Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2024 about CA, households, median, income, and USA.
Facebook
TwitterIn 2024, the median household income in the United States was 83,730 U.S. dollars. This reflected an increase from the previous year. Household income The median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varied from state to state. In 2024, Massachusetts recorded the highest median household income in the country, at 113,900 U.S. dollars. On the other hand, Mississippi, recorded the lowest, at 55,980 U.S. dollars.Household income is also used to determine the poverty rate in the United States. In 2024, 10.6 percent of the U.S. population was living below the national poverty line. This was the lowest level since 2019. Similarly, the child poverty rate, which represents people under the age of 18 living in poverty, reached a three-decade low of 14.3 percent of the children. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.52 in 2024. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality, while a score of one indicates complete inequality.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Bond County: 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 Bond County median household income by age. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Fairfield County: 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 Fairfield County median household income by age. You can refer the same here
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Real Median Household Income in New York (MEHOINUSNYA672N) from 1984 to 2024 about NY, households, median, income, real, and USA.
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Real Median Personal Income in the United States (MEPAINUSA672N) from 1974 to 2024 about personal income, personal, median, income, real, and USA.
Facebook
TwitterVITAL SIGNS INDICATOR
Income (EC4)
FULL MEASURE NAME
Household income by place of residence
LAST UPDATED
January 2023
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 - https://nhgis.org
Count 4Pb (1970)
Form STF3 (1980-1990)
Form SF3a (2000)
U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B19001 (2005-2021; household income by place of residence)
Form B19013 (2005-2021; median household income by place of residence)
Form B08521 (2005-2021; median worker earnings by place of employment)
Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
Income derived from the decennial Census data reflects the income earned in the prior calendar year, whereas income derived from the American Community Survey (ACS) data reflects the prior 12 month period; note that this inconsistency has a minor effect on historical comparisons (see Income and Earnings Data section of the ACS General Handbook - https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020_ch09.pdf). ACS 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.
Quintile income for 1970-2000 is imputed from decennial Census data using methodology from the California Department of Finance. Bay Area income is the population weighted average of county-level income.
Income has been inflated using the Consumer Price Index (CPI) for 2021 specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data uses national CPI for 1970. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Fulton County: 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) 2017-2021 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 Fulton County median household income by age. You can refer the same here
Facebook
TwitterIncome of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Crestwood: 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 Crestwood median household income by age. You can refer the same here
Facebook
TwitterVITAL SIGNS INDICATOR
Income (EC4)
FULL MEASURE NAME
Household income by place of residence
LAST UPDATED
January 2023
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 - https://nhgis.org
Count 4Pb (1970)
Form STF3 (1980-1990)
Form SF3a (2000)
U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B19001 (2005-2021; household income by place of residence)
Form B19013 (2005-2021; median household income by place of residence)
Form B08521 (2005-2021; median worker earnings by place of employment)
Bureau of Labor Statistics: Consumer Price Index - https://www.bls.gov/data/
1970-2021
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
Income derived from the decennial Census data reflects the income earned in the prior calendar year, whereas income derived from the American Community Survey (ACS) data reflects the prior 12 month period; note that this inconsistency has a minor effect on historical comparisons (see Income and Earnings Data section of the ACS General Handbook - https://www.census.gov/content/dam/Census/library/publications/2020/acs/acs_general_handbook_2020_ch09.pdf). ACS 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.
Quintile income for 1970-2000 is imputed from decennial Census data using methodology from the California Department of Finance. Bay Area income is the population weighted average of county-level income.
Income has been inflated using the Consumer Price Index (CPI) for 2021 specific to each metro area; however, some metro areas lack metro-specific CPI data back to 1970 and therefore adjusted data uses national CPI for 1970. Note that current MSA boundaries were used for historical comparison by identifying counties included in today’s metro areas.
Facebook
TwitterVITAL SIGNS INDICATOR Income (EC5)
FULL MEASURE NAME Worker income by workplace (earnings)
LAST UPDATED October 2016
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 B08521 (2006-2015; place of employment) http://api.census.gov
Bureau of Labor Statistics: Consumer Price Index All Urban Consumers Data Table (1970-2015; specific to each metro area) http://data.bls.gov
CONTACT INFORMATION vitalsigns.info@mtc.ca.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.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Madagascar MG: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 14.400 % in 2012. This records an increase from the previous number of 12.800 % for 2010. Madagascar MG: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 14.850 % from Dec 1980 (Median) to 2012, with 8 observations. The data reached an all-time high of 19.100 % in 1980 and a record low of 10.900 % in 2005. Madagascar MG: Proportion of People Living Below 50 Percent Of Median Income: % data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Madagascar – Table MG.World Bank.WDI: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Barbour County: 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) 2017-2021 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 Barbour County median household income by age. You can refer the same here
Facebook
TwitterVITAL SIGNS INDICATOR Displacement Risk (EQ3)
FULL MEASURE NAME Share of lower-income households living in tracts at risk of displacement
LAST UPDATED December 2018
DESCRIPTION Displacement risk refers to the share of lower-income households living in neighborhoods that have been losing lower-income residents over time, thus earning the designation “at risk”. While “at risk” households may not necessarily be displaced in the short-term or long-term, neighborhoods identified as being “at risk” signify pressure as reflected by the decline in lower-income households (who are presumed to relocate to other more affordable communities). The dataset includes metropolitan area, regional, county and census tract tables.
DATA SOURCE U.S. Census Bureau: Decennial Census 1980-1990 Form STF3 https://nhgis.org
U.S. Census Bureau: Decennial Census 2000 Form SF3a https://nhgis.org
U.S. Census Bureau: Decennial Census 1980-2010 Longitudinal Tract Database http://www.s4.brown.edu/us2010/index.htm
U.S. Census Bureau: American Community Survey 2010-2015 Form S1901 5-year rolling average http://factfinder2.census.gov
U.S. Census Bureau: American Community Survey 2010-2017 Form B19013 5-year rolling average http://factfinder2.census.gov
CONTACT INFORMATION vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator) Aligning with the approach used for Plan Bay Area 2040, displacement risk is calculated by comparing the analysis year with the most recent year prior to identify census tracts that are losing lower-income households. Historical data is pulled from U.S. Census datasets and aligned with today’s census tract boundaries using crosswalk tables provided by LTDB. Tract data, as well as regional income data, are calculated using 5-year rolling averages for consistency – given that tract data is only available on a 5-year basis. Using household tables by income level, the number of households in each tract falling below the median are summed, which involves summing all brackets below the regional median and then summing a fractional share of the bracket that includes the regional median (assuming a simple linear distribution within that bracket).
Once all tracts in a given county or metro area are synced to today’s boundaries, the analysis identifies census tracts of greater than 500 lower-income people (in the prior year) to filter out low-population areas. For those tracts, any net loss between the prior year and the analysis year results in that tract being flagged as being at risk of displacement, and all lower-income households in that tract are flagged. To calculate the share of households at risk, the number of lower-income households living in flagged tracts are summed and divided by the total number of lower-income households living in the larger geography (county or metro). Minor deviations on a year-to-year basis should be taken in context, given that data on the tract level often fluctuates and has a significant margin of error; changes on the county and regional level are more appropriate to consider on an annual basis instead.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Australia Standardised Price-Income Ratio: sa data was reported at 149.268 Ratio in Dec 2024. This records a decrease from the previous number of 152.371 Ratio for Sep 2024. Australia Standardised Price-Income Ratio: sa data is updated quarterly, averaging 82.643 Ratio from Mar 1970 (Median) to Dec 2024, with 220 observations. The data reached an all-time high of 153.422 Ratio in Jun 2024 and a record low of 62.554 Ratio in Sep 1983. Australia Standardised Price-Income Ratio: sa data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Australia – Table AU.OECD.AHPI: House Price Index: Seasonally Adjusted: OECD Member: Quarterly. Nominal house prices divided by nominal disposable income per head. Net household disposable income is used. The population data come from the OECD national accounts database. The long-term average is calculated over the whole period available when the indicator begins after 1980 or after 1980 if the indicator is longer. This value is used as a reference value. The ratio is calculated by dividing the indicator source on this long-term average, and indexed to a reference value equal to 100.
Facebook
TwitterThe median annual earnings for full-time employees in the United Kingdom was just over 39,000 British pounds in 2025, compared with 37,400 pounds in the previous year. At the start of the provided time period, in 1999, the average full-time salary in the UK was 17,800 pounds per year, with median earnings exceeding 20,000 pounds per year in 2002, and 30,000 by 2019. Wages continue to grow faster than inflation in 2025 Between November 2021 and July 2023 inflation was higher than wage growth in the UK, with wages still outpacing inflation as of March 2025. At the peak of the recent wave of high inflation in October 2022, the CPI inflation rate reached a 41-year-high of 11.1 percent, wages were growing much slower at 6.1 percent. Since that peak, inflation remained persistently high for several months, only dropping below double figures in April 2023, when inflation was 8.7 percent, down from 10.1 percent in the previous month. For 2023 as a whole, the average annual rate of inflation was 7.3 percent but fell to 2.5 percent in 2024, but is forecast to increase to 3.2 percent in 2025. Highest and lowest-paid occupations As of 2023, the highest-paid occupation in the UK was that of Chief Executives and Senior Officials, who had an average weekly pay of approximately, 1,576 pounds. By contrast, the lowest-paid occupation that year was that of retail cashiers, and check-out operators, who earned approximately 383 pounds a week. For industry sectors as a whole, people who worked full-time in the electricity, gas, steam and air conditioning supply sector had the highest average earnings, at 955 pounds a week, compared with 505 pounds a week in the accommodation and food services sector, the lowest average earnings in 2023.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Braselton: 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 Braselton median household income by age. You can refer the same here
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Time series data for the statistic Gini_Index and country Spain. Indicator Definition: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.The statistic "Gini Index" stands at 33.40 percent as of 12/31/2023, the lowest value since 12/31/2006. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -0.2 percentage points compared to the value the year prior.The 1 year change in percentage points is -0.2.The 3 year change in percentage points is -1.50.The 5 year change in percentage points is -1.30.The 10 year change in percentage points is -2.80.The Serie's long term average value is 34.56 percent. It's latest available value, on 12/31/2023, is 1.16 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2003, to it's latest available value, on 12/31/2023, is +1.60.The Serie's change in percentage points from it's maximum value, on 12/31/1996, to it's latest available value, on 12/31/2023, is -3.10.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Colombia Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 29.300 % in 2022. This records a decrease from the previous number of 30.500 % for 2021. Colombia Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 31.800 % from Dec 1980 (Median) to 2022, with 28 observations. The data reached an all-time high of 37.900 % in 1980 and a record low of 28.200 % in 2017. Colombia Poverty Headcount Ratio at Societal Poverty Lines: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Colombia – Table CO.World Bank.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).
Facebook
Twitterhttps://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2024 about CA, households, median, income, and USA.