Related Experiment Video
Updated: Jun 29, 2025
06:00
Author Spotlight: Development of a Smartphone-Enhanced Paper-Based Device for Rapid Dengue NS1 Detection
Published on: January 26, 2024
1.3K
Quantifying fair income distribution in Thailand
Thitithep Sitthiyot1, Kanyarat Holasut2
1Department of Banking and Finance, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok, Thailand.
Plos One
|April 4, 2024
Summary
Thailand
Area of Science:
- Economics
- Social Sciences
Background:
- Global preference for fair income inequality.
- High income inequality is a concern in Thailand.
Purpose of the Study:
- Examine fairness of Thailand's income distribution over three decades.
- Determine ideal fair income distribution for Thailand.
Main Methods:
- Utilized fairness benchmarks from professional sports salary distributions.
- Applied principles of distributive justice, procedural justice, and no-envy.
- Analyzed Thai quintile income shares and Gini index (1988-2021).
Main Results:
- Bottom 20%, second 20%, and top 20% income earners received more than fair shares.
- Third 20% and fourth 20% income earners received less than fair shares.
- Identified specific fair income distribution benchmarks for Thailand.
Conclusions:
- Fairness benchmarks offer practical policy guidelines for Thailand's income distribution.
- Proposed an optimal, fair income distribution model for Thailand.
Related Concept Videos
01:06Skewness
11.0K
The measures of central tendency calculated from a data set may not reveal much about its intrinsic distribution. If a plot is made of the data set’s values, the mean and the median may not only differ, but also the plot may have more values on one side of the central tendencies. Such a data set is said to be skewed towards that side.
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
The longer the tail of the plot on one side, the more skewed it is. The skewness of a data set’s values suggests that the measures of central tendency...
11.0K
02:16Measures of Central Tendency
16.0K
The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians,...
16.0K
01:26Distributions to Estimate Population Parameter
4.1K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.1K
01:19F Distribution
3.7K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
3.7K
01:23Test for Homogeneity
2.0K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
2.0K
01:19Uniform Distribution
4.9K
The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.
Two essential properties of this distribution are
Two essential properties of this distribution are
4.9K