EconBase
← All papers

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

Silvia De Nicolò, Maria Rosaria Ferrante, Silvia Pacei

arXiv 19 Jul 2021 · Statistics — Methodology · 1 citations (OpenAlex)

arXiv:2107.08950 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

49
references
79
in-text mentions
49
distinct cited
2
self-citations
7,749
main-text words

appendix boundary found by appendix_command · 88% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Breunig, R (2001) An almost unbiased estimator of the coefficient of variation1.00053100%
2Graf, M (2011) Use of survey weights for the analysis of compositional data0.8435460%
3Davidson, R (2009) Reliable inference for the Gini index0.81142100%
4Deltas, G (2003) The small-sample bias of the Gini coefficient: Results and implications for empirical research0.73732100%
5Langel, M. and Tillé, Y (2013) Variance estimation of the Gini index: Revisiting a result several times published0.73732100%
6Breunig, R. and Hutchinson, D. L.-A (2008) Small sample bias corrections for inequality indices0.64441100%
7Atkinson, A (2015) Handbook of Income Distribution, volume 20.64422100%
8Biewen, M. and Jenkins, S. P (2006) Variance estimation for Generalized Entropy and Atkinson inequality indices: The complex survey data case0.64422100%
9Fabrizi, E. and Trivisano, C (2016) Small area estimation of the Gini concentration coefficient0.64422100%
10Van Kerm, P (2007) Extreme incomes and the estimation of poverty and inequality indicators from EU-SILC0.64422100%

Showing the top 10 of 49 scored citations.