Income distribution and inequality measurement : the problem of extreme values
We examine the statistical performance of inequality indices in the presence of extreme values in the data and show that these indices are very sensitive to the properties of the income distribution. Estimation and inference can be dramatically affected, especially when the tail of the income distribution is heavy, even when standard bootstrap methods are employed. However, use of appropriate methods for modelling the upper tail can greatly improve the performance of even those inequality indices that are normally considered particularly sensitive to extreme values.
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- Davidson, Russell & Flachaire, Emmanuel, 2007.
"Asymptotic and bootstrap inference for inequality and poverty measures,"
Journal of Econometrics,
Elsevier, vol. 141(1), pages 141-166, November.
- Russell Davidson & Emmanuel Flachaire, 2004. "Asymptotic and bootstrap inference for inequality and poverty measures," Cahiers de la Maison des Sciences Economiques v04100, Université Panthéon-Sorbonne (Paris 1).
- Russell Davidson & Emmanuel Flachaire, 2007. "Asymptotic and bootstrap inference for inequality and poverty measures," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00175929, HAL.
- Russell Davidson & Emmanuel Flachaire, 2006. "Asymptotic And Bootstrap Inference For Inequality And Poverty Measures," Departmental Working Papers 2005-06, McGill University, Department of Economics.
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