This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. The purpose of this dataset is to track the distribution of aggregate city income between the 5 quintile of population segments. The dataset comes from the 2019 U.S. Census Bureau, American Communities Survey (5yr) Table B19082. The row levels contain total percentage of income shares by the middle 3 quintiles (20-80%) of population. This data can be used to provide insights into growth/decline of middle class. Distribution of household income (Note: This indicator can provide insights into growth/decline of middle class) View more details and insights related to this measure on the story page: https://data.austintexas.gov/stories/s/Distribution-of-Household-Income/i3a3-vjnc/

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Middle Point. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Middle Point. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Middle Point, the median household income stands at $64,659 for householders within the 25 to 44 years age group, followed by $54,844 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $45,250.

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.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

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 Middle Point median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Middle Inlet, Wisconsin, 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 20,755, while the mean income for the highest quintile (20% of households with the highest income) is 186,714. This indicates that the top earners earn 9 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 350,363, which is 187.65% higher compared to the highest quintile, and 1688.09% 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 Middle Inlet town median household income. You can refer the same here

United States US: Income Share Held by Highest 10% data was reported at 30.600 % in 2016. This records an increase from the previous number of 30.100 % for 2013. United States US: Income Share Held by Highest 10% data is updated yearly, averaging 30.100 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 30.600 % in 2016 and a record low of 25.300 % in 1979. United States US: 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 United States – Table US.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.

Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2023 about personal income, personal, median, income, real, and USA.

This dataset and map service provides information on the U.S. Housing and Urban Development's (HUD) low to moderate income areas. The term Low to Moderate Income, often referred to as low-mod, has a specific programmatic context within the Community Development Block Grant (CDBG) program. Over a 1, 2, or 3-year period, as selected by the grantee, not less than 70 percent of CDBG funds must be used for activities that benefit low- and moderate-income persons. HUD uses special tabulations of Census data to determine areas where at least 51% of households have incomes at or below 80% of the area median income (AMI). This dataset and map service contains the following layer.

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between ******* and ******* Indian rupees a year. On the other hand, about ***** percent of households that same year, accounted for the rich, earning over * million rupees annually. The middle class more than doubled that year compared to ** percent in financial year 2005. Middle-class income group and the COVID-19 pandemic During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant. Economic inequality While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last ***** decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

Income statistics by economic family type and income source, annual.

Abstract

Dataset used in World Bank Policy Research Working Paper #2876, published in World Bank Economic Review, No. 1, 2005, pp. 21-44.

The effects of globalization on income distribution in rich and poor countries are a matter of controversy. While international trade theory in its most abstract formulation implies that increased trade and foreign investment should make income distribution more equal in poor countries and less equal in rich countries, finding these effects has proved elusive. The author presents another attempt to discern the effects of globalization by using data from household budget surveys and looking at the impact of openness and foreign direct investment on relative income shares of low and high deciles. The author finds some evidence that at very low average income levels, it is the rich who benefit from openness. As income levels rise to those of countries such as Chile, Colombia, or Czech Republic, for example, the situation changes, and it is the relative income of the poor and the middle class that rises compared with the rich. It seems that openness makes income distribution worse before making it better-or differently in that the effect of openness on a country's income distribution depends on the country's initial income level.

Kind of data

Aggregate data [agg]

About this dataset

Context

The dataset tabulates the median household income in Middle township. It can be utilized to understand the trend in median household income and to analyze the income distribution in Middle township by household type, size, and across various income brackets.

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).

• Middle Township, New Jersey Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Middle Township, New Jersey: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Middle Township, New Jersey
• Middle Township, New Jersey households by income brackets: family, non-family, and total, 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 Middle township median household income. You can refer the same here

United States US: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data was reported at 17.755 % in 2016. This records an increase from the previous number of 17.642 % for 2015. United States US: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data is updated yearly, averaging 14.701 % from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 23.170 % in 1960 and a record low of 10.495 % in 1986. United States US: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Imports. Merchandise imports from low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Latin America and the Caribbean region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

Median household income is the middle value of the incomes earned in the prior year by households in an area. Income and earnings are inflation-adjusted for the last year of the 5-year period. The median value is used as opposed to the average so that both extremely high and extremely low prices do not distort the total amount of income earned by households in an area. Source: American Community SurveyYears Available: 2006-2010, 2007-2011, 2008-2012, 2009-2013, 2010-2014, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2016-2020, 2017-2021, 2018-2022, 2019-2023Please note: We do not recommend comparing overlapping years of data due to the nature of this dataset. For more information, please visit: https://www.census.gov/programs-surveys/acs/guidance/comparing-acs-data.html

Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data was reported at 2.673 % in 2016. This records an increase from the previous number of 2.543 % for 2015. Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data is updated yearly, averaging 1.896 % from Dec 1961 (Median) to 2016, with 56 observations. The data reached an all-time high of 5.491 % in 1985 and a record low of 0.012 % in 1972. Korea Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Korea – Table KR.World Bank: Imports. Merchandise imports from low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Latin America and the Caribbean region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Additional file 1: Stata do-file to generate WIR and TWIR figures.

Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Middle Taylor Township, Pennsylvania, 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 16,456, while the mean income for the highest quintile (20% of households with the highest income) is 200,443. This indicates that the top earners earn 12 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 301,208, which is 150.27% higher compared to the highest quintile, and 1830.38% 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 Middle Taylor township median household income. You can refer the same here

United Arab Emirates AE: Income Share Held by Highest 20% data was reported at 38.200 % in 2014. United Arab Emirates AE: Income Share Held by Highest 20% data is updated yearly, averaging 38.200 % from Dec 2014 (Median) to 2014, with 1 observations. United Arab Emirates AE: Income Share Held by Highest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Arab Emirates – Table AE.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.

Namibia NA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region data was reported at 69.420 % in 2016. This records a decrease from the previous number of 71.557 % for 2015. Namibia NA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region data is updated yearly, averaging 77.959 % from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 86.783 % in 2004 and a record low of 62.161 % in 2014. Namibia NA: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Within Region data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Namibia – Table NA.World Bank: Imports. Merchandise imports from low- and middle-income economies within region are the sum of merchandise imports by the reporting economy from other low- and middle-income economies in the same World Bank region according to the World Bank classification of economies. Data are as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data. No figures are shown for high-income economies, because they are a separate category in the World Bank classification of economies.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Middle Point: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 4(1.36%) households where the householder is under 25 years old, 91(30.85%) households with a householder aged between 25 and 44 years, 121(41.02%) households with a householder aged between 45 and 64 years, and 79(26.78%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the village of Middle Point, showcasing varying income levels among different age demographics.

Content

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

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

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 Middle Point median household income by age. You can refer the same here