It starts with a general concern about comparing economics to other sciences. He writes:
"I’m not sure what it is about economics that makes both its adherents and its detractors feel the need to make constant analogies to other sciences, particularly physics, to try to justify their preferred approach. Unfortunately, this isn’t just a blogosphere phenomenon; the type of throwaway suggestion you get in internet debates. This problem appears in every area of the field, from blogs to articles to widely read economics textbooks."This is frustrating to me too, but it's inevitable to a certain extent. The scientific credentials of economists are regularly questioned for at least two reasons: (1.) people think they're special and reject the idea that their behavior can be studied the same way ape behavior can be, even though we're all just apes. Anatomists and psychologists can often skirt this because we can accept that our brain or our arm or our heart is a "thing" and amenable to study, but when it comes to our social life we get more nervous (even though we think it's perfectly sensible to study the social behavior of other species of ape). (2.) economists are human beings that care about human problems and we have expertise in the economy so we naturally talk about normative things a lot. That's totally fine, but it gives some people the impression that the science of economics is just a sort of extension of political discussions.
If your scientific credentials are questioned, the appropriate thing to do is defend them, and that often comes in the form of "well you accept X as science when Y scientists do it so why isn't economics a science?". We obviously bear some resemblance to all sciences, including physics. Regular readers know, though, that I think the closer cousin is biology for obvious reasons. If gorillas were the primary authors of economics articles, it would be quite clear that economists are biologists, in fact. Since we are biologists, it's no wonder that the best analogies are to non-economist biologists.
He goes on to criticize what I think is a very good point by Greg Mankiw:
"Another, more worrying example, is Greg Mankiw’s widely read Macroeconomics textbook (7th ed, p. 395), when discussing estimates of the NAIRU:As far as measurement and empirics goes, I've always especially liked the physics analogies at our disposal. I'm no physicist, so take that into account in my use of terminology and my approach and try to be kind in distinguishing errors in style from errors in substance!
"If you ask an astronomer how far a particular star is from our sun, he’ll give you a number, but it won’t be accurate. Man’s ability to measure astronomical distances is still limited. An astronomer might well take better measurements and conclude that a star is really twice or half as far away as he previously thought."Mankiw’s suggestion astronomers have this little clue what they are doing is misleading. We are talking about people who can calculate the existence of a planet close to a distant star, based on the (relatively) tiny ‘wobble’ of said star. Astronomers have many different methods for calculating stellar distances: parallax, red shift, luminosity; and these methods can be used and cross-checked against one another. As you will see from the parallax link, there are also in-built, estimable errors in their calculations, which can help them straying too far off the mark. While it is true that at large distances, luminosity can be hard to interpret (a star may be close and dim, or bright and far away) Mankiw is mostly wrong. Astronomers still make many, largely accurate predictions, while economist’s predictions are at best contested and uncertain, or worse, incorrect. The very worst models are unfalsifiable, such as the NAIRU Mankiw is defending, which seems to move around so much that it is meaningless."
Two unknowns are particularly relevant in thinking about stars we observe: brightness and distance. Since we only have one observation at our disposal, we have an identification problem. You need to pin down one of those two things with something you have more confidence in, and then you can back out the other. For astronomers, this means taking a "standard candle" - a similar star of known brightness and distance - and using the inverse square law to back out the distance of the observed star.
This is exactly like an instrumental variable problem. We are interested in supply elasticities and demand elasticities, but a sest of observations does not give us either of those. When we look at variations in the price and quantity of an object we don't know the mix of a change in demand and a change in supply that causes those observations to change. So we look for standard candles, or as economists call them - instruments. We take a known, independent shift in one of the magnitude (say, supply) and then with a little math we can back out the value of the other (demand).
There are other strategies that are similar. Now that I have written this, I realize that a better analogy to standard candles and the inverse square law is probably difference-in-differences. The instrumental variable approach of economists is maybe more comparable to exoplanet detection by physicists (with the regular dimming of a star and the wobble of a star doing the work)?
All of these, however, are variations on the same theme. Most quasi-experimental methods in economics are statistically variations of each other.
The point here is that astronomers largely use quasi-experimental methods too, and the motivation and solution is identical to the things that econometricians do.
This is not the result of physics envy. This is because of the fundamental gulf between observation and explanation that is true of any human interaction with the world.