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Bracketing effects in categorized survey questions and the measurement of economic quantities

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  • Winter, Joachim

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

Abstract

In households surveys, quantities of interest are frequently elicited using categorized (range-card) formats rather than open-ended questions. One advantage of this format is that is typically reduces item non-response. Unfortunately, results from research in social psychology suggest that the choice of bracket values in range-card questions is likely to influence responses. As yet, there is not much known about the effects of bracketing bias on the measurement of economic quantities and regression analysis. This paper reports evidence on existence and size of bracketing bias based on data from controlled survey experiments. I also discuss strategies for avoiding bracketing bias in household surveys.

Suggested Citation

  • 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.
    • Handle: RePEc:xrs:sfbmaa:02-35
    Note: Financial support was provided by the European Union (TMR project
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    Cited by:

    1. 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.
    2. Stocké, Volker, 2003. "Informationsverfügbarkeit und Response-Effects : die Prognose von Einflüssen unterschiedlich kategorisierter Antwortskalen durch Antwortsicherheiten und Antwortlatenzen," Papers 03-25, Sonderforschungsbreich 504.
    3. Joachim Winter, 2004. "Response bias in survey-based measures of household consumption," Economics Bulletin, AccessEcon, vol. 3(9), pages 1-12.
    4. Melanie Lührmann & Matthias Weiss, 2006. "Market Work, Home Production, Consumer Demand and Unemployment among the Unskilled," MEA discussion paper series 06101, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
    5. Thomas F. Crossley & Joachim K. Winter, 2014. "Asking Households about Expenditures: What Have We Learned?," NBER Chapters, in: Improving the Measurement of Consumer Expenditures, pages 23-50, National Bureau of Economic Research, Inc.
    6. Essig, Lothar, 2005. "Methodological aspects of the SAVE data set," Papers 05-17, Sonderforschungsbreich 504.
    7. David Comerford & Liam Delaney & Colm Harmon, 2009. "Experimental Tests of Survey Responses to Expenditure Questions," Fiscal Studies, Institute for Fiscal Studies, vol. 30(Special I), pages 419-433, December.
    8. Winter, Joachim, 0000. "Design effects in survey-based measures of household consumption," Sonderforschungsbereich 504 Publications 02-34, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    9. 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.
    10. Toepoel, V., 2008. "A closer look at web questionnaire design," Other publications TiSEM 119506d1-f613-46f5-ad59-e, Tilburg University, School of Economics and Management.
    11. Daniel McFadden & Albert Bemmaor & Francis Caro & Jeff Dominitz & Byung-Hill Jun & Arthur Lewbel & Rosa Matzkin & Francesca Molinari & Norbert Schwarz & Robert Willis & Joachim Winter, 2005. "Statistical Analysis of Choice Experiments and Surveys," Marketing Letters, Springer, vol. 16(3), pages 183-196, December.
    12. Stocké, Volker, 2003. "Informationsverfügbarkeit und Response-Effects:," Sonderforschungsbereich 504 Publications 03-25, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    13. Martin Browning & Thomas F. Crossley & Joachim Winter, 2014. "The Measurement of Household Consumption Expenditures," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 475-501, August.
    14. repec:ebl:ecbull:v:3:y:2004:i:9:p:1-12 is not listed on IDEAS
    15. Enrico D’Elia & Bianca Martelli, 2003. "Estimation of Households Income from Bracketed Income Survey Data," ISAE Working Papers 35, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    16. Toepoel, V. & Vis, C.M. & Das, J.W.M. & van Soest, A.H.O., 2006. "Design of Web Questionnaires : An Information Processing Perspective for the Effect of Response Categories," Other publications TiSEM bb20f0d3-5f5d-46b3-92f4-2, Tilburg University, School of Economics and Management.
    17. Sweeney, Sedona & Mukora, Rachel & Candfield, Sophie & Guinness, Lorna & Grant, Alison D. & Vassall, Anna, 2018. "Measuring income for catastrophic cost estimates: Limitations and policy implications of current approaches," Social Science & Medicine, Elsevier, vol. 215(C), pages 7-15.

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    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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