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The German SAVE survey: documentation and methodology

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  • Schunk, Daniel

    () (University of Zürich Institute for Empirical Research in Economics)

Abstract

The purpose of this document is to describe methodological details of the German SAVE survey and to provide users of SAVE with all necessary information for working with the publicly available SAVE dataset.

Suggested Citation

  • Schunk, Daniel, 2007. "The German SAVE survey: documentation and methodology," Sonderforschungsbereich 504 Publications 07-08, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  • Handle: RePEc:xrs:sfbmaa:07-08 Note: Financial support from the Deutsche Forschungsgemeinschaft, SFB 504, at the University of Mannheim, is gratefully acknowledged.
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    References listed on IDEAS

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    1. Scheuren, Fritz, 1988. "Missing-Data Adjustments in Large Surveys: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 298-299, July.
    2. Lothar Essig & Joachim K. Winter, 2009. "Item Non-Response to Financial Questions in Household Surveys: An Experimental Study of Interviewer and Mode Effects," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 367-390, December.
    3. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, September.
    4. Axel H. Boersch-Supan & Lothar Essig, 2005. "Household Saving in Germany: Results of the First SAVE Study," NBER Chapters,in: Analyses in the Economics of Aging, pages 317-356 National Bureau of Economic Research, Inc.
    5. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 92(1), pages 101-114, February.
    6. Essig, Lothar, 2005. "Methodological aspects of the SAVE data set," Papers 05-17, Sonderforschungsbreich 504.
    7. Sande, I G, 1988. "Missing-Data Adjustments in Large Surveys: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 296-297, July.
    8. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 300-301, July.
    9. F. Thomas Juster & James P. Smith, 2004. "Improving the Quality of Economic Data: Lessons from the HRS and AHEAD," Labor and Demography 0402010, EconWPA.
    10. Little, Roderick J A, 1988. "Missing-Data Adjustments in Large Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 287-296, July.
    11. Hilary W. Hoynes & Michael D. Hurd & Harish Chand, 1998. "Household Wealth of the Elderly under Alternative Imputation Procedures," NBER Chapters,in: Inquiries in the Economics of Aging, pages 229-257 National Bureau of Economic Research, Inc.
    12. Lothar Essig, 2005. "Methodological aspects of the SAVE data set," MEA discussion paper series 05080, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
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    Cited by:

    1. Pahnke, Luise & Honekamp, Ivonne, 2010. "Different Effects of Financial Literacy and Financial Education in Germany," MPRA Paper 22900, University Library of Munich, Germany.
    2. Axel Börsch-Supan & Anette Reil-Held & Daniel Schunk, 2007. "The savings behaviour of German households: First Experiences with state promoted private pensions," MEA discussion paper series 07136, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    3. Börsch-Supan, Axel & Coppola, Michela & Reil-Held, Anette, 1970. "Riester Pensions in Germany: Design, Dynamics, Targetting Success and Crowding-In," MEA discussion paper series 201220, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    4. Ziegelmeyer, Michael, 2009. "Documentation of the logical imputation using the panel structure of the 2003-2008 German SAVE Survey," Sonderforschungsbereich 504 Publications 08-41, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    5. Luik, Marc-André & Berlemann, Michael, 2014. "Institutional Reform and Depositors’ Portfolio Choice: Evidence from Censored Quantile Regressions," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100291, Verein für Socialpolitik / German Economic Association.
    6. Daniel Schunk, 2007. "A Markov Chain Monte Carlo Multiple Imputation Procedure for Dealing with Item Nonresponse in the German SAVE Survey," MEA discussion paper series 07121, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    7. Ivonne Honekamp, 2012. "Financial Literacy and Retirement Savings in Germany," NFI Working Papers 2012-WP-03, Indiana State University, Scott College of Business, Networks Financial Institute.
    8. Coppola, Michela & Börsch-Supan, Axel, 2011. "The German SAVE Study: Design, selected results and future developments," Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48733, Verein für Socialpolitik / German Economic Association.
    9. Dummann, Kathrin, 2008. "Retirement saving and attitude towards financial intermediaries: Evidence for Germany," Thuenen-Series of Applied Economic Theory 99, University of Rostock, Institute of Economics.

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