Writing Worth Reading
Writing Worth Reading
A number of econometricians – economists who use statistical and mathematical methods – have won the Nobel prize in economics. We’re going to talk about the ones that influenced you in your work. Before we start, what got you excited about econometrics in the first place?
I was in high school at the time of the oil price crisis of the 1970s and I asked my mom, “What causes inflation?” She didn’t know. I think it was from then on that I started wondering about money and inflation and what caused it – how the Fed was involved et cetera. When I got to college I took economics and started answering those questions. Then when I got to graduate school I learned theories about why it happened, and I got interested in how you test those theories. How do you know if this theory is right or that theory is right? How can we figure it out? That’s where econometrics comes in. Time-series econometrics was a set of tools I could use to answer that longstanding question I had about how the Federal Reserve impacts the economy, how it creates inflation and so on.
Time-series econometrics is a particular area of focus for you. Can you give me an example of how it works?
Right now there is this big question about how much impact the Fed can have on the economy and whether or not deficit spending, or a change in government spending, creates employment. Is there a government-spending multiplier? You can use time-series econometrics to go back and look at data from the past, then use that data to estimate a model, and from that model you can figure out whether or not government spending works, and if it does work, when it works, when it doesn’t – all sorts of questions. Almost any policy question that you can formulate, you can take to the data. That’s where the econometric technique comes in, it allows you to determine what impact the policy is likely to have.
So it’s more empirical than straight economics?
Exactly. Our field is divided into two groups – there’s the theorists and the applied people. I’m more of an applied person. I apply and test the theories that the more highbrow, theoretical types build. They might build two different models of the economy, and then the question is which one fits the data best. Which one is the best explanation of the economy? You can use econometrics to sort out competing theoretical models.
What then is your conclusion on the government-spending multiplier?
There’s a lot of uncertainty about it, so I can’t say for sure whether it’s one or two, or somewhere in between. There’s a fairly wide range of estimates, but I think it’s pretty clear that it’s somewhere in that range. I would say it’s about 1.5 presently.
Have econometricians been well represented in the Nobel prize for economics?
I think they have. The committee has been very good at rewarding the people who are building the tools that allow us to test economic models. So it’s not unusual at all for them to give Nobel prizes to econometricians.
Prior to this year’s award to Thomas Sargent and Christopher Sims, there was Robert Engle and Clive Granger in 2003, and before that Daniel McFadden and James Heckman in 2000.
Yes, those are all econometricians. The older cohort were more micro-economists. This morning I was wondering whether this year’s prize was something of a make-up for the macro people, but I don’t think it was. They built their own tools and techniques that were important.
Let’s start by talking about New York University’s Thomas Sargent, who along with Lars Ljungqvist is the author of your first book choice, Recursive Macroeconomic Theory. What is important about Sargent’s work?
Sargent went into the engineering literature, he took the tools and techniques that engineers use to do things like make sure your television is clear, and he brought them over into economics. There were all these tools that scientists were using to control systems. An engineer might build a TV that has a feedback mechanism. Somehow, it can look at the picture and if the picture isn’t right, it can go back and adjust the inputs in a way that clarifies it. If there is a horizontal scroll or a vertical scroll, it does something internally to stabilise the system, and makes sure it doesn’t get out of whack.
All the same tools that engineers use to stabilise your television picture can be used to stabilise the economy. The difference – this is an important difference, and where Sargent’s contribution comes in – is that when I do something with a TV, it doesn’t try to get out of the way to protect itself. It doesn’t say, “Oh! I don’t like having a little more green in my colour, so I’m just going to turn it back down.” Unlike TVs, people have brains and they respond to policies. If you try to tax them, they try to get out of the way of taxes. If you try to tax a TV, it has no way of getting out the way.
That’s where rational expectations comes in. When you’re trying to control a person instead of a TV, you have to take into account their expectations – how they’re going to respond to the things you do as a policy-maker. Sargent took all these tools and techniques for optimal control that were being used in engineering, all this heavy mathematics, brought it over into economics, added rational expectations to it which made it even more complicated mathematically and harder to use than it already was in the engineering literature.
And that’s what he won the Nobel for?
Yes. It wasn’t so much that he was this grand theorist – although he is certainly good at that – it was more the tools and techniques that he brought to the profession.
Mark Thoma is professor of economics at the University of Oregon. He is a macroeconomist and time-series econometrician. His research focuses on how monetary policy affects the economy, and he has also worked on political business cycle models and models of transportation dynamics. Thoma writes an influential daily blog at Economist’s View
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