In the last part of this post, I issued a challenge:
sophisticated statistical techniques that was so well done, it ended a
controversy and created a consensus—a consensus where former opponents
of one viewpoint had to concede they were wrong because of the quality
of the empirical work.
I then discussed why The Monetary History of the United States while an extraordinary piece of empirical work, didn't count. It wasn't fancy regression analysis, but rather a careful marshalling of facts. Not the same thing. I concluded:
I am open to other suggestions. I'd like one example, please. One
example, from either micro or macro where people had to give up their
prior beliefs about how the world works because of some regression
analysis, ideally usually instrumental variables as that is the
technique most used to clarify causation.
One example. There should be dozens. Or hundreds. But I'll take one.
Both Tyler Cowen and Bryan Caplan responded to the challenge. And there were a lot of interesting comments. Here is Tyler's list:
1. The interest-elasticity of investment is lower than people once thought.
2. We have a decent sense of the J Curve and why a devaluation or depreciation doesn't improve the trade balance for some while.
3. Dynamic revenue scoring tells us over what time horizon a tax cut is partially (or fully) self-financing.
4. Most resale price maintenance is not for goods and services involving significant ancillary services.
5. More policing can significantly lower the crime rate (that one does use instrumental variables).
6. The term structure of interest rates is whacky.
Bryan's answer is the entire field of behavioral economics.
Lauren Landsburg, in a very thoughtful email, suggests Time on the Cross, Fogel and Engerman's study of slavery.
Most or all of these observations miss the point, or at least the point I was trying to make.
Empirical work is very important.
Facts matter.
A careful study of the facts can have tremendous influence.
Sophisticated regression analysis can narrow our guesses as to magnitudes. But I don't think we need fancy regression to conclude that people aren't always rational. Or that police can reduce crime. Or to look at the nature of resale price maintenance. On the stuff where people have priors and bias—such as the dynamic impact of taxes on revenue—I don't think the empirical evidence is very convincing of the skeptic.
I understand that science moves slowly and that people at the margin are who eventually count.
But I really don't think the empirical record of sophisticated empirical work is very impressive. In fact, I think I could make a case that sophisticated empirical work is most productive for publishing papers and less productive at establishing truth or useful findings that are reliable.
