Macro modeling godfather Tom Sargent was interviewed by the Minneapolis Fed. When asked about the problems of Macro, he instantly offered these examples of success:
important parts of modern macro are about understanding a large and interesting suite of asset pricing puzzles, brought to us by Hansen and Singleton and their followers—puzzles about empirical failures of simple versions of efficient markets theories. Here I have in mind papers on the “equity premium puzzle,” the “risk-free rate puzzle,” the “Backus-Smith” puzzle, and on and on.
The only real progress I've seen on the equity risk premium is noting it is not nearly as large as initially thought (down from 6.9% to 3.5% by most economists). The theoretical explanations have generally focused on fat tails. This was first proposed as a solution to the equity risk premium by Thomas Rietz in 1988, and later extended by people like Gabaix, Wietzman, and Barro. But they have as their basic problem their solutions generalize and the 'equity risk premium' does not: any of these solutions creates more puzzles than it solves. If this is exhibit A for Sargent, it's clearly bad news for Macro.
The Backus-Smith puzzle relates to how 'real exchange rates' and consumption are not correlated like they 'should be', and the 'risk free rate' puzzle is why are interest rates so low? Since when has creating puzzles been the main point of science? Sure, puzzles are interesting when they are like condiments on your hot dog, but when ketchup is your main meal it's no longer appreciated. While the big things are unanswered (eg, why is Mexico poorer than the USA? What causes business cycles?), the last thing we need are more puzzles. My favorite characteristics of a healthy science are the old fashion ideas like 'explaining more with less', 'estimating important relationships more precisely', or 'predicting out of sample'.
Interestingly, Sargent highlights a dog that didn't bark in this crisis, specifically, the irrelevance of 'behavioral economics' to say much about anything:
Rolnick: I’ll come back to that in a second, but you haven’t said anything yet about what is to be gained in terms of understanding financial crises from importing insights of behavioral economics into macroeconomics.
Sargent: No, I haven’t.
Sargent goes on to point out the relevance of some work on bank runs to the 2008 crisis:
Rolnick: please elaborate further on macro scholarship and financial crises.
Sargent: I like to think about two polar models of bank crises and what government lender-of-last-resort and deposit insurance do to arrest them or promote them. Both models had origins in papers written at the Federal Reserve Bank of Minneapolis, one authored by John Kareken and Neil Wallace in 1978 and the other by John Bryant in 1980, then extended by Diamond and Dybvig in 1983.9 I call them polar models because in the Diamond-Dybvig and Bryant model, deposit insurance is purely a good thing, hile in the Kareken and Wallace model, it is purely bad. These differences occur because of what the two models include and what they omit.
So, of those two models, the Kareken- Wallace model makes you very cautious about lender-of-last-resort facilities and very sensitive to the risk-taking activities of banks. The Diamond-Dybvig and Bryant model makes you very sensitive to runs and very optimistic about the ability of insurance to cure them. Both models leave something out, and I think in the real world we’re in a situation where we have to worry about runs and we also have to worry about moral hazard. As you know, an mportant theme of research for macroeconomics in general and at the Minneapolis Fed in particular has been about how to strike a good balance.
So, they have these great models for two unrealistic cases with opposite implications, and reality is somewhere in between. Unless one can be a little more specific about how to split the difference, I do not see how this framework helps. It's like saying, government spending is beneficial if there is no crowding out of investment, wasteful if there is complete crowding out, and the answer is in the middle. Everything, alas, is an empirical issue, and we don't have enough data.
Sargent's best paper in my opinion is his 'Some Unpleasant Monetarist Arithmetic', which used mere algebra to show a scenario where budget deficits imply a trade-off between some inflation now or more inflation later. I think it will be his signature economic insight. Sargent was one of the those macroeconomists who made the bad inference that since some rigor is good, rigor is not just better, but the very essence of science, and the implications of all these highly parochial, unreal models would manifest itself like a Seurat painting seen from a distance. This was just a really bad idea, one that Frederich Hayek warned about but no one listened too. Smart people can be very clueless when they apply too much precision to imprecise problems.