A week of links

  1. Were the Victorian’s cleverer than us? Patrick Rabbit pulls it apart.
  2. Kevin Mitchell has a shot at the new eugenics. Razib responds. Read the comments on both.
  3. Peter Singer critiques conspicuous consumption. The example is similar to one Robert Frank uses in Luxury Fever, but I still like it.
  4. Gender identity and relative income within households (pdf). I haven’t read it yet, but some interesting results.
  5. Maybe I’d have more time to read if I cut out the distractions. Avoid news (HT Ryan Murphy). Actually, I’ve almost completely cut news from my diet, but blogs and the twitterverse are still very distracting.
  6. Do markets erode moral values? I’ll post about the paper when I’ve digested it some more, but I don’t think it’s the “market” eroding the morals.

IQ is an artificial construct

For lack of time to write a post laying out my complete thoughts on Jason Richwine’s thesis on IQ and immigration (it’s the sort of topic where if you want to engage, you need to engage fully) and doubt whether I have anything new to add, I’ve been waiting for a media piece that would allow me to say “that’s roughly my position”. So far, one hasn’t appeared, but perhaps the closest article is this post by Andrew Sullivan of The Dish.

I agree with Sullivan that red flags should go up around intellectual freedom. We should treat the Heritage report as “agitprop” but distinguish it from Richwine’s thesis. And to ignore any empirics, “even if it is true”, will only push discussions of these topics to the fringes where people can rightfully claim that evidence is being ignored. After all, there was a reason Richwine was writing for “white supremacist magazines” – he’s probably not going to get published in many other forums.

There’s a few things I’d change with Sullivan’s piece. I’d weaken the skepticism about whether racial categories can be made of the “DNA salad”, the basis of IQ and whether ‘g’ means anything. And I certainly would have not used the beagle/poodle analogy. There’s massive opportunity to be misinterpreted there (actually, it’s already happening).

But there is one point in Sullivan’s piece that I found particularly interesting. Sullivan writes:

I believe IQ is an artificial construct created to predict how well a random person is likely to do in an advanced post-industrial society. And that’s all it is. It certainly shouldn’t be conflated with some Platonic idea of “intelligence.”

I don’t consider IQ to be a social construct. However, let’s suppose that Sullivan’s statement is true. The interesting thing is that under that definition, IQ remains a big deal. We’ve passed a point where more than half of the world’s population is living in post-industrial societies. Those numbers are increasing every day. And success in those societies affects poverty, inequality and the success of those societies themselves. This would be a construct worth measuring.

Further, even if IQ were just a construct of this nature, Richwine’s argument would probably not change. After all, Richwine’s argument (whatever its merits) is not about creating a highly intelligent race. It is about creating a successful post-industrial society. IQ as a social construct is still of use.

The IQ barrier

There has been plenty of noise about the Heritage Foundation’s report on immigration reform, with most of that noise centered around the PhD thesis of one of the report’s co-authors, Jason Richwine (part 1 and part 2). In his thesis, Richwine proposed an IQ filter on immigration (dressed up as a skills test) to avoid the potential social and economic consequences of admitting immigrants with persistently low IQ.

The debate (or to be more accurate, the lack thereof) triggered a couple of tangential thoughts. The first is that existing immigration policy in many developed countries already has an IQ filter. Australia and Canada’s skilled immigration systems are often pointed to as being among the most successful; so successful in fact that they are the two OECD countries where second generation immigrants outperform students with native parents in the PISA tests -  see here, here and here. A large part of improvements in Swiss PISA test scores was attributed to immigration changes in the 1990s.

The immigration reforms that triggered the Heritage Foundation’s report also contain a skills-based component, including a points systems like that used in Australia and Canada. The United States is effectively implementing some of Richwine’s recommendations. (Since I first drafted this post, I see that Ed Realist has pointed out how some of Richwine’s ideas were doing just fine until the storm around the Heritage report.)

Another thought is that IQ-barriers are pervasive within countries. Tests for entry into college or university (such as the SAT) are highly correlated with IQ scores. IQ test results predict success in universities and awarding of scholarships. Many jobs have IQ-testing as part of the application process, particularly in police and fire departments (which often makes them the subject of litigation about exclusion of minorities). Intelligence is also a filter for who we are friends with and who we marry. Being of low intelligence has significant costs.

We can have a high level of confidence that the difference in IQ scores within developed countries has a genetic component. Estimates of the heritability of IQ from twin and adoption studies are robust. This means that within many countries we already actively exercise discrimination based on genetic factors, on both an institutional and personal level.

A week of links

Links this week:

  1. Marshall Sahlins says goodbye to the NAS.
  2. A review of Jared Diamond’s The World Until Yesterday that is well worth reading (HT for these first two links: Andrew Badenoch)
  3. There’s been bit of a storm over the last few days over a report by the Heritage Foundation on the cost of unlawful immigrants to the taxpayer. It’s co-authored by Jason Richwine – author of this book on IQ and immigration policy – and has been commented on by the likes of Reiham Salam and Dylan Matthews.
  4. Dan Dennet and memes.

Cluelessness

Some of the reviews of Michael Chwe’s Jane Austen, Game Theorist suggest that it is worth a read (such as Diane Coyle ). One idea in the book that I like the sound of is “cluelessness”.

From Jennifer Schuessler in the NYT:

Most game theory, he noted, treats players as equally “rational” parties sitting across a chessboard. But many situations, Mr. Chwe points out, involve parties with unequal levels of strategic thinking. Sometimes a party may simply lack ability. But sometimes a powerful party faced with a weaker one may not realize it even needs to think strategically.

Applications of game theory to the real world often neglect the limited ability of the players. And this is not simply a case of bounded rationality or biases of the types identified in behavioural economics. It includes straight miscalculation. Some problems are hard and even those that are easy are often messed up. The reviews also hint at another important feature of cluelessness – that not all people are equal and we can expect more clueless behaviour from some people than others.

I am a fan of the analysis of crime, cooperation, war, sports and so on from the perspective of cold rationality (an evolutionary-derived rationality of course). But acknowledging the cluelessness of the players can provide a simple explanation for a lot of apparently mysterious behaviour.

Impatience and aggregate risk

Imagine two populations of asexually reproducing people (asexual reproduction is where each child comes from a single parent, not a couple). In the first population, each person has a 50 per cent chance of having no children, and a 50 per cent chance of having two children. If there is no relationship between the outcomes for each person (i.e. they face idiosyncratic risk) and the population is large, we would expect the population to remain relatively constant over time.

In the second population, each person also has a 50 per cent chance of having no children, and a 50 per cent chance of having two children. However, in this case, the population faces an aggregate risk so every person in the population has the same outcome – either zero or two children. At any time in the future, the expected population (the mean of all possibilities) is constant, just like the first. However, most outcomes lead to the extinction of the population, and as time goes on, this will almost surely occur. The only reason the mean outcome is constant is the small probability of a very large population (doubling every generation).

This difference between aggregate and idiosyncratic risk was used by Arthur Robson and Larry Samuelson (ungated version here)  to partly explain the problem that the rate of time preference (also called the discount rate, or level of patience) estimated in many theoretical evolutionary papers is lower than we see – often around a couple of per cent per year compared to empirical findings that people discount the future at rates of 10 per cent per year or higher. People are far more impatient than many theoretical models predict.

Theoretical evolutionary estimates of the rate of time preference are typically tied to the rate of population growth and the chance of death, as was the case in work by Ronald Fisher, Ingemar Hansson and Charles Stuart and Alan Rogers. If population is growing, investments in the future are worth less. More obviously, death before reproduction erases all future benefit, so a higher probability of death should lead you to discount the future more. But with long-term population growth through our evolutionary history being near flat and death rates each year a couple of per cent at most, theoretical calculations often come out at around two per cent per year.

To resolve this problem, Robson and Samuelson argue that idiosyncratic and aggregate risk affects the optimal discount rates. In a population with idiosyncratic risk, the rate of time preference should approximate the population growth rate and the death rate. But in a population with aggregate risk, the expected population growth rate is not what we should look at.

To see why, look at the example of aggregate risk at the beginning of this post. Although the expected population is constant, the reality is that the population will either double every year, or it will plunge to zero. If it plunges to zero and everyone is wiped out, the rate of time preference does not matter. But what if the aggregate risk did not strike. The population would double every year. As a result, people should discount for the one scenario that matters – the annual doubling – and have a higher discount rate than they would have in the idiosyncratic risk scenario.

This argument holds with less extreme examples. In another (excellent) paper (ungated version here) in which Robson and Samuelson survey the literature on the evolution of preferences, they work through an example similar to the one above, but where people have one or two children. Again, the population with the aggregate risk would be expected to have a higher rate of time preference.

Putting this theory into context, human populations through our evolutionary history would have faced a lot of aggregate risk, such as change in climate, drought and crop failures. So although population growth is near zero, their rate of time preference would be higher.

One way to think about it is to picture population growth as occurring in a saw-tooth manner – increases and then sudden drops. The population growth rate during those periods of increase is more relevant for the rate of time preference than the fact that the sudden drops through droughts and disasters reduce long-term population growth to near zero. The rate of population growth during the good times is what matters.

Ultimately, this paper is one of my favourite in economics. It has a great idea that is not immediately obvious (nor intuitive), but once you wrap your mind around it, it makes a lot of sense.

A week of links

Links this week:

    1. Gender language and economic power – another economic paper with a spurious correlation?
    2. Culture and economic development.
    3. We haven’t yet reached our satiation point. A summary.
    4. It’s been a few weeks since the last, but here’s another Chagnon versus the anthropologists article.
    5. How many priming studies are safe to cite?

Selection during pregnancy

Carl Zimmer writes about a new paper in Trends in Genetics where the authors argue that natural selection during pregnancy is an important driver of recent evolutionary changes:

Women nourish their fetuses by raising the level of sugar in their blood. That’s a dangerous game, because it threatens to throw off their own delicate balance between sugar and insulin. If that balance gets out of whack, women may suffer gestational diabetes. The Harvard researchers suggest that the shift to high-carb agriculture in Europe led to more women dying of gestational diabetes. Women with mutations that lowered their blood sugar level during pregnancy were favored by natural selection. And today, European women enjoy the benefits of that suffering: a low risk of gestational diabetes.

A woman in Bangladesh has a very different history behind her. Her ancestors ate fish, unprocessed rice, and other foods with modest levels of carbohydrates. In that environment, women with mutations that increased their blood sugar during pregnancy might have had healthier children than women without them.  Throw those genes into a modern Western city, and trouble looms. Women with low-sugar genes are now drinking soda and eating bread, ice cream, and lots of other food loaded in carbs. They don’t have the evolved defenses to keep them from developing gestational diabetes.

From New York birth data, Women of European descent have less than a 4 per cent chance of developing gestational diabetes during pregnancy, compared to around 20 per cent for Bangladeshi women.

The paper also points to recent evolution relating to production of vitamin D, altitude and malaria.

Hwang and Horowitt’s The Rainforest

A couple of months ago I linked to a piece by Ronald Coase about the state of economics. Coase wrote:

Economics as currently presented in textbooks and taught in the classroom does not have much to do with business management, and still less with entrepreneurship. The degree to which economics is isolated from the ordinary business of life is extraordinary and unfortunate.

As readers of this blog would know, most of what I read and write is relatively isolated from ordinary business life. But reading a book such as Victor Hwang and Greg Horowitt’s The Rainforest: The Secret to Building the Next Silicon Valley shows that the topic of this blog can be relevant to the business world.

The world dealt with in The Rainforest is innovation ecosystems of the type that we see in Silicon Valley. Why is Silicon Valley such an innovative place, and why do most attempts to create new Silicon Valleys around the world usually end in failure?

To answer this, Hwang and Horowitt turn to a biological metaphor – the rainforest. In a “rainforest”, innovators are able to tinker and engage in trial and error to discover the most efficient ways of combining capital, talent and ideas. This provides for an evolutionary – not engineered – process, where new innovations can emerge.

Hwang and Horowitt argue that to understand a rainforest, we need to understand something of biology, psychology, neuroscience and sociology. Some of the background materials that I had read on the book, such as Victor Hwang’s blog at Forbes, pointed to E.O. Wilson’s recent forays into group selection. However, when you get into the book, it’s ideas from the Wilson of pre-2005 that dominate. And although not explicitly named, the fingerprints of the likes of Robert Trivers are also present.

Hwang and Horowitt described many elements of a successful rainforest, but the one that stood out for me was trust. When trust is high, transaction costs are low (Coase also plays a fairly prominent role) and people can easily enter into new engagements. Lawyers are not required to draft terms and the entrepreneur is willing to share their ideas without fear of them being stolen.

So why does this trust exist? In part, it is because there is a strong normative culture with punishment against defectors. Take a transaction between an entrepreneur and a venture capitalist. In a single transaction, there might be opportunity for the venture capitalist to take as much of a stake in the company as they can. However, with strong norms about what a fair agreement looks like and a willingness to punish those who push for unfair terms, that venture capitalist’s reputation will spread quickly and their one-off gain turns into a long-term loss. Trust is also supported by a strong culture of reciprocation (hence my reference to Trivers above).

While Wilson’s group selection gets mentioned, the rationale given by Hwang and Horowitt for the forming of cooperative groups is generally rooted in the strong individual advantages. They relate the example of people moving to the Western frontier in the early days of settlement in the United States. Despite a reputation as a period of rugged individualism, almost no-one embarked on the journey alone. The personal benefits to cooperation were vital. In the same way, to succeed in an innovative ecosystem, a person needs to be be connected to a broad variety of people. One of the primary ways of measuring the health of the rainforest is to look at those connections and the flows that occur along them.

The question that these types of explanations naturally draw out is how this culture exists in the first place. As Hwang and Horowitt point out, while people are naturally groupish, we distrust people dissimilar from ourselves and will generally act in our self interest. Places like Silicon Valley are particularly diverse, so we might expect them to be relatively atomised.

One reason is what they call extra-rational motivations. People are not purely self-interested in a money sense, but also seek adventure, interest, membership of groups and the like. Embarking on a start-up venture has pay-offs beyond the financial. They pick on neoclassical economists for ignoring these motivations, but I think this is more a case of ignorance in the models than ignorance that they exist. These motivations mean that people are willing to cooperate and enter into new ventures for the non-monetary benefits that they receive.

A second answer that they hint at is the self selection of the people in places such as Silicon Valley. I suspect this is where much of the answer lies, because apart from their wish to be entrepreneurs, one of the selected characteristics are high levels of intelligence, which is in turn correlated with trust (both trusting and trustworthiness). In a community where most people are trusting and trustworthy, and people are willing to punish the occasional defectors (even if that is by simply never dealing with them again), cooperation can be expected to be highly beneficial and will flourish. Hwang and Horowitt return to the self-selection issue at the end of the book when they suggest that the people now moving to Silicon Valley have different characteristics to those who create the innovative culture. They suggest that new arrivals who are more interested in employment than entrepreneurship may change the culture. I also wonder in what other characteristics they differ?

Hwang and Horowitt are regularly engaged to support the establishment of innovative ecosystems in various countries and parts of the world. An interesting experiment would be to run experimental games such as the prisoner’s dilemma and public goods game with the groups whom the authors work and see what the results are. Are the results of these games predictive of whether a vibrant innovative ecosystem will be established? Does the level of cooperation in these games increase in successful environments?

There are plenty of other interesting ideas in the book, although I’m still to be convinced about the degree of control we can have when trying to create these types of innovative ecosystems. I probably need to see it to believe it. Still, it is nice to see ideas that I often talk about abstractly, such as  reciprocation, altruism and trust, being used in some practical analysis.

A week of links

Links this week:

  1. Hodgson and Knudsen have set up a reading group for their book Darwin’s Conjecture: The Search for General Principles of Social and Economic Evolution. Chapter one has already kicked off.
  2. Another from The Umlaut – Conspicuous Frugality.
  3. Flip-flopping selection pressure in a modern population.
  4. Following from my post on Douglas Kenrick and colleagues’ theory of Deep Rationality, below are a couple of short videos – one on How Mating and Self-Protection Motives Alter Loss Aversion, and the other on the upcoming book The Rational Animal: How Evolution Made Us Smarter Than We Think by Kenrick and Vlad Griskevicius, which also looks like it covers similar territory.

 

Altruists and the knowledge problem

I have posted before about Gary Becker’s argument that the evolution of altruism can be explained by a version of his rotten kid theorem. In short, if an altruist cares about other people’s welfare in addition to their own and is willing to transfer their resources to others, an egoist’s action to harm the altruist may also harm the egoist as the amount that the altruist would be willing to transfer to the egoist will be reduced. As a result, the egoist will refrain from hurting the altruist, making the altruist better off than if they were an egoist.

As I raised in my post, Becker’s argument can run into corner solutions, whereby the scale of the gain to the egoist and damage to the altruist are such that the egoist is willing to harm the altruist. However, I only recently realised that the year after publication of Becker’s article, the Journal of Economic Literature published responses to Becker’s paper by Jack Hirshleifer and Gordon Tullock, along with a reply by Becker.

Hirshleifer’s critique focuses on the order in which the altruist and egoist’s actions occur. If the egoist has the last word, they will likely take advantage of the altruist at the end, meaning that the altruist should not be as altruistic to begin with. In the case of altruism between a parent and child, the child will normally have the last word due to differences in ages. Tools such as a legal system that allows the making of wills are required for the altruist to have the last word.

Hirshleifer then goes on to show that Becker’s analysis is powerful where the altruist can keep the last word, and an altruist may be selfishly better off than if they were planning an egoistic action. Their altruism restrains the behaviour of the egoist.

In reply, Becker called Hirshleifer’s comments perceptive, with the note that his scenario can only work among a small number of relatives or neighbours (so Becker had already dealt with part of my criticism).

After quibbling with the definition of altruism, Tullock’s criticism focuses on an altruist’s ability to know the preference ordering of the recipient of the altruism. Tullock suggests judgments of this type are almost impossible. The history of charitable administration and its attempts to prevent recipients from taking advantage of gifts suggests a knowledge problem.

Tullock argues that in this case, the egoist can abuse the situation. For example, they could stop working, which reduces their income considerably but their utility only slightly as they no longer have to work. If the altruist only looks at the slacker’s loss of income, the altruist may effectively overcompensate the egoist.

Tullock also talks of the potential for corner solutions based on different orderings of the size of the gain of the egoist, damage to the altruist and transfer from the altruist. He notes that Becker’s scenario can only occur where the damage inflicted on the donor is greater in size than the gift that would be given to the egoist in the absence of damage, which is greater than the gain to the egoist from damaging the altruist. This is only one of six possible orderings (although two of the others involving no or almost no harm to the altruist are the most common).

Becker’s reply to Tullock is sharp. “Although Tullock’s comment is much longer than Hirshleifer’s, it is less focused and less useful, and my response shall be brief.” His dismissal of Tullock’s argument is largely on the basis that Becker is not seeking to explain altruism to people 1,000 miles away, but rather to kin and close neighbours about whom the altruist will have more knowledge. Further, while this is a restrictive class, Becker (rightfully) considers it an important one.

Becker’s point on knowledge of kin and neighbours does not completely nullify Tullock’s, as parents have imperfect knowledge of their children. That same criticism could be applied to kin selection, which requires some degree of understanding of what actions will benefit kin. However, Tullock may be comfortable that the criticism would also apply to kin selection given that he prefers group selection based explanations of altruism and cooperation.