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Variance estimation techniques for poverty and inequality measures from complex surveys: a simulation study

Riccardo De Santis (), Lucio Barabesi () and Gianni Betti ()

Department of Economics University of Siena from Department of Economics, University of Siena

Abstract: The theme of variance estimation is central in sampling surveys, due to the necessity of furnishing a measure of accuracy for the estimates. In the ambit of social surveys, where we have to face with complex designs and complex statistics, it may be a major issue. To solve this matter, two main approaches can be found in the literature, and both have advantages and disadvantages. However, linearization methods can be safely used in a design-based approach. On the contrary, resampling methods are introduced only in a model-based approach, which means that the properties have to be assessed. Furthermore, some approximations are required. Therefore, we decide to conduce a simulation study by the use of a complete population available. We will focus on some poverty measures considered by the statistical office of the European Union

Keywords: variance estimation; poverty measures; simulation study (search for similar items in EconPapers)
JEL-codes: C15 C83 I32 (search for similar items in EconPapers)
Date: 2020-05
New Economics Papers: this item is included in nep-ore
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