Category: Uncategorized

Last week, Miles Kimball and Noah Smith, two economists (one at Michigan, one at Long Island) had a column on the Atlantic‘s website (ht: Joaquin Morales, via Facebook) in which they took to task those who claim that math ability is genetic.

Kimball and Smith argue that that’s largely a cop-out, and that there is no such thing as “I’m bad at math.” Rather, being good at math is the product of good, old-fashioned hard work:

Is math ability genetic? Sure, to some degree. Terence Tao, UCLA’s famous virtuoso mathematician, publishes dozens of papers in top journals every year, and is sought out by researchers around the world to help with the hardest parts of their theories. Essentially none of us could ever be as good at math as Terence Tao, no matter how hard we tried or how well we were taught. But here’s the thing: We don’t have to! For high-school math, inborn talent is much less important than hard work, preparation, and self-confidence.

How do we know this? First of all, both of us have taught math for many years—as professors, teaching assistants, and private tutors. Again and again, we have seen the following pattern repeat itself:

1. Different kids with different levels of preparation come into a math class. Some of these kids have parents who have drilled them on math from a young age, while others never had that kind of parental input.
2. On the first few tests, the well-prepared kids get perfect scores, while the unprepared kids get only what they could figure out by winging it—maybe 80 or 85%, a solid B.
3. The unprepared kids, not realizing that the top scorers were well-prepared, assume that genetic ability was what determined the performance differences. Deciding that they “just aren’t math people,” they don’t try hard in future classes, and fall further behind.
4. The well-prepared kids, not realizing that the B students were simply unprepared, assume that they are “math people,” and work hard in the future, cementing their advantage.

Kimball and Smith’s column resonated deeply with me, because I discovered quite late (but just in time!) that hard work trumps natural ability any day of the week when it comes to high-school math–if not PhD-level math for economists.

My good friend and coauthor Nick Carnes’ book White-Collar Government: The Hidden Role of Class in Economic Policy Making is coming out today. You can order it here from Amazon. My copy arrived early last week, so I read it over the weekend.

The book’s release could not be better timed, what with last month’s government shutdown and given how some politicians seem to have it in for those at the bottom of the economic ladder. My advice: Buy it; read it. I suspect it will soon become one of those classics of American politics that one cannot afford to not have read.

In his book, Nick overwhelmingly makes the case that class matters in US politics. That is, working-class folks — folks who have spent most of their career in blue-collar occupations — are underrepresented at all levels of government.

Not only are they underrepresented, class also seems to affect how legislators vote. Members of Congress who come from big business tend to favor the business sector when they vote in the House or Senate; those who were farmers tend to favor the agricultural sector; and so on. So given that working-class folks are underrepresented, this means that few of our legislators favor the working class in how they vote in Congress–what we have is effectively a white-collar government.

Though there was a time where critics of development economics could get away with throwing around terms like “neoliberal” and “Washington consensus” around in order to be heard by policy makers, it seems that nowadays, the views of development economists largely prevail in development policy. Part of that is most likely due to the overwhelming focus of development economists on answering narrower but answerable questions. That is, on questions like “Do deworming drugs improve educational outcomes?” rather than on questions like “Do structural adjustment programs foster economic growth?”

The focus on smaller questions has led to impact evaluation activities that are much more credible than they used to be. Whereas in the 1980s and 1990s one could get away with comparing outcomes pre- and post-intervention, today any impact evaluation worth its salt has to have a credible research design, i.e., one that allows credibly estimating the causal impacts of a given intervention.

So in the last few years, “impact evaluation” has become quite the buzzword, and everyone — from the greenest of students in Masters programs in development to the development NGOs, and from the big development agencies like USAID to philanthropies like the Gates Foundation — is obsessed with impact evaluation.

That’s a good thing, at least on the face of it: If we know what works, we can better target development interventions, and so development policy can more effectively lift people out of poverty.

Not in my Backyard?

But does everyone really want to be evaluated? I’ve long suspected that, for many actors in development policy, but specifically for NGOs, the answer is “No.” Indeed, many people work with NGOs because they are true believers in the mission of the NGO they work for. Oh, sure: they’ll talk about impact evaluation because the donors want to hear about it. But do they really want to be evaluated? On the one hand, there are true believers. On the other hand, there are those who think “Well, what if an impact evaluation finds no impact? In my heart of hearts I know what we do is right.”