The Dangers of Scientific Capitalism

Cloud Daniel Cloud in Project Syndicate:

Military strategists have known for centuries that there is, and can be, no final science of war. In a real struggle over things that actually matter, we must assume that we are up against thinking opponents, who may understand some things about us that we don’t know about ourselves. For example, if profit can be made by understanding the model behind a policy, as is surely the case with the models used by the United States Federal Reserve, sooner or later so much capital will seek that profit that the tail will begin to wag the dog, as has been happening lately.

The truth is that such models are most useful when they are little known or not universally believed. They progressively lose their predictive value as we all accept and begin to bet on them. But there can be no real predictive science for a system that may change its behavior if we publish a model of it.

Markets might once have been fairly efficient, before we had the theory of efficient markets. If investing is simply a matter of allocating money to an index, however, liquidity becomes the sole determinant of prices, and valuations go haywire. When a substantial fraction of market participants are simply buying the index, the market’s role in ensuring good corporate governance also disappears.

The formation of large bubbles in recent decades was partly a consequence of the commonness and incorrigibility of the belief that no such thing could ever happen. Our collective belief that markets are efficient helped make them wildly inefficient.

Despite this, over the course of the last 20 years, economists began to act as if we thought we could genuinely predict the economic future. If the universe didn’t oblige, it wasn’t because our models were wrong; “market failure” was to blame. It is not clear how we could know that markets were failing whenever they fell significantly, but believed that we had no business second-guessing them when they climbed.