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Measuring the Evolution of Complex Indicators: Theory and Application to the Poverty Rate in France

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  • Xavier D'haultfoeuille
  • Fabien Dell

Abstract

This paper addresses the issue of measuring and testing evolutions of complex indicators estimated by surveys. This problem amounts to compute the variance of these complex statistics, but also their covariance over time. Rotating designs may indeed bring important positive correlations between indicators. These correlations are often neglected in testing temporal stability, leading to conclusions deemed to be too conservative. We obtain variance and covariance estimators by adapting the functional delta method to survey sampling. Finally, our method is applied to the evolution of the poverty rate in France.

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  • Xavier D'haultfoeuille & Fabien Dell, 2008. "Measuring the Evolution of Complex Indicators: Theory and Application to the Poverty Rate in France," Annals of Economics and Statistics, GENES, issue 90, pages 259-290.
    • Handle: RePEc:adr:anecst:y:2008:i:90:p:259-290
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    1. Yves Berger, 2004. "A Simple Variance Estimator for Unequal Probability Sampling without Replacement," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(3), pages 305-315.
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