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Item nonresponse to financial questions in household surveys: An experimental study of interviewer and mode effects

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  • Essig, Lothar

    ()
    (Mannheim Research Institute for the Economics of Aging (MEA) and Sonderforschungsbereich 504)

  • Winter, Joachim

    ()
    (Mannheim Research Institute for the Economics of Aging (MEA))

Abstract

We analyze nonresponse to questions on financial items such as income and asset holdings in the SAVE survey, exploiting a controlled field experiment. As part of the SAVE study, a representative survey conducted in Germany in 2001, questions on household income and financial assets were administered using different interview modes (personal interview vs. drop-off questionnaire). The data also allow investigating the influence of interviewer characteristics on nonresponse. Our results are in line with predictions derived from models of survey response behavior that have been developed in survey research and social psychology.

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Bibliographic Info

Paper provided by Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim in its series Sonderforschungsbereich 504 Publications with number 05-18.

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Length: 34 pages
Date of creation: 26 Sep 2003
Date of revision:
Handle: RePEc:xrs:sfbmaa:05-18

Note: Financial support from the Deutsche Forschungsgemeinschaft, SFB 504, at the University of Mannheim, is gratefully acknowledged.
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  1. Michael D. Hurd & Daniel McFadden & Harish Chand & Li Gan & Angela Menill & Michael Roberts, 1998. "Consumption and Savings Balances of the Elderly: Experimental Evidence on Survey Response Bias," NBER Chapters, in: Frontiers in the Economics of Aging, pages 353-392 National Bureau of Economic Research, Inc.
  2. Philipson, Tomas & Malani, Anup, 1999. "Measurement errors: A principal investigator-agent approach," Journal of Econometrics, Elsevier, vol. 91(2), pages 273-298, August.
  3. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, vol. 84(1), pages 37-58, May.
  4. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
  5. F. Thomas Juster & James P. Smith, 2004. "Improving the Quality of Economic Data: Lessons from the HRS and AHEAD," Labor and Demography 0402010, EconWPA.
  6. Winter, Joachim, 0000. "Bracketing effects in categorized survey questions and the measurement of economic quantities," Sonderforschungsbereich 504 Publications 02-35, Sonderforschungsbereich 504, Universität Mannheim & Sonderforschungsbereich 504, University of Mannheim.
  7. Regina Riphahn & Oliver Serfling, 2005. "Item non-response on income and wealth questions," Empirical Economics, Springer, vol. 30(2), pages 521-538, 09.
  8. Philipson, Tomas, 1997. "Data Markets and the Production of Surveys," Review of Economic Studies, Wiley Blackwell, vol. 64(1), pages 47-72, January.
  9. Axel Borsch-Supan & Lothar Essig, 2003. "Household Saving in Germany: Results of the first SAVE study," NBER Working Papers 9902, National Bureau of Economic Research, Inc.
  10. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843 Elsevier.
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Citations

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Cited by:
  1. Michael Ziegelmeyer, 2013. "Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey," AStA Advances in Statistical Analysis, Springer, vol. 97(1), pages 49-76, January.
  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. Daniel Schunk, 2006. "The German SAVE Survey: Documentation and Methodology," MEA discussion paper series 06109, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  4. Daniel Schunk, 2009. "What Determines Household Saving Behavior? An Examination of Saving Motives and Saving Decisions," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 229(4), pages 467-491, August.
  5. Pfarr, Christian, 2012. "Meltzer-Richard and social mobility hypothesis: revisiting the income-redistribution nexus using German choice data," MPRA Paper 43325, University Library of Munich, Germany.
  6. Pfarr, Christian & Schmid, Andreas, 2013. "The political economics of social health insurance: the tricky case of individuals’ preferences," MPRA Paper 44534, University Library of Munich, Germany.
  7. 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.
  8. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures National Bureau of Economic Research, Inc.
  9. Coppola, Michela & Lamla, Bettina, 2012. "Empirical Research on Households’ Saving and Retirement Security: First Steps towards an Innovative Triple‐Linked‐Dataset," MEA discussion paper series 12258, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
  10. Beatrice Scheubel & Joachim Winter, 2008. "Rente mit 67: Wie lange die Deutschen arbeiten können und wollen," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 61(01), pages 26-32, 01.
  11. Daniel Schunk, 2008. "A Markov chain Monte Carlo algorithm for multiple imputation in large surveys," AStA Advances in Statistical Analysis, Springer, vol. 92(1), pages 101-114, February.

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