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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
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Graph and download economic data for Median Personal Income in the United States (MEPAINUSA646N) from 1974 to 2023 about personal income, personal, median, income, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
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 Amherst, New York, 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 Amherst town median household income. You can refer the same here
Income statistics by economic family type and income source, annual.
Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.
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Graph and download economic data for Real Median Household Income in New York (MEHOINUSNYA672N) from 1984 to 2023 about NY, households, median, income, real, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
U.S. Government Workshttps://www.usa.gov/government-works
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Amherst, New York, 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 Amherst, New York 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 Amherst town 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 Amherst town median household income. You can refer the same here
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 Minnesota, 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 Minnesota median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Additional file 1: Stata do-file to generate WIR and TWIR figures.
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]
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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;
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.
Families of tax filers; Census families by total income, family type and number of children (final T1 Family File; T1FF).
The table only covers individuals who have some liability to Income Tax. The percentile points have been independently calculated on total income before tax and total income after tax.
These statistics are classified as accredited official statistics.
You can find more information about these statistics and collated tables for the latest and previous tax years on the Statistics about personal incomes page.
Supporting documentation on the methodology used to produce these statistics is available in the release for each tax year.
Note: comparisons over time may be affected by changes in methodology. Notably, there was a revision to the grossing factors in the 2018 to 2019 publication, which is discussed in the commentary and supporting documentation for that tax year. Further details, including a summary of significant methodological changes over time, data suitability and coverage, are included in the Background Quality Report.
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/
Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).
The Global Consumption Database (GCD) contains information on consumption patterns at the national level, by urban/rural area, and by income level (4 categories: lowest, low, middle, higher with thresholds based on a global income distribution), for 92 low and middle-income countries, as of 2010. The data were extracted from national household surveys. The consumption is presented by category of products and services of the International Comparison Program (ICP) 2005, which mostly corresponds to COICOP. For three countries, sub-national data are also available (Brazil, India, and South Africa). Data on population estimates are also included.
The data file can be used for the production of the following tables (by urban/rural and income class/consumption segment):
- Sample Size by Country, Area and Consumption Segment (Number of Households)
- Population 2010 by Country, Area and Consumption Segment
- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the National Population
- Population 2010 by Country, Area and Consumption Segment, as a Percentage of the Area Population
- Population 2010 by Country, Age Group, Sex and Consumption Segment
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Sector, Area and Consumption Segment in US$ (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$ (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in Local Currency (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in $PPP (Million)
- Household Consumption 2010 by Country, Product/Service, Area and Consumption Segment in US$ (Million)
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Sector, Area and Consumption Segment in $PPP
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Category of Product/Service, Area and Consumption Segment in $PPP
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in Local Currency
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in US$
- Per Capita Consumption 2010 by Country, Product or Service, Area and Consumption Segment in $PPP
- Consumption Shares 2010 by Country, Sector, Area and Consumption Segment (Percent)
- Consumption Shares 2010 by Country, Category of Products/Services, Area and Consumption Segment (Percent)
- Consumption Shares 2010 by Country, Product/Service, Area and Consumption Segment (Percent)
- Percentage of Households who Reported Having Consumed the Product or Service by Country, Consumption Segment and Area (as of Survey Year)
For all countries, estimates are provided at the national level and at the urban/rural levels. For Brazil, India, and South Africa, data are also provided at the sub-national level (admin 1): - Brazil: ACR, Alagoas, Amapa, Amazonas, Bahia, Ceara, Distrito Federal, Espirito Santo, Goias, Maranhao, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Para, Paraiba, Parana, Pernambuco, Piaji, Rio de Janeiro, Rio Grande do Norte, Rio Grande do Sul, Rondonia, Roraima, Santa Catarina, Sao Paolo, Sergipe, Tocatins - India: Andaman and Nicobar Islands, Andhra Pradesh, Arinachal Pradesh, Assam, Bihar, Chandigarh, Chattisgarh, Dadra and Nagar Haveli, Daman and Diu, Delhi, Goa, Gujarat, Haryana, Himachal Pradesh, Jammu and Kashmir, Jharkhand, Karnataka, Kerala, Lakshadweep, Madya Pradesh, Maharastra, Manipur, Meghalaya, Mizoram, Nagaland, Orissa, Pondicherry, Punjab, Rajasthan, Sikkim, Tamil Nadu, Tripura, Uttar Pradesh, Uttaranchal, West Bengal - South Africa: Eastern Cape, Free State, Gauteng, Kwazulu Natal, Limpopo, Mpulamanga, Northern Cape, North West, Western Cape
Data derived from survey microdata
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