China 
Africa 
Explore chapters and articles related to this topic
Probability Distributions
Published in Alan R. Jones, Probability, Statistics and Other Frightening Stuff, 2018
In truth, the answer is ‘only as an empirical Rule of Thumb’. It was first observed by Pareto in 1906, based on his earlier work in 1896 in relation to wealth distribution. It was later observed by Juran (published in 1951, but used by him previously it would seem for at least ten years) as being relevant to many other natural and man-made situations. However, Max Otto Lorenz (1905) must also take a lot of the credit for this principle; he demonstrated that the distribution of wealth across the population could be predicted by what is now known as a family of Lorenz Curves. In particular, if we take the Pareto Distribution (which only shows the proportion of the population with a given value of income or wealth) we can generate a model for the distribution of total wealth or income across the population. It is this Lorenz Curve that is the ‘Darwinian missing link’ in the evolution of the Pareto Distribution to the Pareto Principle.
The economics–ecology nexus
Published in Peter N. Nemetz, Unsustainable World, 2022
Gross domestic product (GDP) and its growth are considered the sine qua non of the economic health of a nation. However, Table 2.5 illustrates how the most common measure of well-being, GDP per capita, can lead to a seriously skewed interpretation of the relative well-being of alternative countries. In this table, two pairs of countries have been chosen with relatively similar per capita GDP. It should be apparent from a cursory examination of this table that there are profound differences between the two sets of countries despite their superficial similarity based on an average economic value (UNDP 2019). One of the most important distinctions is related to the level of income inequality. There are two common methods for measuring this variable: the Gini coefficient and comparative shares of income between the highest and lowest decile or centile. The World Bank (n.d.) defines and illustrates the Gini concept as follows:[The] Gini index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
Bayesian Estimation of Bonferroni Curve and Zenga Curve in the Case of Dagum Distribution
Published in Dinesh C. S. Bisht, Mangey Ram, Recent Advances in Time Series Forecasting, 2021
Sangeeta Arora, Kalpana K. Mahajan, Prerna Godura
The Lorenz curve gives the connection between the cumulative proportion of income units and the cumulative proportion of income received when the incomes are arranged in ascending order. The Lorenz curve has an intuitive appeal, and its graphical representation is an added advantage. The Lorenz curve, L(u), itself is a distribution function with support on [0, 1] (Aaberge, 2000;Klefsjö, 1984; Kleiber, 2003).
Assessing the energy efficiency potential of a closed-loop supply chain for household durable metal products in China
Published in International Journal of Production Research, 2023
Furthermore, the cumulative function of the income distribution function constitutes the Lorenz curve, which can generate the Gini coefficient to estimate the inequality of different income residents. NBSC (2022) surveyed approximately 66,000 families from 2004 to 2012. Households were divided into eight groups according to different incomes in this time period and counted the ownership of durable goods, such as private cars and refrigerators, under different groups. However, the sampling survey of different income groups has been cancelled since 2013. The relationship between residents’ income and car ownership is shown in Figure 3. Not surprisingly, car ownership will increase with the increase in residents’ income. However, there are different degrees of vertical displacement in the curve between adjacent years, which is caused by the price index. Referring to the historical data of developed countries, car prices will decline with the development of technologies. In other words, the rise in residents’ income and the decline in car prices have jointly driven the increase in total ownership. Figure 3 shows that the interval of different years is significantly decreased after taking car prices into account. Therefore, we can take per-capita disposal income over the price index (ratio of price in year t compared to the base year) as residents’ purchasing ability for durable products.