The article doesn't say that income causes higher scores (as I recently speculated), but the article is nevertheless criticised by an economics professor here. In his blog post, Prof. Mankiw suggests that a significant part of the slope is due to genes, with an argument along the following lines, which I've made more explicit here:
- IQ correlates positively with income
- The ability to perform well on an IQ test is influenced by heredity
- IQ correlates positively with SAT
It would be interesting to see the above graph reproduced for adopted children only. I bet that the curve would be a lot flatter.I interpret "a lot flatter" to mean that the IQ contribution accounts for a significant part of the slope. This is all reminiscent of the The Bell Curve and the controversy of genes vs. environment in the creation of intelligence.
Some analysis is in order. The inheritability of intelligence is a very political topic. The left would like to assume that all people really are created equal, and that the "blank slate" is there to be written upon. This legitimizes interventions that affect socio-economic status (SES). The right would like to believe that interventions are counter-productive because intelligence is fixed at birth. Both argue from the conclusions back to reasons for believing them, which is probably some kind of tragedy of the commons in the public realm: in order to stay in power, parties have to act sometimes in a way that is contrary to the common good. Since I don't have to be elected I can freely wish a pox on both their houses. Where is the science on the matter?
1. Income and IQ
There seems to be good evidence that IQ and income correlate positively. It's important to remember that IQ and intelligence are not the same thing. The first is a monological definition based on a particularly kind of cognitive test, and the second is a vocabulary item in common usage. In The Bell Curve and subsequent articles, the authors try to make the case that intelligence stratifies the employment landscape with the Very Dull at the bottom, hardly educated and hardly employable, and the Very Bright at the top. (Those words annoy me because dull is not the opposite of bright. Dim is.) In reading those arguments, it conjures up for me a kind of overarching social history that's implied--something on the order of what Marx sparked. In any case, it's a very strong conclusion they try to reach. You can spend a lot of time reading the debate about that book and related concepts.
It's noteworthy that physical attractiveness seems to also be linked to higher income.
2. Genes and Intelligence
The problem with an approach like The Bell Curve is that it's the wrong discipline. If you want to make conclusions about genetics, you need to actually look at some genes. This is especially true if you want to make big conclusions. The authors try very hard to control for environmental factors, but that doesn't substitute for identifying DNA that is causally linked to intelligence. That kind of work is being done by biologists, however. Here are some examples you can find on ScienceDaily.com:
- Smart babies make smart adults (2009)
- Genes affect brain processing speed (2009)
- Gene identified with intelligence (2006)
- Physically larger brains are smarter (2005)
- Eating better makes you smarter (2007)
- Training helps memory (2005)
- Training helps fluid intelligence (2008)
- Attitude matters (2007)
I think a reasonable person has to conclude that genes, epigenetics, and environment all play a role. Because genes are discrete, it ought to be possible to identify consequent effects with more precision than the other categories. The third article linked in the list above pins a particular gene to an R^2 of 3% of IQ.
One of the puzzling things about IQ is that if it really describes a primarily genetic effect, how can we explain the dramatic rise in scores in the last decades? This is the so-called Flynn Effect, summarized in Wikepedia as the change over a 30-year period where:
- the mean IQ had increased by 9.7 points (the Flynn effect),
- the gains were concentrated in the lower half of the distribution and negligible in the top half, and
- the gains gradually decreased from low to high IQ.[reference]
I think it's also fair to conclude from the evidence we have that smarter parents on average will produce smarter offspring, all other things being equal, but that this is not fully deterministic. The question of how much intelligence is inheritable is still open.
3. IQ and SAT
The link between IQ and SAT is also controversial, at least from test-maker's point of view. See an overview here. There seems to be a strong correlation between the two, which you can read about in this research article.
SAT isn't very good at predicting first year college grades, but that's what it's designed for. It's even less good at predicting success beyond the first year. This isn't perhaps surprising: the content of the test resembles high school and college freshmen academic work. There are many other factors that influence success. I was interested to read here that:
Bates College, which dropped all pre-admission testing requirements in 1990, first conducted several studies to determine the most powerful variables for predicting success at the college. One study showed that students' self-evaluation of their "energy and initiative" added more to the ability to predict performance at Bates than did either Math or Verbal SAT scores.Is IQ similarly limited in predicting college success? I couldn't find anything definitive about that in the time I had at my disposal, so I'll leave the question open.
If we can reach any conclusion, it's a very weak one. Almost certainly income is indirectly linked to SAT scores through the associations advanced. However, how much that bonus is remains unclear. My blog post last time pointed out that it's not only that higher incomes get higher SATs, but that the year-to-year differential is also higher. If this is not some statistical artifact, it doesn't jibe with a purely genetic explanation, as it would require the gene pool to be evolving at a very high rate, implying extraordinary pressure from a fitness gradient.
I looked for more historical data on this increase as a function of wealth, but unfortunately it's only in the last two years that the SAT included the salary range from zero all the way to $200,000+. The old version only went to $100,000, and the most interesting part of the curve is above that. Having said that, I did not find any evidence for my theory about the economic value of error with the data that is available. We'll have to wait for next year's results.
There is, however, a direct causal explanation that is difficult to imagine away. It contrasts with the somewhat specious illustration Prof. Mankiw gives:
Suppose we were to graph average SAT scores by the number of bathrooms a student has in his or her family home. That curve would also likely slope upward.Correlation and causation are different things. But consider another scenario. Suppose we were to graph SAT scores by the number of prep-tests a student attended, or the number of times they took the test (guaranteed on average to raise the maximum score), or the quality of the high school they attended. All of those have plausible causal connections to how well a student performs on a test of high-school cognitive material, no? And which students have access to the best high schools? Can afford to take the test multiple times? Can afford prep-tests that are advertised to raise scores 100 points?
The ironic thing is that the economic value of raising the SAT is real because of the usual policies in awarding financial aid. So the wealthiest are in the best position to reap that aid for both reasons of intelligence and the ability to buy error (over-prediction due to coaching or taking multiple tests). This trend has been documented for a long time here.
This line of thought gave me an interesting idea some time ago, which I hope to turn into a project. At my current institution we have embarked on a shift toward recruiting better students (students who have a better chance of success). But the conversation with the board, as well as public perception, includes the median SAT scores of the students we admit. My preference is to use better predictors (including noncognitive ones) to find the best students, but this is largely independent of their SATs, which creates a tension between actual goals and perceptions.
The idea is to create a grant-funded summer camp for the low-SAT that are nevertheless predicted to do well. In this camp they would receive SAT test-taking preparation and then retake the test immediately afterwards. This would raise median SATs without affecting our ability to get the students we want.
Update: here are some references: