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Using Quality of Interview Information to Assess Nonrandom Attrition Bias in Developing-Country Panel Data

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  • John A. Maluccio

Abstract

Panel data often provide an understanding of household behavior not possible with cross-sectional information alone. However, a disturbing feature of such data is that there can be substantial, nonrandom attrition and many analysts share the concern that this inhibits the ability to make accurate inferences. The author examines attrition in the KwaZulu-Natal Income Dynamics Study 1993-1998, assesses the extent of attrition bias for a specific empirical example, and proposes and implements a selection correction methodology using quality of first round interview variables as identifying instruments. The results show that attrition does lead to statistical bias in the "behavioral" coefficients in estimation of household-level expenditure functions. Since it is typically difficult to determine the bias for a particular analysis a priori, and such bias is by its nature model-specific, it behooves researchers using panel data to evaluate the effects of attrition in their analyses. Copyright Blackwell Publishing Ltd 2004.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:rdevec:v:8:y:2004:i:1:p:91-109
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    Citations

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    Cited by:

    1. 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.
    2. Tefera, Nigussie, 2012. "Welfare Impacts of Rising Food Prices in Rural Ethiopia: a Quadratic Almost Ideal Demand System Approach," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126698, International Association of Agricultural Economists.
    3. Akresh, Richard & Edmonds, Eric V., 2010. "The Analytical Returns to Measuring a Detailed Household Roster," IZA Discussion Papers 4759, Institute for the Study of Labor (IZA).
    4. Harold Alderman & Jere Behrman & Hans-Peter Kohler & John A. Maluccio & Susan Watkins, 2001. "Attrition in Longitudinal Household Survey Data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(4), pages 79-124, November.
    5. Zhiying Xu & Zhengfei Guan & T.S. Jayne & Roy Black, 2009. "Factors influencing the profitability of fertilizer use on maize in Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 40(4), pages 437-446, July.
    6. Nicola Branson & Murray Leibbrandt, 2017. "Assessing the usability of the Western Cape Graduate Destination Survey for the analysis of labour market outcomes," SALDRU Working Papers 198, Southern Africa Labour and Development Research Unit, University of Cape Town.
    7. Nobuhiko Fuwa, 2010. "Should We Track Migrant Households When Collecting Household Panel Data? Household Relocation, Economic Mobility, and Attrition Biases in the Rural Philippines," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(1), pages 56-82.
    8. Thomas, Duncan & Witoelar, Firman & Frankenberg, Elizabeth & Sikoki, Bondan & Strauss, John & Sumantri, Cecep & Suriastini, Wayan, 2012. "Cutting the costs of attrition: Results from the Indonesia Family Life Survey," Journal of Development Economics, Elsevier, vol. 98(1), pages 108-123.
    9. Ueno, Yuko, 2014. "Updating Behavior of Inflation Expectations: Evidence from Japanese Household Panel Data," CIS Discussion paper series 617, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    10. Bignebat, Celine & Piot-Lepetit, Isabelle, 2015. "Transaction costs and the market access in Sub-Saharan Africa: The case of maize," 2015 Conference, August 9-14, 2015, Milan, Italy 211341, International Association of Agricultural Economists.
    11. Sarkar, Sudipa & Sahoo, Soham & Klasen, Stephan, 2017. "Employment Transitions of Women in India: A Panel Analysis," IZA Discussion Papers 11086, Institute for the Study of Labor (IZA).
    12. Haddad, Lawrence James & Maluccio, John A., 2002. "Trust, membership in groups, and household welfare," FCND discussion papers 135, International Food Policy Research Institute (IFPRI).
    13. Christian D. Mina & Katsushi S. Imai, 2017. "Estimation of Vulnerability to Poverty Using a Multilevel Longitudinal Model: Evidence from the Philippines," Journal of Development Studies, Taylor & Francis Journals, vol. 53(12), pages 2118-2144, December.
    14. Ueyama, Mika, 2007. "Mortality, mobility, and schooling outcomes among orphans: Evidence from Malawi," IFPRI discussion papers 710, International Food Policy Research Institute (IFPRI).
    15. Carter, Michael R. & Maluccio, John A., 2002. "Social capital and coping with economic shocks," FCND discussion papers 142, International Food Policy Research Institute (IFPRI).
    16. Farshid Vahid & Pushkar Maitra, 2005. "The Effect of Household Characteristics on Living Standards in South Africa 1993 - 98: A Quantile Regression Analysis with Sample Attrition," ANU Working Papers in Economics and Econometrics 2005-452, Australian National University, College of Business and Economics, School of Economics.
    17. repec:kap:sbusec:v:49:y:2017:i:2:d:10.1007_s11187-016-9817-7 is not listed on IDEAS
    18. World Bank, 2005. "Central America : Education Strategy Paper," World Bank Other Operational Studies 8397, The World Bank.

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