In 2024, the average annual net income per capita for individuals aged 30-44 amounted to approximately ****** euros. The 65 and over age group has the highest average annual net income at ****** euros, which was five thousand euros higher than the ** to ** age group at ****** euros.

Americans start managing their retirement finances early in life, also thanks to many financial instruments and products for those who want save money for their late years. This is true also for the wealthiest one percent of the population. Among top one percent individuals, those between 65 and 69 years saved on average nearly *** million U.S. dollars for retirement.

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Colorado. Based on the latest 2022 1-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Colorado. 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 2022

In terms of income distribution across age cohorts, in Colorado, householders within the 45 to 64 years age group have the highest median household income at $106,655, followed by those in the 25 to 44 years age group with an income of $99,253. Meanwhile householders within the 65 years and over age group report the second lowest median household income of $63,445. Notably, householders within the under 25 years age group, had the lowest median household income at $48,585.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2022 1-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-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 2022 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 Colorado median household income by age. You can refer the same here

Graph and download economic data for Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1246) from Q3 1989 to Q1 2025 about net worth, wealth, percentile, Net, and USA.

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

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are geography-specific; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% income threshold of Nova Scotian tax filers. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Swanton: 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 9(1%) households where the householder is under 25 years old, 243(27.03%) households with a householder aged between 25 and 44 years, 374(41.60%) households with a householder aged between 45 and 64 years, and 273(30.37%) 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 Swanton, 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 Swanton median household income by age. You can refer the same here

Ice core records demonstrate a glacial-interglacial atmospheric CO2 increase by ~100 ppm, while 14C calibration efforts document a strong decrease in atmospheric 14C concentration during this period. A calculated transfer of ~530 Gt of 14C depleted carbon is required to produce the deglacial coeval rise of carbon in the atmosphere and terrestrial biosphere. This amount is usually ascribed to oceanic carbon release, although the actual mechanisms remained elusive, since an adequately old and carbon-enriched deep-ocean reservoir seemed unlikely. Here we present a new, though still fragmentary, ocean-wide d14C dataset showing that during the Last Glacial Maximum (LGM) and Heinrich Stadial 1 (HS-1) the maximum 14C age difference between ocean deep waters and the atmosphere exceeded the modern values by up to 1500 14C yr, in the extreme reaching 5100 14C yr. Below 2000 m depth the 14C ventilation age of modern ocean waters is directly linked to the concentration of dissolved inorganic carbon (DIC). We propose as working hypothesis that the modern regression of DIC vs d14C also applies for LGM times, which implies that a mean LGM aging by ~600 14C yr corresponded to a global rise of ~85-115 µmol DIC/kg in the deep ocean. Thus, the prolonged residence time of ocean deep waters may indeed have made it possible to absorb an additional ~730-980 Gt DIC, one third of which possibly originated from intermediate waters. We also infer that LGM deep-water O2 dropped to suboxic values of <10µmol/kg in the Atlantic sector of the Southern Ocean, possibly also in the subpolar North Pacific. The outlined deglacial transfer of the extra aged, deep-ocean carbon to the atmosphere via the dynamic ocean-atmosphere carbon exchange would be sufficient to account for two trends observed, (1) for the increase in atmospheric CO2 and (2) for the 190-permil drop in atmospheric d14C during the so-called HS-1 'Mystery Interval', when atmospheric 14C production rates were largely constant.

Australia Average Number of Persons in Household: One Family: Other: Age: 65 Years And Over data was reported at 0.400 Person in 2020. This records a decrease from the previous number of 0.500 Person for 2018. Australia Average Number of Persons in Household: One Family: Other: Age: 65 Years And Over data is updated yearly, averaging 0.400 Person from Jun 2001 (Median) to 2020, with 11 observations. The data reached an all-time high of 0.500 Person in 2018 and a record low of 0.300 Person in 2003. Australia Average Number of Persons in Household: One Family: Other: Age: 65 Years And Over data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H037: Survey of Income and Housing: Average Number of Persons in Household: by Age.

Graph and download economic data for Minimum Wealth Cutoff for the Top 0.1% (99.9th to 100th Wealth Percentiles) (WFRBLTP1311) from Q3 1989 to Q3 2022 about wealth, percentile, and USA.

Australia Average Number of Persons in Household: One Family: Other data was reported at 3.000 Person in 2020. This stayed constant from the previous number of 3.000 Person for 2018. Australia Average Number of Persons in Household: One Family: Other data is updated yearly, averaging 3.000 Person from Jun 2001 (Median) to 2020, with 11 observations. The data reached an all-time high of 4.000 Person in 2001 and a record low of 2.900 Person in 2010. Australia Average Number of Persons in Household: One Family: Other data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H037: Survey of Income and Housing: Average Number of Persons in Household: by Age.

Estimated number of persons on July 1, by 5-year age groups and gender, and median age, for Canada, provinces and territories.

In 2022, the state with the highest median age of its population was Maine at 45.1 years. Utah had the lowest median age at 32.1 years. View the distribution of the U.S. population by ethnicity here.

Additional information on the aging population in the United States

High birth rates during the so-called baby boom years that followed World War II followed by lower fertility and morality rates have left the United States with a serious challenge in the 21st Century. However, the issue of an aging population is certainly not an issue unique to the United States. The age distribution of the global population shows that other parts of the world face a similar issue.

Within the United States, the uneven distribution of populations aged 65 years and over among states offers both major challenges and potential solutions. On the one hand, federal action over the issue may be contentious as other states are set to harbor the costs of elderly care in states such as California and Florida. That said, domestic migration from comparably younger states may help to fill gaps in the workforce left by retirees in others.

Nonetheless, aging population issues are set to gain further prominence in the political and economic decisions made by policymakers regardless of the eventual distribution of America’s elderly. Analysis of the financial concerns of Americans by age shows many young people still decades from retirement hold strong concern over their eventual financial position.

Distribution of total income in constant 2020 dollars by age and gender.

Australia Average Number of Persons in Household: One Family: Couple with Dependent Children: Age: Under 18 Years data was reported at 1.700 Person in 2020. This stayed constant from the previous number of 1.700 Person for 2018. Australia Average Number of Persons in Household: One Family: Couple with Dependent Children: Age: Under 18 Years data is updated yearly, averaging 1.800 Person from Jun 2001 (Median) to 2020, with 11 observations. The data reached an all-time high of 1.900 Person in 2003 and a record low of 1.700 Person in 2020. Australia Average Number of Persons in Household: One Family: Couple with Dependent Children: Age: Under 18 Years data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.H037: Survey of Income and Housing: Average Number of Persons in Household: by Age.

Teenagers make up the largest group of active users on TikTok.

Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2024 about personal income, personal, median, income, and USA.

Women and Men in Spain: Average annual net income by household by age of the reference person and period. Annual. National.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Respondents could report more than one major for their bachelor's degree. This table only counts the first major that was reported and does not necessarily reflect the first degree earned..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.