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Your search keyword '"PARETO distribution"' showing total 5 results
Start Over Descriptor "PARETO distribution" Region malaysia
5 results on '"PARETO distribution"'

1. Three-Part Composite Pareto Modelling for Income Distribution in Malaysia.

Author

Majid, Muhammad Hilmi Abdul, Ibrahim, Kamarulzaman, and Masseran, Nurulkamal

Subjects
*INCOME distribution, *PARETO distribution, *INCOME inequality, *GAUSSIAN distribution
Abstract

Income distribution models can be useful for describing the economic properties of a population. In this study, three-part composite Pareto models are fitted to the income distribution in Malaysia for the years 2007, 2009, 2012, 2014, and 2016. The three-part composite Pareto models divide the population into three parts, each following a different distribution model. The lower part follows the inverse Pareto distribution, the upper part follows the Pareto distribution, and the middle part follows another unspecified distribution model. For application in income data, the use of Gaussian mixture distribution is proposed for the middle part, making the inverse Pareto–Gaussian mixture-Pareto distribution model semi-parametric. From the model, it is found that the levels of income inequality in the lower and upper income groups decrease over the period of study. Additionally, the proportion of data following the inverse Pareto distribution in the model is highly correlated with the official absolute poverty incidence. [ABSTRACT FROM AUTHOR]

Published
2023
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2. Analysis of inequality in the upper-tail of urban household incomes in Malaysia.

Author

Masseran, Nurulkamal, Safari, Muhammad Aslam Mohd, Lok, Chau Meng, Hussain, Saiful Izzuan, Ibrahim, Siti Nur Iqmal, Ibrahim, Noor Akma, Ismail, Fudziah, Lee, Lai Soon, Leong, Wah June, Midi, Habshah, and Wahi, Nadihah

Subjects
*INCOME, *INCOME inequality, *LORENZ curve, *ECONOMIC expansion, *PARETO distribution
Abstract

Income inequality is a matter of concern for any society and an interesting discussion topic, particularly for developing countries, since high-income inequality could be detrimental to economic growth. In Malaysia, upper-income earners are classified as the T20 group. This study analyzes the demographic profile of members of the T20 group living in urban areas in Malaysia. The upper-income distribution is described using the Pareto model, and a robust and efficient estimator called the probability integral transform statistic estimator is utilized to estimate the shape parameter of this model. Thereafter, a Gini index and Lorenz curve are derived to analyze the severity of income inequality among T20 group members. [ABSTRACT FROM AUTHOR]

Published
2020
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3. Probability Distribution of Extreme Share Returns in Malaysia.

Author

Wan Zin, Wan Zawiah, Mohd Safari, Muhammad Aslam, Jaaman, Saiful Hafizah, and Wendy Ling Shin Yie

Subjects
*DISTRIBUTION (Probability theory), *RATE of return on stocks, *L-moments, *EXTREME value theory, *PARETO distribution, *LOGNORMAL distribution, *FINANCIAL market reaction
Abstract

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively. [ABSTRACT FROM AUTHOR]

Published
2014
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4. Measuring income inequality: A robust semi-parametric approach.

Author

Safari, Muhammad Aslam Mohd, Masseran, Nurulkamal, Ibrahim, Kamarulzaman, and Hussain, Saiful Izzuan

Subjects
*INCOME inequality, *LORENZ curve, *GINI coefficient, *PARETO distribution, *INCOME, *INTEGRAL transforms
Abstract

In practice, income distributions are often contaminated with outliers that can affect the estimation of the income inequality. In this study, we propose a robust method for measuring income inequality based on a semi-parametric approach that applicable to positive income data. The semi-parametric approach introduced here combines the inverse-Pareto, empirical, and Pareto distributions. In addition, a robust estimation method based on probability integral transform statistic is applied to estimate the shape parameters of the inverse-Pareto and Pareto models to allow for the presence of outliers in the lower and upper tails of an income distribution. Then, a semi-parametric form of the Lorenz curve and three inequality measures are derived, including the Gini coefficient, generalized entropy index, and Atkinson index. We conduct a simulation study to compare the performance of the proposed semi-parametric approach with that of the conventional non-parametric method for estimating income inequality in the presence of outliers. The results show that the income inequality measure based on the proposed semi-parametric approach outperforms the conventional non-parametric method. Lastly, we apply the proposed semi-parametric approach in the measurement of income inequality among households in Malaysia based on survey data of household incomes for the years 2007, 2009, 2012, and 2014. • A robust semi-parametric approach for measuring income inequality is proposed. • The PITSE is used to estimate the tail index of the inverse-Pareto and Pareto. • A semi-parametric form of several inequality indices are derived. • The proposed approach is applied for measuring income inequality in Malaysia. [ABSTRACT FROM AUTHOR]

Published
2021
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5. Outliers detection for Pareto distributed data.

Author

Safari, M. A. Mohd, Masseran, N., Ibrahim, K., Ibrahim, Hanafiah, Jumali, Noorani, and Hasbullah

Subjects
*OUTLIERS (Statistics), *PARETO distribution, *BOX plots (Graphs), *INCOME inequality, *COMPUTER simulation
Abstract

This study aims to examine the presence of outliers in the upper tail of Malaysian income distribution under the assumption that the data follow Pareto model. For this purpose, three types of boxplot: standard boxplot, adjusted boxplot and generalized boxplot are considered. The performance of these boxplots is determined by a simulation study. In this study, the data were simulated from Pareto distribution, P(1, α = 2, 3, 4), then the simulated data were contaminated by replacing a proportion ε (3%, 5%, 10%) of randomly selected data. It is found that the generalized boxplot gives higher power value compared to the standard and adjusted boxplots. Therefore, the generalized boxplot was used for determining the presence of outliers in the upper tail of income distribution, while the threshold for Pareto tail modelling was determined by using Van Kerm’s formula. The results showed that 0.4%, 0.4%, 0.9% and 1.2% outliers were detected by the generalized boxplot in the household income data that exceeded the threshold for the years of 2007, 2009, 2012 and 2014. [ABSTRACT FROM AUTHOR]

Published
2018
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