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Misreporting of program take-up in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data

Author

Listed:
  • Kerstin Bruckmeier

    (IAB)

  • Regina T. Riphahn

    (Friedrich-Alexander-University Erlangen-Nürnberg)

  • Jürgen Wiemers

    (IAB)

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. In our data, we observe both actual welfare receipt and respondents’ survey information on their program 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 misreporting. This indicates that survey-based analyses of take-up behavior are likely subject to severe biases.

Suggested Citation

  • Kerstin Bruckmeier & Regina T. Riphahn & Jürgen Wiemers, 2021. "Misreporting of program take-up in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," Empirical Economics, Springer, vol. 61(3), pages 1567-1616, September.
    • Handle: RePEc:spr:empeco:v:61:y:2021:i:3:d:10.1007_s00181-020-01921-4
    DOI: 10.1007/s00181-020-01921-4
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Akanksha Negi & Digvijay Singh Negi, 2022. "Difference-in-Differences with a Misclassified Treatment," Papers 2208.02412, arXiv.org.
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    3. Feichtmayer, Jennifer & Riphahn, Regina T., 2023. "Intergenerational Transmission of Welfare Benefit Receipt: Evidence from Germany," IZA Discussion Papers 16660, Institute of Labor Economics (IZA).
    4. Diego Muñoz-Higueras & Stephan Köppe & Rafael Granell & Amadeo Fuenmayor, 2024. "Non-take-up of in-work benefits: determinants, benefit erosion and indexing," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 58(1), pages 1-19, December.
    5. Warwick, Ross & Harris, Tom & Phillips, David & Goldman, Maya & Jellema, Jon & Inchauste, Gabriela & Goraus-Tańska, Karolina, 2022. "The redistributive power of cash transfers vs VAT exemptions: A multi-country study," World Development, Elsevier, vol. 151(C).
    6. Chlond, Bettina & Goeschl, Timo & Kesternich, Martin & Werthschulte, Madeline, 2024. "Transporting behavioral insights to low-income households: A field experiment on energy efficiency investments," Working Papers 0755, University of Heidelberg, Department of Economics.
    7. Richiardi, Matteo & Vella, Melchior, 2024. "Mind vs matter: economic and psychologic determinants of take-up rates of social benefits in the UK," Centre for Microsimulation and Policy Analysis Working Paper Series CEMPA6/24, Centre for Microsimulation and Policy Analysis at the Institute for Social and Economic Research.

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    More about this item

    Keywords

    Take-up; Welfare; Misreporting; Survey data; Administrative data; Data linkage;
    All these keywords.

    JEL classification:

    • 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
    • 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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