“DSGE or GTFO”: Macroeconomics took a wrong turn somewhere

Dec 31, JDN 2458119

The state of macro is good,” wrote Oliver Blanchard—in August 2008. This is rather like the turkey who is so pleased with how the farmer has been feeding him lately, the day before Thanksgiving.

It’s not easy to say exactly where macroeconomics went wrong, but I think Paul Romer is right when he makes the analogy between DSGE (dynamic stochastic general equilbrium) models and string theory. They are mathematically complex and difficult to understand, and people can make their careers by being the only ones who grasp them; therefore they must be right! Nevermind if they have no empirical support whatsoever.

To be fair, DSGE models are at least a little better than string theory; they can at least be fit to real-world data, which is better than string theory can say. But being fit to data and actually predicting data are fundamentally different things, and DSGE models typically forecast no better than far simpler models without their bold assumptions. You don’t need to assume all this stuff about a “representative agent” maximizing a well-defined utility function, or an Euler equation (that doesn’t even fit the data), or this ever-proliferating list of “random shocks” that end up taking up all the degrees of freedom your model was supposed to explain. Just regressing the variables on a few years of previous values of each other (a “vector autoregression” or VAR) generally gives you an equally-good forecast. The fact that these models can be made to fit the data well if you add enough degrees of freedom doesn’t actually make them good models. As Von Neumann warned us, with enough free parameters, you can fit an elephant.

But really what bothers me is not the DSGE but the GTFO (“get the [expletive] out”); it’s not that DSGE models are used, but that it’s almost impossible to get published as a macroeconomic theorist using anything else. Defenders of DSGE typically don’t even argue anymore that it is good; they argue that there are no credible alternatives. They characterize their opponents as “dilettantes” who aren’t opposing DSGE because we disagree with it; no, it must be because we don’t understand it. (Also, regarding that post, I’d just like to note that I now officially satisfy the Athreya Axiom of Absolute Arrogance: I have passed my qualifying exams in a top-50 economics PhD program. Yet my enmity toward DSGE has, if anything, only intensified.)

Of course, that argument only makes sense if you haven’t been actively suppressing all attempts to formulate an alternative, which is precisely what DSGE macroeconomists have been doing for the last two or three decades. And yet despite this suppression, there are alternatives emerging, particularly from the empirical side. There are now empirical approaches to macroeconomics that don’t use DSGE models. Regression discontinuity methods and other “natural experiment” designs—not to mention actual experiments—are quickly rising in popularity as economists realize that these methods allow us to actually empirically test our models instead of just adding more and more mathematical complexity to them.

But there still seems to be a lingering attitude that there is no other way to do macro theory. This is very frustrating for me personally, because deep down I think what I would like to do as a career is macro theory: By temperament I have always viewed the world through a very abstract, theoretical lens, and the issues I care most about—particularly inequality, development, and unemployment—are all fundamentally “macro” issues. I left physics when I realized I would be expected to do string theory. I don’t want to leave economics now that I’m expected to do DSGE. But I also definitely don’t want to do DSGE.

Fortunately with economics I have a backup plan: I can always be an “applied micreconomist” (rather the opposite of a theoretical macroeconomist I suppose), directly attached to the data in the form of empirical analyses or even direct, randomized controlled experiments. And there certainly is plenty of work to be done along the lines of Akerlof and Roth and Shiller and Kahneman and Thaler in cognitive and behavioral economics, which is also generally considered applied micro. I was never going to be an experimental physicist, but I can be an experimental economist. And I do get to use at least some theory: In particular, there’s an awful lot of game theory in experimental economics these days. Some of the most exciting stuff is actually in showing how human beings don’t behave the way classical game theory predicts (particularly in the Ultimatum Game and the Prisoner’s Dilemma), and trying to extend game theory into something that would fit our actual behavior. Cognitive science suggests that the result is going to end up looking quite different from game theory as we know it, and with my cognitive science background I may be particularly well-positioned to lead that charge.

Still, I don’t think I’ll be entirely satisfied if I can’t somehow bring my career back around to macroeconomic issues, and particularly the great elephant in the room of all economics, which is inequality. Underlying everything from Marxism to Trumpism, from the surging rents in Silicon Valley and the crushing poverty of Burkina Faso, to the Great Recession itself, is inequality. It is, in my view, the central question of economics: Who gets what, and why?

That is a fundamentally macro question, but you can’t even talk about that issue in DSGE as we know it; a “representative agent” inherently smooths over all inequality in the economy as though total GDP were all that mattered. A fundamentally new approach to macroeconomics is needed. Hopefully I can be part of that, but from my current position I don’t feel much empowered to fight this status quo. Maybe I need to spend at least a few more years doing something else, making a name for myself, and then I’ll be able to come back to this fight with a stronger position.

In the meantime, I guess there’s plenty of work to be done on cognitive biases and deviations from game theory.

The Asymmetry that Rules the World

JDN 2456921 PDT 13:30.

One single asymmetry underlies millions of problems and challenges the world has always faced. No, it’s not Christianity versus Islam (or atheism). No, it’s not the enormous disparities in wealth between the rich and the poor, though you’re getting warmer.

It is the asymmetry of information—the fundamental fact that what you know and what I know are not the same. If this seems so obvious as to be unworthy of comment, maybe you should tell that to the generations of economists who have assumed perfect information in all of their models.

It’s not clear that information asymmetry could ever go away—even in the utopian post-scarcity economy of the Culture, one of the few sacred rules is the sanctity of individual thought. The closest to an information-symmetric world I can think of is the Borg, and with that in mind we may ask whether we want such a thing after all. It could even be argued that total information symmetry is logically impossible, because once you make two individuals know and believe exactly the same things, you don’t have two individuals anymore, you just have one. (And then where do we draw the line? It’s that damn Ship of Theseus again—except of course the problem was never the ship, but defining the boundaries of Theseus himself.)

Right now you may be thinking: So what? Why is asymmetric information so important? Well, as I mentioned in an earlier post, the Myerson-Satterthwaithe Theorem proves—mathematically proves, as certain as 2+2=4—that in the presence of asymmetric information, there is no market mechanism that guarantees Pareto-efficiency.

You can’t square that circle; because information is asymmetric, there’s just no way to make a free market that insures Pareto efficiency. This result is so strong that it actually makes you begin to wonder if we should just give up on economics entirely! If there’s no way we can possibly make a market that works, why bother at all?

But this is not the appropriate response. First of all, Pareto-efficiency is overrated; there are plenty of bad systems that are Pareto-efficient, and even some good systems that aren’t quite Pareto-efficient.

More importantly, even if there is no perfect market system, there clearly are better and worse market systems. Life is better here in the US than it is in Venezuela. Life in Sweden is arguably a bit better still (though not in every dimension). Life in Zambia and North Korea is absolutely horrific. Clearly there are better and worse ways to run a society, and the market system is a big part of that. The quality—and sometimes quantity—of life of billions of people can be made better or worse by the decisions we make in managing our economic system. Asymmetric information cannot be conquered, but it can be tamed.

This is actually a major subject for cognitive economics: How can we devise systems of regulation that minimize the damage done by asymmetric information? Akerlof’s Nobel was for his work on this subject, especially his famous paper “The Market for Lemons” in which he showed how product quality regulations could increase efficiency using the example of lemon cars. What he showed was, in short, that libertarian deregulation is stupid; removing regulations on product safety and quality doesn’t increase efficiency, it reduces it. (This is of course only true if the regulations are good ones; but despite protests from the supplement industry I really don’t see how “this bottle of pills must contain what it claims to contain” is an illegitimate regulation.)

Unfortunately, the way we currently write regulations leaves much to be desired: Basically, lobbyists pay hundreds of staffers to make hundreds of pages that no human being can be expected to read, and then hands them to Congress with a wink and a reminder of last year’s campaign contributions, who passes them without question. (Can you believe the US is one of the least corrupt governments in the world? Yup, that’s how bad it is out there.) As a result, we have a huge morass of regulations that nobody really understands, and there is a whole “industry” of people whose job it is to decode those regulations and use them to the advantage of whoever is paying them—lawyers. The amount of deadweight loss introduced into our economy is almost incalculable; if I had to guess, I’d have to put it somewhere in the trillions of dollars per year. At the very least, I can tell you that the $200 billion per year spent by corporations on litigation is all deadweight loss due to bad regulation. That is an industry that should not exist—I cannot stress this enough. We’ve become so accustomed to the idea that regulations are this complicated that people have to be paid six-figure salaries to understand them that we never stopped to think whether this made any sense. The US Constitution was originally printed on 6 pages.

The tax code should contain one formula for setting tax brackets with one or two parameters to adjust to circumstances, and then a list of maybe two dozen goods with special excise taxes for their externalities (like gasoline and tobacco). In reality it is over 70,000 pages.

Laws should be written with a clear and general intent, and then any weird cases can be resolved in court—because there will always be cases you couldn’t anticipate. Shakespeare was onto something when he wrote, “First, kill all the lawyers.” (I wouldn’t kill them; I’d fire them and make them find a job doing something genuinely useful, like engineering or management.)

All told, I think you could run an entire country with less than 100 pages of regulations. Furthermore, these should be 100 pages that are taught to every high school student, because after all, we’re supposed to be following them. How are we supposed to follow them if we don’t even know them? There’s a principle called ignorantia non excusatignorance does not excuse—which is frankly Kafkaesque. If you can be arrested for breaking a law you didn’t even know existed, in what sense can we call this a free society? (People make up strawman counterexamples: “Gee, officer, I didn’t know it was illegal to murder people!” But all you need is a standard of reasonable knowledge and due diligence, which courts already use to make decisions.)

So, in that sense, I absolutely favor deregulation. But my reasons are totally different from libertarians: I don’t want regulations to stop constraining businesses, I want regulations to be so simple and clear that no one can get around them. In the system I envision, you wouldn’t be able to sell fraudulent derivatives, because on page 3 it would clearly say that fraud is illegal and punishable in proportion to the amount of money involved.

But until that happens—and let’s face it, it’s gonna be awhile—we’re stuck with these ridiculous regulations, and that introduces a whole new type of asymmetric information. This is the way that regulations can make our economy less efficient; they distort what we can do not just by making it illegal, but by making it so we don’t know what is illegal.

The wealthy and powerful can hire people to explain—or evade—the regulations, while the rest of us are forced to live with them. You’ve felt this in a small way if you’ve ever gotten a parking ticket and didn’t know why. Asymmetric information strikes again.