Inequality’s Most Pivotal Scorekeeper?

That just may be Martine Durand, the chief statistician of the developed world’s most important research agency. How does she view her role and our inequality data future? We asked.

To really understand inequality, OECD chief statistician Martine Durand believes, we need yardsticks that tell us what’s happening in every corner of the income distribution, the top included.

Earlier this fall, in Guadalajara, Mexico, the Paris-based OECD — the official economic research agency of the developed world — brought together social scientists from all over the world for its fifth World Forum on Statistics, Knowledge, and Policy.

One of the world’s top experts on inequality, the Nobel Prize-winning economist Joseph Stiglitz, keynoted the gathering, and he gave the OECD considerable credit for helping the world start to understand “that more equal societies perform better” than their more unequal peers.

That better understanding rests, in no small part, on the wealth of data that OECD statisticians have compiled over recent years. The French economist Martine Durand directs the OECD statistical effort, and Sam Pizzigati, the editor of the Institute for Policy Studies inequality monthly Too Much, explored that work with her in an interview at Guadalajara’s World Forum site.

Too Much: This OECD World Forum has been partly about encouraging “people-focused” policy tools for measuring economic activity. Do you think a policy tool can be described as people-focused if it’s difficult for the public to understand. So, for instance, the Gini coefficient for measuring inequality, would you term that a people-focused measurement tool?

Martine Durand: All measures have to be solid conceptually. But you cannot simply say that because a measure may be difficult to explain or to understand, we need to move to another measure. We have to be serious.

But I agree with you that the Gini shouldn’t be the single measure we use. The Gini puts a lot of emphasis on the middle of the income distribution. But we want to understand what’s up in all parts of the distribution, the top and also the bottom, and for that you have simpler measures than the Gini. We have ratios, for instance, between the income share of people in the top 10 percent of the distribution and the population at the bottom end.

TM: Like the Palma ratio, the measure that compares the income share of the top 10 percent to the share of the bottom 40 percent?

Durand: Yes, the Palma ratio can be easier to understand. But I think that each of the measures we have has a particular focus, one for the bottom of the distribution, another one for the top, the Gini for the middle. The panoply of these measures, well explained, will tell you the full story about what’s happening in income distribution, and that’s what probably should be our “people focus.”[pullquote]The Gini coefficient shouldn’t be the only inequality measure we use.[/pullquote]

TM: Does the OECD have a role in developing a global consensus on a particular set of inequality measures?

Durand: If you look at our documents, we present the Gini, we present these other measures. And we go beyond income because if you’re people-focused, you have to realize that inequalities are not just income inequalities.

So in our new publication How’s Life? we present a number of indicators on what matters in people’s lives. We have kind of a dashboard of inequality numbers, and there we have a role to play certainly. We will not come up with a composite single index of inequality.

We’ve also launched on our Web site a tool called Compare your income. People can actually go online and compare their household income to the household income distribution of their country. They can compare where they feel they stand to where they actually stand in reality. They can compare what they would see as the optimum income distribution for their country with the actual distribution. They can see the discrepancy.

We’ve just analyzed these perceptions for some countries, and we see that people at the top part of the income distribution, the richest people, tend to think that they’re in the middle of the distribution. People who are poor also tend to think that. In other words, everybody thinks they’re in the middle.

This Compare your income pedagogical tool provides an understanding of what we mean by income. But we focus a lot on other inequalities as well. We think that’s very important, because people who have low income tend to also accumulate disadvantages in many other areas. We try to paint the full picture.[pullquote]Wealth has become much more unequally distributed than income.[/pullquote]

TM: Let’s switch to wealth for a moment. The Credit Suisse Research Institute has recently released its latest annual Global Wealth Report, and it almost seems that the production of global wealth reports has these days become a private operation. We have reports from all sorts of different financial industry firms, from Credit Suisse and Merrill Lynch to Capgemini and the Boston Consulting Group. Is this something the OECD is also going to do?

Durand: We have actually started. We have just published a paper on the distribution of wealth, and the way we’ve gone about that is exactly what we have done for income distribution. We’ve worked with national statistical offices, and we are collecting data on the wealth distribution for those countries that collect these numbers. For the moment, we have, I believe, 18 countries.

With wealth, even more so than with income, we have a lot of discrepancies on the information that different countries collect. So we spend a lot of time on harmonizing our data.

And the data we have show the same thing as the reports from those private providers. They show that wealth is much more unequally distributed than income. There’s a much higher concentration of wealth.

TM: Does the OECD have a consumer protection role to play here? With all these private wealth reports out there, many making headlines, do you see the OECD in the future comparing these private reports or doing a critique of them?

Durand: In fact, in the working paper I just mentioned we do have an inventory of what’s being done and kind of an assessment of the quality of these other collections. So, yes, we’ve done that. And the Credit Suisse report, we think, probably rates as one of the best.

We have also published two sets of guidelines, one about standards for measuring household wealth and the other on measuring the joint distribution of household income, consumption, and wealth.

We have a big role in designing standards because we want to make sure we compare likes and likes when we do comparative analysis. You would think that when you say income in France, that would be the same as income in the United States, but even the definition of the household, the basic unit of analysis, may differ from one country to another. We provide guidelines to national statistical offices so we are all standing on the same ground.

TM: This past August, the Securities and Exchange Commission in the United States adopted final regulations that require publicly traded corporations to annually disclose the ratio between their CEO and median worker compensation. India last year put similar regulations into effect, and there’s a strong movement in the UK to introduce a similar sort of corporate disclosure requirement. Does the OECD have a statistical advocacy role in promoting new information sources like these disclosure requirements?

Durand: I don’t think so, not for the moment. But on the other hand we have another instrument, our corporate governance guidelines. These are regularly revised and encompass these sorts of recommendations.

Sam Pizzigati edits Too Much, the Institute for Policy Studies online monthly on excess and inequality. His latest book: The Rich Don’t Always Win: The Forgotten Triumph over Plutocracy that Created the American Middle Class, 1900-1970 (Seven Stories Press).