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Improving Survey Quality using Paradata: Lessons from the India Working Survey

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Listed:
  • Goel, Deepti
  • Abraham, Rosa
  • Lahoti, Rahul

Abstract

We describe the design and implementation of a paradata based method to reduce interviewer induced measurement error in a household survey in India. Our method identifies enumerators exhibiting deviant field practices, and provides them feedback to correct potentially faulty behavior. A novel feature is the emphasis on dynamic benchmarking within a group of enumerators facing similar field conditions. This helps to correctly pin down steady state levels of multiple data generating processes that exist within our survey. We also present evidence that our method succeeded in changing actual enumerator behavior in the field. Furthermore, we provide a complete prototype of how to operationalize paradata use in a resource constrained environment. At each step, we highlight the trade-offs involved, share insights from our own shortcomings, and provide recommendations to help make more informed choices. We hope our work will encourage the use of paradata to improve survey quality, especially in low- and middle-income countries where their use is still rare.

Suggested Citation

  • 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).
  • Handle: RePEc:zbw:glodps:1035
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    References listed on IDEAS

    as
    1. Johanna Choumert‐Nkolo & Henry Cust & Callum Taylor, 2019. "Using paradata to collect better survey data: Evidence from a household survey in Tanzania," Review of Development Economics, Wiley Blackwell, vol. 23(2), pages 598-618, May.
    2. anonymous, 2010. "Interview with Thomas Sargent," The Region, Federal Reserve Bank of Minneapolis, vol. 24(Sep), pages 26-39.
    3. Cohen, Mollie J. & Warner, Zach, 2021. "How to Get Better Survey Data More Efficiently," Political Analysis, Cambridge University Press, vol. 29(2), pages 121-138, April.
    4. repec:iab:iabfme:201902(en is not listed on IDEAS
    5. 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].
    6. 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].
    7. anonymous, 2010. "Interview with Gary Gorton," The Region, Federal Reserve Bank of Minneapolis, vol. 24(Dec), pages 26-39.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Paradata; Interviewer Effects; India;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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