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Identification of interviewer falsification in the IAB-BAMF-SOEP Survey of Refugees in Germany

Author

Listed:
  • Kosyakova, Yuliya

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

  • Olbrich, Lukas

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

  • Sakshaug, Joseph

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

  • Schwanhäuser, Silvia

    (Institute for Employment Research (IAB), Nuremberg, Germany ; Univ. Mannheim)

Abstract

"Interviewer-administered surveys are susceptible to intentional deviant behavior by interviewers and this type of behavior is a potential source of survey error. One example of such deviant behaviour is the falsification of entire interviews, which can negatively impact data quality if such cases are not identified. Therefore, the development and application of falsification detection methods is important to ensure high quality data. However, methods of detecting falsification are usually evaluated using simulated or laboratory data instead of actual falsified data. This report examines the effectiveness of statistical identification methods for detecting falsifiers in the IAB-BAMF-SOEP Survey of Refugees in Germany, in which there was an actual case of interviewer fraud." (Author's abstract, IAB-Doku) ((en))

Suggested Citation

  • Kosyakova, Yuliya & Olbrich, Lukas & Sakshaug, Joseph & Schwanhäuser, Silvia, 2019. "Identification of interviewer falsification in the IAB-BAMF-SOEP Survey of Refugees in Germany," FDZ-Methodenreport 201902 (en), Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    • Handle: RePEc:iab:iabfme:201902(en)
    DOI: 10.5164/IAB.FDZM.1902.en.v1
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    Cited by:

    1. Goel, Deepti & Abraham, Rosa & Lahoti, Rahul, 2022. "Improving Survey Quality using Paradata: Lessons from the India Working Survey," GLO Discussion Paper Series 1035, Global Labor Organization (GLO).

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