Secondary special education of the republic of uzbekistan

1) Occupational Status – it is weighted average of the mean level of earnings and education of certain occupations. It has advantages such a collecting important information about parents, which can be reported retrospectively by adult children. It also remains relatively stable in between the occupation career so single measuring provides adequate information of long run standing. On the other hand, it has also limitations for the mobility analyzing. Whereas occupational earning of men usually tends to be higher than by women, by the occupational education it is the other way around.
2) Class mobility – Classes are instead categorical groupings based on specific occupational assets that determine life chances as expressed in outcomes such as income, health or wealth.
3) Earnings mobility – Earning mobility evaluates the relationship between two certain generations by means of linear regression (upper math) of the long transformed measure of children's and parents' earnings. Example from the Stanford Centre paper: With this formulation, a regression coefficient of, say, 0.4, indicates that a 10% difference in parents’ earnings will lead, on average, to 4% difference in the children’s generation. In other words, this shows, that if two dads earnings are different by 10%, their children's earnings will probably differ on average just by 4%.
4) Total Family income mobility and the mobility of women – Old economic analysis has been making one mistake, that they did analysis that focused mostly on the father-son pairs and their individual earnings. In the last two decades, they have expanded their researches and now they focus more on the mother-daughter pairs as well. Generally earnings provides a stable measure of well-being independently of another financial assets or any kind of transfers. ^[7]
Distribution measurement internationally[edit]
Main article: List of countries by income inequality
Using Gini coefficients, several organizations, such as the United Nations (UN) and the US Central Intelligence Agency (CIA), have measured income inequality by country. The Gini index is also widely used within the World Bank.^[8] It is an accurate and reliable index for measuring income distribution on a country by country level. The Gini index measurements go from 0 to 1 for 1 being perfect inequality and 0 being perfect equality. The world Gini index is measured at 0.52 as of 2016.^[9]
Classical economists such as Adam Smith (1723–1790), Thomas Malthus (1766–1834), and David Ricardo (1772–1823) concentrated their attention on factor income-distribution, that is, the distribution of income between the primary factors of production (land, labour and capital). Modern economists have also addressed issues of income distribution, but have focused more on the distribution of income across individuals and households. Important theoretical and policy concerns include the balance between income inequality and economic growth, and their often inverse relationship.^[3]
The Lorenz curve can represent the distribution of income within a society. The Lorenz curve is closely associated with measures of income inequality, such as the Gini coefficient.
Measurement[edit]

Income before (green) and after (pink) taxes and Transfer payments for different income groups starting with the lowest quintile. Top 20% people take approximately 45% of the all income.

Main article: Income inequality metrics
The concept of inequality is distinct from that of poverty^[4] and fairness. Income inequality metrics (or income distribution metrics) are used by social scientists to measure the distribution of income, and economic inequality among the participants in a particular economy, such as that of a specific country or of the world in general. While different theories may try to explain how income inequality comes about, income inequality metrics simply provide a system of measurement used to determine the dispersion of incomes.