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May 29, 2014

Why Thomas Piketty should have chosen his software more carefully

Or why you shouldn't use spreadsheets to crunch heavy stats

By Cbr Rolling Blog

It’s been hard to open a paper these past few weeks without seeing some article about Thomas Piketty, a French economist whose recent book "Capital in the Twenty-First Century" has captured the post-crash anxiety over financial inequality.

Newspapers as laissez-faire as the Economist were not alone in highlighting the strength of his statistical analysis, even as they rebuffed his policy recommendations. The consensus was that the man knew how to work a spreadsheet, at least until the Financial Times went on the attack last weekend.

The Financial Times’ economics editor Chris Giles accused Piketty of "fat finger" mistakes in transcribing data, and even fixing data to suit his argument. Piketty dismissed the complaints, saying "I have tried … to make the most justified choices and arbitrages about data sources and adjustments," before adding that he felt sure others would improve on his analysis in the future.

Yet a computer scientist from Montreal, Canada has now argued that Piketty’s mistakes were neither the result of bending data to fit trends nor ham-fisted typing, but were instead caused by his use of the wrong software.

Writing on his personal blog Damien Lemire, professor at University of Quebec, said: "Spreadsheets are convenient but error prone. They are at their best when errors are of little consequence or when problems are simple. It looks to me like Piketty was doing complicated work and betting his career on the accuracy of his results."

Lemire drew comparisons between Piketty and Harvard professors Carmen Reinhart and Kenneth Rogoff, who wrote a paper and a book on the relationship between national debt and economic growth. Thomas Herndon, a graduate student, was not able to achieve their findings with the data they had released online, and when they sent him their Excel spreadsheet he found it riddled with problems.

"I think that economists will have to cope with very complex and abundant data," Lemire writes. "They will need to do ever more complicated analysis. I hope that they will learn to use better tools and techniques."

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