On the identification of extreme outliers and dragon-kings mechanisms in the upper tail of income distribution |
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| Authors: | Muhammad Aslam Mohd Safari Kamarulzaman Ibrahim |
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| Institution: | 1. School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Selangor, Malaysia;2. Present address: Centre for Modelling and Data Science, Universiti Kebangsaan Malaysia, Selangor, Malaysia |
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| Abstract: | The presence of extreme outliers in the upper tail data of income distribution affects the Pareto tail modeling. A simulation study is carried out to compare the performance of three types of boxplot in the detection of extreme outliers for Pareto data, including standard boxplot, adjusted boxplot and generalized boxplot. It is found that the generalized boxplot is the best method for determining extreme outliers for Pareto distributed data. For the application, the generalized boxplot is utilized for determining the exreme outliers in the upper tail of Malaysian income distribution. In addition, for this data set, the confidence interval method is applied for examining the presence of dragon-kings, extreme outliers which are beyond the Pareto or power-laws distribution. |
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| Keywords: | Income distribution Pareto model generalized boxplot extreme outliers probability integral transform statistics |
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