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Benefit underreporting in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data

Author

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  • Bruckmeier, Kerstin

    (Institute for Employment Research (IAB), Nuremberg, Germany)

  • Riphahn, Regina T.
  • Wiemers, Jürgen

    (Institute for Employment Research (IAB), Nuremberg, Germany)

Abstract

"The international literature studies non-take-up behavior of eligible populations to evaluate the effectiveness of government programs. A major challenge in this literature is the measurement error regarding benefit take-up. Measurement error is typically addressed by structural assumptions in the modeling framework. In our data, we observe both actual welfare receipt and respondents' survey information on their take-up. This allows us to observe the measurement errors that other researchers must estimate. We describe survey misreporting and investigate how it biases the estimates of the magnitude and patterns of benefit take-up among eligible households. Our findings suggest that the extent of measurement error can be substantial. It varies with the characteristics of the misreporting population and is associated with the drivers of underreporting. This indicates that survey-based analyses of take-up behavior are likely subject to severe biases." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Bruckmeier, Kerstin & Riphahn, Regina T. & Wiemers, Jürgen, 2019. "Benefit underreporting in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," IAB-Discussion Paper 201906, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabdpa:201906
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    Cited by:

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    2. Céline Marc & Mickaël Portela & Cyrine Hannafi & Rémi Le Gall & Antoine Rode & Stéphanie Laguérodie, 2022. "Non-take-up of minimum social benefits: quantification in Europe," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-04082347, HAL.

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    More about this item

    Keywords

    Bundesrepublik Deutschland ; Befragung ; Messfehler ; IAB-Leistungsempfängerhistorik ; Inanspruchnahme ; Datenfusion ; Leistungsbezug ; Antwortverhalten ; Sozialleistungen ; Arbeitslosengeld II ; IAB-Haushaltspanel ; 2008-2013;
    All these keywords.

    JEL classification:

    • 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
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare

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