This statistic shows the inequality of income distribution in China from 2005 to 2023 based on the Gini Index. In 2023, China reached a score of ************ points. The Gini Index is a statistical measure that is used to represent unequal distributions, e.g. income distribution. It can take any value between 1 and 100 points (or 0 and 1). The closer the value is to 100 the greater is the inequality. 40 or 0.4 is the warning level set by the United Nations. The Gini Index for South Korea had ranged at about **** in 2022. Income distribution in China The Gini coefficient is used to measure the income inequality of a country. The United States, the World Bank, the US Central Intelligence Agency, and the Organization for Economic Co-operation and Development all provide their own measurement of the Gini coefficient, varying in data collection and survey methods. According to the United Nations Development Programme, countries with the largest income inequality based on the Gini index are mainly located in Africa and Latin America, with South Africa displaying the world's highest value in 2022. The world's most equal countries, on the contrary, are situated mostly in Europe. The United States' Gini for household income has increased by around ten percent since 1990, to **** in 2023. Development of inequality in China Growing inequality counts as one of the biggest social, economic, and political challenges to many countries, especially emerging markets. Over the last 20 years, China has become one of the world's largest economies. As parts of the society have become more and more affluent, the country's Gini coefficient has also grown sharply over the last decades. As shown by the graph at hand, China's Gini coefficient ranged at a level higher than the warning line for increasing risk of social unrest over the last decade. However, the situation has slightly improved since 2008, when the Gini coefficient had reached the highest value of recent times.

In the 2022/23 financial year, various measures of inequality in the United Kingdom decreased when compared with 2021/22. The S80/20 ratio fell from *** to ***, the P90/10 ratio from *** to ***, and the Palma ratio between *** and ***.

Cross-national research on the causes and consequences of income inequality has been hindered by the limitations of existing inequality datasets: greater coverage across countries and over time is available from these sources only at the cost of significantly reduced comparability across observations. The goal of the Standardized World Income Inequality Database (SWIID) is to overcome these limitations. A custom missing-data algorithm was used to standardize the United Nations University's World Income Inequality Database and data from other sources; data collected by the Luxembourg Income Study served as the standard. The SWIID provides comparable Gini indices of gross and net income inequality for 192 countries for as many years as possible from 1960 to the present along with estimates of uncertainty in these statistics. By maximizing comparability for the largest possible sample of countries and years, the SWIID is better suited to broadly cross-national research on income inequality than previously available sources: it offers coverage double that of the next largest income inequality dataset, and its record of comparability is three to eight times better than those of alternate datasets.

Based on the degree of inequality in income distribution measured by the Gini coefficient, Colombia was the most unequal country in Latin America as of 2022. Colombia's Gini coefficient amounted to 54.8. The Dominican Republic recorded the lowest Gini coefficient at 37, even below Uruguay and Chile, which are some of the countries with the highest human development indexes in Latin America. The Gini coefficient explained The Gini coefficient measures the deviation of the distribution of income among individuals or households in a given country from a perfectly equal distribution. A value of 0 represents absolute equality, whereas 100 would be the highest possible degree of inequality. This measurement reflects the degree of wealth inequality at a certain moment in time, though it may fail to capture how average levels of income improve or worsen over time. What affects the Gini coefficient in Latin America? Latin America, as other developing regions in the world, generally records high rates of inequality, with a Gini coefficient ranging between 37 and 55 points according to the latest available data from the reporting period 2010-2023. According to the Human Development Report, wealth redistribution by means of tax transfers improves Latin America's Gini coefficient to a lesser degree than it does in advanced economies. Wider access to education and health services, on the other hand, have been proven to have a greater direct effect in improving Gini coefficient measurements in the region.

The OECD Income Distribution database (IDD) has been developed to benchmark and monitor countries' performance in the field of income inequality and poverty. It contains a number of standardised indicators based on the central concept of "equivalised household disposable income", i.e. the total income received by the households less the current taxes and transfers they pay, adjusted for household size with an equivalence scale. While household income is only one of the factors shaping people's economic well-being, it is also the one for which comparable data for all OECD countries are most common. Income distribution has a long-standing tradition among household-level statistics, with regular data collections going back to the 1980s (and sometimes earlier) in many OECD countries.

Achieving comparability in this field is a challenge, as national practices differ widely in terms of concepts, measures, and statistical sources. In order to maximise international comparability as well as inter-temporal consistency of data, the IDD data collection and compilation process is based on a common set of statistical conventions (e.g. on income concepts and components). The information obtained by the OECD through a network of national data providers, via a standardized questionnaire, is based on national sources that are deemed to be most representative for each country.

Small changes in estimates between years should be treated with caution as they may not be statistically significant.

Fore more details, please refer to: https://www.oecd.org/els/soc/IDD-Metadata.pdf and https://www.oecd.org/social/income-distribution-database.htm

Income Inequality in Denver County, CO was 17.97779 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Denver County, CO reached a record high of 20.23338 in January of 2010 and a record low of 17.13318 in January of 2021. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Denver County, CO - last updated from the United States Federal Reserve on July of 2025.

The percentage of income held by the richest 20 percent of the population in Mexico decreased by 0.9 percentage points (-1.78 percent) compared to the previous year. In 2022, the percentage of income held thereby reached its lowest value in recent years. These figures refer to the share of total income held by the top fifth of earners in a given population.

Chile CL: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.000 % in 2022. This records a decrease from the previous number of 47.000 % for 2020. Chile CL: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 49.600 % from Dec 1987 (Median) to 2022, with 16 observations. The data reached an all-time high of 57.200 % in 1990 and a record low of 43.000 % in 2022. Chile CL: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Social: Poverty and Inequality. 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.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Income Inequality in Broward County, FL was 17.32913 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Broward County, FL reached a record high of 17.32913 in January of 2023 and a record low of 14.78784 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Broward County, FL - last updated from the United States Federal Reserve on June of 2025.

Historical dataset showing World income inequality - gini coefficient by year from N/A to N/A.

Czech Republic - Inequality of income distribution was 3.32 in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Czech Republic - Inequality of income distribution - last updated from the EUROSTAT on June of 2025. Historically, Czech Republic - Inequality of income distribution reached a record high of 3.54 in December of 2011 and a record low of 3.32 in December of 2024.

Historical dataset showing American Samoa income inequality - gini coefficient by year from N/A to N/A.

Historical dataset showing East Asia & Pacific income inequality - gini coefficient by year from N/A to N/A.

Historical dataset showing Africa income inequality - gini coefficient by year from N/A to N/A.

Examines how taxes and benefits redistribute income between various groups of households in the UK. The study shows where different types of households and individuals are in the income distribution and looks at the changing levels of income inequality over time.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: household income

Nigeria NG: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 43.000 % in 2009. This records an increase from the previous number of 40.100 % for 2003. Nigeria NG: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 43.000 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 51.900 % in 1996 and a record low of 38.700 % in 1985. Nigeria NG: Gini Coefficient (GINI Index): World Bank Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Poverty. 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.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

The percentage of income held by the richest 20 percent of the population in El Salvador saw no significant changes in 2022 in comparison to the previous year 2021 and remained at around 44.8 percent. Still, 2022 marked the second consecutive decline of the percentage of income held. These figures refer to the share of total income held by the top fifth of earners in a given population.Find more key insights for the percentage of income held by the richest 20 percent of the population in countries like Honduras and Costa Rica.

The 2019 International Social Survey Programme (ISSP) studied economic inequality in Finland. The respondents' attitudes were surveyed on income disparity between social groups, occupations and societies as well as which actors in society should solve these disparities. In addition, the survey charted the respondents' socio-economic situation, Finnish taxation, and conflicts between social groups. The previous ISSP survey regarding inequality was collected in 2009. First, the respondents' opinions were charted concerning the importance of different factors for succeeding in life, such as parents' wealth, ambition, social networks, corruption, or gender. Additionally, views were canvassed on fairness of differences in wealth between rich and poor countries. The respondents were also asked to estimate what persons in different occupations earned (euros/month, gross) and what the respondents thought they ought to be paid. Next, the respondents were presented with a set of statements that they were asked to agree or disagree with on a 5-point Likert scale. The questions concerned, for example, whether income disparity was too great in Finland, who should intervene with income disparity, whether the policies of the government were justified and whether the current level of taxation was justified. The respondents also placed themselves on a 10-point scale according to whether they considered themselves to be at the top or the bottom in society - currently, in childhood home and ten years into the future. Their views were also enquired on which factors they deemed important in deciding one's level of pay. Views on the hierarchical structure of society were examined by showing the respondents five figures representing differently built societies and asking which of the figures corresponded most closely to the situation in the respondent's own country, and which figure corresponded most closely to an optimal situation. The respondents were also asked questions regarding their economic situation at the time of the survey. Background variables included, for instance, gender, year of birth, region of residence (NUTS2), occupation, educational background, religious affiliation, which party the respondent voted for in previous elections, number of children, income, marital status, and statistical grouping of municipalities (urban, semi-urban, rural). The survey also included questions concerning the respondent's spouse/partner and parents' occupations.

Income Inequality in Bronx County, NY was 25.92554 Ratio in January of 2023, according to the United States Federal Reserve. Historically, Income Inequality in Bronx County, NY reached a record high of 25.92554 in January of 2023 and a record low of 17.84934 in January of 2010. Trading Economics provides the current actual value, an historical data chart and related indicators for Income Inequality in Bronx County, NY - last updated from the United States Federal Reserve on July of 2025.

Historical dataset showing Vietnam income inequality - gini coefficient by year from N/A to N/A.