Income, consumption and wealth Income, consumption and wealth

Why do we produce statistics on the joint distribution of income,
consumption and wealth?    Experimental statistics logo

Disparities in income and wealth are increasingly scrutinized, not only by the academic world but also by the public. The joint distribution of income, consumption and wealth data provides links between the three economic dimensions. These data help to describe more thoroughly material well-being and households' economic vulnerability. They also help to explain the dynamics of wealth inequalities. Further details on the results and the derived indicators can be found here.

Why are these data published as 'experimental statistics'?

To obtain statistics on the joint distribution of income, consumption and wealth requires that information on these three dimensions is collected/available for the same household. This can be very cumbersome and almost impossible, in particular if surveys are used.
To overcome this, the European Statistical System has proposed several options (see in particular Vienna conference). The only option that could be implemented immediately consists of merging information coming from different datasets/data sources. This merged dataset contains information on the three dimensions for each household. To build such a dataset, some assumptions needed to be made. These assumptions, which are well documented in academic literature, are based on the hypothesis that the link between income, consumption and wealth could be completely explained by the other variables such as age, household structure, etc. that all data sources have in common. However, depending on the variables, such an assumption can be easily challenged.

Feedback

European statistics user forum bannerTo help us improve these experimental statistics, users and researchers are invited to participate in the dedicated discussion on the European Statistics User Forum, focusing on the following questions:

  • How useful are such indicators? Would you recommend the publication of other indicators, which ones?
  • Would you recommend having access also to data on uncertainty? In case yes, would you like the statistics to come along with information on the range of plausible values for the indicator?

Here is a specific question for researchers who can be granted access to microdata for scientific purpose: Would you consider it useful to have access to scripts that performed the matching, provided that you have access to the necessary microdata?