France - Inequality of income distribution was 4.66 in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Inequality of income distribution - last updated from the EUROSTAT on July of 2025. Historically, France - Inequality of income distribution reached a record high of 4.66 in December of 2024 and a record low of 4.23 in December of 2018.

France - Income distribution was 4.66 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.

In 2021, ****percent of French households had a net wealth exceeding 633,200 euros, and ** percent had a net wealth exceeding 394,300 euros. Conversely, ****percent of households (those in the first decile) had a net worth of less than 3,000 euros. In the same year, over a third of French people reported having experienced poverty at least once in their lives.

In 2021, the ten percent of French households with the highest wealth held **** percent of total gross wealth, almost six percentage points more than in 2010. In addition, the richest ** percent of households held more than three quarters of total wealth, and half of the richest households held **** percent of total wealth.

France - Income inequality for older people was 3.65 in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Income inequality for older people - last updated from the EUROSTAT on July of 2025. Historically, France - Income inequality for older people reached a record high of 4.60 in December of 2012 and a record low of 3.40 in December of 2021.

In 2023 in France, the average net monthly full-time equivalent salary was ***** euros. That year, ** percent of the poorest French employees earned less than ***** euros per month. On the other hand, ** percent of the richest French employees received more than ***** euros. The French people who were part of the richest one percent of the working population earned a salary over ***** euros per month.

This statistic shows information on the income distribution in France as of 2012, broken down by quintiles. That year, the income share held by the third ** percent in France was ***** percent. The highest ** percent held over ** percent of all income in France.

Using large samples of estate tax returns, we construct new series on wealth concentration in Paris and France from 1807 to 1994. Inequality increased until 1914 because industrial and financial estates grew dramatically. Then, adverse shocks, rather than a Kuznets-type process, led to a massive decline in inequality. The very high wealth concentration prior to 1914 benefited retired individuals living off capital income (rentiers) rather than entrepreneurs. The very rich were in their seventies and eighties, whereas they had been in their fifties a half century earlier and would be so again after World War II. Our results shed new light on ongoing debates about wealth inequality and growth.

France: Gini income inequality index: The latest value from 2021 is 31.5 index points, an increase from 30.7 index points in 2020. In comparison, the world average is 35.28 index points, based on data from 71 countries. Historically, the average for France from 1970 to 2021 is 32.39 index points. The minimum value, 29.7 index points, was reached in 2006 while the maximum of 37.1 index points was recorded in 1970.

France - Income inequality for older people: Females was 3.58 in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Income inequality for older people: Females - last updated from the EUROSTAT on August of 2025. Historically, France - Income inequality for older people: Females reached a record high of 4.56 in December of 2016 and a record low of 3.34 in December of 2021.

About this dataset

Context

The dataset presents the median household income across different racial categories in French Lick. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of French Lick population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 80.91% of the total residents in French Lick. Notably, the median household income for White households is $49,722. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $124,643. This reveals that, while Whites may be the most numerous in French Lick, Black or African American households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/french-lick-in-median-household-income-by-race.jpeg" alt="French Lick median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in French Lick.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

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 French Lick median household income by race. You can refer the same here

The World Top Incomes Database provides statistical information on the shares of top income groups for 30 countries. The construction of this database was possible thanks to the research of over thirty contributing authors. There has been a marked revival of interest in the study of the distribution of top incomes using tax data. Beginning with the research by Thomas Piketty of the long-run distribution of top incomes in France, a succession of studies has constructed top income share time series over the long-run for more than twenty countries to date. These projects have generated a large volume of data, which are intended as a research resource for further analysis. In using data from income tax records, these studies use similar sources and methods as the pioneering work by Kuznets for the United States.The findings of recent research are of added interest, since the new data provide estimates covering nearly all of the twentieth century -a length of time series unusual in economics. In contrast to existing international databases, generally restricted to the post-1970 or post-1980 period, the top income data cover a much longer period, which is important because structural changes in income and wealth distributions often span several decades. The data series is fairly homogenous across countries, annual, long-run, and broken down by income source for several cases. Users should be aware also about their limitations. Firstly, the series measure only top income shares and hence are silent on how inequality evolves elsewhere in the distribution. Secondly, the series are largely concerned with gross incomes before tax. Thirdly, the definition of income and the unit of observation (the individual vs. the family) vary across countries making comparability of levels across countries more difficult. Even within a country, there are breaks in comparability that arise because of changes in tax legislation affecting the definition of income, although most studies try to correct for such changes to create homogenous series. Finally and perhaps most important, the series might be biased because of tax avoidance and tax evasion. The first theme of the research programme is the assembly and analysis of historical evidence from fiscal records on the long-run development of economic inequality. “Long run” is a relative term, and here it means evidence dating back before the Second World War, and extending where possible back into the nineteenth century. The time span is determined by the sources used, which are based on taxes on incomes, earnings, wealth and estates. Perspective on current concerns is provided by the past, but also by comparison with other countries. The second theme of the research programme is that of cross-country comparisons. The research is not limited to OECD countries and will draw on evidence globally. In order to understand the drivers of inequality, it is necessary to consider the sources of economic advantage. The third theme is the analysis of the sources of income, considering separately the roles of earned incomes and property income, and examining the historical and comparative evolution of earned and property income, and their joint distribution. The fourth theme is the long-run trend in the distribution of wealth and its transmission through inheritance. Here again there are rich fiscal data on the passing of estates at death. The top income share series are constructed, in most of the cases presented in this database, using tax statistics (China is an exception; for the time being the estimates come from households surveys). The use of tax data is often regarded by economists with considerable disbelief. These doubts are well justified for at least two reasons. The first is that tax data are collected as part of an administrative process, which is not tailored to the scientists' needs, so that the definition of income, income unit, etc., are not necessarily those that we would have chosen. This causes particular difficulties for comparisons across countries, but also for time-series analysis where there have been substantial changes in the tax system, such as the moves to and from the joint taxation of couples. Secondly, it is obvious that those paying tax have a financial incentive to present their affairs in a way that reduces tax liabilities. There is tax avoidance and tax evasion. The rich, in particular, have a strong incentive to understate their taxable incomes. Those with wealth take steps to ensure that the return comes in the form of asset appreciation, typically taxed at lower rates or not at all. Those with high salaries seek to ensure that part of their remuneration comes in forms, such as fringe benefits or stock-options which receive favorable tax treatment. Both groups may make use of tax havens that allow income to be moved beyond the reach of the national tax net. These shortcomings limit what can be said from tax data, but this does not mean that the data are worthless. Like all economic data, they measure with error the 'true' variable in which we are interested. References Atkinson, Anthony B. and Thomas Piketty (2007). Top Incomes over the Twentieth Century: A Contrast between Continental European and English-Speaking Countries (Volume 1). Oxford: Oxford University Press, 585 pp. Atkinson, Anthony B. and Thomas Piketty (2010). Top Incomes over the Twentieth Century: A Global Perspective (Volume 2). Oxford: Oxford University Press, 776 pp. Atkinson, Anthony B., Thomas Piketty and Emmanuel Saez (2011). Top Incomes in the Long Run of History, Journal of Economic Literature, 49(1), pp. 3-71. Kuznets, Simon (1953). Shares of Upper Income Groups in Income and Savings. New York: National Bureau of Economic Research, 707 pp. Piketty, Thomas (2001). Les Hauts Revenus en France au 20ème siècle. Paris: Grasset, 807 pp. Piketty, Thomas (2003). Income Inequality in France, 1901-1998, Journal of Political Economy, 111(5), pp. 1004-42.

France FR: Gini Coefficient (GINI Index): World Bank Estimate data was reported at 32.700 % in 2015. This records an increase from the previous number of 32.300 % for 2014. France FR: Gini Coefficient (GINI Index): World Bank Estimate data is updated yearly, averaging 32.500 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 33.700 % in 2010 and a record low of 29.700 % in 2006. France FR: 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 France – Table FR.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.

France FR: Income Share Held by Highest 10% data was reported at 26.600 % in 2015. This records an increase from the previous number of 26.100 % for 2014. France FR: Income Share Held by Highest 10% data is updated yearly, averaging 26.200 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 27.100 % in 2010 and a record low of 23.500 % in 2006. France FR: Income Share Held by Highest 10% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. 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.

About this dataset

Context

The dataset tabulates the French Lick median household income by race. The dataset can be utilized to understand the racial distribution of French Lick income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• French Lick, IN median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in French Lick, IN (2021, in 2022 inflation-adjusted dollars)

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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of French Lick median household income by race. You can refer the same here

In France, in 2022, the minimum standard of living for the richest ten percent of the French population was **** times higher than the maximum standard for the poorest ten percent. In comparison, the ratio was *** in 1970, meaning society was more unequal back then.

Many of Europe's largest economies have seen falling shares of their national wealth taken by the bottom ** percent of the wealth distribution since the 1990s. Italy in particular stands out as a particularly stark case, as the bottom half owned around ** percent of the wealth in the country in 1995, while in 2023 they owned only *** percent. Russia is the other country which has seen a consistent decline in the wealth of its poorest ** percent, with the economic crises of the 1990s causing the poor to rapidly lose their share of wealth, but without any recovery during the years of economic success in the run-up to the 2008 financial crisis. Germany, France, Spain, and the United Kingdom have seen more moderate decreases in the bottom ** percent share, with Spain and the UK in fact showing increases in their shares during the early 2000s, as their respective housing booms inflated the wealth of the poorest, before retracting during the financial crisis and great recession. Turkey stands out as an outlier among the large European economies, as the share taken by its bottom half has more than tripled since the 1990s, now having a higher share than in Russia and Italy. This period in Turkey has been marked by rapid economic growth, modernization, and urbanization, some of which has benefitted the poorest by providing new economic opportunities.

France FR: Income Share Held by Third 20% data was reported at 16.700 % in 2015. This stayed constant from the previous number of 16.700 % for 2014. France FR: Income Share Held by Third 20% data is updated yearly, averaging 16.700 % from Dec 2003 (Median) to 2015, with 13 observations. The data reached an all-time high of 17.300 % in 2006 and a record low of 16.300 % in 2010. France FR: Income Share Held by Third 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Poverty. 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, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. 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.

Demographics data France 2023 at municipality level - 24+ attributes, including total population, population 15+, population 15-64, employment, average income.

France - Distribution of population by tenure status, type of household and income group - EU-SILC survey was 61.20% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Distribution of population by tenure status, type of household and income group - EU-SILC survey - last updated from the EUROSTAT on August of 2025. Historically, France - Distribution of population by tenure status, type of household and income group - EU-SILC survey reached a record high of 65.10% in December of 2018 and a record low of 60.50% in December of 2007.