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
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.
In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between 125,000 and 500,000 Indian rupees a year. On the other hand, about three percent of households that same year, accounted for the rich, earning over 3 million rupees annually. The middle class more than doubled that year compared to 14 percent in financial year 2005.
Middle-class income group and the COVID-19 pandemic
During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant.
Economic inequality
While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last three decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.
Income statistics by economic family type and income source, annual.
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
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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.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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This folder contains files to help you replicate the analyses from the study "The Myth of the Middle Class Squeeze: Employment and Income by Class in Six Western Countries, 1980-2020". The study uses data from the Luxembourg Income Study (LIS, 2024). To access this data, you must request access to the LIS data by visiting this website: https://www.lisdatacenter.org/data-access/lissy/eligibility/. Once you have access, you can use the codes in this folder to analyze the data. The analysis was conducted in R, and all the packages used are included in the R scripts. Note: The LIS data are not directly accessible. Instead, researchers can access an online platform to submit their analysis codes. The platform then returns the results. You can't download or physically access the data, but you can still use the codes provided here to get the same results as the original study. The LIS regularly updates new modules and revises old ones. This project started in 2022 and, therefore, uses the selection of countries released in LIS in that year. The final execution of this set of modules was done in 2024. To ensure you get the same results, please select the modules in the code and run them on the 2024 release.
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.
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).
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/
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 Greenville, NC, 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 Greenville 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 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
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/
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Context
The dataset illustrates the median household income in Greenville, 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 Greenville increased by $3,463 (7.35%), 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 7 years and declined for 6 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 Greenville median household income. You can refer the same here
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Hermes web scraped data
About the website
The luxury retail industry in the Asia Pacific region, particularly in South Korea, has been witnessing significant growth in the recent years. Undeniably fuelled by a rising middle-class population, increasing disposable income, and rapid urbanization, luxury goods demand is booming. French high-fashion label, Hermes, is one of the giants operating in this market. The brand has established a remarkable presence in South… See the full description on the dataset page: https://huggingface.co/datasets/DBQ/Hermes.Product.prices.South.Korea.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comparison of footprint pattern classes and MODUM clusters for output areas in England Wales.
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 Bartlett, IL, 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 Bartlett 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 the household distribution across 16 income brackets among four distinct age groups in Port St. Lucie: 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 Port St. Lucie median household income by age. 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 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