A plea for consistent income inequality figures

24/05/2018 10:15 / Author: Masja de Ree
Income statistics produced by Statistics Netherlands (CBS) are a rich source of data for scientific research. In order to make even better use of these data for policy purposes and to step up cooperation, CBS and Leiden University organised a meeting for scientists from various research institutes on 24 April 2018. At the meeting, special attention was devoted to the income inequality figure.

Gini coefficient

The nearly 8 million households in the Netherlands do not all have the same income. The Gini coefficient is a measure of inequality, expressed as a value ranging between 0 and 1. A value of 0 means that all households have an equal income while a value of 1 means perfect inequality: one household has all the income and the rest of the households have zero income. In the Netherlands, the Gini coefficient has been relatively stable and low (0.29) for many years in comparison with other members of the European Union.

Trend break

There is, however, something striking about the income inequality figure. Researcher Ferdy Otten of CBS: "We base this figure on income data which have been derived from the data we obtain from the Dutch Tax and Customs Administration (Belastingdienst). We have access to income data as from 1977, but because the Belastingdienst switched to a new system in 2001, there is a trend break in the income inequality figure. Figures from before and after 2001 cannot be adequately compared with each other.” One year ago, Koen Caminada, Professor of Empirical Analysis of Tax and Social Policy at Leiden University, called for a consistent set of income inequality figures. “This is important for our research,” explains Egbert Jongen, researcher at CPB Netherlands Bureau for Economic Policy Analysis and Associate Professor at Leiden Law School. “There is a lot of social debate about income inequality. Has income inequality increased over the longer term or not? There is only one way to establish this properly and that is with a consistent set of figures from CBS.”

“We would be happy to see figures on wealth inequality over time”

Remaining sharp

During the meeting, which was also attended by researchers from other universities, the Dutch central bank (DNB), the CPB Netherlands Bureau for Economic Policy Analysis, several ministries and Netspar, a discussion was held on how to tackle the trend break. Other suggestions for income statistics were discussed as well. The way in which the costs of childcare are included, for example. Jongen: “Not everyone has the same opinion on this, so it’s good to discuss this together.” Jongen has many more ideas: “We would be very happy to have figures on wealth inequality over time. We realise CBS has limited capacity for the compilation of these data. That makes it interesting to work together.”

Practical cooperation

“It was a fruitful meeting,” Jongen says, “Very useful to have an exchange on how CBS obtains its figures and what information is necessary to us researchers. What’s more: we are a big fan of CBS. We are very pleased with the microdata we are allowed to use [under strict conditions, ed.] and which are the envy of our colleagues in other countries.” Ferdy Otten: “We in turn are very happy with all the input we received through this meeting. Discussions help us maintain our focus. It is remarkable how many research institutes rely on CBS figures and that, like CBS, they’re interested in practical cooperation.”

First results of cooperation CBS and the municipality of Leiden
CBS not only plans to team up with Leiden University in the field of income statistics; at the end of last year, the statistics office and the municipality of Leiden signed an agreement to establish the ‘Urban Data Centre Leiden071’. The first payoff from this partnership became known recently: Leiden municipality funds a number of financial support schemes in the form of social assistance to households living below a certain income and wealth threshold. CBS has studied the coverage of these schemes. Overall, coverage was found to be 63 percent of all households involved.