Modeling the incomes of the upper-class group in Malaysia using new pareto-type distribution
Document Type
Article
Publication Date
10-1-2022
Abstract
The new Pareto-type distribution has been previously introduced as an alternative to the conventional Pareto distribution in modeling income distribution. It is claimed to provide better flexibility for mathematical simplicity of probability functions and has a more straightforward mathematical form. In this study, the new Pareto-type distribution is used to model the income of the Malaysian upper-class group. The threshold is determined using the fixed proportion technique and the maximum likelihood estimator method is used to estimate the shape parameter. Then, the goodness-of-fit of the fitted new Pareto model is measured using the coefficient of determination, R-2 and Kolmogorov-Smirnov statistics. We also measure the income inequality among the Malaysian top income earners using the Lorenz curve, Gini and Theil indices based on the fitted new Pareto model. Finally, the new Pareto distribution is compared to alternative distributions to analyze which model can give the best fit for the data. Our analysis shows that the Pareto type-1 and the new Pareto models are well fitted to the top income data for all years considered. However, the new Pareto model provides better flexibility which covering more incomes in the upper tail of the distribution than the Pareto type-1 model.
Keywords
Gini index, Income inequality, Lorenz curve, Pareto model, Theil index
Publication Title
Sains Malaysiana
Recommended Citation
Abd Raof, Anis Syazwani; Haron, Mohd Azmi; Mohd Safari, Muhammad Aslam; and Siri, Zailan, "Modeling the incomes of the upper-class group in Malaysia using new pareto-type distribution" (2022). Research Publications (2021 to 2025). 1365.
https://knova.um.edu.my/research_publications_2021_2025/1365
Divisions
MathematicalSciences
Funders
Universiti Malaya GPF088B-2020,RF011B 2018FS
Volume
51
Issue
10
Publisher
Penerbit Universiti Kebangsaan Malaysia
Publisher Location
FACULTY SCIENCE & TECHNOLOGY, BANGI, SELANGOR, 43600, MALAYSIA