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Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys

Author

Listed:
  • Marcel Das

    (CentERdata, Tilburg, The Netherlands, Tilburg University, Tilburg, The Netherlands, das@uvt.nl)

  • Vera Toepoel

    (Tilburg University, Tilburg, The Netherlands)

  • Arthur van Soest

    (Tilburg University, Tilburg, The Netherlands, Netspar, Tilburg, The Netherlands)

Abstract

Over the past decades there has been an increasing use of panel surveys at the household or individual level. Panel data have important advantages compared to independent cross sections, but also two potential drawbacks: attrition bias and panel conditioning effects. Attrition bias arises if dropping out of the panel is correlated with a variable of interest. Panel conditioning arises if responses are influenced by participation in the previous wave(s); the experience of the previous interview(s) may affect the answers to questions on the same topic, such that these answers differ systematically from those of respondents interviewed for the first time. In this study the authors discuss how to disentangle attrition and panel conditioning effects and develop tests for panel conditioning allowing for nonrandom attrition. First, the authors consider a nonparametric approach with assumptions on the sample design only, leading to interval identification of the measures for the attrition and panel conditioning effects. Second, the authors introduce additional assumptions concerning the attrition process, which lead to point estimates and standard errors for both the attrition bias and the panel conditioning effect. The authors illustrate their method on a variety of repeated questions in two household panels. The authors find significant panel conditioning effects in knowledge questions, but not in other types of questions. The examples show that the bounds can be informative if the attrition rate is not too high. In most but not all of the examples, point estimates of the panel conditioning effect are similar for different additional assumptions on the attrition process.

Suggested Citation

  • Marcel Das & Vera Toepoel & Arthur van Soest, 2011. "Nonparametric Tests of Panel Conditioning and Attrition Bias in Panel Surveys," Sociological Methods & Research, , vol. 40(1), pages 32-56, February.
  • Handle: RePEc:sae:somere:v:40:y:2011:i:1:p:32-56
    DOI: 10.1177/0049124110390765
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    3. Khandker, Shahidur R. & Samad, Hussain A., 2014. "Dynamic effects of microcredit in Bangladesh," Policy Research Working Paper Series 6821, The World Bank.
    4. Nic Baigrie & Katherine Eyal, 2014. "An Evaluation of the Determinants and Implications of Panel Attrition in the National Income Dynamics Survey (2008-2010)," South African Journal of Economics, Economic Society of South Africa, vol. 82(1), pages 39-65, March.
    5. Bach, Ruben L. & Eckman, Stephanie, 2017. "Does participating in a panel survey change respondents' labor market behavior?," IAB-Discussion Paper 201715, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    12. Bert Van Landeghem, 2012. "Panel Conditioning and Self-Reported Satisfaction: Evidence from International Panel Data and Repeated Cross-Sections," SOEPpapers on Multidisciplinary Panel Data Research 484, DIW Berlin, The German Socio-Economic Panel (SOEP).
    13. Van Landeghem, Bert, 2014. "A test based on panel refreshments for panel conditioning in stated utility measures," Economics Letters, Elsevier, vol. 124(2), pages 236-238.
    14. Brown, Sarah & Harris, Mark N. & Spencer, Christopher & Taylor, Karl, 2020. "Financial Expectations and Household Consumption: Does Middle Inflation Matter?," IZA Discussion Papers 13023, Institute of Labor Economics (IZA).
    15. John Robert Warren & Andrew Halpern-Manners, 2012. "Panel Conditioning in Longitudinal Social Science Surveys," Sociological Methods & Research, , vol. 41(4), pages 491-534, November.
    16. Chadi, Adrian, 2021. "Identification of attrition bias using different types of panel refreshments," Economics Letters, Elsevier, vol. 201(C).
    17. Hans-Jürgen Andreß, 2017. "The need for and use of panel data," IZA World of Labor, Institute of Labor Economics (IZA), pages 352-352, April.
    18. Andrew Halpern-Manners & John Warren, 2012. "Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1499-1519, November.
    19. Mark Wooden & Ning Li, 2014. "Panel Conditioning and Subjective Well-being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 117(1), pages 235-255, May.
    20. Khandker, Shahidur R & Samad, Hussain A, 2016. "Bangladesh’s Achievement in Poverty Reduction: The Role of Microfinance Revisited," Working Papers 114, JICA Research Institute.
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