Inequality matters. Photographer: Tim Graham/Getty Images Photographer: Tim Graham/Getty Images
Inequality matters. Photographer: Tim Graham/Getty Images Photographer: Tim Graham/Getty Images

Wherever the debate about the data in Thomas Piketty's work on inequality may lead, there's at least one bright side: The argument itself reflects a desirable shift in the field of economics toward answering questions that really matter.

Economics, at its best, is about what makes us better off and how we can have more of it. For decades preceding the financial crisis, though, the mainstream strayed from that laudable goal. The workhorse models economists used to understand the world became largely thought experiments, filled with perfectly rational beings, benign equilibriums and absurd assumptions that bore little relation to reality. As a result, the crisis caught much of the profession unprepared.

Piketty's approach is completely different. He focuses on three profoundly relevant questions: What is happening with inequality, is it a problem for society, and what can be done about it? He has spent much of his academic career collecting and cobbling together the data on income and wealth needed to find answers. He has put the data online for others to use, and helped create valuable resources such as the World Top Incomes Database.

Many, including Bloomberg View, reasonably disagree with the sweeping conclusions Piketty has drawn from his data, and the Financial Times has stirred up controversy by questioning some of the wealth data. In doing so, they contribute to our understanding of a phenomenon crucial to our well-being. This wouldn’t be possible without Piketty's original work.

Piketty is not alone. The style of empirical economics he represents is enjoying a sort of renaissance. Consider the work of Raj Chetty and colleagues on equality of opportunity, Carmen Reinhart and Kenneth Rogoff on the history of financial crises, Justin Wolfers and Betsey Stevenson on happiness, or Amy Finkelstein and co-authors on the Oregon Health Insurance Experiment.

One takeaway from Piketty's experience -- and from that of Reinhart and Rogoff before him -- is that empirical work is difficult. Cobbling together big data sets and teasing out the important trends involve all manner of assumptions, adjustments and judgment calls. Errors are inevitable, and decisions should be questioned. The more transparent the process, and the more people try to replicate the work, the faster our understanding will develop.

In this spirit, whether Piketty or any of these researchers are "right" or "wrong" hardly matters. As long as they are acting competently and in good faith, and generating data that others can use to explore relevant questions, they are absolutely heading in the right direction.

To contact the writer of this article: Mark Whitehouse at mwhitehouse1@bloomberg.net.

To contact the editor responsible for this article: Max Berley at mberley@bloomberg.net