
Interview with Sandra Black: Education Outcomes and A Stint in Politics
The title sums up the topics: "Seeing the margins: An interview with Columbia University economist Sandra Black on education, family wealth, her time at the White House, COVID-19, and the cost of bad policy."Like a lot of the interviews done by Clement, the interviewee is encouraged to describe the basic insight behind some of their own prominent research, which in turn gives a look into how economists think about research.
Let’s look at how parents value living in a house that is associated with a better school. That’s an indirect value of the school—what the parents are willing to pay to have the right to send their children to a particular school. The problem is that when you buy a house, it has a whole bunch of different attributes. You’re buying the school that you get to send your kids to, but you’re also buying the neighborhood and the house itself and all the public amenities and all kinds of other things. And those things tend to be positively correlated. Better school districts tend to be in better neighborhoods with nicer houses—so isolating the part due just to schools is somewhat complicated. ...
What I did was look, in theory, at two houses sitting on opposite sides of the same street, where the attendance district boundary divides the street. The houses are clearly in the same neighborhood, they’re of similar quality, et cetera. The only difference between them is which elementary school the child from each home attends. And then you can ask, How different are the prices of those houses, and how does that difference relate to the differences in school quality?
What I found was that parents were willing to pay more for better schools, but much less than you would casually estimate if you didn’t take into account all these other factors. In Massachusetts, parents were willing to pay 2.5 percent more for a 5 percent increase in school test scores. ...
[T]this was a long time ago, so pretty much all the information was hand-collected. The housing prices were in a database, but for the attendance district boundaries, I had to contact each school district to ask for their map. I would call them and say, “Can I get the map of your boundaries?” And they would ask, “What house are you thinking of buying?” I’d reply, “No, I actually just want the map.” They’d usually send me a list of streets that were in the attendance district, and a friend of mine and I would sit down and try to create these maps. She was a very good friend.Here's another example. Back in 1997 the state of Texas passed the "Top Ten Percent Plan."
The idea is that the top 10 percent of every high school in Texas would be automatically admitted to any University of Texas institution—any one of their choice. All of a sudden, disadvantaged high schools that originally sent very few students to selective universities like the University of Texas, Austin—the state’s top public university— found that their top students were now automatically admitted to UT Austin. If they wanted to go, all the student had to do was apply. There was also outreach, to make students aware of the new admissions policy. The hope was that it would maintain racial diversity because the disadvantaged high schools were disproportionately minority.
It’s not obvious that the goal of maintaining diversity was realized, in part because even though a school may have a disproportionate number of minority students, its top 10 percent academically is often less racially diverse than the rest of the school. There is some debate about whether it maintained racial diversity.
What you do see, however, is that more students from these disadvantaged schools started to attend UT Austin. And students from the more advantaged high schools who were right below their school’s top 10 percent were now less likely to attend. So there’s substitution—for every student gaining admission, another loses. I think that is true in every admissions policy, but we don’t always consciously weigh these trade-offs. ... Here, we’re trying to explicitly think about, and measure, these trade-offs. ...
But what was really interesting is that the students who are pushed out—that’s how we referred to them—didn’t really suffer as a result of the policy. These students would probably have attended UT Austin before the TTP plan. But now, because they were not in the top 10 percent [of their traditional “feeder” school], they got pushed out of the top Texas schools like UT Austin. We see that those students attend a slightly less prestigious college, in the sense that they’re not going to UT Austin, the flagship university. But they’ll go to another four-year college, and they’re really not hurt. They’re still graduating, and they’re getting similar earnings after college.
So the students who weren’t attending college before [because they didn’t attend a traditional feeder school] now are, and they’re benefiting from that in terms of graduation rates and income, while the ones who lose out by not going to Texas’ top university aren’t really hurt that much. It seems like a win-win.
Back in 2015, Black spent some time at the White House Council of Economic Advisers. Here's one of her reflections on that time:
[W]hich job do I prefer: adviser or academic? That’s easy to answer: being a professor. I like thinking about things for long periods of time, and it was quite the opposite when I was in D.C. There, I was scheduled every 15 minutes. Each meeting would cover a different topic, and I had to be ready to be an expert on A, then an expert on B, and then an expert on C.It is the antithesis of being an academic, and it’s a skill that I think a lot of academics don’t naturally have, me included. It was a really hard transition from academia to the policy world. Coming back to academia was hard too. I noticed that my attention span had become so much shorter. It took six months, at least, before I could sit and read a whole paper and just think about that paper. Being at the CEA was a very different experience. I really enjoyed it, but I was happy to come back to academia.
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