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A novel sampling strategy for surveying high-worth individuals: An application using the socio-economic panel

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Listed:
  • Schröder, Carsten
  • Bartels, Charlotte
  • Kroh, Martin
  • Grabka, Markus
  • Siegers, Rainer

Abstract

High-worth individuals are typically underrepresented or completely missing in population surveys. The lack of a register-based sampling frame on high-worth individuals in many countries challenged previous attempts to sample high-worth individuals in voluntary scientific surveys. In a novel research design, we draw on register data on the shareholding structures of companies as a sampling frame. Our design builds on the empirical regularity that high-worth 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 identified individuals who are both German residents and registered shareholders of companies. In a feasibility study, we interviewed 124 households from a gross sample of 2,000 anchor persons. Our analysis shows that register data on shareholding structures correctly identifies the individuals' rank in the wealth distribution, that the quality of personal information, particularly the residential address, is efficiently high for subsequent interviewing, and that the approach can fill a major data and research gap in the study of high-worth individuals and the top-end of the wealth distribution.

Suggested Citation

  • Schröder, Carsten & Bartels, Charlotte & Kroh, Martin & Grabka, Markus & Siegers, Rainer, 2019. "A novel sampling strategy for surveying high-worth individuals: An application using the socio-economic panel," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203543, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc19:203543
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    References listed on IDEAS

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    1. Joachim R. Frick & Markus M. Grabka & Jan Marcus, 2010. "Editing und Multiple Imputation der Vermögensinformation 2002 und 2007 im SOEP," Data Documentation 51, DIW Berlin, German Institute for Economic Research.
    2. Brzezinski, Michal, 2014. "Do wealth distributions follow power laws? Evidence from ‘rich lists’," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 155-162.
    3. Christian Westermeier & Markus M. Grabka, 2015. "Große statistische Unsicherheit beim Anteil der Top-Vermögenden in Deutschland," DIW Wochenbericht, DIW Berlin, German Institute for Economic Research, vol. 82(7), pages 123-133.
    4. Joshua D. Coval & Tobias J. Moskowitz, 1999. "Home Bias at Home: Local Equity Preference in Domestic Portfolios," Journal of Finance, American Finance Association, vol. 54(6), pages 2045-2073, December.
    5. Royston, Patrick & White, Ian R., 2011. "Multiple Imputation by Chained Equations (MICE): Implementation in Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i04).
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    Cited by:

    1. Michele Cantarella & Andrea Neri & Giovanna Ranalli, 2021. "Mind the wealth gap: a new allocation method to match micro and macro statistics on household wealth," Questioni di Economia e Finanza (Occasional Papers) 646, Bank of Italy, Economic Research and International Relations Area.
    2. Moritz Hennicke & Moritz Lubczyk & Lukas Mergele, 2020. "Die Treuhandanstalt: Eine empirische Bestandsaufnahme 30 Jahre nach der Deutschen Wiedervereinigung," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 27(05), pages 17-21, October.
    3. Karla Cordova & Markus M. Grabka & Eva Sierminska, 2022. "Pension Wealth and the Gender Wealth Gap," European Journal of Population, Springer;European Association for Population Studies, vol. 38(4), pages 755-810, October.
    4. Thilo N. H. Albers & Charlotte Bartels & Moritz Schularick, 2020. "The Distribution of Wealth in Germany, 1895-2018," ECONtribute Policy Brief Series 001, University of Bonn and University of Cologne, Germany.
    5. Schröder Carsten & König Johannes & Fedorets Alexandra & Goebel Jan & Grabka Markus M. & Lüthen Holger & Metzing Maria & Schikora Felicitas & Liebig Stefan, 2020. "The economic research potentials of the German Socio-Economic Panel study," German Economic Review, De Gruyter, vol. 21(3), pages 335-371, September.
    6. Charlotte Bartels & Carsten Schroeder, 2020. "The role of rental income, real estate and rents for inequality in Germany," Working Papers 7, Forum New Economy.
    7. Tahnee Christelle Ooms, 2021. "Correcting the Underestimation of Capital Incomes in Inequality Indicators: with an Application to the UK, 1997–2016," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(3), pages 929-953, October.
    8. Ooms, Tahnee, 2021. "Correcting the underestimation of capital incomes in inequality indicators: with an application to the UK, 1997–2016," LSE Research Online Documents on Economics 108900, London School of Economics and Political Science, LSE Library.

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    More about this item

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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