Correcting for sampling bias in the measurement of welfare and poverty : the case of the Cote d'Ivoire living standards survey

Over the years, household surveys have become a popular, valuable data source for empirical research in microeconomics. In developing countries, household survey data have become more available in the past decade, as a result of several international programs. This has spurred interest in the economics of the household in the context of development economics. Many analysts give little attention to the sampling design of the surveys they use, taking the data produced by statisticians and survey practitioners as is. At best, sampling weights are applied to ensure that the results are representative. The authors illustrate the need to pay close attention to the sampling aspects of a household survey used in applied microeconomic analysis - particularly for comparisons over time. This case study shows that observed changes in household welfare and in the incidence of poverty in Cote d'Ivoire between 1985 and 1988 vanish when corrections are applied to the data for changes in sampling procedures; even the direction of the trend is reversed. Similarly, the cross-sectional patterns of welfare and poverty observed in earlier analyses for 1985-86 prove to be incorrect. The Cote d'Ivoire Living Standards Survey, conducted between 1985 and 1988, has provided a popular, fruitful data set for policy analysis. But according to the authors, the recorded decline in mean household size during this period is due to sampling bias in the early years of the survey. If this is true, the robustness of the analyses based on these data is questionable.