Date of Award
11-28-2007
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr. Gengsheng (Jeff) Qin - Chair
Second Advisor
Dr. Xu Zhang
Third Advisor
Dr. Pulak Ghosh
Fourth Advisor
Dr. Yu-Sheng Hsu
Abstract
Lorenz curves are extensively used in economics to analyze income inequality metrics. In this thesis, we discuss confidence interval estimation methods for generalized Lorenz curve. We first obtain normal approximation (NA) and empirical likelihood (EL) based confidence intervals for generalized Lorenz curves. Then we perform simulation studies to compare coverage probabilities and lengths of the proposed EL-based confidence interval with the NA-based confidence interval for generalized Lorenz curve. Simulation results show that the EL-based confidence intervals have better coverage probabilities and shorter lengths than the NA-based intervals at 100p-th percentiles when p is greater than 0.50. Finally, two real examples on income are used to evaluate the applicability of these methods: the first example is the 2001 income data from the Panel Study of Income Dynamics (PSID) and the second example makes use of households’ median income for the USA by counties for the years 1999 and 2006
DOI
https://doi.org/10.57709/1059694
Recommended Citation
Belinga-Hill, Nelly E., "Empirical Likelihood Confidence Intervals for Generalized Lorenz Curve." Thesis, Georgia State University, 2007.
doi: https://doi.org/10.57709/1059694