If DSGE models work, why don't people use them to get rich?
When I studied macroeconomics in grad school, I was told something along these lines:
"DSGE models are useful for policy advice because they (hopefully) pass the Lucas Critique. If all you want to do is forecast the economy, you don't need to pass the Lucas Critique, so you don't need a DSGE model."
This is usually what I hear academic macroeconomists say when asked to explain the fact that essentially no one in the private sector uses DSGE models. Private-sector people can't set economic policy, the argument goes, so they don't need Lucas Critique-robust models.
The problem is, this argument is wrong. If you have a model that both A) satisfies the Lucas Critique and B) is a decent model of the economy, you can make huge amounts of money. This is because although any old spreadsheet can be used to make unconditional forecasts of the economy, you need Lucas-robust models to make good policy-conditional forecasts.
Let me explain. An unconditional forecast is when you say "GDP growth will be 2.4% next year", or "inflation will be 1.7% next quarter". For this kind of thing, any old spreadsheet will do.
A policy-conditional forecast is when you say "If the Fed tapers, inflation will fall by 0.5% next year." To get these forecasts as good as possible, you need to know how policy affects the economy. and if your model is not Lucas-robust, then you will not be able to know how policy affects the economy, so you will react sub-optimally to a policy change.
For example, suppose the Fed suddenly lowers interest rates substantially. Most people, using their silly spreadsheets with their 70s-vintage Phillips Curves, will forecast a rise in GDP growth, so they will pay a lot for stocks, expecting higher profits from the increased growth. But wise DSGE modelers, using the Nobel-winning and ostensibly Lucas-robust Kydland-Prescott 1982 model, know that the Phillips Curve is not structural. They know that the promised growth will not occur, so as soon as stocks become overpriced, they short the S&P. When the hoped-for growth does not materialize and stocks fall, the DSGE modelers reap a huge profit at the expense of the spreadsheet modelers.
Now that's a bit of an old example, so let's take a more modern one. Suppose the Fed launches a new program of QE. Clever DSGE modelers, armed with Steve Williamson's 2013 QE paper, know that QE will be deflationary rather than inflationary (as most people think). This allows them to take other investors, who are armed only with spreadsheets, for a ride, shorting TIPS and buying Treasuries. Voila - instant riches. Williamson himself endorses this idea, writing:
[I]f it does anything, QE will lower the inflation rate over the long run. And the long run comes sooner than you might think, i.e. if QE gives you a short-run increase in inflation, then if it's like typical monetary easing, then that effect lasts only a year or two. More to the point, there are other forces post-financial crisis that will cause the real interest rate on safe assets to rise, and inflation to fall further, so long as the Fed keeps short nominal rates at or near the zero lower bound. And there are good reasons to think that the Fed will be stuck at the zero lower bound indefinitely. Conclusion: expect less inflation rather than more. That has to matter for your portfolio choices. (emphasis mine)So as we see, a Lucas-robust DSGE model has the potential to make its wielders a LOT of money. This is especially true in the current environment, where correlations are high and macro events have become much more important to investors' performance.
But not necessarily. Being Lucas-robust is necessary for making optimal policy-contingent forecasts, but it is not sufficient. You also need the model to be a good model of the economy. If your parameters are all structural, but you've assumed the wrong microfoundations, then your model will make bad predictions even though it's Lucas-robust.
So now let's get to the point of this post. As far as I'm aware, private-sector firms don't hire anyone to make DSGE models, implement DSGE models, or even scan the DSGE literature. There are a lot of firms that make macro bets in the finance industry - investment banks, macro hedge funds, bond funds. To my knowledge, none of these firms spends one thin dime on DSGE. I've called and emailed everyone I could think of who knows what financial-industry macroeconomists do, and they're all unanimous - they've never heard of anyone in finance using a DSGE model.
If you know someone who does, please reply in the comments. I'm sure there's someone out there. But even if there is, they haven't soared to fame and fortune on the back of their DSGE model.
So maybe they're just using the wrong DSGE models? Maybe they're using Williamson (2012) instead of Williamson (2013). I mean, after all, there is a huge, vast, unending array of DSGE models out there, most of which purport to explain the entire macroeconomy, and most of which are thus mutually exclusive at any point in time. Maybe two or three of them are right at any given point in time, but maybe this set switches around as conditions change. Perhaps finance-industry people are simple unable to pick out the right DSGE model to use on any given day.
But if finance-industry people can't know which DSGE model to use, how can policymakers or policy advisors?
In other words, DSGE models (not just "Freshwater" models, I mean the whole kit & caboodle) have failed a key test of usefulness. Their main selling point - satisfying the Lucas critique - should make them very valuable to industry. But industry shuns them.
Many economic technologies pass the industry test. Companies pay people lots of money to use auction theory. Companies pay people lots of money to use vector autoregressions. Companies pay people lots of money to use matching models. But companies do not, as far as I can tell, pay people lots of money to use DSGE to predict the effects of government policy. Maybe this will change someday, but it's been 32 years, and no one's touching these things.
As I see it, this is currently the most damning critique of the whole DSGE paradigm.
Matt Yglesias comments.
Tony Yates comments, at greater length.
The anonymous denizens of EJMR discuss DSGE and the private sector. Interesting post:
Insider in a small, boutique private equity firm. We do not use DSGE models, but we do use DSGE models as a screening device, in the same spirit as graduate programs use real analysis. It turns out that we can get these guys cheaper than MBAs, and they have similar levels of firepower.So DSGE does function as a kind of signaling - the ability to make DSGE models is valuable to companies even if the models themselves aren't, because they indicate general intelligence, computer skills, creativity, and/or work ethic. That makes sense.
Chris House, my old first-year macro instructor and a prof at the University of Michigan, has A) started a blog, which you should read, and B) attempted to rebut this post. Check it out! Fun fact: The argument in quotes at the top of this post is actually paraphrased from stuff Chris House said to me, which is very similar to what he now writes in his post. I must say, though, I think Chris' post actually reiterates and strengthens the point I make in my post. The difference between policy-conditional and other forecasts is key here. If the average policymaker can use a DSGE model to improve her predictions of the results of her policies, then the average financial trader can use the same model to improve her predictions of the results of the policymaker's policies.
Tyler Cowen thinks I'm too quick to dismiss DSGE, and that instead, critiques like this one should merely make us "downgrade" DSGE. This is a very Bayesian approach, and I like it. But notice that Bayesian beliefs depend on your priors. If you started out thinking that DSGE was totally awesome, then critiques like this one should make you temper your enthusiasm. But if you started out thinking that DSGE was hocus-pocus, then critiques like this should tend to strengthen your belief somewhat.