European Rich List Database [erldb]

The European Rich List Database provides information on the richest individuals in Europe. The dataset comprises more than 13,300 observations from 23 countries and is mainly based on journalistic data collections.

Rich lists provide important information for estimating the missing top in wealth distributions based on survey data. These lists are commonly used as auxiliary information in statistical estimations to obtain a more realistic assessment of wealth distribution. The data may only be used for research purposes.

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The European Rich List Database is available for research at:

Disslbacher, F., Ertl, M., List, E., Mokre, P., Schnetzer, M. (2022): European Rich List Database (ERLDB)
Mendeley Data, V1, DOI: 10.17632/zpsr99hn35.1

Working Paper

Disslbacher, F., Ertl, M., List, E., Mokre, P., Schnetzer, M. (2023):
On Top of the Top: A Generalized Approach to the Estimation of Wealth Distributions [PDF]

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We estimate a (Generalized) Pareto distribution with HFCS and ERLDB data and replace survey observations where the data becomes unreliable.

For most countries, the net wealth share of the top 1% rises substantially when estimating a (Generalized) Pareto distribution with ERLDB data to adjust for underreporting in wealth survey data.

Adjustment for underreporting in wealth survey data with (Generalized) Pareto estimation based on ERLDB leads to a substantial increase in aggregate wealth.

Team

Franziska Disslbacher
Vienna University of Economics and Business

Michael Ertl
Chamber of Labor Vienna

Emanuel List
Vienna University of Economics and Business | Macroeconomic Policy Institute

Patrick Mokre
New School for Social Research | Chamber of Labor Vienna

Matthias Schnetzer
Chamber of Labor Vienna

Contact

If you encounter technical issues with the database, please contact matthias.schnetzer@akwien.at.

Acknowledgments

We thank the Austrian Federal Chamber of Labour for generous support and the Research Institute Economics of Inequality (INEQ) for hosting this database. The website was built with R shiny and FullPage.