How to think like a microeconomist
Yesterday we were pleased to have Suresh Naidu guest lecture in The Platform. He came in and explained, very efficiently because he was leaving at 11am for a flight at noon at LGA (which he made!!) how to think like an economist. Or at least an applied microeconomist. Here are his notes:
Applied microeconomics is basically organized a few simple metaphors.
- People respond to incentives.
- A lot of data can be understood through the lens of supply and demand.
- Causality is more important than prediction.
There was actually more on the schedule, but Suresh got into really amazing examples to explain the above points and we ran out of time. At some point, when he was describing itinerant laborers in the United Arab Emirates, and looking at pay records and even visiting a itinerant labor camp, I was thinking that Suresh is possibly an undercover hardcore data journalist as well as an amazing economist.
As far as the “big data” revolution goes, we got the impression from Suresh that microeconomists have been largely unmoved by its fervor. For one, they’ve been doing huge analyses with large data sets for quite a while. But the real reason they’re unmoved, as I infer from his talk yesterday, is that big data almost always focuses on descriptions of human behavior, and sometimes predictions, and almost never causality, which is what economists care about.
A side question: why is it that economists only care about causality? Well they do, and let’s take that as a given.
So, now that we know how to think like an economist, let’s read this “Room For Debate” about overseas child labor with our new perspective. Basically the writers, or at least three out of four of them, are economists. So that means they care about “why”. Why is there so much child labor overseas? How can the US help?
The first guy says that strong unions and clear signals from American companies works, so the US should do its best to encourage the influence of labor unions.
The lady economist says that bans on child labor are generally counterproductive, so we should give people cash money so they won’t have to send their kids to work in the first place.
The last guy says that we didn’t even stop having child labor in our country until wage workers were worried about competition from children. So he wants the U.S. to essentially ignore child labor in other countries, which he claims will set the stage for other countries to have that same worry and come to the same conclusion by themselves. Time will help, as well as good money from the US companies.
So the economists don’t agree, but they all share one goal: to figure out how to tweak a tweakable variable to improve a system. And hopefully each hypothesis can be proven with randomized experiments and with data, or at least evidence can be gathered for or against.
One more thing, which I was relieved to hear Suresh say. There’s a spectrum of how much people “believe” in economics, and for that matter believe in data that seems to support a theory or experiment, and that spectrum is something that most economists run across on a daily basis. Even so, it’s not clear there’s a better way to learn things about the world than doing your best to run randomized experiments, or find close-to-randomized experiments and see how what they tell you.