Fuzzy sets and the biggest scandal in economics
I hope “fuzzy sets” is the correct mathematical term for the concept I’m interest in—ideas that have closely related meanings, without clear and distinct boundaries. In a recent post, Scott Alexander applied this concept in several different contexts. (Read his entire post, there is much more of interest than what I discuss here.) Here’s one example:
[If] you ask people to “value their lives today on a 0 to 10 scale, with the worst possible life as a 0 and the best possible life as a 10”, you will find that Scandinavian countries are the happiest in the world.
But if you ask people “how much positive emotion do you experience?”, you will find that Latin American countries are the happiest in the world.
And if you ask “how meaningful would you rate your life?” you find that African countries are the happiest in the world.
It’s tempting to completely dismiss “happiness” as a concept at all, but that’s not right either. Who’s happier: a millionaire with a loving family who lives in a beautiful mansion in the forest and spends all his time hiking and surfing and playing with his kids? Or a prisoner in a maximum security jail with chronic pain? If we can all agree on the millionaire – and who wouldn’t? – happiness has to at least sort of be a real concept.
The solution is to understand words as hidden inferences – they refer to a multidimensional correlation rather than to a single cohesive property. So for example, we have the word “strength”, which combines grip strength and arm strength (and many other things). These variables really are heavily correlated (see the graph above), so it’s almost always worthwhile to just refer to people as being strong or weak. I can say “Mike Tyson is stronger than an 80 year old woman”, and this is better than having to say “Mike Tyson has higher grip strength, arm strength, leg strength, torso strength, and ten other different kinds of strength than an 80 year old woman.” This is necessary to communicate anything at all and given how nicely all forms of strength correlate there’s no reason not to do it.
But the tails still come apart. If we ask whether Mike Tyson is stronger than some other very impressive strong person, the answer might very well be “He has better arm strength, but worse grip strength”.
This is a problem in economics and other social sciences. Consider:
1. What does it mean to say the labor market is “tight”? That’s not at all obvious. The unemployment rate? Wage growth? The prime age employment ratio? Weekly claims for unemployment compensation? These 4 metrics often give very different answers. And yet most people have an intuitive sense that 2009 was clearly not a tight labor market. So there is a sort of core concept buried here somewhere.
2. What does it mean to say a firm is a monopoly? Is Amazon a monopoly or is retailing highly competitive? While there are different ways of thinking about “monopoly”, almost everyone agrees that the local power company is more monopolistic than the dry cleaning business down the street. So there is a core meaning somewhere.
3. What about political and economic freedom? I recall that California showed up near the bottom in one freedom ranking of US states, and yet life here seems relatively free to me. But perhaps if I were a landlord or businessperson I’d feel differently.
4. There are many ways of measuring inflation, but almost everyone agrees that Venezuela has a high inflation rate. NGDP is also a fuzzy set, but seems less fuzzy than inflation, as you don’t have to worry about quality adjustments and other index number problems.
Alexander uses the example of Mike Tyson and the old lady to suggest that in the extreme cases there is often agreement. I think that’s true, but oddly the happiness example he uses sort of undercuts that claim. Certainly Scandinavia and Africa are pretty far apart under almost any given metric, and yet each leads on one measure of happiness. And even if you don’t think life having “meaning” is a plausible definition of happiness, the high levels of “positive emotion” observed in (poor) places like Central America do call into question our understanding of international happiness rankings. Positive emotion is certainly a plausible definition of happiness, albeit not the only valid one.
I’d say the same about rankings of economic freedom. Hong Kong and Singapore always come first and second, and New Zealand and Switzerland are third and fourth in the most recent Heritage and Cato rankings. So there seems to be a core underlying concept. But other people point to the fact that most of the real estate in Hong Kong is owned by the government. That’s also true in Singapore, which also owns big stakes in many businesses. When you get further down the Heritage and Cato rankings, you start to see significant divergences:
#10 UAE #6 USA
#12 Denmark #16 Denmark
#18 USA #37 UAE
I presume the US/Denmark comparison depends on the relative importance placed on high levels of government spending. As far as the US/UAE comparison, this is presumably one of those “apples and oranges” problems. I’d guess the UAE has really low taxes, but heavy government involvement in the energy industry (which is a huge share of their GDP.) The truth is that all governments are heavily involved in the economy, but in different ways.
So far I do not see any major scandal, just the inevitable problems we have in making sense out of a messy, highly complex world.
Until we get to monetary policy, where there doesn’t seem to be any coherent core meaning at all.
Economists frequently speak of changes in the “stance of monetary policy”, without having the slightest idea of what they are talking about. Easy money? Tight money? What do those terms even mean?
Just a few days ago, markets responded strongly to Jerome Powell’s comments regarding the removal of the term “accommodative” from the official statement of Fed policy. Most people believe Fed policy is gradually becoming less accommodative. I believe the Fed is now becoming more accommodative.
This scandalous lack of clarity on the meaning of the “stance of monetary policy” (and even a lack of clarity as to what we mean by “monetary policy” itself) causes real problems. The Great Recession of 2008-09 was partly caused by the Fed having the mistaken impression that money was “accommodative” during 2008, and hence that monetary policy was “not the problem”. When prominent New Keynesian economists went back and actually studied the period in question, they discovered that money was actually quite tight, in the sense that the policy rate (averaging roughly 2% during 2008) was way above the natural rate of interest (which was negative throughout 2008.) This graph is from an October 2015 paper by Vasco Cúrdia (and kudos to Cúrdia for a pretty accurate natural rate forecast for the following three years):
Just to be clear, this is not just a problem of slight differences in meaning; the disagreement is often most pronounced at the “tails”, such as 1980 and 2009. Thus most economists believe that money was quite tight in 1980 and very accommodative in 2009, whereas the opposite was actually true (and if Milton Friedman were alive he’d likely agree with me):
Low interest rates are generally a sign that money has been tight, as in Japan; high interest rates, that money has been easy.
. . .
After the U.S. experience during the Great Depression, and after inflation and rising interest rates in the 1970s and disinflation and falling interest rates in the 1980s, I thought the fallacy of identifying tight money with high interest rates and easy money with low interest rates was dead. Apparently, old fallacies never die.
This is much different from debates about whether the CPI or PCE is a more appropriate definition of inflation, as both price indices showed high inflation in 1980 and mild deflation in 2009. And even people who point to the heavy ownership of land by the HK government would freely concede that Hong Kong is nonetheless freer than North Korea. But in monetary economics we don’t even agree on the extreme cases.