Unrestricted Statistical Inference with Lorenz Curves and Income Shares
AbstractThis paper considers the problem of statistical inference with estimated Lorenz curves and income shares. The asymptotic distribution of a vector of Lorenz curve ordinates corresponding to a set of cdf abscissa values is shown to be normal with a variance-covariance structure that depends only on condition first and second moments that can be estimated consistently without specification of the population density underlying the sample data.
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Bibliographic InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 464.
Date of creation: 1982
Date of revision:
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- Gordon Anderson, 2008. "The empirical assessment of multidimensional welfare, inequality and poverty: Sample weighted multivariate generalizations of the Kolmogorov–Smirnov two sample tests for stochastic dominance," Journal of Economic Inequality, Springer, vol. 6(1), pages 73-87, March.
- Gordon Anderson, 2003. "Poverty in America 1970-1990: who did gain ground? An application of stochastic dominance criteria employing simultaneous inequality tests in a partial panel," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 621-640.
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