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Graph and download economic data for Real Disposable Personal Income: Per Capita (A229RX0) from Jan 1959 to Jun 2025 about disposable, personal income, per capita, personal, income, real, and USA.
In October 2024, real hourly earnings of all employees in the United States increased 0.1 percent in comparison to the previous month. The data have been seasonally adjusted. The deflators used for constant-dollar earnings shown here come from the Consumer Price Indexes Programs. The Consumer Price Index for All Urban Employees (CPI-U) is used to deflate the data for all employees.
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Graph and download economic data for Average Weekly Earnings of All Employees, Total Private (CES0500000011) from Mar 2006 to Jul 2025 about earnings, establishment survey, private, employment, and USA.
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Median Household Income in Oklahoma was 67330.00000 Current $ in January of 2023, according to the United States Federal Reserve. Historically, Median Household Income in Oklahoma reached a record high of 67330.00000 in January of 2023 and a record low of 20950.00000 in January of 1986. Trading Economics provides the current actual value, an historical data chart and related indicators for Median Household Income in Oklahoma - last updated from the United States Federal Reserve on August of 2025.
Costa Rica is the country with the highest minimum monthly wage in Latin America. According to the minimum salary established by law as of January 2025, workers in the Central American country enjoy a basic monthly wage of over 726 U.S. dollars, an increase of 2.37 percent compared to the previous year. They also earn over 200 U.S. dollars more than the second place, Uruguay. On the other side of the spectrum is Venezuela, where employees are only guaranteed by law a minimum salary of 130 bolívares or little more than 2.50 dollars per month. Can Latin Americans survive on a minimum wage? Even if most countries in Latin America have instated laws to guarantee citizens a basic income, these minimum standards are often not enough to meet household needs. For instance, it was estimated that almost 25 million people in Mexico lacked basic housing services. Salary levels also vary greatly among Latin American economies. In 2020, the average net monthly salary in Mexico was barely higher than Chile's minimum wage in 2021. What can a minimum wage afford in Latin America? Latin American real wages have generally risen in the past decade. However, consumers in this region still struggle to afford non-basic goods, such as tech products. Recent estimates reveal that, in order to buy an iPhone, Brazilian residents would have to work at least two months to be able to pay for it. A gaming console, on the other hand, could easily cost a Latin American worker several minimum wages.
In 2023, the median household income in Minnesota amounted to 90,340 U.S. dollars. This is a decrease from the previous year, when the median household income in the state was 90,390 U.S. dollars. Median household income for the United States as a whole can be found here.
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Graph and download economic data for Household Debt Service Payments as a Percent of Disposable Personal Income (TDSP) from Q1 1980 to Q1 2025 about disposable, payments, debt, personal income, percent, personal, households, services, income, and USA.
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Graph and download economic data for Average Hourly Earnings of All Employees, Manufacturing (CES3000000003) from Mar 2006 to Jul 2025 about earnings, establishment survey, hours, wages, manufacturing, employment, and USA.
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The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]
How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.
The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.
Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.
Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.
As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.
Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.
For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.
[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.
[2] Ibid.
Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).
As of the first half of 2023, Australia had the highest net salaries in the Asia-Pacific region at an average ***** U.S. dollars per month. In contrast, the average monthly net salary in Pakistan amounted to *** U.S. dollars per month in the same period.
VITAL SIGNS INDICATOR Income (EC4)
FULL MEASURE NAME Household income by place of residence
LAST UPDATED May 2019
DESCRIPTION Income reflects the median earnings of individuals and households from employment, as well as the income distribution by quintile. Income data highlight how employees are being compensated for their work on an inflation-adjusted basis.
DATA SOURCE U.S. Census Bureau: Decennial Census Count 4Pb (1970) Form STF3 (1980-1990) Form SF3a (2000) https://nhgis.org
U.S. Census Bureau: American Community Survey Form B19013 (2006-2017; place of residence) http://api.census.gov
Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2017; specific to each metro area) http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Income data reported in a given year reflects the income earned in the prior year (decennial Census) or in the prior 12 months (American Community Survey); note that this inconsistency has a minor effect on historical comparisons (for more information, go to: http://www.census.gov/acs/www/Downloads/methodology/ASA_nelson.pdf). American Community Survey 1-year data is used for larger geographies – metropolitan areas and counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Quintile income for 1970-2000 is imputed from Decennial Census data using methodology from the California Department of Finance (for more information, go to: http://www.dof.ca.gov/Forecasting/Demographics/Census_Data_Center_Network/documents/How_to_Recalculate_a_Median.pdf). Bay Area income is the population weighted average of county-level income.
Income has been inflated using the Consumer Price Index specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data is unavailable for some historical data points. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.
In 2024, Meta Platforms generated a revenue of over 164 billion U.S. dollars, up from 134 billion USD in 2023. The majority of Meta’s profits come from its advertising revenue.Meta’s total Family of Apps revenue for 2022 amounted to 114 billion U.S. dollars. Additionally, Meta’s Reality Labs, the company’s VR division, generated around 2.1 billion dollars. Meta’s marketing expenditure for 2022 amounted to just over 15 billion U.S. dollars, up from 14 billion U.S. dollars in the previous year. Increasing audience base despite privacy misgivings Meta’s user numbers have continued to grow steadily throughout past years. In the fourth quarter of 2022, there was a total of 3.74 billion worldwide users across all of Meta’s platforms. For this same time frame, the company recorded 407 million monthly active users across Europe. Downloads of Meta’s app Oculus, for which virtual reality headsets are required, increased greatly from 2020 to 2021, reaching a total of 10.62 million downloads by the end of last year. Up until 2021, downloads had grown in a steady manner but from 2020 to 2021, they more than doubled.User numbers have increased despite data security issues and past controversy such as the Cambridge Analytica scandal in 2018. There remains skepticism surrounding the idea of the metaverse in which Meta aims to immerse itself. Of surveyed adults in the United States, the majority said that they were concerned about their privacy if Meta were to succeed in creating the metaverse.
Table from the American Community Survey (ACS) B24021 occupation by median earnings. These are multiple, nonoverlapping vintages of the 5-year ACS estimates of population and housing attributes starting in 2010 shown by the corresponding census tract vintage. Also includes the most recent release annually.King County, Washington census tracts with nonoverlapping vintages of the 5-year American Community Survey (ACS) estimates starting in 2010. Vintage identified in the "ACS Vintage" field.The census tract boundaries match the vintage of the ACS data (currently 2010 and 2020) so please note the geographic changes between the decades. Tracts have been coded as being within the City of Seattle as well as assigned to neighborhood groups called "Community Reporting Areas". These areas were created after the 2000 census to provide geographically consistent neighborhoods through time for reporting U.S. Census Bureau data. This is not an attempt to identify neighborhood boundaries as defined by neighborhoods themselves.Vintages: 2010, 2015, 2020, 2021, 2022, 2023ACS Table(s): B24021<div style=
Out of the five studied countries in Latin America, Brazilians devoted the largest share of their monthly income to entertainment in early 2024 – ** percent. In Mexico, consumers spent ** percent of their monthly income on entertainment at that time.
In 2023, the median household income in Michigan amounted to 76,960 U.S. dollars. This is a slight increase from the previous year, when the median household income amounted to 68,990 U.S. dollars. The household median income of the United States can be accessed here.
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Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Monee: 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income brackets:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Monee median household income by age. You can refer the same here
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License information was derived automatically
Context
The dataset presents the distribution of median household income among distinct age brackets of householders in Gray town. 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 Gray town. 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 Gray town, the median household income stands at $127,388 for householders within the 25 to 44 years age group, followed by $92,009 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 $79,833.
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:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Gray town median household income by age. You can refer the same here
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License information was derived automatically
United States Household Income: Wisconsin data was reported at 63,451.000 USD in 2017. This records an increase from the previous number of 59,817.000 USD for 2016. United States Household Income: Wisconsin data is updated yearly, averaging 45,217.000 USD from Mar 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 63,451.000 USD in 2017 and a record low of 20,743.000 USD in 1984. United States Household Income: Wisconsin data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s United States – Table US.H048: Household Income: by State.
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License information was derived automatically
Context
The dataset presents the mean household income for each of the five quintiles in Sunfish Lake, 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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Sunfish Lake median household income. You can refer the same here
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License information was derived automatically
United States Personal Income (PI) data was reported at 9,312.608 USD bn in Oct 2003. This records an increase from the previous number of 9,277.510 USD bn for Sep 2003. United States Personal Income (PI) data is updated monthly, averaging 2,559.232 USD bn from Jan 1959 (Median) to Oct 2003, with 538 observations. The data reached an all-time high of 9,312.608 USD bn in Oct 2003 and a record low of 382.124 USD bn in Jan 1959. United States Personal Income (PI) data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A201: NIPA 1999: Personal Income and Disposition.
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Graph and download economic data for Real Disposable Personal Income: Per Capita (A229RX0) from Jan 1959 to Jun 2025 about disposable, personal income, per capita, personal, income, real, and USA.