Figure 6
Figure 6 conceals as much as it reveals. It shows that the median income after 15 years for the individuals with the highest AFQT score was around five times greater than the median income for the individuals with the lowest AFQT score. But it tells us nothing about the variation around the median of the individuals within each group. As a result, Figure 6 cannot tell us whether IQ is strong or weak predictor of income.
Another section in Murray's paper, however, helps with this question. In a multiple regression analysis using IQ and parents' income as the two independent variables, Murray found that IQ explains (predicts) around 12% of the subjects' income, while parents' income explains 4%.
As we shall see in Why We Have What We Have, other scholars come to very different conclusions as to the relative importance of IQ and parents' income as predictors of children's income. However, for our purposes, it doesn't matter whether the more important ticket is drawn in the Genes Lottery or in the Parents Lottery. We choose neither our genes nor our parents. Both are birth accidents.
Parents Lottery
Oh your daddy's rich, and your mammy's good lookin'
So hush little baby, don't you cry.
-- DuBose Heyward, Porgy and Bess
The last of the birth lotteries is the one in which we draw tickets for who our parents are. These are by far the most important of the birth lottery tickets. Not only do they come with genes lottery tickets stapled to them, but they bring with them a host of other advantages or disadvantages that are equally if not more important to our prospects than genes.
The correlation between the socio-economic status of parents and that of their children is much-studied by sociologists and economists. In the Genes Lottery, we noted Charles' Murrary's work in this field, and his conclusion that IQ “explains” 12% of income, while parents' socio-economic status explains 4%. More recently, however, a collection of papers published under the title Unequal Chances: Family Background and Economic Success, reaches rather different conclusions. In Table I.2 of the Introduction, authors Bowles, Gintis and Groves report findings that only 25% of the correlation between parents' and children's income is the result of genetic factors, and 75% is due to “environmental” and “wealth” factors.”
What are these environmental and wealth factors that account for three-quarters of the correlation? Let's look at three "channels" through which parents might transmit their economic status to their children.
First is the parent-to-child transmission of character traits --persistence, self-discipline, self-confidence, ambition, gregariousness, risk-taking, and their opposites--that influence how well their children will do. The research indicates that some trait-transmission is genetic, but much is the result of parent behavior. "Monkey see, monkey do" applies also to homo sapiens, especially in relations between parents and children.
Second, parents invest in their children's "human capital"-to the extent they are able, and to the extent they are willing. They may invest both time and money. Recent study of the time variable shows a strong relationship between parents' level of education and the time they spend with their children.
The “Patticake and Goodnight Moon” gap (Figure 7) shows that parents with a college degree or more spend 50% more time on early childhood development activities than parents with a high school degree or less. [9] For older children, parents' time investment is equally if not more important. Helping with homework, talking through problems-whether the world's or the child's-is time spent developing skills and outlook that is critical preparation for adult life. And the research shows a widening gap between the amounts of time that more and less-educated parents spend on this (“Time With Mom and Dad Gap”).
Figure 7
In addition to time, parents also invest money in their children's human capital. This includes lessons in an array of non-academic pursuits, private tutors, test-prep and, of course, private school education. Figure 8 (“Enrichment Dollar Gap”) shows that parents in the top income quartile now spend almost eight times as much on enrichment activities (not including private school education) for their children as do parents in the bottom income quartile. [10]
What I cannot show here, because I have not found suitable supporting data, is a figure comparing what parents in the upper and lower income brackets spend on private schools and colleges. I am certain that the “private education gap” figure would show much more dramatic spreads between expenditures by high and low income families than the gaps shown in Figure 7.
Figure 8
Then there's sports. As we shall see, sports achievement can be quite important in boosting your chances in the two remaining lotteries: Education, and Jobs. The research shows a widening gap between the high school sports achievements of children of richer parents compared to children of poorer parents. Here are a couple of rather extreme examples of this phenomenon:
When I grew up in Greenwich Connecticut in the 1950's, there were a couple of squash courts at the tennis club of which our family was a member. I fooled around some before going away to prep school, where I made the team because few other classmates had ever played the game. At Yale I made the team because few other classmates had ever played he game. By the time I graduated, I probably had played for around 1000 hours.
Things have moved on in Greenwich since my day. Résumé planning and management is now a major league sport for Greenwich families hoping to find a slot for their child in the Ivy League. Squash has become a feature item here, because a good 13-year-old squash player has a leg up in getting into squash-playing prep schools like Andover, Exeter or Deerfield, from where they have a leg up at getting into the Ivies, most of which care a lot about their squash teams.
So what is a Greenwich mom doing these days to manage the squash component of her daughter's résumé? Two things. First, her husband (who played varsity squash at college) pays to have a squash court erected behind one of the garages. Next, a personal trainer is engaged to ensure that from the age of eight, the child works tirelessly to nail her rail shots, sharpen her reverse-corner, and perfect her boast. She plays with her dad an hour every morning before he goes to work and she goes to school, and she plays an hour with her mom every evening before dinner. By the time she is thirteen and applying to Deerfield, she has racked up 5,000 hours in the court, and is ranked #3 in the country.
Dads on the other coast pay Steve Clarkson $3000 to assess their 8-year-old boys for admission to Clarkson's quarterback academy in Pasadena, California. If Junior is admitted, dad will pay Clarkson many more thousands annually for five years' of intensive QB coaching. The payoff comes when Junior is thirteen, and USC offers him a scholarship, good for the day he graduates from high school.
These are extreme examples of how parents' money helps their children do well in sports. But the correlation between parents' income and children's sports achievements reaches down through all levels of the income pyramid. For example, children's participation in high school sports bears a strong relationship with parents' income, In 2004, you were twice as likely to play sports during your senior year in high school if your parents were in the top income quartile than if they are in the bottom quartile. You were 2.5 times as likely to be a team captain, as shown in Figure 9.
Figure 9
Finally, there is the direct route by which we transmit our "economic status" to our children-we buy them homes, we invest in their businesses, we give them gifts, we set up trusts for their benefit, and we leave our assets to them when we die. I have found no useful data on any of this, so I am unable to say whether these transfers are quantitatively significant, or to compare their importance to that of the other transmission vectors discussed here. My guess, however, is that they are quite important, and increasingly so.
These, then, are the channels through which economic position can be transmitted from one generation to the next. And it is no surprise that, as we shall see in (“
Why We Have What We Have”), there is a very strong correlation between parents' and children's income. The important point is that, from children's standpoint, all of this transmission is accidental. We don't choose our parents, so we can neither be blamed, nor claim credit, for the tickets we draw in this lottery, or the value these tickets have in the marketplace. And if we can't claim credit for these tickets, we can't claim that we deserve what these tickets turn out to be worth in the market place.
Education Lottery
In the education lottery, schools and colleges screen and select for aptitude and achievement. The more selective schools look for this not only in the academic subjects, but in other areas as well. How well we do in this lottery depends largely on tickets we drew in the birth lotteries--key being IQ, talent, motivation, self- discipline and social skills learned from our parents, and our parents' ability to pay for private secondary and college education. Hard work is also important, although, as we have seen, good genes and well-off parents can create opportunities to work hard, and bad genes or poverty can thwart those opportunities.
Other chance factors are also at play in the education lottery. Whether we draw a good, bad or indifferent teacher can make a difference in how much we learn, and how much we like to learn. The lottery in which we draw teachers is not a highly-repeatable one that would allow good and bad luck to even out. Most of us will have no more than eight teachers by the time we start high school.
Teachers can also matter in another way. One of my wiser but more delinquent college classmates described the process by which he finally received his BA degree as “a successful series of negotiations.” That was in 1967. My impression is that negotiating with teachers to improve one's grades has become an even more important determinant of GPA since then. How successful you are depends on your negotiating skills, but also on the teacher's willingness to negotiate.
As for standardized tests, I have to wonder if scores don't depend more than a little on chance. One of the goals of test designers is “repeatability”--a person taking a test more than once should get nearly the same score each time. The only standardized test I remember taking twice was the law school admission test (LSAT). The first time I scored 625 out of 800 (only good enough for a tier 2 school), and the second time I scored 750. My suspicion is that test designers have found it difficult to come up with highly “repeatable” tests, and that this explains why schools these days allow students to take the tests as often as they like, and submit only their best score. But how many students take these tests more than once or twice?
Finally, pity the poor admissions director who, after accepting the 5% of applicants who are clearly keepers and rejecting the 10% who clearly are not, is left with five times as many applicants as he has places in the class. On measures of aptitude and achievement, they all look pretty much alike. What to do? It's a lottery.
So at the end of the day, how much difference does hard work make in the education lottery? Can a person of average intelligence, with no special talents, make it to the top by dint of hard work? Of course she can, but the odds are not in her favor. Remember, this system selects for aptitude and achievement. The higher she rises, the smarter and more talented are the people around her, and they, too, work hard.
How much difference does the education lottery make to lifetime earnings? In Figure 4.2, we saw an apparently strong relationship between levels of education and lifetime earnings. But we must not be fooled by averages. If we want to know whether levels of education “explain” earnings, we need to look at the variation of each individual's around the median or average for his or her education class. We do this in Figure 10. [11]
Figure 10
Figure 10 suggests that educational attainment is indeed strongly correlated with how much we earn. A randomly selected person who doesn't go beyond high school has an 18% chance of earning more than the population median of $1.1 million during his lifetime. The randomly selected person with a graduate degree has an 82% chance of earning more than the population median.
We should not confuse correlation with causation. In part, college graduates earn more than K-12 graduates because the jobs that require a college degree pay more than the jobs you can get with a K-12 degree. However, the reason why they pay more is because they require higher levels of intelligence and motivation, which is what college selects for. In this respect, in the education lottery can be seen as a screening system used by employers to select for the final lottery-the Jobs Lottery.
Job Lottery
You can get it if you really want.
--Jimmy Cliff
I didn't become Head Jailer because I like head jailing. I didn't become Assistant Tormenter because I like assistant tormenting.
--Wilfred Shadbolt, The Yeoman of the Guard
After we have been screened, sorted and selected (or rejected) in the education lottery, we present ourselves to the job lottery, the last we will look at. Unlike the birth lotteries, in which tickets are drawn only once, or the education lottery, in which they are drawn only a few times, in the jobs lottery we draw tickets continuously throughout our working lives.
Success in the education lottery is no guarantee of success in the job lottery, nor is failure in the one a guarantee of failure in the other. This is apparent from the size of the “tails” of the distributions shown in Figure 10. Bill Gates and Steve Jobs are the poster boys for the idea that you can drop out of college and still succeed. Peter Theil has established a foundation whose objective is to persuade college students with talent to drop out and jump-start their careers without wasting their time and talent on completing that “successful series of negotiations.”
Notice, however, that among the many fabled stories of drop-out success, it's hard to find anyone who was of average intelligence, had no particular talents, was raised by ordinary, middle class parents, and achieved extraordinary success by hard work alone.. These stories almost always involve people who drew top tickets in two or more the four birth lotteries.
Let's broaden the discussion to the entrepreneurial class as a whole. This includes a much larger number of people, most with less distinguished intellects than Gates, Jobs or Thiel's chosen few, but all with sufficient drive and determination to start a business. Here, if anywhere, is where “hard work” should explain why those with relatively less education end up out in the right-hand tails in Figure 10.
Persistence obviously matters. People who fall down, pick themselves up and try again, over and over, have a higher probability of succeeding than those who slink away after the first failure. The persistent ones “make their own luck.” They try their idea, or variations thereupon repeatedly until they succeed.
Figure 11 illustrates the importance for entrepreneurs of picking yourself up, dusting yourself off, and trying again. [12] In 1992, approximately 600,000 businesses were started (and around the same number were shut down). Of these, 25% had failed after one year, 36% after two years, 50% after five years, and 71% after ten years. Starting a single new business is clearly not a route to lifetime prosperity. Starting serial new businesses may be. Here more than anywhere, you learn from your mistakes. You must be able to “try, try and try, till you succeed at last.”
Figure 11
The problem here is that in order to start a business, you need capital. The first time you cold-call VC's, angel investors or your local bank, a good idea may be all that you need. But if you have tried and failed once, twice or thrice, the sell gets harder and harder. Each time you fail, it gets harder to raise money from people you don't know. So you turn to people you do know--family and friends. And now we are back into the territory where the success we may attribute to entrepreneurial persistence should perhaps also be attributed to the accident of having family and friends with money.
More generally, there is this question: is success or failure in small business “explained” by gender, genes, and parents to the same extent that econo
mic success or failure generally is explained by these variables? How important is the entrepreneur's hard work compared to the tickets she draws in the birth lotteries?
Hard work is not the only variable that explains the variation around the median lifetime earnings for each education class in Figure 10. Many other, serendipitous factors are at play. Take the process by which we get first jobs. Wilfred Shadbolt may have become Head Jailer and Assistant Tormentor because that was the job to which his class and education suited him in Tudor England. These days, while class and education do play an important role in the “first-job” selection process, luck also matters.
Michael Lewis, the author of Liar's Poker and Moneyball, gives this account of how he got his first job, with a BA in art history from Princeton and an MA from the London School of Economics, and then wrote his first book. This is an excerpt from Lewis's commencement address to Princeton's class of 2012, which he titled, “Don't Eat Fortune's Cookie.”
One night I was invited to a dinner, where I sat next to the wife of a big shot at a giant Wall Street investment bank, called Salomon Brothers. She more or less forced her husband to give me a job. I knew next to nothing about Salomon Brothers. But Salomon Brothers happened to be where Wall Street was being reinvented-into the place we have all come to know and love. When I got there I was assigned, almost arbitrarily, to the very best job in which to observe the growing madness: they turned me into the house expert on derivatives. A year and a half later Salomon Brothers was handing me a check for hundreds of thousands of dollars to give advice about derivatives to professional investors.