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Attrition in longitudinal household survey data

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  • Alderman, Harold
  • Watkins, Susan Cotts
  • Kohler, Hans-Peter
  • Maluccio, John A.
  • Behrman, Jere R.

Abstract

Longitudinal household data can have considerable advantages over much more widely used cross-sectional data. The collection of longitudinal data, however, may be difficult and expensive. One problem that has concerned many analysts is that sample attrition may make the interpretation of estimates problematic. Such attrition may be particularly severe in areas where there is considerable mobility because of migration between rural and urban areas. Many analysts share the intuition that attrition is likely to be selective on characteristics such as schooling and that high attrition is likely to bias estimates made from longitudinal data. This paper considers the extent of and implications of attrition for three longitudinal household surveys from Bolivia, Kenya, and South Africa that report very high per-year attrition rates between survey rounds. Our estimates indicate that (1) the means for a number of critical outcome and family background variables differ significantly between attritors and nonattritors; (2) a number of family background variables are significant predictors of attrition; but (3) nevertheless, the coefficient estimates for “standard” family background variables in regressions and probit equations for the majority of the outcome variables considered in all three data sets are not affected significantly by attrition. Therefore, attrition apparently is not a general problem for obtaining consistent estimates of the coefficients of interest for most of these outcomes. These results, which are very similar to results for developed economies, suggest that for these outcome variables—despite suggestions of systematic attrition from univariate comparisons between attritors and nonattritors, multivariate estimates of behavioral relations of interest may not be biased due to attrition.

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Bibliographic Info

Paper provided by International Food Policy Research Institute (IFPRI) in its series FCND briefs with number 96.

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Date of creation: 2000
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Handle: RePEc:fpr:fcndbr:96

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Keywords: Household surveys Methodology ;

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References

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  1. 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, 02.
  2. Datt, Gaurav & Jolliffe, Dean & Sharma, Manohar, 1998. "A profile of poverty in Egypt: 1997," FCND discussion papers 49, International Food Policy Research Institute (IFPRI).
  3. Foster, Andrew D & Rosenzweig, Mark R, 1995. "Learning by Doing and Learning from Others: Human Capital and Technical Change in Agriculture," Journal of Political Economy, University of Chicago Press, vol. 103(6), pages 1176-1209, December.
  4. Jere R. Behrman & Hans-Peter Kohler & Susan Cotts Watkins, 2001. "How can we measure the causal effects of social networks using observational data? Evidence from the diffusion of family planning and AIDS worries in South Nyanza District, Kenya," MPIDR Working Papers WP-2001-022, Max Planck Institute for Demographic Research, Rostock, Germany.
  5. Duncan Thomas & Elizabeth Frankenberg & James P. Smith, 2000. "Lost But Not Forgotten: Attrition and Follow-up in the Indonesian Family Life Survey," Working Papers 00-03, RAND Corporation Publications Department.
  6. Sean Becketti & William Gould & Lee Lillard & Finis Welch, 1985. "The Panel Study of Income Dynamics After Fourteen Years: An Evaluation," UCLA Economics Working Papers 361, UCLA Department of Economics.
  7. Armar-Klemesu, Margaret & Ruel, Marie T. & Maxwell, Daniel G. & Levin, Carol E. & Morris, Saul Sutkover, 2000. "The constraints to good child care practices in Accra," FCND discussion papers 81, International Food Policy Research Institute (IFPRI).
  8. James P. Smith & Duncan Thomas, 2004. "Migration in Retrospect: Remembrances of Things Past," Labor and Demography 0408009, EconWPA.
  9. Becketti, Sean, et al, 1988. "The Panel Study of Income Dynamics after Fourteen Years: An Evaluatio n," Journal of Labor Economics, University of Chicago Press, vol. 6(4), pages 472-92, October.
  10. Jere R. Behrman & Yingmei Cheng & Petra E. Todd, 2004. "Evaluating Preschool Programs When Length of Exposure to the Program Varies: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 108-132, February.
  11. Evangelos M. Falaris & H. Elizabeth Peters, 1998. "Survey Attrition and Schooling Choices," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 531-554.
  12. 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.
  13. Lee A. Lillard & Constantijn W. A. Panis, 1998. "Panel Attrition from the Panel Study of Income Dynamics: Household Income, Marital Status, and Mortality," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 437-457.
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