A different way to tell a story.

Photographer: Peter Macdiarmid/Getty Images

In Search of the Science in Economics

Noah Smith is a Bloomberg View columnist. He was an assistant professor of finance at Stony Brook University, and he blogs at Noahpinion.
Read More.
a | A

Economics, as a profession, gets a lot of grief -- from within its own ranks, from other disciplines and from the public at large. Some of this criticism is well-deserved, but other points are way off the mark. In particular, I’d like to discuss the idea that economics is only a social science, and should discard its mathematical pretensions and return to a more literary approach. 

First, let’s talk about the idea that when you put the word “social” in front of “science,” everything changes. The idea here is that you can’t discover hard-and-fast principles that govern human behavior, or the actions of societies, the way physicists derive laws of motion for particles or biologists identify the actions of the body’s various systems. You hear people say this all the time

But is it true? As far as I can tell, it’s just an assertion, with little to back it up. No one has discovered a law of the universe that you can’t discover patterns in human societies. Sure, it’s going to be hard -- a human being is vastly more complicated than an electron. But there is no obvious reason why the task is hopeless. 

To the contrary, there have already been a great many successes. Economists, for example, have been able to understand a lot about how groups of human beings bid in auctions. Think about what an achievement that is! A group of people enter an auction hall, with a mix of different backgrounds, different emotional tendencies, different desires and different levels of understanding. And yet despite all that kaleidoscopic diversity, an economist can walk into that hall and hand the auctioneer a post-it note with a few simple rules that will almost always make the auction take less time and leave the bidders more satisfied. 

That isn’t just a hypothetical situation. It’s the force that powers the Internet that you use every day. The Internet is funded mostly by advertising, and online ads are sold using an auction method created by economists. It is in large part thanks to social science -- and mathematically precise theories of human behavior -- that the Web is so effective at getting you the information you want, and that companies such as Google can make money and hire people. 

It isn't always so easy, of course. Humans are smart. We can break or circumvent any rules that society lays down. If you find a rule that appears to describe how groups of people act, you should be very careful about trying to use that rule to control people. If you do, you will often be disappointed. For example, if you discover that more crimes are committed on Thanksgiving, you might try to reduce law-breaking by putting more cops on the street on that day. But the criminals might just switch to Christmas or Halloween. This is why economist Charles Goodhart counsels against trying to use empirical correlations as tools of social control. 

But sometimes, you really can design human systems that work. For example, creating universal norms of sanitation has dramatically reduced the threat of communicable disease. Taxing people to pay for roads has resulted in more, better roads than we would have had if things had been left to the private sector. Everywhere we look, we see examples of social science at work. 

What about math? It’s true that many of social science’s greatest successes have come without any equations, theorems or computer simulations. You don’t need matrix analysis to know that if you tell everyone to wash their hands, infections will go down. Does this mean that economists should give up the fancy tools that they are so enamored with? Should they simply walk around observing humans and writing long, literary descriptions of how they think the economy behaves? 

Occasionally, perhaps. I do think economists would often benefit from closer observation of the real world. For example, macroeconomists have been scrambling since 2008 to put banks into their models of the business cycle, but these models are probably not good descriptions of the way banks actually behave. Macroeconomists would be well-advised to consult banking researchers in the finance departments of business schools, who have spent their lives studying real-world banks. Inevitably, that kind of communication is going to require English (or some other written language), rather than math. Math is precise, which makes it good for modeling behavior, but bad for communicating general ideas. 

But that doesn’t mean math needs to go. Math allows quantitative measurement and prediction, which literary treatises do not. It was math that led to auction theory and to improved systems for organ exchange, or to any number of other successful economic theories that have been applied throughout our society. 

It is math that allows economic forecasters to make quantitative predictions of all types. Those predictions are not always accurate, and they don’t reach that far into the future, but they are far better than the vague forecasts of people who use only words. 

And it is math -- statistics, actually -- that allows economists to use natural experiments to understand which policies work and which don’t. Math is an essential tool of the empirical revolution that is reshaping the economics profession for the better. 

So yes, social science can be science. There will always be a place in the world for people who walk around penning long, literary tomes full of vague ideas about how humans and societies function. But thanks to quantitative social science, we now have additional tools at our disposal. Those tools have already improved our world, and to throw them away would be a big mistake.

This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.

To contact the author of this story:
Noah Smith at nsmith150@bloomberg.net

To contact the editor responsible for this story:
James Greiff at jgreiff@bloomberg.net