Empirical likelihood confidence intervals for the Gini measure of income inequality

• Published in: Economic modelling Vol. 27; no. 6; pp. 1429 - 1435
• Main Authors: Qin, Yongsong, Rao, J.N.K., Wu, Changbao
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2010; Elsevier; Elsevier Science Ltd
• Series: Economic Modelling
• Subjects: Approximation; Bootstrap mechanism; Bootstrap method; Bootstrap percentile; Bootstrap percentile Bootstrap-t Confidence interval Coverage probability Gini coefficient Normal approximation; Bootstrap-t; Bootstrap-Verfahren; Confidence interval; Confidence intervals; Coverage probability; Economic inequality; Economic models; Gini coefficient; Gini-Koeffizient; Income concentration; Income distribution; Income inequality; Macroeconomics; National income; Normal approximation; Random sampling; Sampling techniques; Schätztheorie; Simulation; Studies; Bootstrap-t; Normal approximation; Coverage probability; Bootstrap percentile; Gini coefficient; Confidence interval
• ISSN: 0264-9993; 1873-6122
• DOI: 10.1016/j.econmod.2010.07.015

Gini coefficient is among the most popular and widely used measures of income inequality in economic studies, with various extensions and applications in finance and other related areas. This paper studies confidence intervals on the Gini coefficient for simple random samples, using normal approximation, bootstrap percentile, bootstrap-t and the empirical likelihood method. Through both theory and simulation studies it is shown that the intervals based on normal or bootstrap approximation are less satisfactory for samples of small or moderate size than the bootstrap-calibrated empirical likelihood ratio confidence intervals which perform well for all sample sizes. Results for stratified random sampling are also presented.