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Testing Lorenz Curves with Non-Simple Random Samples

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  • Buhong Zheng

    (Dept. of Economics, University of Colorado at Denver, U.S.A.)

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  • Buhong Zheng, 2002. "Testing Lorenz Curves with Non-Simple Random Samples," Econometrica, Econometric Society, vol. 70(3), pages 1235-1243, May.
    • Handle: RePEc:ecm:emetrp:v:70:y:2002:i:3:p:1235-1243
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    Cited by:

    1. Francesco Andreoli & Arnaud Lefranc, 2013. "Equalization of opportunity: Definitions and implementable conditions," Working Papers 310, ECINEQ, Society for the Study of Economic Inequality.
    2. Gengsheng Qin & Baoying Yang & Nelly Belinga-Hall, 2013. "Empirical likelihood-based inferences for the Lorenz curve," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 1-21, February.
    3. Roosen J. & Hennessy D.A., 2004. "Testing for the Monotone Likelihood Ratio Assumption," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 358-366, July.
    4. Andreoli, Francesco & Havnes, Tarjei & Lefranc, Arnaud, 2014. "Equalization of Opportunity: Definitions, Implementable Conditions and Application to Early-Childhood Policy Evaluation," IZA Discussion Papers 8503, Institute of Labor Economics (IZA).
    5. Beat Hulliger & Tobias Schoch, 2014. "Robust, distribution-free inference for income share ratios under complex sampling," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 63-85, January.
    6. Louis Mesnard, 2022. "About some difficulties with the functional forms of Lorenz curves," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 939-950, December.
    7. Francesco Andreoli & Tarjei Havnes & Arnaud Lefranc, 2019. "Robust Inequality of Opportunity Comparisons: Theory and Application to Early Childhood Policy Evaluation," The Review of Economics and Statistics, MIT Press, vol. 101(2), pages 355-369, May.
    8. Bram Thuysbaert, 2008. "Inference for the measurement of poverty in the presence of a stochastic weighting variable," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 33-55, March.
    9. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2021. "Extremal points of Lorenz curves and applications to inequality analysis," Papers 2103.03286, arXiv.org.
    10. Stephen Jenkins, 2006. "Variance estimation for quantile group shares, cumulative shares, and Gini coefficient," United Kingdom Stata Users' Group Meetings 2006 07, Stata Users Group.
    11. Francesco Andreoli, 2013. "Inference for Inverse Stochastic Dominance," Working Papers 295, ECINEQ, Society for the Study of Economic Inequality.
    12. Dean Jolliffe, 2003. "On the Relative Well‐Being of the Nonmetropolitan Poor: An Examination of Alternate Definitions of Poverty during the 1990s," Southern Economic Journal, John Wiley & Sons, vol. 70(2), pages 295-311, October.
    13. Zhang, Xiaoke & Gastwirth, Joseph L., 2019. "Large sample properties of a new measure of income inequality," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 50-56.
    14. Zhao, Puying & Haziza, David & Wu, Changbao, 2020. "Survey weighted estimating equation inference with nuisance functionals," Journal of Econometrics, Elsevier, vol. 216(2), pages 516-536.
    15. Pier Luigi Conti & Alberto Iorio & Alessio Guandalini & Daniela Marella & Paola Vicard & Vincenzina Vitale, 2020. "On the estimation of the Lorenz curve under complex sampling designs," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 1-24, March.
    16. Bhattacharya, Debopam, 2005. "Asymptotic inference from multi-stage samples," Journal of Econometrics, Elsevier, vol. 126(1), pages 145-171, May.
    17. Amparo Ba'illo & Javier C'arcamo & Carlos Mora-Corral, 2024. "Tests for almost stochastic dominance," Papers 2403.15258, arXiv.org.
    18. Francesco Andreoli, 2018. "Robust Inference for Inverse Stochastic Dominance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 146-159, January.

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