Measuring Significance of Inequalities with Heterogeneous Groups and Income Sources
The aim of this paper is threefold. First, we propose a bidimensional decomposition of the Gini ratio that combines two decomposition techniques of inequality measurement in a bivariate distribution context. Usually decomposed measures of inequality are gauged to be significant or not, using non-stratified bootstrap techniques. Second, we show, with an illustrative example on the Italian survey on household’s income and wealth, that the stratified bootstrap yields less distortion in estimated parameters. Finally, a brief review of the well-known confidence intervals follows.
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- Mills, Jeffrey A & Zandvakili, Sourushe, 1997.
"Statistical Inference via Bootstrapping for Measures of Inequality,"
Journal of Applied Econometrics,
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- Stephane Mussard, 2004. "The bidimensional decomposition of the Gini ratio. A case study: Italy," Applied Economics Letters, Taylor & Francis Journals, vol. 11(8), pages 503-505.
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