Sorry but I’m going to be a few days late and a few dollars short to all the interesting discussions over the next few weeks – some life changes ongoing. So I missed the big discussion on genes and education that broke out over the weekend, starting at Greg Mankiw’s blog: “The NY Times Economix blog offers us the above graph, showing that kids from higher income families get higher average SAT scores…Smart parents make more money and pass those good genes on to their offspring.”
I like a lot of the things that economists do. But there are other things they do that I’m not a huge fan of. A good friend, who deals with ethnography, law, music and international copyright has a rule that whenever an economist uses an interview with one person and tries to pass it off as a piece of ethnography (“I had an interesting conversation with the cab driver who picked me up from the airport…From this conversation, I think it is safe to say that the local population is behind rapid capital market deregulation”) her mind wanders away from the argument. For me, the same thing happens whenever economists start talking about genetics.
There’s nothing in the education of economists, which is training in a subset of engineering math techniques known as ‘convex optimization’, that prepares one for the biological sciences. Is there an economics class lab that compares to organic chemistry lab? I know economics people and I know bio/chem/biophysics people, and the techniques and research are way different. Now if economists approached their research into genetics in a manner that was “here’s an interesting thing…” as opposed to “here we have clearly solved for genetic influence…”, humbler conclusions, that would be one thing. But it tends to be of the “fighting out the door” manner.
Here is a good writeup of the last round of follow-up with Mankiw at Marginal Revolutions, along with this provocative graph:
The graph does not say that adopted children necessarily have low income. On the contrary, some have high and some have low income and the same is true of biological children. What the graph says is that higher parental income predicts higher child income but only for biological children and not for adoptees.
Since the children in question were randomly assigned to families in the United States from Korea the researcher, Bruce Sacerdote in his paper “What Happens When We Randomly Assign Children to Families?”, uses the data to find many interesting results; adoptees education is correlated with parent’s education, but not as much as non-adoptees. I’m more interested in the way it has been characterized in the current debate. Can that graph really be true?
The data ‘Public Use Data Set of Adoptees’ is available on Professor Sacerdote’s webpage. Taking a peek at it, the adoptees average age is 28, while non-adoptees is 32. Well that’s a problem for the graph. The red line in question is 4 years old, and an important 4 years – 28 year olds may still be in graduate school, volunteering, traveling, etc., while people in their 30s are entering what is a more mature (and important for us, consistent) earning potential years.
How do the genders match up? To be an economist about it, the frustrating thing is that the study assumes that the ‘treatment effect for nurture’ is consistent across the entire cross-panel within families, but girls and boys are nurtured in different ways in our society. And 70% of the adoptees are female. Only 39% of the non-adoptees are female. Well that’s a problem for the graph. Women make less than men. Also, it isn’t clear at all that high income status transfers privilege the same way to daughters as it does to sons. Perhaps it is easier for male children to inherit social and cultural capital that is deployable into economic capital than it is for female children.
Nepotism has a gendered connotation, coming from the greek word usually reserved for nephew or grandson. Though Liz Cheney, Megan McCain and now Jenna Bush are making headways into breaking the glass ceiling of nepotism, and I’m rooting for them to help achieve a world in which the powerful can transmit their privilege across merit-less generations regardless of color or gender, I’m not sure if it applies for this sample study.
Anyway, the paper acknowledges this, noting “The survey measure of family income is much higher for the non-adoptees than for the adoptees: $61,000 per year versus $42,000 per year [as in the graph above]. But this huge difference narrows to $1,600 when I control for age, education, and gender.”
So $1,600 is very narrow. My next question is how do they measure income? Three-year averages? Five-year averages? How do they account for investment income? What’s the minimum value they report income in – $1,000? $100? Well, checking the data and research the income is a box in a questioneer the mother fills out about what she thinks her children make. The box are in $20,000 increments (she checks $10K, $25K, $40K, $60K, $80K, $125K, $175K, $200K). Does your mom know what box your income goes in? Mine wouldn’t.
So this strikes me as a major problem for the graph. Your Mom guessing, in $20,000 increments, what your income is not the best proxy for actual income, and it seems like a rather blunt sword to use to declare the knot of “Nature/Nuture” cut. I think the lack of granularity among the categories alone could easily noise out that $1,600, no?
Just for kicks, I re-estimated the graph just using people in their 30s to cancel out the “people hanging out in their 20s” effect:
The x-axis isn’t draw to proportion like the top graph (I can’t get excel or google documents to do it); however there is a correlation, a small but significant one; beta of .1, t-stat of 3.
This study introduces a lot of interesting questions for follow-up, especially with the way education levels transmit across generations. Personally I’d like to see work in how the habitus of female adoptees from foreign countries are constructed to deal with the fields of race and gender in our country, especially in regards to educational opportunities. But the idea that this study is the end of a discussion rather than the beginning of one isn’t giving it credit for what it does accomplish, and gives off a bad impression of what economists can do with subtly.