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

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Tác giả: Silvia De Nicolò, Maria Rosaria Ferrante, Silvia Pacei

Ngôn ngữ: eng

Ký hiệu phân loại: 339.22 Distribution of aggregate personal income and wealth

Thông tin xuất bản: 2021

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 167455

Comment: 21 pages, 4 figuresIncome 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.
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