IDEAS home Printed from https://ideas.repec.org/p/diw/diwsop/diw_sp3.html
   My bibliography  Save this paper

Representative Wealth Data for Germany from the German SOEP: The Impact of Methodological Decisions around Imputation and the Choice of the Aggregation Unit

Author

Listed:
  • Joachim R. Frick
  • Markus M. Grabka
  • Eva M. Sierminska

Abstract

The definition and operationalization of wealth information in population surveys and the corresponding microdata requires a wide range of more or less normative assumptions. However, the decisions made in both the pre- and post-data-collection stage may interfere considerably with the substantive research question. Looking at wealth data from the German SOEP, this paper focuses on the impact of collecting information at the individual rather than household level, and on "imputation and editing" as a means of dealing with measurement error. First, we assess how the choice of unit of aggregation or unit of analysis affects wealth distribution and inequality analysis. Obviously, when measured in "per capita household" terms, wealth is less unequally distributed than at the individual level. This is the result of significant redistribution within households, and also provides evidence of a significant persisting gender wealth gap. Secondly, we find multiple imputation to be an effective means of coping with selective nonresponse. There is a significant impact of imputation on the share of wealth holders (increasing on average by 15%) and also on aggregate wealth (plus 30%). However, with respect to inequality, the results are ambiguous. Looking at the major outcome variable for the whole population-net worth-the Gini coefficient decreases, whereas a top-sensitive measure doubles. The non-random selectivity built into the missing process and the consideration of this selectivity in the imputation process clearly contribute to this finding. Obviously, the treatment of measurement errors after data collection, especially with respect to the imputation of missing values, affects cross-national comparability and thus may require some cross-national harmonization of the imputation strategies applied to the various national datasets.

Suggested Citation

  • Joachim R. Frick & Markus M. Grabka & Eva M. Sierminska, 2007. "Representative Wealth Data for Germany from the German SOEP: The Impact of Methodological Decisions around Imputation and the Choice of the Aggregation Unit," SOEPpapers on Multidisciplinary Panel Data Research 3, DIW Berlin, The German Socio-Economic Panel (SOEP).
  • Handle: RePEc:diw:diwsop:diw_sp3
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.56534.de/diw_sp0003.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    2. Joachim R. Frick & Markus M. Grabka, 2007. "Item Non-response and Imputation of Annual Labor Income in Panel Surveys from a Cross-National Perspective," SOEPpapers on Multidisciplinary Panel Data Research 49, DIW Berlin, The German Socio-Economic Panel (SOEP).
    3. René Böheim & Stephen P. Jenkins, 2000. "Do Current Income and Annual Income Measures Provide Different Pictures of Britain's Income Distribution?," Discussion Papers of DIW Berlin 214, DIW Berlin, German Institute for Economic Research.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jaanika Meriküll & Merike Kukk & Tairi Rõõm, 2021. "What explains the gender gap in wealth? Evidence from administrative data," Review of Economics of the Household, Springer, vol. 19(2), pages 501-547, June.
    2. GRABKA Markus & MARCUS Jan & SIERMINSKA Eva, 2013. "Wealth distribution within couples and financial decision making," LISER Working Paper Series 2013-02, Luxembourg Institute of Socio-Economic Research (LISER).
    3. Sierminska, Eva & Piazzalunga, Daniela & Grabka, Markus M., 2018. "Transitioning towards more equality? Wealth gender differences and the changing role of explanatory factors over time," GLO Discussion Paper Series 252, Global Labor Organization (GLO).
    4. James B. Davies & Susanna Sandström & Anthony Shorrocks & Edward N. Wolff, 2011. "The Level and Distribution of Global Household Wealth," Economic Journal, Royal Economic Society, vol. 121(551), pages 223-254, March.
    5. David Gallusser & Matthias Krapf, 2022. "Joint Income-Wealth Inequality: Evidence from Lucerne Tax Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 251-295, August.
    6. Sierminska, Eva M. & Frick, Joachim R. & Grabka, Markus M., 2010. "Examining the gender wealth gap," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 62(4), pages 669-690.
    7. Ziebarth, Nicolas R. & Frick, Joachim R., 2010. "Revisiting the Income-Health Nexus: The Importance of Choosing the," IZA Discussion Papers 4787, Institute of Labor Economics (IZA).
    8. Joachim R. Frick & Markus M. Grabka & Jan Marcus, 2007. "Editing and Multiple Imputation of Item-Non-Response in the 2002 Wealth Module of the German Socio-Economic Panel (SOEP)," SOEPpapers on Multidisciplinary Panel Data Research 18, DIW Berlin, The German Socio-Economic Panel (SOEP).
    9. 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.
    10. Grabka, Markus M. & Marcus, Jan & Sierminska, Eva, 2015. "Wealth Distribution within Couples," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 13(3), pages 459-486.
    11. Sierminska, Eva & Frick, Joachim R. & Grabka, Markus M., 2008. "Examining the Gender Wealth Gap in Germany," IZA Discussion Papers 3573, Institute of Labor Economics (IZA).
    12. Joachim Frick & Nicolas Ziebarth, 2013. "Welfare-related health inequality: does the choice of measure matter?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(3), pages 431-442, June.
    13. repec:zbw:rwirep:0258 is not listed on IDEAS
    14. Matthias Keese, 2011. "Thrifty Wives and Lavish Husbands? – Bargaining Power and Financial Dicisions in Germany," Ruhr Economic Papers 0258, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    15. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2012. "The Luxembourg Household Finance and Consumption Survey (LU-HFCS): Introduction and Results," BCL working papers 73, Central Bank of Luxembourg.
    16. Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung (ed.), 2007. "Das Erreichte nicht verspielen. Jahresgutachten 2007/08 [The gains must not be squandered. Annual Report 2007/08]," Annual Economic Reports / Jahresgutachten, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, volume 127, number 200708.
    17. Julia Groiß & Alyssa Schneebaum & Barbara Schuster, 2018. "Vermögensunterschiede nach Geschlecht in Österreich," Wirtschaft und Gesellschaft - WuG, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik, vol. 44(1), pages 45-72.
    18. Jaanika Meriküll & Merike Kukk & Tairi Rõõm, 2021. "What explains the gender gap in wealth? Evidence from administrative data," Review of Economics of the Household, Springer, vol. 19(2), pages 501-547, June.
    19. Lorenz, Hanno & Christl, Michael, 2015. "Armut: Ungleichheit & Verteilung," EconStor Books, ZBW - Leibniz Information Centre for Economics, number 119606, December.
    20. S. Anger & J. R. Frick & J. Goebel & M. M. Grabka & O. Groh-Samberg & H. Haas & E. Holst & P. Krause & M. Kroh & H. Lohmann & R. Pischner & J. Schupp & I. Sieber & T. Siedler & C. Schmitt & C. K. Spie, 2008. "Zur Weiterentwicklung von SOEPsurvey und SOEPservice," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 77(3), pages 157-177.
    21. Keese, Matthias, 2011. "Thrifty Wives and Lavish Husbands? – Bargaining Power and Financial Dicisions in Germany," Ruhr Economic Papers 258, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    22. Julia Groiß & Alsyssa Schneebaum & Barbara Schuster, 2017. "Vermögensunterschiede nach Geschlecht in Österreich und Deutschland: Eine Analyse auf der Personenebene," Working Paper Reihe der AK Wien - Materialien zu Wirtschaft und Gesellschaft 168, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik.
    23. David Gallusser & Matthias Krapf, 2019. "Joint Income-Wealth Inequality: An Application Using Administrative Tax Data," CESifo Working Paper Series 7876, CESifo.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Robert Breunig & Joseph Mercante, 2010. "The Accuracy of Predicted Wages of the Non‐Employed and Implications for Policy Simulations from Structural Labour Supply Models," The Economic Record, The Economic Society of Australia, vol. 86(272), pages 49-70, March.
    2. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    3. Song, Wei-Ling & Uzmanoglu, Cihan, 2016. "TARP announcement, bank health, and borrowers’ credit risk," Journal of Financial Stability, Elsevier, vol. 22(C), pages 22-32.
    4. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    5. Jonathan Gruber & Aaron Yelowitz, 1999. "Public Health Insurance and Private Savings," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1249-1274, December.
    6. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    7. Leye Li & Louise Yi Lu & Dongyue Wang, 2022. "External labour market competitions and stock price crash risk: evidence from exposures to competitor CEOs’ award‐winning events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1421-1460, April.
    8. Calcagno, R. & Renneboog, L.D.R., 2004. "Capital Structure and Managerial Compensation : The Effects of Renumeration Seniority," Discussion Paper 2004-120, Tilburg University, Center for Economic Research.
    9. Son K. Lam & Thomas E. DeCarlo & Ashish Sharma, 2019. "Salesperson ambidexterity in customer engagement: do customer base characteristics matter?," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 659-680, July.
    10. McCausland, David & Pouliakas, Konstantinos & Theodossiou, Ioannis, 2005. "Some are Punished and Some are Rewarded: A Study of the Impact of Performance Pay on Job Satisfaction," MPRA Paper 14243, University Library of Munich, Germany.
    11. Gary F. Peters & Andrea M. Romi & Juan Manuel Sanchez, 2019. "The Influence of Corporate Sustainability Officers on Performance," Journal of Business Ethics, Springer, vol. 159(4), pages 1065-1087, November.
    12. Fossen, Frank M. & König, Johannes, 2015. "Public health insurance and entry into self-employment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112934, Verein für Socialpolitik / German Economic Association.
    13. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    14. Fernando Rios-Avila & Gustavo Canavire-Bacarreza, 2018. "Standard-error correction in two-stage optimization models: A quasi–maximum likelihood estimation approach," Stata Journal, StataCorp LP, vol. 18(1), pages 206-222, March.
    15. Brian H. Boyer & Taylor D. Nadauld & Keith P. Vorkink & Michael S. Weisbach, 2023. "Discount‐Rate Risk in Private Equity: Evidence from Secondary Market Transactions," Journal of Finance, American Finance Association, vol. 78(2), pages 835-885, April.
    16. Kadreva, Olga, 2016. "The influence of quantity and age of children on working women’ salaries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 41, pages 62-77.
    17. Stolowy, Hervé & Jeanjean, Thomas & Erkens, Michael, 2011. "The economic consequences of increasing the international visibility of financial reports," HEC Research Papers Series 957, HEC Paris.
    18. Bruneel, Johan & Clarysse, Bart & Bobelyn, Annelies & Wright, Mike, 2020. "Liquidity events and VC-backed academic spin-offs: The role of search alliances," Research Policy, Elsevier, vol. 49(10).
    19. Leon Zolotoy & Don O’Sullivan & Keke Song, 2021. "The Role of Ethical Standards in the Relationship Between Religious Social Norms and M&A Announcement Returns," Journal of Business Ethics, Springer, vol. 170(4), pages 721-742, May.
    20. Hans A. Holter & Dirk Krueger & Serhiy Stepanchuk, 2019. "How do tax progressivity and household heterogeneity affect Laffer curves?," Quantitative Economics, Econometric Society, vol. 10(4), pages 1317-1356, November.

    More about this item

    Keywords

    Wealth; Item Non-response; Multiple Imputation; SOEP;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. SOEP based publications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:diw:diwsop:diw_sp3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/sodiwde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.