Czech Republic Household Income: by Head Status (HS): per Capita Avg: Net data was reported at 259,850.000 CZK in 2023. This records an increase from the previous number of 241,160.000 CZK for 2022. Czech Republic Household Income: by Head Status (HS): per Capita Avg: Net data is updated yearly, averaging 150,488.000 CZK from Dec 2001 (Median) to 2023, with 23 observations. The data reached an all-time high of 259,850.000 CZK in 2023 and a record low of 90,166.821 CZK in 2001. Czech Republic Household Income: by Head Status (HS): per Capita Avg: Net data remains active status in CEIC and is reported by Czech Statistical Office. The data is categorized under Global Database’s Czech Republic – Table CZ.H015: Household Income and Expenditure: per Capita Average.

United States Household Income: $200,000 & Over data was reported at 7.700 % in 2017. This records an increase from the previous number of 7.200 % for 2016. United States Household Income: $200,000 & Over data is updated yearly, averaging 3.400 % from Mar 1967 (Median) to 2017, with 51 observations. The data reached an all-time high of 7.700 % in 2017 and a record low of 1.000 % in 1968. United States Household Income: $200,000 & Over data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H049: Household Income: by Income Level.

The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple generalized theoretical model for establishing social hierarchy via pair-wise interactions between individuals and investigate its stability. In each interaction or fight, the probability of “winning” depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one high-status individual and all other individuals having status approaching zero. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. As we show, our model allows us to make predictions consistent with animal interaction data and their evolution over a number of years. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a distinct high-status class. Using household income as a proxy for societal status in human societies, we find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status “tail”. We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.

Mortgage Status By Household Income Report based on US Census and American Community Survey Data.

In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

The American Community Survey (ACS) 5 Year 2016-2020 socioeconomic estimate data is a subset of information derived from the following census tables:B08013 - Aggregate Travel Time To Work Of Workers By Sex;B08303 - Travel Time To Work;B17019 - Poverty Status In The Past 12 Months Of Families By Household Type By Tenure;B17021 - Poverty Status Of Individuals In The Past 12 Months By Living Arrangement;B19001 - Household Income In The Past 12 Months;B19013 - Median Household Income In The Past 12 Months;B19025 - Aggregate Household Income In The Past 12 Months;B19113 - Median Family Income In The Past 12 Months;B19202 - Median Non-family Household Income In The Past 12 Months;B23001 - Sex By Age By Employment Status For The Population 16 Years And Over;B25014 - Tenure By Occupants Per Room;B25026 - Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit;B25106 - Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months;C24010 - Sex By Occupation For The Civilian Employed Population 16 Years And Over;B20004 - Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over;B23006 - Educational Attainment by Employment Status for the Population 25 to 64 Years, and;B24021 - Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

To learn more about the American Community Survey (ACS), and associated datasets visit: https://www.census.gov/programs-surveys/acs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_ACS 5-Year Socioeconomic Estimate Data by StateDate of Coverage: 2016-2020

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled by the 2010 US Decennial Census Tracts. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

2016-2020 ACS 5-Year estimates of socioeconomic characteristics compiled at the Place level. These characteristics include Aggregate Travel Time To Work Of Workers By Sex, Travel Time To Work, Poverty Status In The Past 12 Months Of Families By Household Type By Tenure, Poverty Status Of Individuals In The Past 12 Months By Living Arrangement, Household Income In The Past 12 Months, Median Household Income In The Past 12 Months, Aggregate Household Income In The Past 12 Months, Median Family Income In The Past 12 Months, Median Non-family Household Income In The Past 12 Months, Sex By Age By Employment Status For The Population 16 Years And Over, Tenure By Occupants Per Room, Total Population in Occupied Housing Units by Tenure by year Householder Moved into Unit, Tenure By Housing Costs As A Percentage Of Household Income In The Past 12 Months, Sex By Occupation For The Civilian Employed Population 16 Years And Over, Median Earnings In the Past 12 Months (In 2015 Inflation-Adjusted Dollars) by Sex by Educational Attainment for the Population 25 Years and Over, Educational Attainment by Employment Status for the Population 25 to 64 Years, and Occupation By Median Earnings In The Past 12 Months (In 2015 Inflation-Adjusted Dollars) For The Full-Time, Year-Round Civilian Employed Population 16 Years And Over.

A more recent web map on this same topic is available for ArcGIS Online subscribers here.This map shows the socioeconomic status of each census tract. Data come from the US Census Bureau's 2011-2015 American Community Survey. Neighborhood Socioeconomic Status, over and above individual socioeconomic status, is a predictor of many health outcomes. The Neighborhood Socioeconomic Status (NSES) Index is on a scale from 0 to 100 with 50 being the national average around 2010. The Index incorporates the following indicators (fields in this layer's attribute table):Median Household Income (from Table B19013)Percent of individuals with income below the Federal Poverty Line (from Table S1701)The educational attainment of adults (age 25+) (from Table B15003)Unemployment Rate (from Table S2301)Percent of households with children under the age of 18 that are "female-headed" (no male present) (from Table B11005)NSES = log(median household income) + (-1.129 * (log(percent of female-headed households))) + (-1.104 * (log(unemployment rate))) + (-1.974 * (log(percent below poverty))) + .451*((high school grads)+(2*(bachelor's degree holders)))To learn more about how the NSES Index was developed, please explore this journal articleMiles, Jeremy and Weden, Margaret; Lavery, Diana; Escarce, José; Kathleen Cagney; Shih, Regina. 2016. “Constructing a Time-Invariant Measure of the Socio-Economic Status of U.S. Census Tracts.” Journal of Urban Health, vol. 93, issue no.1, pp. 213-232. or this PPT presentation presented at the University of Texas at San Antonio's Applied Demography Conference in 2014.

The purpose of this project was to measure and estimate the distribution of personal income in both rural and urban areas of the People's Republic of China. The principal investigators based their definition of income on cash payments and on a broad range of additional components: payments in kind valued at market prices, agricultural output produced for self-consumption valued at market prices, the value of food and other direct subsidies, and the imputed value of housing services. The rural component of this collection consists of two data files, one in which the individual is the unit of analysis (Part 1) and a second in which the household is the unit of analysis (Part 2). Individual rural respondents reported on their employment status, level of education, Communist Party membership, type of employer (e.g., public, private, or foreign), type of economic sector in which they were employed, occupation, whether they held a second job, retirement status, monthly pension, monthly wage, and other sources of income. Demographic variables include relationship to householder, gender, age, and student status. Rural households reported extensively on the character of the household and residence. Information was elicited on type of terrain surrounding the house, geographic position, type of house, and availability of electricity. Also reported were sources of household income (e.g., farming, industry, government, rents, and interest), taxes paid, value of farm, total amount and type of cultivated land, financial assets and debts, quantity and value of various crops, amount of grain purchased or provided by a collective, use of chemical fertilizers, gasoline, and oil, quantity and value of agricultural machinery, and all household expenditures (e.g., food, fuel, medicine, education, transportation, and electricity). The urban component of this collection also consists of two data files, one in which the individual is the unit of analysis (Part 3) and a second in which the household is the unit of analysis (Part 4). Individual urban respondents reported on their economic status within the household, Communist Party membership, sex, age, nature of employment, and relationship to the household head. Information was collected on all types and sources of income from each member of the household whether working, nonworking, or retired, all revenue received by owners of private or individual enterprises, and all in-kind payments (e.g., food, durable goods, and nondurable goods). Urban households reported total income (including salaries, interest on savings and bonds, dividends, rent, leases, alimony, gifts, and boarding fees), all types and values of food subsidies received, and total debt. Information was also gathered on household accommodations and living conditions, including number of rooms, total living area in square meters, availability and cost of running water, sanitary facilities, heating and air-conditioning equipment, kitchen availability, location of residence, ownership of home, and availability of electricity and telephone. Households reported on all their expenditures including amounts spent on food items such as wheat, rice, edible oils, pork, beef and mutton, poultry, fish and seafood, sugar, and vegetables by means of coupons in state-owned stores and at free market prices. Information was also collected on rents paid by the households, fuel available, type of transportation used, and availability and use of medical and child care. The Chinese Household Income Project collected data in 1988, 1995, 2002, and 2007. ICPSR holds data from the first three collections, and information about these can be found on the series description page. Data collected in 2007 are available through the China Institute for Income Distribution.

This collection automatically includes metadata sourced from the GOVERNMENT OF THE REPUBLIC OF SLOVENIA STATISTICAL OFFICE OF THE REPUBLIC OF SLOVENIA and corresponding to the source collection entitled "Available household income by household tenure status, age and sex (EUR), Slovenia, annually".

The actual data is available in PC-Axis format (.px). Among the additional links, you can access the pages of the source portal for insight and selection of data, and there is also the PX-Win program, which can be downloaded for free. Both allow you to select data for display, change the format of the printout and save it in different formats, as well as view and print tables of unlimited size and some basic statistical analyses and graphical representations.

Mortgage Status By Selected Monthly Owner Costs As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

This dataset contains information on minority veteran healthcare usage, educational attainment, unemployment rates, median income, and projected population figures.

The Singapore Department of Statistics undertakes the Household Expenditure Survey (HES) once in 5 years to collect detailed information from resident households in Singapore. The latest HES was conducted from Oct 2012 to Sep 2013. Topics covered include household consumption expenditure, households' income, socio-economic characteristics and ownership of selected consumer durables.

About this dataset

Context

The dataset illustrates the median household income in Bowdon, 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 Bowdon decreased by $987 (2.16%), 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.

Content

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:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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.

Inspiration

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/.

Recommended for further research

This dataset is a part of the main dataset for Bowdon median household income. You can refer the same here

Updated for 2013-17: US Census American Community Survey data table for: Housing subject area. Provides information about: MORTGAGE STATUS BY SELECTED MONTHLY OWNER COSTS AS A PERCENTAGE OF HOUSEHOLD INCOME IN THE PAST 12 MONTHS for the universe of: Owner-occupied housing units. These data are extrapolated estimates only, based on sampling; they are not actual complete counts. The data is based on 2010 Census Tracts. Table ACS_B25091_MORTGAGEPERCENTHSEHLDINC contains both the Estimate value in the E item for the census topic and an adjacent M item which defines the Margin of Error for the value. The Margin of Error (MOE) is the plus/minus range for the item estimate value, where the range between the Estimate minus the Margin of Error and the Estimate plus the Margin of Error defines the 90% confidence interval of the item value. Many of the Margin of Error values are significant relative to the size of the Estimate value. This table contains 23 item(s) extracted from a larger sequence table. This extracted subset represents that portion of the sequence that is considered high priority. Other portions of this sequence that are not included can be identified in the data dictionary information provided in the Supplemental Information section below. This table information is also provided as a customized layer file: B25091_AREA_MORTGAGEPERCENTHSEHLDINC.lyr where the table information is joined to the 2010 TRACTS_AREA census geography on the GEOID item. Both the table and customized lyr file name do not contain the year descriptor (i.e. 2012-2016) for the current ACS series. This is intentional in order to maintain the same table name in each successive ACS update. The alias of each item's (E)stimate and (M)easure of Error value stores this year date information as beginning YY and ending YY, i.e., 'E1216' and 'M1216' followed by the rest of the alias description. In this way users of the data tables or lyr files that support field aliases can determine which ACS series is being represented by the current table contents.

Association between socioeconomic status and irregular menstruation (N = 4,709).

Gross Rent As A Percentage Of Household Income Report based on US Census and American Community Survey Data.

United States Household Income: South Carolina data was reported at 54,336.000 USD in 2016. This records an increase from the previous number of 46,360.000 USD for 2015. United States Household Income: South Carolina data is updated yearly, averaging 37,570.000 USD from Mar 1984 (Median) to 2016, with 33 observations. The data reached an all-time high of 54,336.000 USD in 2016 and a record low of 20,036.000 USD in 1985. United States Household Income: South Carolina data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H045: Household Income.

United States Household Income: $100,000 to $149,999 data was reported at 14.500 % in 2017. This records an increase from the previous number of 14.400 % for 2016. United States Household Income: $100,000 to $149,999 data is updated yearly, averaging 13.100 % from Mar 1967 (Median) to 2017, with 51 observations. The data reached an all-time high of 15.000 % in 1999 and a record low of 6.500 % in 1967. United States Household Income: $100,000 to $149,999 data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.H049: Household Income: by Income Level.