In Germany, the Gini index increased from **** points in 2005 to **** 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.

Germany - Inequality of income distribution was 4.49 in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Germany - Inequality of income distribution - last updated from the EUROSTAT on June of 2025. Historically, Germany - Inequality of income distribution reached a record high of 5.12 in December of 2014 and a record low of 4.30 in December of 2012.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in New Germany, MN, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 30,969, while the mean income for the highest quintile (20% of households with the highest income) is 215,949. This indicates that the top earners earn 7 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 309,570, which is 143.35% higher compared to the highest quintile, and 999.61% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany median household income. You can refer the same here

In 2024, *** percent of the population in Germany were considered to have a high income, while **** percent were at risk of poverty. The income wealth rate thus remained unchanged compared to the previous year, while the at-risk-of-poverty rate fell for the second year in a row. The sum of the two rates as an indicator of social inequality thus fell by *** percentage points to **** percentage points.

Germany - Income distribution was 4.49 in December of 2024, according to the EUROSTAT. The income distribution ratio considers the total income received by the 20 % of the population with the highest income to that received by the 20 % of the population with the lowest income.

This article provides an overview of wealth inequality in Germany during 1300-1850, introducing a novel database. We document four alternating phases of inequality decline and growth. The Black Death (1347-1352) led to inequality decline, until about 1450. Thereafter, inequality rose steadily. The Thirty Years’ War (1618-1648) and the 1627-1629 plague triggered a second phase of inequality reduction. This distinguishes Germany from other European areas where inequality grew monotonically. Inequality growth resumed from about 1700, well before the Industrial Revolution. Our findings offer new material to current debates on the determinants of inequality change in western societies, past and present

Germany - Gini coefficient of equivalised disposable income was 29.50% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Germany - Gini coefficient of equivalised disposable income - last updated from the EUROSTAT on June of 2025. Historically, Germany - Gini coefficient of equivalised disposable income reached a record high of 31.20% in December of 2021 and a record low of 28.30% in December of 2012.

The deposited data allows replication of the statistical analysis and figures in "Warfare and Economic Inequality: Evidence from Preindustrial Germany (c. 1400-1800)". The question the project adresses is simple: What was the impact of military conflict on economic inequality? I argue that ordinary military conflicts increased local economic inequality. Warfare raised the financial needs of towns in preindustrial times, leading to more resource extraction from the population. This resource extraction happened via inequality-promoting channels, such as regressive taxation. Only in truly major wars might inequality-reducing destruction outweigh inequality-promoting extraction and reduce inequality. To test this argument I construct a novel panel dataset combining information about economic inequality in 75 localities, and more than 700 conflicts over four centuries. I find that the many ordinary conflicts — paradigmatic of life in the preindustrial world — were continuous reinforcers of economic inequality. I confirm that the Thirty Years’ War was indeed a great equaliser, but this was an exception and not the rule. Rising inequality is an underappreciated negative externality in times of conflict.

In 2023, there were 577,000 German households with a household net income of under 500 euros per month. Approximately 18 percent of households had a monthly income of 5,000 euros and more. Disposable net income While at first glance the aforementioned monthly income may seem manageable, based on general German standards of living, it is worth noting that flexibility and expenditure depends on the number of people living in a household, or rather the number of earners in relation to that number. In the case of employed population members, what remains as disposable net income is influenced by various regular payments made by households after the already taxed salary arrives. These payments include, but are not limited to, rent, different types of insurance, repaying loans, fees for internet and mobile phone services. Food and housing When looking at private household spending in Germany, consistent patterns emerge. Housing, water, electricity, gas and other fuel made up the largest share and will increase even further in the coming months, followed by food, beverages, and tobacco.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in New Germany. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In New Germany, the median income for all workers aged 15 years and older, regardless of work hours, was $53,438 for males and $33,889 for females.

These income figures highlight a substantial gender-based income gap in New Germany. Women, regardless of work hours, earn 63 cents for each dollar earned by men. This significant gender pay gap, approximately 37%, underscores concerning gender-based income inequality in the city of New Germany.

- Full-time workers, aged 15 years and older: In New Germany, among full-time, year-round workers aged 15 years and older, males earned a median income of $62,778, while females earned $47,813, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in New Germany.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Germany median household income by race. You can refer the same here

Germany DE: Income Share Held by Second 20% data was reported at 12.800 % in 2020. This records a decrease from the previous number of 13.100 % for 2019. Germany DE: Income Share Held by Second 20% data is updated yearly, averaging 13.100 % from Dec 1991 (Median) to 2020, with 30 observations. The data reached an all-time high of 13.700 % in 1996 and a record low of 12.800 % in 2020. Germany DE: Income Share Held by Second 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Poverty and Inequality. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.;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).

The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to observe them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the dashboard, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
The data on the area of life ´Income and Income Distribution´ is composed as follows:

Level and growth: Net national income (net national product) per inhabitant in constant prices (in euros), growth of the net national product per inhabitant, ratio of household income in old/new federal states (SOEP). Inequality in the income dimension: concentration of net income (EVS), concentration of net income (SOEP), share of income of the poorest 20% of the population, share of income of the richest 10% of the population. Poverty in the income dimension: Poverty rate for relative poverty - overall/West/East specific 40% poverty threshold (EVS), poverty rate for relative poverty - overall/West/East specific 40% poverty threshold (SOEP), poverty rate for relative poverty - overall /West/East specific 50% poverty threshold (EVS), poverty rate for relative poverty - overall/West/East specific 60% poverty threshold (SOEP), poverty rate for relative poverty - overall/West/East specific 60% poverty threshold (EVS), Poverty Gap Ratio. Performance adequacy of income: multiple of factor income (EVS), multiple of labor income (EVS), multiple of labor income (SOEP). Assessment of income: satisfaction with household income (SOEP), concern about one´s own economic situation, importance of income. Poverty in the consumption dimension: poverty rate for consumption poverty - 50% line (EVS), poverty rate for consumption poverty - 60% line (EVS). Inequality in the consumption dimension: Concentration of consumer spending (EVS).

As of 2022, Portugal was the EU country with the most respondents agreeing that income differences between citizens have become too great, with almost 95 percent of respondents either agreeing or strongly agreeing with the statement. Other countries which had high shares of respondents agreeing with the statement included Bulgaria, Hungary, and Lithuania, all post-communist countries which have experienced sharp upticks in inequality over recent decades. Interestingly, in Germany there is a relatively large divergence between eastern and western Germany on this issue, as the former communist East had the joint highest amount of people agreeing, with almost two-thirds strongly agreeing. On the other hand in the West, 9 percent less of respondents agreed with the statement, illustrating that 33 years since German reunification, there are still significant differences in opinion, especially concerning inequality. The three countries which agree with the statement the least were the three Nordic member states of the EU, Denmark, Finland, and Sweden. Their disagreement with the statement is likely related to the tradition of the 'Nordic model' of the welfare state in these countries, which provides comprehensive welfare support to citizens and acts to reduce inequalities. Whilst this model has come under pressure in recent decades, it is still clear tha it has resulted in the citizens of these countries viewing inequality as a much lesser problem than in other EU member states.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Germany township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Germany township, the median income for all workers aged 15 years and older, regardless of work hours, was $59,549 for males and $35,117 for females.

These income figures highlight a substantial gender-based income gap in Germany township. Women, regardless of work hours, earn 59 cents for each dollar earned by men. This significant gender pay gap, approximately 41%, underscores concerning gender-based income inequality in the township of Germany township.

- Full-time workers, aged 15 years and older: In Germany township, among full-time, year-round workers aged 15 years and older, males earned a median income of $71,813, while females earned $58,942, leading to a 18% gender pay gap among full-time workers. This illustrates that women earn 82 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Germany township.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Germany township median household income by race. You can refer the same here

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).

Germany DE: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 11.000 % in 2020. This stayed constant from the previous number of 11.000 % for 2019. Germany DE: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 8.700 % from Dec 1991 (Median) to 2020, with 30 observations. The data reached an all-time high of 11.000 % in 2020 and a record low of 6.700 % in 1993. Germany DE: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;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).

Germany DE: Poverty Headcount Ratio at National Poverty Lines: % of Population data was reported at 14.800 % in 2021. This records a decrease from the previous number of 16.000 % for 2020. Germany DE: Poverty Headcount Ratio at National Poverty Lines: % of Population data is updated yearly, averaging 16.000 % from Dec 2019 (Median) to 2021, with 3 observations. The data reached an all-time high of 16.100 % in 2019 and a record low of 14.800 % in 2021. Germany DE: Poverty Headcount Ratio at National Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Poverty and Inequality. National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.;World Bank, Poverty and Inequality Platform. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.;;This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

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.

The rising share of national income taken by the top one percent of earners is a common thread amongst almost all European countries over the past half century. As economic globalization took hold throughout the 1980s and 1990s, European countries experienced de-industrialization due to the emergence of international competitors, mostly in East Asia. At the same time, information technology and finance became much more important for most European economies, while growth in these sectors tends to favor high earners. This rise in inequality is also often also attributed to the ascendence of 'neoliberal' economic and political ideas which prioritized free markets and the privatization of government-owned businesses. Russia: the explosion of inequality after the fall of communismAmong the largest European economies, the Russian Federation stands out as the country which experienced the sharpest increase in inequality, as a small number of 'oligarchs' took control of the major industries after the collapse of the Soviet Union and the end of communist rule in 1991. The top one percent in Russia increased their share of national income five-fold over the 20 years from 1987 to 2007, when inequality in the country reached its peak as the oligarchs took home over a quarter of the country's income. Turkey: falling share of national income taken by top earners****** has bucked the trend of the rising income share for the richest over this period, as its extremely concentrated income distribution has in fact become somewhat more equitable. The highest earners in Turkey saw their share of national income drop from almost ** percent in the early *****, to a low of ** percent in 2007, after which it has stabilized between ** and ** percent. Western Europe: gradually rising share of national income for the richThe five western European democracies, Germany, France, Italy, Spain, and the United Kingdom, have all seen increases in their top earners' shares of national income over this period. The United Kingdom, Italy, and Germany have in particular seen their shares increase sharply, while Spain and France have experienced a more gradual increase.

Germany DE: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 32.400 % in 2020. This records an increase from the previous number of 31.800 % for 2019. Germany DE: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 30.350 % from Dec 1991 (Median) to 2020, with 30 observations. The data reached an all-time high of 32.400 % in 2020 and a record low of 28.000 % in 1996. Germany DE: 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 Germany – Table DE.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).