Is the Dismal Science Really a Science?

Topics: Economics, Macroeconomics, John Maynard Keynes Pages: 3 (834 words) Published: June 14, 2013
Is the Dismal Science Really a Science?
By Russ Roberts
This article originally appeared in the Wall Street Journal on February 26, 2010

For an economist, these are the best of times and the worst of times. We live in the best of times because everyone wants to understand what happened to the economy and what's going to happen next.

Is the mess we're in a market failure or a government failure? Is the stimulus plan working? Would tax cuts for small business spur employment? When will the job market improve? Is inflation coming? Do deficits matter?

So many questions and so little in the way of answers. And so it is the worst of times for economists. There is no consensus on the cause of the crisis or the best way forward.

There were Nobel Laureates who thought the original stimulus package should have been twice as big. And there are those who blame it for keeping unemployment high. Some economists warn of hyperinflation while others tell us not to worry.

It makes you wonder why people call it the Nobel Prize in Economic Science. After all, most sciences make progress. Nobody in medicine wants to bring back lead goblets. Sir Isaac Newton understood a lot about gravity. But Albert Einstein taught us more.

But in economics, theories that were once discredited surge back into favor. John Maynard Keynes and the view that government spending can create prosperity seem immortal. I thought stagflation had put a stake in the heart of this idea back in the 1970s. Suddenly, he's a genius once again. F.A. Hayek, Keynes's more laissez-faire sparring partner, is drawing interest. There are various monetarists to choose from, too. Which paradigm is the "right" way to think about the boom and the bust? Or are they all wrong?

I once thought econometrics—the application of statistics to economic questions—would settle these disputes and the truth would out. Econometrics is often used to measure the independent impact of one variable holding the rest of the...
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