Date of Award
5-2023
Document Type
Thesis
Degree Name
Master of Arts in Mathematics
Department
Mathematics
First Reader/Committee Chair
Suthakaran Ratnasingam
Abstract
A Lorenz curve is a graphical representation of the distribution of income or wealth within a population. The generalized Lorenz curve can be created by scaling the values on the vertical axis of a Lorenz curve by the average output of the distribution. In this thesis, we propose two nonparametric methods for testing the equality of two generalized Lorenz curves. Both methods are based on empirical likelihood and utilize a U -statistic. We derive the limiting distribution of the likelihood ratio, which is shown to follow a chi-squared distribution with one degree of freedom. We conduct simulations to compare the proposed methods and an existing method by examining Type I error rates and power across various sample sizes and distribution assumptions. Our results show that the proposed methods exhibit superior performance in finite samples, particularly in small sample sizes, and are robust across various scenarios. Finally, we use real-world data to illustrate the methods of testing two generalized Lorenz curves.
Recommended Citation
Butenko, Anton, "Jackknife Empirical Likelihood Tests for Equality of Generalized Lorenz Curves" (2023). Electronic Theses, Projects, and Dissertations. 1624.
https://scholarworks.lib.csusb.edu/etd/1624