Significant Statistical Uncertainty over Share of High Net Worth Households
Christian Westermeier and
Markus Grabka
DIW Economic Bulletin, 2015, vol. 5, issue 14/15, 210-219
Abstract:
The analyses of wealth inequality based on survey data usually suffer from undercoverage of the upper percentiles of the very wealthy. Yet given this group’s substantial share of total net worth, it is of particular relevance. As no tax data are available in Germany, the largest fortunes can only be simulated using “rich lists.” For example, combining the Forbes list, with its approximately 50 German US dollar billionaires, with survey data results in an increased aggregate total net worth for all households in Germany in 2012 of between one-third and 50 percent, depending on the scenario. Moreover, the share of the richest one percent of the population (about 400,000 households) rises from approximately one-fifth to one-third. After reassessment, the richest ten percent of the population’s share of total net worth is estimated to be between 64 and 74 percent, depending on the scenario. These reassessments are characterized by a high degree of uncertainty which eventually can only be reduced by improving the base data.
Keywords: Wealth Inequality; pareto distribution; SOEP (search for similar items in EconPapers)
JEL-codes: D31 I31 (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
https://www.diw.de/documents/publikationen/73/diw_ ... n_bull_2015-14-3.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:diw:diwdeb:2015-14-3
Access Statistics for this article
More articles in DIW Economic Bulletin from DIW Berlin, German Institute for Economic Research Contact information at EDIRC.
Bibliographic data for series maintained by Bibliothek ().