How much do economists really know?
It’s a question worth asking as the forecast season is upon us. Over the next few weeks, hundreds of economists in government, thinktanks and investment banks will run data through their beloved multi-equation regression models, and try to guess how fast the economy will grow during this financial year. Most will predict a continuation of the good times—and for valid reasons, undoubtedly.
The problem is that economic forecasts have traditionally failed to predict major turning points, when good times turn into bad and vice versa. Go back to 2002. The Indian economy was growing at a snail’s pace. How many economists can you think of who stuck their necks out then and said that India was on the verge of a fantastic boom? There were a few honourable exceptions, but I cannot think of too many. What’s worse, the few economists such as Vijay Kelkar or the Goldman Sachs team, who did say that the Indian economy was headed for a golden run, were often scoffed at. Sure, forecasts do go wrong, but if someone were to do a detailed study of growth expectations in the early years of this decade, you’d find very little bullishness out there. Are there limits to how much we can really know about the economy?
Abhijit Banerjee of the Massachusetts Institute of Technology (MIT) has recently written a wonderful essay that deals with the problem of economic knowledge. It’s called Inside The Machine and was published in the Boston Review. He asks, for example, why China has been such a success story in recent decades. Is it a matter of luck? Do people invest in China because everybody else is? Is it because China has a docile labour force? Or is it because of its entrepreneurs? “The truth is that the Chinese machine has so many potential drivers that it is anybody’s guess why it runs,” says Banerjee. “Moreover, no one really knows why all the forces that could have pushed China the other way—a corrupt and opaque system of governance, a decrepit banking system, dwindling natural resources—have not done more damage.”
Economists these days rarely look at individual countries in isolation. They use cross-country panel data to look at the grander issues. But Banerjee says that these are often not very useful. Take the strong correlation between property rights and average incomes. “The problem is that like many correlations, it is not clear what this ultimately tells us. Is private property secure because rich countries can afford to build a court system that protects it, or have rich countries become rich by offering security of private property?” asks Banerjee.
The problem is that economists see the economy as a giant machine with fixed relationships between the various parts. When I first read Banerjee’s essay and then later met him a couple of months ago, I was reminded of F.A. Hayek’s eloquent Nobel Prize speech in 1974. He titled it The Pretence of Knowledge. There, Hayek said that economics is closer to biology than to physics, in the sense that it examines complex phenomena that cannot be predicted exactly. “I confess I prefer true but imperfect knowledge, even if it leaves much undetermined and unpredictable, to a pretence of exact knowledge that is likely to be false,” said Hayek.
There is no doubt that mathematics does help us understand certain economic relationships. “I want to do this to avoid giving the impression that I generally reject the mathematical method in economics. I regard it in fact as the great advantage of the mathematical technique that it allows us to describe, by means of algebraic equations, the general character of a pattern even where we are ignorant of the numerical values which will determine its particular manifestation. We could scarcely have achieved that comprehensive picture of the mutual interdependencies of the different events in a market without this algebraic technique. It has led to the illusion, however, that we can use this technique for the determination and prediction of the numerical values of those magnitudes; and this has led to a vain search for quantitative or numerical constants,” Hayek said.
Data has become a plaything for economists today, even though their forecasting record with this data has often been pathetic. I have for long been sceptical about the ability of economists (and consultants as well) to exactly predict the really significant long-term trends that change the destinies of nations. The important word here is “exactly”. It is one thing to use general economic principles to predict a broad shift in output or prices. It is quite another thing to pretend that you can tell for sure, right down to the second decimal point.
And now I have to prepare myself to face angry phone calls from my many economist friends.
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