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A Novel Sampling Strategy for Surveying High Net‐Worth Individuals—A Pretest Application Using the Socio‐Economic Panel
Author(s) -
Schröder Carsten,
Bartels Charlotte,
Grabka Markus M.,
König Johannes,
Kroh Martin,
Siegers Rainer
Publication year - 2020
Publication title -
review of income and wealth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.024
H-Index - 57
eISSN - 1475-4991
pISSN - 0034-6586
DOI - 10.1111/roiw.12452
Subject(s) - sample (material) , sampling frame , interview , shareholder , sampling design , german , population , actuarial science , net worth , missing data , national wealth , distribution (mathematics) , quality (philosophy) , panel data , marketing , economics , business , demographic economics , accounting , econometrics , finance , statistics , corporate governance , geography , political science , sociology , demography , debt , philosophy , mathematics , law , mathematical analysis , chemistry , archaeology , epistemology , chromatography
High‐wealth individuals are typically underrepresented or completely missing in population surveys. The lack of comprehensive national registers on high‐wealth individuals in many countries challenged previous attempts to remedy this under‐representation. In a novel research design, we draw on public data on the shareholding structures of companies as a sampling frame. Our design builds on the empirical regularity that high‐wealth individuals are likely to hold at least part of their assets in the form of shareholdings. Based on data from over 270 million companies worldwide, we select all individuals who are both German residents and registered shareholders of companies. In a pretest, we interviewed 124 households from a gross sample of 2,000 anchor persons. Our analysis shows that values of shareholdings from register data highly correlate with individual ranks in the wealth distribution, that the quality of personal information, particularly the residential address, is sufficiently high for subsequent interviewing, and that the approach can fill a major data and research gap in the study of high‐wealth individuals.