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Variance estimation for generalized entropy and Atkinson inequality indices: The complex survey data case

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Martin Biewen () (University of Frankfurt)

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Abstract

We derive the sampling variances of generalized entropy and Atkinson indices when estimated from complex survey data, and we show how they can be calculated straightforwardly by using widely available software. We also show that, when the same approach is used to derive variance formulae for the i.i.d. case, it leads to estimators that are simpler than those proposed before. Both cases are illustrated with a comparison of income inequality in Britain and Germany.

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Paper provided by Stata Users Group in its series German Stata Users' Group Meetings 2006 with number 04.

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Date of creation: 24 May 2006
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Handle: RePEc:boc:dsug06:04

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  1. Stephen P. Jenkins & John Micklewright, 2007. "New Directions in the Analysis of Inequality and Poverty," Working Papers 71, ECINEQ, Society for the Study of Economic Inequality. [Downloadable!]
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  2. Stéphane Mussard & Pi Alperin María Noel, 2006. "Measuring Significance of Inequalities with Heterogeneous Groups and Income Sources," Cahiers de recherche 06-13, Departement d'Economique de la Faculte d'administration à l'Universite de Sherbrooke. [Downloadable!]
  3. Jenkins, Stephen P. & Burkhauser, Richard V. & Feng, Shuaizhang & Larrimore, Jeff, 2009. "Measuring Inequality Using Censored Data: A Multiple Imputation Approach," IZA Discussion Papers 4011, Institute for the Study of Labor (IZA). [Downloadable!]
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