“How can a whole profession fail?” asked Lord Meghnad Desai, Professor Emeritus at the London School of Economics, during an introductory talk on his new book Hubris: Why economists failed to predict the crisis and how to avoid the next one .

He was referring to the way economics is practised today and whether it is out of touch with the real world.

“Even predictions of failure (and the global meltdown) were not taken seriously enough to change the way the system works. And since the crisis began, there is the difference of opinions on how to get the world out of the crisis,” Lord Desai said, in reference to the public spats in recent years between Keynesian theorists who want governments to pump more money in and neo-classical champions of austerity.

In his book, Lord Desai said the world should look at economic cycles – the upturns and downturns – differently. “We need another perspective when looking for evidence of economic cycles. Economists should start looking at cycles not for four-five years but over 200 years (to find different patterns). And then, they must use new statistical techniques to refurbish the old theories.”

Meanwhile, the LSE Professor launched the Meghnad Desai Academy of Economics here in Mumbai.

Starting this July, the academy will offer an 11-month post-graduate programme in economics and finance.

The course costs ₹5.25 lakh (plus taxes) and will accept 30 students. Lord Desai hoped that students would conduct new research into how economic cycles function and are able to better predict the next crisis.

But if everything in economics as we know it now has failed then what kind of statistical modelling and prediction techniques should we look at?

“In economics,” Lord Desai said, “The questions never change, only the answers do. While the book is only a general introduction to the topic, I hope someone in the academia will take up a research programme on how to build a proper model of economics and will lay out guidelines on how to combine long cycles and short cycles and build appropriate models (to understand them).”

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