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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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Middle Inlet town median household income. You can refer the same here
The Pew Research Center defines the middle class as households that earn between two-thirds and double the median U.S. household income, which was $65,000 in 2021, according to the U.S. Census Bureau. Using this measure, middle income is made up of households making between $43,350 and $130,000 annually.This map isolates 7 income brackets within the middle class income range, and maps the relative predominance of each income range across the country for census tracts, counties, and states. The brackets defined in the map, drawn from ACS Household Income Distribution data, are as follows:Households whose income in the past 12 months was $125,000 to $149,999Households whose income in the past 12 months was $100,000 to $124,999Households whose income in the past 12 months was $75,000 to $99,999Households whose income in the past 12 months was $60,000 to $74,999Households whose income in the past 12 months was $50,000 to $59,999Households whose income in the past 12 months was $45,000 to $49,999Households whose income in the past 12 months was $40,000 to $44,999Click on each feature reveals more detailed information in the pop-up regarding the current predominant income bracket and compares these figures to historical data. Information included in the pop-up:The total number of homes falling into the predominant Middle Class income bracketThe total number of homes compared to the 2010 - 2014 ACS Household Income Distribution Variables.The percent change in homes within the predominant income bracket between the current ACS, and 2010 - 2014 ACS and whether or not this change is considered statistically significant.This map uses the most current release of data from the American Community Survey (ACS) about household income ranges and cutoffs. Web Map originally owned by Summers Cleary
Income statistics by economic family type and income source, annual.
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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.
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.
Aggregate data [agg]
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United States US: Income Share Held by Highest 20% data was reported at 46.900 % in 2016. This records an increase from the previous number of 46.400 % for 2013. United States US: Income Share Held by Highest 20% data is updated yearly, averaging 46.000 % from Dec 1979 (Median) to 2016, with 11 observations. The data reached an all-time high of 46.900 % in 2016 and a record low of 41.200 % in 1979. United States US: 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 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. 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.
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
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Context
The dataset presents the mean household income for each of the five quintiles in Sands Point, NY, 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 Sands Point median household income. You can refer the same here
U.S. Government Workshttps://www.usa.gov/government-works
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California State Income Limits reflect updated median income and household income levels for acutely low-, extremely low-, very low-, low- and moderate-income households for California’s 58 counties (required by Health and Safety Code Section 50093). These income limits apply to State and local affordable housing programs statutorily linked to HUD income limits and differ from income limits applicable to other specific federal, State, or local programs.
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Graph and download economic data for Median Household Income in California (MEHOINUSCAA646N) from 1984 to 2023 about CA, households, median, income, and USA.
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Context
The dataset presents a breakdown of households across various income brackets in Fresno, CA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Fresno, CA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Fresno households based on income levels.
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 Fresno median household income. You can refer the same here
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/
Tax morals and economic situation of the self-employed middle class. Topics: Attitude to government (scales); evaluation of the tax system and possibilities to reduce taxes illegally; attitude to type and amount of punishment for tax offenders; knowledge about one´s own tax rate and progression with additional income; types of taxes paid; utilization of opportunities to save taxes; perceived unfavorable changes of tax regulations in the last few years; tax accountant costs; profitability of tax accountant costs for the business; assessment of management work to determination company taxes; distribution of authority within the company; legal form of the company; turnover development in the past few years; attitude to an increase in company size; housing of the company in a residential building; judgement on one´s situation regarding provision for old age; obstacles to transfer into retirement; judgement on the extent of leisure time for the self-employed; income from capital assets; party preference. Demography: school education; size of household; religious denomination; age; income; sex Interviewer rating: willingness of respondent to cooperate; interest in topic; number of contact attempts. Steuermoral und wirtschaftliche Situation der Selbständigen des Mittelstandes. Themen: Einstellung zum Staat (Skalometer und Skala); Bewertung des Steuersystems und Möglichkeiten zur illegalen Steuerverkürzung; Einstellung zur Art und Höhe der Strafzumessung für Steuersünder; Kenntnis des eigenen Steuersatzes und der Progression bei zusätzlichen Einkommen; gezahlte Steuerarten; Inanspruchnahme von Möglichkeiten zur Steuerersparnis; empfundene ungünstige Veränderungen der steuerlichen Bestimmungen in den letzten Jahren; Steuerberatungskosten; Rentabilität der Steuerberatungskosten für das Unternehmen; Einschätzung der Verwaltungsarbeit zur Ermittlung der betrieblichen Steuern; Kompetenzverteilung innerhalb des Betriebes; Rechtsform des Betriebes; Umsatzentwicklung in den vergangenen Jahren; Einstellung zu einer Betriebsvergrößerung; Unterbringung des Betriebes im Wohngebäude; Beurteilung der eigenen Altersversorgungssituation; Hinderungsgründe für den Übergang in den Ruhestand; Beurteilung des Umfangs von Freizeit für die Selbständigen; Einkünfte aus Kapitalvermögen; Parteipräferenz. Demographie: Schulbildung; Haushaltsgröße; Konfession; Alter; Einkommen; Geschlecht. Interviewerrating: Kooperationsbereitschaft des Befragten; Interesse am Thema; Anzahl der Kontaktversuche.
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Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Jul 2025 about disposable, personal income, personal, income, real, and USA.
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India Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 9.800 % in 2021. This records a decrease from the previous number of 10.000 % for 2020. India Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 6.200 % from Dec 1977 (Median) to 2021, with 14 observations. The data reached an all-time high of 10.300 % in 2019 and a record low of 5.100 % in 2004. India 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 India – Table IN.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).
Extent and difficulties of property accumulation or provision for one´s old age as well as suitability of various savings possibilities for an adequate provision for old age of the self-employed. Topics: General economic situation of the last few years and assessment of the economic development (Katona questions); expected development of monetary value; preferred investment form; image of selected forms of financial investment; property accumulation; detailed information on type and amount of stocks and shares possessed; experience with shares; inclination to speculate; conduct with stock market fluctuations; maintaining a bank account; significance of government measures to support property accumulation with saving with a building and loan association, saving with government premium in addition to interest, insurance saving; possibilities and problems of personal responsibility for or compulsory provision for old age; expenditures for insurance premiums; attitude to compulsory insurance; leisure time and vacation trips; vacation duration and vacation costs; house and land possession and interest in acquiring a house; company size and production branch; party preference. Demography: age (classified); sex; marital status; number of children; religious denomination; school education; occupation; type of company; income; household income; size of household; composition of household; head of household; state; refugee status; possession of durable economic goods; possession of assets. Interviewer rating: social class and willingness of respondent to cooperate; number of contact attempts; length of interview; impression of respondent and residence furnishing. Ausmaß und Schwierigkeiten der Eigentumsbildung bzw. Altersversorgung sowie Eignung der verschiedenen Sparmöglichkeiten für eine ausreichende Altersversicherung der Selbständigen. Themen: Allgemeine wirtschaftliche Situation der letzten Jahre und Einschätzung der wirtschaftlichen Entwicklung (Katona-Fragen); erwartete Entwicklung des Geldwerts; präferierte Anlageform; Image ausgewählter Geldanlageformen; Eigentumsbildung; detaillierte Angaben über Art und Höhe des Wertpapierbesitzes; Erfahrung mit Aktien; Spekulationsneigung; Verhalten bei Börsenkursschwankungen; Kontenhaltung; Bedeutung staatlicher Maßnahmen zur Förderung der Eigentumsbildung beim Bausparen, Prämiensparen Versicherungssparen; Möglichkeiten und Probleme eigenverantwortlicher oder gesetzlicher Altersvorsorge; Ausgaben für Versicherungsbeiträge; Einstellung zur Pflichtversicherung; Freizeit und Urlaubsreisen; Urlaubsdauer und Urlaubskosten; Haus- und Grundbesitz und Interesse am Hauserwerb; Betriebsgröße und Produktionszweig; Parteipräferenz. Demographie: Alter (klassiert); Geschlecht; Familienstand; Kinderzahl; Konfession; Schulbildung; Beruf; Art des Betriebs; Einkommen; Haushaltseinkommen; Haushaltsgröße; Haushaltszusammensetzung; Haushaltungsvorstand; Bundesland; Flüchtlingsstatus; Besitz langlebiger Wirtschaftsgüter; Besitz von Vermögen. Interviewerrating: Schichtzugehörigkeit und Kooperationsbereitschaft des Befragten; Anzahl der Kontaktversuche; Interviewdauer; Eindruck vom Befragten und der Wohnungseinrichtung; Ortsgröße.
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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;
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Vietnam VN: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data was reported at 35.344 % in 2016. This records a decrease from the previous number of 38.222 % for 2015. Vietnam VN: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data is updated yearly, averaging 14.210 % from Dec 1960 (Median) to 2016, with 40 observations. The data reached an all-time high of 41.390 % in 2014 and a record low of 0.364 % in 1985. Vietnam VN: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: East Asia & Pacific data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Imports. Merchandise imports from low- and middle-income economies in East Asia and Pacific are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the East Asia and Pacific 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;
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Context
The dataset illustrates the median household income in Fontana, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.
Key observations:
From 2010 to 2023, the median household income for Fontana increased by $9,322 (10.49%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.
Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 8 years and declined for 5 years.
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 2022-inflation-adjusted dollars.
Years for which data is available:
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 Fontana median household income. You can refer the same here
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Disposable Personal Income in India increased to 296383300 INR Million in 2023 from 273364818.90 INR Million in 2022. This dataset provides - India Total Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Middle Inlet town median household income. You can refer the same here