Income modeling with the Weibull mixtures

Abu Bakar, Shaiful Anuar and Pathmanathan, Dharini (2022) Income modeling with the Weibull mixtures. Communications In Statistics-Theory And Methods, 51 (11). pp. 3612-3628. ISSN 0361-0926, DOI

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In this paper, we introduce six Weibull based mixture distributions to model income data. Several statistical properties of these models are derived and their closed forms are presented. The mixture model parameters are estimated using the maximum likelihood method and their performances are assessed with respect to average income per tax unit data for ten countries using information based criteria approaches as well as graphical observations. In addition, we provide application of these models to two popular inequality measures, the Gini and Bonferroni indexes as well as the common generalized entropy index. Analytic expressions of the poverty measures are given for head-count ratio and poverty-gap ratio. All the mixture models show good fit to the data with close proximity to empirical Gini and Bonferroni indexes in almost all ten countries where the income data sets are studied.

Item Type: Article
Funders: Universiti Malaya (Grant No. GPF028B-2018)
Uncontrolled Keywords: Weibull mixture models; maximum likelihood estimation; income data; information criteria
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 06 Oct 2023 15:02
Last Modified: 08 Oct 2023 12:58

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