Mind the Income Gap: Bias Correction of Inequality Estimators in Small-Sized Samples

Silvia De Nicol\`o, Maria Ferrante and Silvia Pacei

Papers from arXiv.org

Abstract: Income inequality estimators are biased in small samples, leading generally to an underestimation. This aspect deserves particular attention when estimating inequality in small domains and performing small area estimation at the area level. We propose a bias correction framework for a large class of inequality measures comprising the Gini Index, the Generalized Entropy and the Atkinson index families by accounting for complex survey designs. The proposed methodology does not require any parametric assumption on income distribution, being very flexible. Design-based performance evaluation of our proposal has been carried out using EU-SILC data, their results show a noticeable bias reduction for all the measures. Lastly, an illustrative example of application in small area estimation confirms that ignoring ex-ante bias correction determines model misspecification.

Date: 2021-07, Revised 2023-05
New Economics Papers: this item is included in nep-dcm and nep-ecm
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