دورية أكاديمية

The first moment of income density functions and estimation of single-parametric Lorenz curves.

التفاصيل البيبلوغرافية
العنوان: The first moment of income density functions and estimation of single-parametric Lorenz curves.
المؤلفون: Liang Frank Shao
المصدر: PLoS ONE, Vol 17, Iss 6, p e0267828 (2022)
بيانات النشر: Public Library of Science (PLoS), 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: This paper discusses the first moment, i.e., the mean income point, of income density functions and the estimation of single-parametric Lorenz curves. The mean income point is implied by an income density function and associated with a single-parametric Lorenz function. The boundary of the mean income point can show the flexibility of a parametric Lorenz function. I minimize the sum of squared errors in fitting both grouped income data and the mean income point and identify the best parametric Lorenz function using a large panel dataset. I find that each parametric Lorenz function may do a better job than others in fitting particular grouped data; however, a zero- and unit-modal single-parametric Lorenz function is identified to be the best of eight typical optional functions in fitting most (666 out of 969) observations of a large panel dataset. I perform a Monte Carlo simulation as a robustness check of the empirical estimation.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
Relation: https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0267828
URL الوصول: https://doaj.org/article/7d76d975e3374de2b3a98016fe9bef45
رقم الأكسشن: edsdoj.7d76d975e3374de2b3a98016fe9bef45
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0267828