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Determinants of attrition between Waves 1 and 2 of South Africa's National Income Dynamics Study – Coronavirus Rapid Mobile Survey (NIDS‐CRAM)

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  • Reza Che Daniels
  • Kim P. Ingle
  • Timothy S. L. Brophy

Abstract

We introduce a new approach to the analysis of attrition in South African longitudinal surveys by supplementing the public‐use data with paradata about the survey process and interview experience. The number of successfully interviewed respondents reduced from 7,073 in Wave 1 of NIDS‐CRAM to 5,676 in Wave 2—a level of attrition of almost 20%. We fit probit regression models to predict the determinants of attrition. In the fully specified model, attrition was most affected by contact effort by the survey organisation, the sample batch the respondent was in during Wave 1, employment status and whether they had a missing value for household income. Another important finding was that respondents who underwent COVID‐19 tests were 3% more likely to attrite, a trend that could negatively affect the efficacy of the survey to track COVID‐19 testing behaviour in future waves. Attrition was not influenced by how often respondents previously participated or refused in NIDS, the interviewer‐interviewee experience in the interview or by the respondent's observable demographic characteristics. This is a new contribution to the South African literature on attrition and shows the importance of using paradata to understand nonresponse.

Suggested Citation

  • Reza Che Daniels & Kim P. Ingle & Timothy S. L. Brophy, 2022. "Determinants of attrition between Waves 1 and 2 of South Africa's National Income Dynamics Study – Coronavirus Rapid Mobile Survey (NIDS‐CRAM)," South African Journal of Economics, Economic Society of South Africa, vol. 90(4), pages 535-552, December.
  • Handle: RePEc:bla:sajeco:v:90:y:2022:i:4:p:535-552
    DOI: 10.1111/saje.12318
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    References listed on IDEAS

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    1. Jeffrey E. Zabel, 1998. "An Analysis of Attrition in the Panel Study of Income Dynamics and the Survey of Income and Program Participation with an Application to a Model of Labor Market Behavior," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 479-506.
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    5. John A. Maluccio, 2004. "Using Quality of Interview Information to Assess Nonrandom Attrition Bias in Developing‐Country Panel Data," Review of Development Economics, Wiley Blackwell, vol. 8(1), pages 91-109, February.
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