Do bright people earn more than others? If not, it would strengthen the view that intelligence tests are no more than meaningless scores on paper and pencil tests composed of arbitrary items which have no relevance to real life. So, it is with trepidation that I responded to a suggestion by a reader that I look at a paper appearing to show that there is no relationship between intellect and wealth, and furthermore that clever people are just as likely to experience financial difficulties as any other citizen.
Do you have to be smart to be rich? The impact of IQ on wealth, income and financial distress
Jay L. Zagorsky. Intelligence 35 (2007) 489–501
The abstract apparently bears out that interpretation:
How important is intelligence to financial success? Using the NLSY79, which tracks a large group of young U.S. baby boomers, this research shows that each point increase in IQ test scores raises income by between \$234 and \$616 per year after holding a variety of factors constant. Regression results suggest no statistically distinguishable relationship between IQ scores and wealth. Financial distress, such as problems paying bills, going bankrupt or reaching credit card limits, is related to IQ scores not linearly but instead in a quadratic relationship. This means higher IQ scores sometimes increase the probability of being in financial difficulty.
Happily, another reader, “res” had a closer look at the paper, and found that all was not as it seems in the abstract. That is to say, the results in the paper actually show a relationship between intelligence, earnings and wealth, as shown in the histogram below, which I have drawn based on the results from that very paper:
I think this shows that income gradually increases with intelligence, and wealth increases more strongly with intelligence, in a roughly linear trend. It is relevant to know that income at the lower levels of ability include welfare payments and that incomes at the very highest level have been capped for reasons of confidentiality which both reduce the real relationship between intelligence and earning power. However, the general picture is clear, and somewhat different from what the abstract suggests.
Introduction. How important is intelligence to success in life? Success is a multi-dimensional concept but one key component for many individuals is how well they do financially. It is still not well understood why some people are rich and others are poor. Previous research, discussed below, has investigated the relationship between intelligence and income and found individuals with higher IQ test scores have higher income. Income alone is not a complete measure of financial success. This research completes the picture by investigating if there is a relationship between IQ scores and wealth and if there is a relationship between IQ scores and financial difficulty. What are the differences between these three financial measures? Income is the amount of money earned each time period, such as a weekly pay check. It is the stream of money off which people live. Wealth is the difference between a person’s assets and liabilities. It is the reserve or cushion that people fall back upon to meet large expenditures, unexpected emergencies and periods when income is expected to be low. Financial difficulty is getting into a situation where a respondent’s credit is adversely impacted such as not paying bills or charging a credit card to the maximum limit. These situations prevent or reduce the ability of individuals to borrow money in the future. Financial success for most people is a combination of all three measures; having a steady income stream, a stock of wealth to buffer life’s storms, and not worrying about being close to or beyond their financial limits. Previous research has focused on intelligence’s impact on income and found a positive relationship.
The authors have given an interpretation in the abstract which does not fairly reflect what they actually found. The data plot above, taken from that paper, shows a strong relationship between intelligence, income and wealth.
Commentator “res” shows that the 2007 figures probably under-estimate the effects of intelligence. First, incomes at the lower level of intelligence are inflated by welfare payments, and those are not shown separately. That is a real problem, since it hides the lower wages actually paid to low ability workers. Second, the wages of the brightest 2% of workers have been truncated, apparently so as to protect their anonymity. Not sure how their anonymity was threatened, but it is a nuisance, since in the early years top income were artificially capped at \$75,000 then later at \$100,000 and finally shown as the average of that category. This is a real pity, because it obscures the incomes of the smart fraction. Though the sample size is perfectly adequate for most purposes, eminent minds are 1 in 10,000 so the sample will contain only 1 or 2 of them. It would be good to know how much they earn, and how much wealth they have.
As luck would have it, I had commented on the same dataset in 2015 and, despite a few cautionary statements, came to the conclusion that intelligence was strongly related to income, and to savings. I also established a rule-of-thumb, that when young adults are doing well financially, their savings equal 4 years of their normal annual earnings.
I should explain that the 2007 paper being referred to above was an early look at the data, and the later work a more up-to-date set of findings. Both give substantially the same pattern of results, though the actual numbers have changed somewhat, as one would expect as the subjects get older, earn more, and have more time in which to save.
Looking back, there is a lot to ponder in these posts by Steve Hsu. For example, it seems that for both white and black children in the NLSY dataset, progress is identical when children are considered in terms of their IQ.
Steve dryly notes:
This last figure is very problematic for the “Social Status/Wealth causes IQ” position. It seems to be the other way around: the kids escaping bottom quintile childhoods all experienced poverty, but the ones with higher cognitive ability were more likely to move up. (Recall that adopted children tend to resemble their biological parents much more than their adoptive ones; family environment has a limited effect on IQ, which is highly heritable.)
Pew: Individuals with higher test scores in adolescence are more likely to move out of the bottom quintile, and test scores can explain virtually the entire black-white mobility gap. Figure 13 plots the transition rates against percentiles of the AFQT test score distribution. The upward-sloping lines indicate that, as might be expected, individuals with higher test scores are much more likely to leave the bottom income quintile. For example, for whites, moving from the first percentile of the AFQT distribution to the median roughly doubles the likelihood from 42 percent to 81 percent. The comparable increase for blacks is even more dramatic, rising from 33 percent to 78 percent. Perhaps the most stunning finding is that once one accounts for the AFQT score, the entire racial gap in mobility is eliminated for a broad portion of the distribution. At the very bottom and in the top half of the distribution a small gap remains, but it is not statistically significant.
What other data are available?
Pumpkin Person looked at intelligence and income, and suggests that they correlate at 0.49 which is higher than most published estimates. This analysis looks at the rarity of high wealth and the stated scholastic attainment scores of some people in wealthy groups.
Pumpkin Person notes that Dalliard in a very detailed analysis of average income over several years found that men’s average income and intelligence scores correlated at 0.48
Dalliard argues that many of the low estimates for the correlation between intelligence and income are based on single year earning figures, and it is better to look at rolling averages over several years, and to note that very early in career and very late in career figures may be a poor reflection of overall career earnings. Better to calculate “permanent” earnings of the sort achieved between ages 25 and 55. He looks at NLSY79 data, wisely taking only earnings and wages (no welfare payments). Wages above the cutoff are set to the average of all wages above the cutoff. Using a log transform he shows that one additional IQ point predicts a 2.5% boost in income. The standardized effect size, or correlation, is 0.36 and the R squared is 13%.
Men’s income is more strongly related to intelligence:
For example, the expected permanent annual income of a man with an IQ of 100 is e^(8.004 + 0.027 * 100), or \$44,530. The expected permanent annual income of a woman with the same IQ is e^(8.004 + 0.021 * 100), or \$24,440.
Below, income by racial group, which should be compared with group differences in intelligence, with which there are close parallels.
Looking at how to predict the effect of intelligence on each racial group, and interesting finding emerges:
Black men have a significantly lower intercept and a significantly higher slope coefficient: each additional IQ point predicts 3.6% (95% CI: 2.6%-4.5%) more income for black men.
This suggests that employers value intelligence, and pay higher wages for all brighter employees, an effect which is bigger in a group with a lower average ability level.
The OECD studied the intelligence and income link in a roundabout way, because these researchers appear not to believe in intelligence and intelligence testing.
You will see that I was irritated that they would not mention the fact that some people are brighter than others.
The median hourly wage of workers who can make complex inferences and evaluate subtle truth claims or arguments in written texts is more than 60% higher than for workers who can, at best, read relatively short texts to locate a single piece of information. Those with low literacy skills are also more than twice as likely to be unemployed.
“Across the countries involved in the study, between 4.9% and 27.7% of adults are proficient at the lowest levels in literacy and 8.1% to 31.7% are proficient at the lowest levels in numeracy. At these levels, adults can regularly complete tasks that involve very few steps, limited amounts of information presented in familiar contexts with little distracting information present, and that involve basic cognitive operations, such as locating a single piece of information in a text or performing basic arithmetic operations, but have difficulty with more complex tasks.”
The report contains descriptions of skill levels, and that is a good thing. Skills make sense, and if you say that someone has the skill to drive a car, but not the skill to service a car, (another Gottfredson quip) that immediately makes sense to most people. We can distinguish between a driver and a mechanic. We can also understand that someone who can only handle one concept at a time should not be given the task of integrating disparate conceptual inputs. That cuts out being in the control room of most industrial processes. In does not preclude employment as a university teacher, where to manage one concept may lead to a successful career.
Another approach to the relationship between intelligence and life outcomes is to do a birth cohort study and starting examining children at age 3.
The Dunedin study has calculated the cost to society of the most demanding section of the population. 20% of the population account for 80% of the social costs. Low intelligence is an important aspect of this needy section of the population.
Here is a more up to date paper on their work
A segment comprising one-fifth [20%] of the cohort accounted for 36% of the cohort’s injury insurance-claims; 40% of excess obese-kilograms; 54% of cigarettes smoked; 57% of hospital nights; 66% of welfare benefits; 77% of fatherless childrearing; 78% of prescription fills; and 81% of criminal convictions.
Childhood risks, including poor age-three brain health, predicted this segment with large effect sizes.
IQ is a strong factor, as is low self control.
You can also look at this from a States level (in the United States), and you will know roughly how wealthy those states are.
There are other studies which could be added, and more detail which can be explained in each of these sources, but I have picked a selection of studies to make a general point: I think it is pretty clear that intelligence has real-world implications.