Instrumental beliefs, prediction and reality
Note: Feel free to skim past the philosophy to the discussion of monetary policy at the end.
In a recent podcast, Penn Jillette said something to the effect that people don’t believe conspiracy theories because they are true, rather because they are entertaining, like a good story or a good song.
The term ‘entertaining’ has a rather frivolous connotation, so lets make the concept more general and include beliefs that add deep and profound meaning to life, in areas such as art, religion, and politics.
There is another set of beliefs about the world that are more instrumental. If I believe the two objects in front of my eye are a hammer and nail, it’s not because I enjoy this belief, rather because this belief is useful. I know (or “predict”) that if I pick up the hammer I can drive the nail through a piece of wood. Similarly, I believe that New York City exists in the sense that I predict that if I traveled to that spot I’d see tall buildings, art galleries and yellow taxis.
So you might say that our view of reality is a set of beliefs that we find either directly rewarding or at least instrumentally useful. In the rest of this post I’ll mostly focus on the latter.
The sciences contain the most famous examples of instrumental beliefs. In principle, the laws of “physics” should be able to explain the behavior of the entire physical universe, or at least the non-random portion. But in practice, people use the term ‘physics’ to refer to the subset of physics problems that are very simple and easy to model. The term ‘chemistry’ refers to physics problems that are slightly messier and more complex, whereas geology, meteorology, ecology and economics refers to highly complex areas of physics—the motion of molecules in complex and chaotic environments.
In the simpler branches of science, it is possible to do controlled experiments and reach a broad consensus about cause and effect. Two physicists will have similar predictions about the speed at which an object will fall if dropped in a vacuum at sea level. In contrast, in the more complex sciences even the experts will often disagree, as it is tough to do controlled experiments that replicate the specific empirical question you want answered. What controlled experiment would tell you the odds of an 8.0 earthquake in LA next year, or the odds of global temps rising by 2 degrees by 2100, or the odds of rhinos going extinct in the wild by 2100, or the odds of a recession in 2021?
So this raises an important question. How should “we” decide what to believe about reality in the areas where the systems are complex? If the “we” is policymakers, then Robin Hanson has argued that prediction markets are the best way to ascertain the truth. I agree.
But most people disagree and are skeptical of market forecasts; they would rather import the methods of the “hard sciences”. Let the experts decide. Let experts set monetary policy. If not all experts agree, then let a panel of 12 experts vote on the policy, majority rules. (Actually, not all FOMC members are experts.)
People often define fault lines in economics in terms of left/right, Keynesian/classical, Austrian/Marxist, etc. But the fault line that really matters is methodological. How do we decide what we know?
The standard view is that reality is best understood in terms of what the experts believe to be true. I see reality as what the markets believe to be true. Expert opinion is an input, but only one of many inputs, into market forecasts.
In the past, the Fed has tended to rely on the experts. (Albeit not exclusively, they have always paid some attention to markets.)
You might wonder why I spend so much time fighting against the asset price bubble view of markets. If bubbles exist, if they are a part of reality, then they are useful for making forecasts. (I’m ignoring the fact that people might get utility merely from believing in bubbles.) If they are useful, then market forecasts are not reliable, and that makes expert opinion relatively more valuable. The fight over bubbles is a fight over the future of macroeconomics.
I’m actually not ideologically opposed to rule by experts—after all, I’m an expert on monetary policy. I’d like to be a ruler, to have others ask me where the Fed should set interest rates. But my reading of the evidence suggests that market forecasts are superior. Thus I try to infer the market prediction of the interest rate most likely to achieve the Fed’s policy goal.
Robert Shiller is one of the most famous proponents of the view that asset price bubbles are important. Thus you’d also expect him to be skeptical of the view that markets can guide monetary policy. And that seems to be the case.
Consider the past 12 months, a good example of the difference between expertise and markets. Monetary policy experts tend to rely on Phillips curve type models, which suggest that very low unemployment is a sign the economy is in danger of overheating. Here’s a discussion of Robert Shiller’s ideas from July of this year:
Nobel-prize winning economist Robert Shiller sees justification for a quarter-point interest rate hike.
That’s right: A hike — not the cut Wall Street is expecting Wednesday from the Federal Reserve.
“We still have a very low unemployment rate. The economy is hot,” the Yale University professor told CNBC’s “Trading Nation” on Monday. “One could easily make a case for staying the course and doing another interest rate increase at this meeting to cool this economy.”
That’s an almost perfect example of the methodological split that I described earlier. “Nobel-prize winning” vs. “Wall Street”. The financial markets were suggesting that inflation would stay low even if the Fed cut interest rates; whereas Shiller worried that the economy would overheat, even without a rate cut. Olivier Blanchard recently expressed similar concerns, although he later backed off a bit.
This year, the Fed decided to follow the markets and ignore the models constructed by experts. That’s partly because even the experts are losing a bit of faith in Phillips curve models as a policy tool. Even some of the experts are beginning to follow the markets.
The view that markets should guide monetary policy is just one part of a much broader agenda—markets should determine what is true, what is reality.
Consider the following two cases:
Los Angeles policymakers decide to spend $300 million in a new high school, believing it will make LA better off.
A small town in New Hampshire holds a town meeting, and decides to spend $2 million remodeling an elementary school, believing if will make the small town better off.
I would argue that while neither decision is, strictly speaking, a market outcome, the New Hampshire town more closely mimics a market. That’s because the decision-makers in LA have almost no personal stake in what happens. They are engaged in “expressive voting”. It makes them feel good to build a shiny new high school for mostly low-income students. Sort of like when Penn Jillette’s acquaintances believe in conspiracy theories. In the New Hampshire town, the residents who vote at the town meeting have a real stakes in the decision. It will affect their property taxes and their children’s education.
[Yes, even LA policymakers pay property taxes, but the gains they personally derive from “big government” far outweigh the cost of their taxes going up.]
This also explains why Switzerland is more successful than most other countries; its policymaking apparatus more closely resembles a market outcome.
At the Fed, some people feel good when they vote in a “dovish” or “hawkish” direction. They have a lot invested in their ideology. Contrast that with Wall Street. In 1932, New York financiers voted for Herbert Hoover. But in 1933, the financial markets “voted” that FDR’s policies were likely to boost prices and output. Markets are unsentimental, and hence more likely to produce useful predictions, useful maps of “reality”.
Unlike markets, Fed officials are reluctant to reverse course soon after a major decision, as it makes them look bad—to most people, not to me. I have a higher opinion of Powell after he reversed course on interest rates. I believe the Fed was right to raise rates in 2017-18, and right to cut them this year. Why? Because the outcome was good.
PS. The question of whether reality is actually “out there” or is merely a mental construct is not important for the purposes of this post, or indeed for any other purpose.