In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.
This annual study provides selected income and tax items classified by State, ZIP Code, and the size of adjusted gross income. These data include the number of returns, which approximates the number of households; the number of personal exemptions, which approximates the population; adjusted gross income; wages and salaries; dividends before exclusion; and interest received. Data are based who reported on U.S. Individual Income Tax Returns (Forms 1040) filed with the IRS. SOI collects these data as part of its Individual Income Tax Return (Form 1040) Statistics program, Data by Geographic Areas, ZIP Code Data.
https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/
Dataset Card for 100 Richest People In World
Dataset Summary
This dataset contains the list of Top 100 Richest People in the World Column Information:-
Name - Person Name NetWorth - His/Her Networth Age - Person Age Country - The country person belongs to Source - Information Source Industry - Expertise Domain
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Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]… See the full description on the dataset page: https://huggingface.co/datasets/nateraw/100-richest-people-in-world.
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 State Center, IA, 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 State Center 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 State College, PA, 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 State College 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: Account: Income: Richest 60%: % Aged 15+ data was reported at 97.904 % in 2014. This records an increase from the previous number of 92.810 % for 2011. United States US: Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 95.357 % from Dec 2011 (Median) to 2014, with 2 observations. The data reached an all-time high of 97.904 % in 2014 and a record low of 92.810 % in 2011. United States US: Account: Income: Richest 60%: % Aged 15+ 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: Banking Indicators. Denotes the percentage of respondents who report having an account (by themselves or together with someone else). For 2011, this can be an account at a bank or another type of financial institution, and for 2014 this can be a mobile account as well (see year-specific definitions for details) (income, richest 60%, % age 15+). [ts: data are available for multiple waves].; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;
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 United States, 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 United States median household income. You can refer the same here
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
This article investigates the relationship between the increasing concentration of income among the wealthiest households, the increasing geographic concentration of the wealthiest households, and relative changes in state per capita income. An increasing share of the super-rich accounts for much of the difference in income growth between the richest northeastern states and the rest of the country. Several other states with fast-growing income levels, however, experienced more balanced growth.
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in United States Virgin Islands per the most current US Census data, including information on rank and average income.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Why do the rich and poor support different parties in some places? We argue that voting along class lines is more likely to occur where states can tax the income and assets of the wealthy. In low bureaucratic capacity states, the rich are less likely to participate in electoral politics because they have less to fear from redistributive policy. When wealthy citizens abstain from voting, politicians face a more impoverished electorate. Because politicians cannot credibly campaign on anti-tax platforms, they are less likely to emphasize redistribution and partisan preferences are less likely to diverge across income groups. Using cross-national survey data, we show there is more class voting in countries with greater bureaucratic capacity. We also show that class voting and fiscal capacity were correlated in the United States in the mid-1930s when state-level revenue collection and party systems were less dependent on national economic policy.
This map shows the USGS (United States Geologic Survey), NWIS (National Water Inventory System) Hydrologic Data Sites for Rich County, Utah.
The scope and purpose of NWIS is defined on the web site:
The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent dataset, or they can be combined to cover the entire nation. The Area Hydrography Shapefile contains the geometry and attributes of both perennial and intermittent area hydrography features, including ponds, lakes, oceans, swamps (up to the U.S. nautical three-mile limit), glaciers, and the area covered by large rivers, streams, and/or canals that are represented as double-line drainage. Single-line drainage water features can be found in the Linear Hydrography Shapefile (LINEARWATER.shp). Linear water features includes single-line drainage water features and artificial path features, where they exist, that run through double-line drainage features such as rivers, streams, and/or canals, and serve as a linear representation of these features.
While most Americans appear to acknowledge the large gap between the rich and the poor in the U.S., it is not clear if the public is aware of recent changes in income inequality. Even though economic inequality has grown substantially in recent decades, studies have shown that the public's perception of growing income disparities has remained mostly unchanged since the 1980s. This research offers an alternative approach to evaluating how public perceptions of inequality are developed. Centrally, it conceptualizes the public's response to growing economic disparities by applying theories of macro-political behavior and place-based contextual effects to the formation of aggregate perceptions about income inequality. It is argued that most of the public relies on basic information about the economy to form attitudes about inequality and that geographic context---in this case, the American states---plays a role in how views of income disparities are produced. A new measure of state perceptions of growing economic inequality over a 25-year period is used to examine whether the public is responsive to objective changes in economic inequality. Time-series cross-sectional analyses suggest that the public's perceptions of growing inequality are largely influenced by objective state economic indicators and state political ideology. This research has implications for how knowledgeable the public is of disparities between the rich and the poor, whether state context influences attitudes about inequality, and what role the public will have in determining how expanding income differences are addressed through government policy.
This map shows specific water-quality items and hydrologic data site information which come from QWDATA (Water Quality) and GWSI (Ground Water Information System). Both QWDATA and GWSI are subsystems of NWIS (National Water Inventory System)of the USGS (United States Geologic Survey). This map is for Rich County, Utah. The scope and purpose of NWIS is defined on the web site: http://water.usgs.gov/public/pubs/FS/FS-027-98/
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset illustrates the median household income in Rich County, 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 Rich County decreased by $27 (0.04%), 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 6 years and declined for 7 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 Rich County median household income. You can refer the same here
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in New Jersey per the most current US Census data, including information on rank and average income.
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in South Carolina per the most current US Census data, including information on rank and average income.
https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS
A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.
This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The All Roads Shapefile includes all features within the MTDB Super Class "Road/Path Features" distinguished where the MAF/TIGER Feature Classification Code (MTFCC) for the feature in MTDB that begins with "S". This includes all primary, secondary, local neighborhood, and rural roads, city streets, vehicular trails (4wd), ramps, service drives, alleys, parking lot roads, private roads for service vehicles (logging, oil fields, ranches, etc.), bike paths or trails, bridle/horse paths, walkways/pedestrian trails, and stairways.
https://www.georgia-demographics.com/terms_and_conditionshttps://www.georgia-demographics.com/terms_and_conditions
A dataset listing the 20 richest counties in Georgia for 2024, including information on rank, county, population, average income, and median income.
In 2023, the real median household income in the state of Alabama was 60,660 U.S. dollars. The state with the highest median household income was Massachusetts, which was 106,500 U.S. dollars in 2023. The average median household income in the United States was at 80,610 U.S. dollars.