In Germany, the Gini index increased from 26.1 points in 2005 to 28.2 points in 2022. The Gini Index is a measurement of inequality within economies, a lower score indicates more equality while a higher score implies more inequality. Germany's index score has increased since 2019 to 2021, however, it has decreased in the most recent period recorded, reaching its lowest rate since 2012.

In 2023, Bulgaria had the highest Gini Index score in the European Union at 37.2, implying that the country had the highest level of inequality among European countries. The Gini Index is a measure of inequality within economies, a lower score indicates more equality, and a higher score less equality. Slovakia had the lowest score among EU countries for 2023 with a score of 21.6, suggesting that it is the most egalitarian society in Europe.

Comparing the 130 selected regions regarding the gini index , South Africa is leading the ranking (0.63 points) and is followed by Namibia with 0.58 points. At the other end of the spectrum is Slovakia with 0.23 points, indicating a difference of 0.4 points to South Africa. The Gini coefficient here measures the degree of income inequality on a scale from 0 (=total equality of incomes) to one (=total inequality).The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

Out of the G20 countries, South Africa, Brazil, and Mexico have the highest levels of income inequality while France, the Republic of Korea, and Germany have the lowest levels of inequality. Other G20 countries in the middle have Gini coefficients between 32.5 and 42.0. The Gini coefficient measures the level of income inequality worldwide, where a higher score indicates a higher level of income inequality.

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 46.5 (0.465) 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 0.32 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 0.47 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.

Social and economic figures for 67 large West German cities. The data aggregated at city level have been collected for most topics over several years, but not necessarily over the entire reference time period.

Topics: 1. Situation of the city: surface area of the city; fringe location in the Federal Republic.

1. Residential population: total residential population; German and foreign residential population.

2. Population movement:live births; deaths; influx; departures; birth rate; death rate; population shifts; divorce rate; migration rate; illegitimate births.

3. Education figures: school degrees; occupational degrees; university degrees.

4. Wage and income: number of taxpayers in the various tax classes as well as municipality income tax revenue in the respective classes; calculated income figures, such as e.g. inequality of income distribution, mean income or mean wage of employees as well as standard deviation of these figures; GINI index.

5. Gross domestic product and gross product: gross product altogether; gross product organized according to area of business; gross domestic product; employees in the economic sectors.

6. Taxes and debts: debt per resident; income tax and business tax to which the municipality is entitled; municipality tax potential and indicators for municipality economic strength.

7. Debt repayment and management expenditures: debt repayment, interest expenditures, management expenditures and personnel expenditures.

8. From the ´BUNTE´ City Test of 1979 based on 100 respondents per city averages of satisfaction were calculated. satisfaction with: central location of the city, the number of green areas, historical buildings, the number of high-rises, the variety of the citizens, openness to the world, the dialect spoken, the sociability, the density of the traffic network, the OEPNV prices {local public passenger transport}, the supply of public transportation, provision with culture, the selection for consumers, the climate, clean air, noise pollution, the leisure selection, real estate prices, the supply of residences, one´s own payment, the job market selection, the distance from work, the number of one´s friends, contact opportunities, receptiveness of the neighbors, local recreational areas, sport opportunities and the selection of further education possibilities.

9. Traffic and economy: airport and Intercity connection; number of kilometers of subway available, kilometers of streetcar, and kilometers of bus lines per resident; car rate; index of traffic quality; commuters; property prices; prices for one´s own home; purchasing power.

10. Crime: recorded total crime and classification according to armed robbery, theft from living-rooms, of automobiles as well as from motor vehicles, robberies and purse snatching; classification according to young or adult suspects with these crimes; crime stress figures. 12. Welfare: welfare recipients and social expenditures; proportion of welfare recipients in the total population and classification according to German and foreign recipients; aid with livelihood; expenditures according to the youth welfare law; kindergarten openings; culture expenditures per resident. 13. Foreigners: proportion of foreigners in the residential population.

11. Students: number of German students and total number of students; proportion of students in the residential population.

12. Unemployed: unemployment rate; unemployed according to employment office districts and employment office departments.

13. Places of work: workers employed in companies, organized according to area of business.

14. Government employees: full-time, part-time and total government employees of federal government, states and municipalities as well as differentiated according to workers, employees, civil servants and judges.

15. Employees covered by social security according to education and branch of economy: proportion of various education levels in the individual branches of the economy.

The research project is a subproject of the research association “Strengthening of integration potentials within a modern society” (Scientific head: Prof. Dr. Wilhelm Heitmeyer, Bielefeld) which contains 17 subprojects and is supported by the ministry of education and research. In almost all the economically highly developed countries violent crime increased significantly in the second part of the last century - in contrast to the long term trend of decline of individual (non-governmental) violence since the beginning of modern times. The authors develop an explanatory approach for these facts which is inspired mainly by Norbert Elias´s civilization theory and Emil Durkheim´s theory on society. Detailed time series on the development of different forms of violent crime are presented and set in relation with certain aspects of economic and social structural changes in three countries and also refer to the changes in integration of modern societies. The analysis deals especially with effectivity and legitimacy of the governmental monopoly of violence, the public beneficial security and power system, forms of building social capital, economic and social inequality, precarity of employment, different aspects of increasing economization of society, changes in family structures and usage of mass media and modern communication technologies. Register of tables in HISTAT: A: Crime statistics A.01 Frequency of types of crimes in different countries (1953-2000) A.02 Suspects by crimes of 100.000 inhabitants of Germany, England and Sweden (1955-1998) A.03 Murders, manslaughter and intentional injuries by other persons by sex of 100.000 persons after the statistics of causes of death (1953-2000) A.04 Clearance rate by types of crimes in Germany, England and Sweden (1953-1997) A.05 Prisoners of 100.000 inhabitants of Germany, Great Britain and Sweden (1950-2000) B: Key indicators for economic development in Germany, Great Britain, Sweden and the USA B1: Data on the overall economic framework B1.01 Percent changes in the real GDP per capita in purchasing power parities (1956-1987) B1.02 Percent changes in GDP per capita in prices from 2000 (1955-1998) B1.03 GDP of Germany, Sweden and the United Kingdom in purchasing power parities in percent og the US GDP (1950-1992) B1.04 Labor productivity index for different countries, base: USA 1996 = 100 (1950-1999) B1.05 GDP per hour of labor in different countries in EKS-$ from 1999 (1950-2003) B1.06 Foreign trade - exports and imports in percent of the GDP of different countries (1949-2003) B1.07 GDP, wages and Unit-Labor-Cost in different countries (1960-2003) B2: Unemployment B2.01 Standardized unemployment rate in different countries with regard to the entire working population (1960-2003) B2.02 Share of long-term unemployed of the total number of unemployed in different countries in percent (1992-2004) B2.03 Youth unemployment in different countries in percent (1970-2004) B2.04 Unemployment rate in percent by sex in different countries (1963-2000) B3: Employment B3.01 Employment rate in percent in different countries (1960-2000) B3.02 Share of fixed-term employees and persons in dependent employment in percent in different countries (1983-2004) B3.03 Share of part-time employees by sex compared to the entire working population in different countries (1973-2000) B3.04 Share of un-voluntarily part-time employees by sex in different countries (1983-2003) B3.05 Share of contract workers in different countries in percent of the entire working population (1975-2002) B3.06 Share of self-employed persons in different countries in percent of the entire working population (1970-2004) B3.07 Shift worker rate in different countries in percent (1992-2005) B3.08 Yearly working hours per employee in different countries (1950-2004) B3.09 Employment by sectors in different countries (1950-2003) B3.10 Share of employees in public civil services in percent of the population between 15 and 64 years in different countries (1960-1999) B3.11 Female population, female employees and female workers in percent of the population between 16 and 64 years in different countries (1960-2000) B3.12 Employees, self-employed persons in percent of the entire working population in different countries (1960-2000) B4: Taxes and duties B4.01 Taxes and social security contributions in percent of the GDP (1965-2002) B4.02 Social expenditure in percent of the GDP (1965-2002) B4.03 Social expenditure in percent of the GDP (1960-2000) B4.04 Public expenditure in percent of the GDP in different countries (1960-2003) B4.05 Education expenditure in percent of GDP (1950-2001) B5: Debt B5.01 Insolvencies in Germany and England (1960-2004) B5.02 Insolvencies with regard to total population in different countries (1950-2002) B5.03 Consumer credits in different countries (1960-2002) C: Income distribution in Germany, Great Britain and Sweden C.01 Income inequality in different countries Einkommensungleicheit in verschiedenen Ländern (1949-2000) C.02 Income inequality after different indices and calculations in different countries (1969-2000) C.03 Redistribution: Decline in Gini-Index through transfers and taxes in percent in different countries (1969-2000) C.04 Redistribution: Decline in Gini-Index through transfers and taxes in percent with a population structure as in the United Kingdom in 1969 in different countries (1969-2000) C.05 Redistribution efficiency: Decline in Gini-/ Atkinson-Index through transfers and the share of social expenditure of the GDP in different countries (1969-2000) C.06 Index for concentration of transfers in different countries (1981-2000) C.07 Distribution of wealth in West-Germany (1953-1998) C.08 Distribution of wealth in the United Kingdom (1950-2000) C.09 Distribution of wealth in Sweden (1951-1999) C.10 Relative income poverty in different countries (1969-2000) C.11 Reduction of poverty in different countries (1969-2000) C.12 Neocorporalism index in different countries (1960-1994) D: Perception of safety D.01 Satisfaction with democracy in different countries (1976-2004) D.02 Revenues and employees in the private security sector in different countries (1950-2001) D.03 Decommodification-Score in different countries (1971-2002) E: Demographics E.01 Birth rates: Birth per 1000 women between 15 and 49 years in different countries (1951-2001) E.02 Fertility rate in different countries (1950-2004) E.03 Marriages per 100.000 persons in different countries (1950-2003) E.04 Share of foreigners of the entire population in different countries (1951-2002) E.05 Internal migration in different countries (1952-2001)

Im Jahr 2022 lag der Gini-Index in Deutschland bei 28,8 Punkten und ist somit um 2,4 Punkte gesunken. Der Durchschnitt in der Europäischen Union (EU-27) betrug 2022 geschätzt 29,6 Punkte (siehe auch EU-Länder nach Einkommensungleichheit im Gini-Index). br>

Der Gini-Index oder Gini-Koeffizient ist ein statistisches Maß, das zur Darstellung von Ungleichverteilungen verwendet wird. Er kann einen beliebigen Wert zwischen 0 und 100 Punkten annehmen. Der Gini-Index zeigt die Abweichung der Verteilung des verfügbaren Einkommens auf Personen oder Haushalte innerhalb eines Landes von einer vollkommen gleichen Verteilung. Ein Wert von 0 bedeutet absolute Gleichheit, ein Wert von 100 absolute Ungleichheit.