© 1993 International Bank for Reconstruction and Development / The World Bank
research-article |
Correcting for Sampling Bias in the Measurement of Welfare and Poverty in the Côte d'Ivoire Living Standards Survey
Lionel Demery is with the Education and Social Policy Department, and Christiain Grootaert is with the Transportation, Water, and Urban Development Department, both at the World Bank. This article is a result of the research project "Poverty and the Social Dimensions of Structural Adjustment in Côte d'Ivoire, 1985–88: A Policy-Oriented Analysis" (RPO 675–26). It has benefited from comments received from Chris Scott and three anonymous referees. The authors would like to thank Gi-Taik Oh and Meera Venkataraman for excellent computer programming assistance
The sampling aspects of a household data set are important to analysts. The early years of the Côte d'Ivoire Living Standards Survey (CILSS) had a sampling bias, which seriously affected estimates of population statistics such as household size. The bias arose from sampling procedures that overrepresented larger dwellings. Assuming that samples drawn in later years were unbiased, a correction procedure is applied that uses weights based on household size. Results from the weighted data are then compared with the unweighted findings to assess the seriousness of the bias. Estimates of household expenditure per capita in the early years of the survey are found to be significantly underestimated, resulting in an overestimation of poverty. The sampling bias also resulted in an underestimation of the upward trend in poverty during 1985–88. The CILSS has been a popular and fruitful data set for policy analysis. These findings, however, cast doubt on the robustness of earlier work. Thus, the effort to trace sampling information is particularly worthwhile for policy-oriented applied research.