Criticising economics for not being scientific enough is a crime of which many of us are guilty. But there's a right way to do it. Alex Rosenberg and Tyler Curtain, writing in The New York Times , have done it the wrong way. They claim: "Over time, the question of why economics has not (yet) qualified as a science has become an obsession among theorists, including philosophers of science like us ... The trouble with economics is that it lacks the most important of science's characteristics - a record of improvement in predictive range and accuracy ... In fact, when it comes to economic theory's track record, there isn't much predictive success to speak of at all." Economics doesn't have predictive success, eh? Once you look beyond the well-publicised fact that economists can't predict recessions, you can see that the claim just isn't true. My favourite example is the story of Daniel McFadden and the BART. In 1972, San Francisco introduced a new train: the Bay Area Rapid Transit. The authorities predicted that 15 per cent of area commuters would use the system. But, with a grant from the National Science Foundation, University of California, Berkeley, economist McFadden and his team of researchers predicted that usage would be only 6.3 per cent. The actual number? 6.2 per cent. They used models called random-utility discrete choice models, which have been applied in areas such as product development, pricing decisions and marketing. In 2000, McFadden won a Nobel Prize for his efforts. Look at auction theory. Google's real money-maker is the system by which it auctions its advertisement space. Those auctions are conducted with a set-up known as a generalised second-price auction, developed relatively recently by economists such as Hal Varian (now employed by Google). That auction set-up is based on game theory - another basic element of the economics toolbox. Auction theory is focused on predicting which types of auctions most reliably lead to profitable trades. It is more and more crucial to the profits of online-services firms. Want yet another example? So-called gravity models of international trade do a good job of predicting how much trade will occur between any two countries, given the size of their economies and the distance between them. Rosenberg and Curtain are just plain wrong. But economists, don't do a good job of trumpeting their predictive successes to the world. Some economists still defend the idea that economic theory doesn't need to make predictions in order to be useful, and merely has to give people a framework for thinking about the world. That argument hasn't carried much water. Without empirical support, you can't really be confident that a theory is a good framework for thinking about the world. However, detractors of economics tend to ignore the waning of the boom in economic-theory-for-theory's-sake. Theory papers peaked as a percentage of the economics literature sometime in the 1980s, and are now down to less than a fifth of all papers published in top journals. As University of Chicago economist John Cochrane puts it: "Empirical economics has become very fact-oriented in the last 20 years. The stars in their 30s are scraping data off the internet." Connection of theory to reality is becoming more and more important in economics, and predictive success exists in many areas. The notable exception is macroeconomics. In terms of predicting booms and busts, economics is still looking for its first big success. But if you think that predicting recessions is economists' only mission in life, think again.