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Familiar Faces, Honest Answers? The Impacts of Enumerator Familiarity and Modality on Survey Responses

Author

Listed:
  • Travis Baseler

    (University of Rochester)

  • Lipeng Chen

    (Analysis Group)

  • Thomas Ginn

    (Center for Global Development)

Abstract

Survey data can be distorted through mistrust, discomfort, or demand effects on the part of respondents. We test whether familiar enumerators—those with whom a respondent has completed a prior survey—influence data quality in a panel survey with small business owners in Uganda. We randomly assign respondents to a familiar or a new enumerator and cross-cut a second randomization to an in-person or phone-based interview modality. Across a broad set of outcome types, we observe few impacts of either survey method on means, distributions, or attrition. However, respondents are significantly more likely to give socially desirable answers to new surveyors compared to familiar ones. The effect of familiarity does not interact significantly with a prior experiment conducted with the same sample, suggesting that familiarity influences estimates of levels but not of treatment impacts. These findings suggest that surveys by familiar enumerators can improve the measurement of sensitive beliefs.

Suggested Citation

  • Travis Baseler & Lipeng Chen & Thomas Ginn, 2026. "Familiar Faces, Honest Answers? The Impacts of Enumerator Familiarity and Modality on Survey Responses," Working Papers 754, Center for Global Development.
  • Handle: RePEc:cgd:wpaper:754
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    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • 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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