Heckman on Econtalk
James Heckman was recently interviewed by Russ Roberts on Econtalk which I quite enjoyed. Some bits:
(37:35) Heckman: […] What I worry about is what I think is more general, not just even about empirical work, is kind of the non-cumulative nature of a lot of work in economics.
In macroeconomics and other parts of economics there’s a practice called calibration. The calibrated models are models that are kind of looking at some old stylized facts that are putting together different pieces of data that are not mutually consistent. I mean, literally: you take estimates of this area, estimates of that area, and you assemble something that’s like a Frankenstein that then stalks the planet and stalks the profession, walking around. It’s got a labor supply parameter from labor economics and it’s got an output analysis study from Ohio, and on and on and on. And the out comes something–and sometimes a compelling story is told. But it’s a story. It’s not the data. And I think there’s a lack of discipline in some areas where people just don’t want to go to primary data sources.
But back in the 1940s at Chicago, there was a debate that broke out; and it was a debate really between Milton Friedman and Tjalling Koopmans. Although it wasn’t quite stated that way, it ended up that way. And that was this idea of measurement without theory. […] And so, it’s very appealing to say, ‘Let’s not let the theory get in the way. We have all the facts. We should look at facts. We should basically have a structure that is free of a lot of arbitrary theory and a lot of arbitrary structure. That’s very appealing. I would like it. The idea that we have is this purely inductive, Francis Bacon-like style–not the painter but the original philosopher. So, but the problem with that is, as Koopmans pointed out, and as people pointed out: that every fact is subject to multiple interpretations. You’ve got to place it in context.
So, people will say, ‘Let the facts speak for themselves.’ But in fact, the facts almost never fully speak for themselves. But they do speak.
(48:47) Heckman: Well, it’s–I think that’s a general process of aging. If you do empirical work as I do and you get into issues, you inevitably are confronted with your own failures of perception and your own blind sides. And I think–I think the profession as a whole is probably better, much better, now. I mean the whole enterprise is bigger to start with. You are getting a lot of diverse points of view. And the whole capacity of the profession to replicate, to simulate, to check other people’s studies, has become much greater than it was in the past. I think the big development that’s occurred inside economics, and it’s in economics journals and in the professional–that if people put out a study, except for having those studies based on proprietary data–that many studies essentially have to be out there and to be replicated. And it’s literally been the kiss of death for people not to allow others to replicate their data.
And I think that–yes, I think we’ve all come to recognize the limits of the data. But on the other hand, I think we should also be amazed at how much richer the data base is these days–how much more we can actually investigate. […] So I think the empirical side of economics is much healthier than it was, before–I mean long before, going back to the 1920s and 1930s. That was just a period with no data. So I think we have a better understanding of the economy than we did. And I think that’s still there. And I think we have better interpretive frameworks than we had out there. […]. I think these are things that we shouldn’t underlook, overlook, here, understate where we’ve come from. We’ve come a long way.
I found it interesting that Milton Friedman was apparently more on the “let the data speak” reduced-form side of the spectrum.
For a different perspective on similar issues, I also recommend the podcast with Joshua Angrist.