Nature: Why Violence Has Declined:

Yes, I present extensive statistics showing the non-state peoples (hunter-gatherers, hunter-horticulturalists, pastoralists, and others living outside the control of states) have far higher rates of violence than modern states, even at their worst. I think this very long prehistory of life under anarchy probably selected for motives that can continue to lead to violence today, particularly dominance and revenge, both of which are adaptive in a state of anarchy but not in societies with well-functioning systems for nonviolent dispute resolution. This does not mean that we harbor a thirst for blood which must periodically be discharged—even the most bellicose societies modulate their violence, and can live for decades in peace. Evolution gave us motives that impel us to violence, such as greed, dominance, revenge, and the urge to mete out moralistic punishment, but it also gave us motives that undermine or control the violent inclinations, such as self-control, empathy, and reason—the better angels of our nature.

Flipping through Ronald Fisher’s The Genetical Theory of Natural Selection this morning, I was reminded of this quite stunning factoid from the 1912 Australian Census:

The extraordinary variation in fertility in  Man has been noticed in a somewhat different manner by Dr. D. Heron, using material provided by the deaths (30,285 males and 21,892 females) recorded in the Commonwealth of Australia for 1912. Heron finds that half of the total number of children come from families of 8 or more, which are supplied by only one-ninth of the men or one-seventh of the women of the previous generation. It would be an overstatement to suggest that the whole of this differential reproduction is selective; a substantial portion of it is certainly due to chance, but on no theory does it seem possible to deny that an equally substantial portion is due to a genuine differential fertility, natural or artificial, among the various types which compose the human population.

As Fisher suggests, some of this variation must be due to luck, but how different might a population with this level of variation in reproductive success look several generations later?

First, from Rob Brooks:

Lead author Moshe Hoffman and his collaborators compared two tribes living in north-east India. …

Karbi women may not own land, and property is passed from father to the oldest surviving son.

But the Khasi ban men from owning land, and men are expected to hand their earnings over to their wives. The youngest daughter in a Khasi family traditionally inherits the land from her mother. …

They gave villagers a very simple four-piece puzzle and timed how quickly each person solved it.

It turns out that, in the patrilineal Karbi, men took an average of 42 seconds but women took around 57 seconds to solve the puzzle. But Khasi girls and boys did not differ significantly (35 and 32 seconds respectively) from one another. …

Such a simple experiment shows a persistent and common sex difference can entirely disappear in a culture where girls and their education are considered every bit as valuable as boys and theirs.

Meanwhile, Robert Kurzban notes that some sex differences are more robust when he takes on a new paper on six potential sex differences:

They discuss six areas of potential differences, and even though it’s a bit like starting the meal with dessert, I can’t resist opening with the second of the questions that they pose (p. 297). After discussing the issue of whether men or women want to have more sexual partners, they ask:

But what about when actual number of sexual partners are assessed? Are men actually having sex with large numbers of women whereas women are more selective?

Now, because of the way that averages work – and the fact that sex is a two player game –  it just has to be true that, on average, men and women are having sex with the same number of partners. So, this is a silly question to ask, like, How many times have you committed suicide? or, Is anyone at Current Directions editing manuscripts?

Kurzban concludes:

Anyway, of the six differences they discuss, the authors conclude that four of them are genuine (though they add “but’s” and offer some (proximate) explanations for the differences). In one of the remaining two, they find that women and men have the same number of actual partners, on average, a fact that had to be true. Finally, they conclude that women and men have the same preferences “in real world contexts,” based on a narrow set of data in the “real world context” of speed dating events set up by academics for college students.

I recommend subscribing to Kurzban’s feed.

There have been a few reviews of Robert Frank’s The Darwin Economy: Liberty, Competition, and the Common Good recently (my own included), but John Whitfield’s in Slate is one of the more interesting.

First, Whitfield picks on Frank’s choice of evolutionary metaphor:

As a biological analogy, Frank suggests the difference between running speed and antler size. A faster gazelle is better equipped to outrun a cheetah, and so, he writes, “being faster conferred advantages for both the individual and the species.” Antlers, on the other hand, are used for fighting with other males. The pressure to have bigger ones than your rivals leads to an arms race that consumes resources that could have been used more efficiently for other things, such as fighting off disease. As a result, every male ends up with a cumbersome and expensive pair of antlers, says Frank, and “life is more miserable for bull elk as a group.”

… But evolutionarily speaking, the distinction is bogus.

Natural selection sees no difference between running speed and antler size: All evolution is positional. When one gazelle got faster, the slower ones got eaten (a point Frank relegates to a footnote). And when gazelles got fast, so did cheetahs. Cheetahs and gazelles would all be better off if they’d stayed slow, because running fast uses energy you might “better” invest in offspring, and legs that are built for speed are more prone to fracture. The lissome cheetah, meanwhile, is bullied and often killed by bigger carnivores such as lions.

Whitfield’s argument picks up on a broader point in evolution. When a new gene spreads through a species, it is not really for the good of the species. All of the members of the species without that gene die out. The “species” that now has this gene is solely composed of descendants of the lucky individual that had the gene. A fitness enhancing mutation is a highly positional good.

The second thread of Whitfield’s review is that Robert Frank is running a group-selectionist argument. I don’t see the group selection analogy, but Whitfield does have a more pertinent point:

From Frank’s book, you might conclude that what stands in the way of his reforms is not differing interests, but irrationality—an imperfect understanding of how competition works. … But what evolutionary biology teaches us is that it’s not enough to assume, as Frank does, that everyone just wants to create the biggest economic pie. That’s like saying a gazelle cares more about the average speed of its herd than whether it can outrun a hungry cheetah.

In fact, those leading and funding opposition to progressive taxation are rational enough—they’re the one who do best if society becomes an arms race won by those with the biggest antlers and the priciest suitcases, with the lions getting anyone who can’t keep up. What those opposing them need to show is not just how the common good can be maximized, but how it can be reconciled with the self-interest of enough people to vote it into being.

On one hand, this misrepresents Frank’s case, as he does try to show that self-interest and group-interest can be aligned. But it is fair to ask why some people fight proposals such as Frank’s. As Frank states through his book, his arguments don’t need irrationality at the micro-level, but the fact they are not accepted implies that either some people are irrational in their understanding of policy, or that there is another piece to the puzzle.

One possible reconciliation is that Frank’s ideas come as a package which have only a few attractive elements. Frank’s argument is not simply that we should constrain positional competition, but he also wants more funding for government and to give it a greater role in some areas.

But the deeper side to the opposition is that some people benefit from positional competition. In an evolutionary scenario, while the rank matters, the size of the win also matters. For example, if  one person has vastly more resources than another and there is an environmental shock, the difference in probability of survival is likely to be significant. However, if someone has only marginally more resources than the other, the difference in probability of survival may be small, and luck may result in the lower ranked individual coming out on top.