Abstract

This dataset includes all individuals from the 1870 US census.

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Documentation

This dataset was developed through a collaboration between the Minnesota Population Center and the Church of Jesus Christ of Latter-Day Saints. The data contain demographic variables, economic variables, migration variables and race variables. Unlike more recent census datasets, pre-1900 census datasets only contain individual level characteristics and no household or family characteristics, but household and family identifiers do exist.

The official enumeration day of the 1870 census was 1 June 1870. The main goal of an early census like the 1870 U.S. census was to allow Congress to determine the collection of taxes and the appropriation of seats in the House of Representatives. Each district was assigned a U.S. Marshall who organized other marshals to administer the census. These enumerators visited households and recorder names of every person, along with their age, sex, color, profession, occupation, value of real estate, place of birth, parental foreign birth, marriage, literacy, and whether deaf, dumb, blind, insane or “idiotic”.

Sources: Szucs, L.D. and Hargreaves Luebking, S. (1997). Research in Census Records, The Source: A Guidebook of American Genealogy. Ancestry Incorporated, Salt Lake City, UT Dollarhide, W.(2000). The Census Book: A Genealogist’s Guide to Federal Census Facts, Schedules and Indexes. Heritage Quest, Bountiful, UT

Abstract

The Integrated Public Use Microdata Series (IPUMS) Complete Count Data include more than 650 million individual-level and 7.5 million household-level records. The microdata are the result of collaboration between IPUMS and the nation’s two largest genealogical organizations—Ancestry.com and FamilySearch—and provides the largest and richest source of individual level and household data.

Before Manuscript Submission

All manuscripts (and other items you'd like to publish) must be submitted to

phsdatacore@stanford.edu for approval prior to journal submission.

We will check your cell sizes and citations.

For more information about how to cite PHS and PHS datasets, please visit:

https:/phsdocs.developerhub.io/need-help/citing-phs-data-core

Documentation

Historic data are scarce and often only exists in aggregate tables. The key advantage of historic US census data is the availability of individual and household level characteristics that researchers can tabulate in ways that benefits their specific research questions. The data contain demographic variables, economic variables, migration variables and family variables. Within households, it is possible to create relational data as all relations between household members are known. For example, having data on the mother and her children in a household enables researchers to calculate the mother’s age at birth. Another advantage of the Complete Count data is the possibility to follow individuals over time using a historical identifier.

In sum: the historic US census data are a unique source for research on social and economic change and can provide population health researchers with information about social and economic determinants.

The historic US 1920 census data was collected in January 1920. Enumerators collected data traveling to households and counting the residents who regularly slept at the household. Individuals lacking permanent housing were counted as residents of the place where they were when the data was collected. Household members absent on the day of data collected were either listed to the household with the help of other household members or were scheduled for the last census subdivision.

Notes

• We provide household and person data separately so that it is convenient to explore the descriptive statistics on each level. In order to obtain a full dataset, merge the household and person on the variables SERIAL and SERIALP. In order to create a longitudinal dataset, merge datasets on the variable HISTID.

• Households with more than 60 people in the original data were broken up for processing purposes. Every person in the large households are considered to be in their own household. The original large households can be identified using the variable SPLIT, reconstructed using the variable SPLITHID, and the original count is found in the variable SPLITNUM.

• Coded variables derived from string variables are still in progress. These variables include: occupation and industry.

• Missing observations have been allocated and some inconsistencies have been edited for the following variables: SPEAKENG, YRIMMIG, CITIZEN, AGE, BPL, MBPL, FBPL, LIT, SCHOOL, OWNERSHP, MORTGAGE, FARM, CLASSWKR, OCC1950, IND1950, MARST, RACE, SEX, RELATE, MTONGUE. The flag variables indicating an allocated observation for the associated variables can be included in your extract by clicking the ‘Select data quality flags’ box on the extract summary page.

• Most inconsistent information was not edited for this release, thus there are observations outside of the universe for some variables. In particular, the variables GQ, and GQTYPE have known inconsistencies and will be improved with the next release.

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Section 2

This dataset was created on 2020-01-10 18:46:34.647 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1920 households: This dataset includes all households from the 1920 US census.

IPUMS 1920 persons: This dataset includes all individuals from the 1920 US census.

IPUMS 1920 Lookup: This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1920 datasets.

Website alows the public full access to the 1940 Census images, census maps and descriptions.

This data collection constitutes a portion of the historical data collected by the project "Early Indicators of Later Work Levels, Disease, and Death." With the goal of constructing datasets suitable for longitudinal analyses of factors affecting the aging process, the project is collecting military, medical, and socioeconomical data on a sample of white males mustered into the Union Army during the Civil War. The project seeks to examine the influence of environmental and host factors prior to recruitment on the health performance and survival of recruits during military service, to identify and show relationships between socioeconomic and biomedical conditions (including nutritional status) of veterans at early ages and mortality rates from diseases at middle and late ages, and to study the effects of health and pensions on labor force participation rates of veterans at ages 65 and over. This installment of the collection, Version C-3, supersedes all previous collections (Versions C-1 and C-2), and contains data from the censuses of 1850, 1860, 1900, and 1910 on veterans who were originally mustered into the Union Army in Connecticut, Delaware, District of Columbia, Illinois, Iowa, Kansas, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Vermont, and West Virginia. This version of the collection also contains observations from Wisconsin, Indiana, California, and New Mexico. Census Data, Part 1, includes place of residence, relationship to head of household, date and place of birth, number of children, education, disability status, employment status, number of years in the United States, literacy, marital status, occupation, parents' birthplace, and property/home ownership. The variables in Part 2, Linkage Data, indicate which document sources were located for each recruit.

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

Two novel datasets—French 19th-century and U.S. 1950 Census records—to demonstrate our approach.

The average American family in 2023 consisted of 3.15 persons. Families in the United States According to the U.S. Census Bureau, a family is a group of two people or more (one of whom is the householder) related by birth, marriage, or adoption and residing together; all such people (including related subfamily members) are considered as members of one family. As of 2023, the U.S. Census Bureau counted about 84.33 million families in the United States. The average family consisted of 3.15 persons in 2021, down from 3.7 in the 1960s. This is reflected in the decrease of children in family households overall. In 1970, about 56 percent of all family households had children under the age of 18 living in the household. This percentage declined to about 40 percent in 2020. The average size of a family household varies greatly from state to state. The largest average families can be found in Utah, California, and Hawaii, while the smallest families can be found in Wisconsin, Vermont and Maine.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

Data from: American Community Survey, 5-year Series

Sample of family names (U.S. Census) and given names (mortgage data).

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The 1950 Census population schedules were created by the Bureau of the Census in an attempt to enumerate every person living in the United States on April 1, 1950, although some persons were missed. The 1950 census population schedules were digitized by the National Archives and Records Administration (NARA) and released publicly on April 1, 2022. The 1950 Census enumeration district maps contain maps of counties, cities, and other minor civil divisions that show enumeration districts, census tracts, and related boundaries and numbers used for each census. The coverage is nation wide and includes territorial areas. The 1950 Census enumeration district descriptions contain written descriptions of census districts, subdivisions, and enumeration districts.

The estimated median household income and estimated median family income are two separate measures: every family is a household, but not every household is a family. According to the U.S. Census Bureau definitions of the terms, a family “includes a householder and one or more people living in the same household who are related to the householder by birth, marriage, or adoption,”[1] while a household “includes all the people who occupy a housing unit,” including households of just one person[2]. When evaluated together, the estimated median household income and estimated median family income provide a thorough picture of household-level economics in Champaign County.

Both estimated median household income and estimated median family income were higher in 2023 than in 2005. The changes in estimated median household income and estimated median family income between 2022 and 2023 were not statistically significant. Estimated median family income is consistently higher than estimated median household income, largely due to the definitions of each term, and the types of household that are measured and are not measured in each category.

Median income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Median Household Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) and Median Family Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars).

[1] U.S. Census Bureau. (Date unknown). Glossary. “Family Household.” (Accessed 19 April 2016).

[2] U.S. Census Bureau. (Date unknown). Glossary. “Household.” (Accessed 19 April 2016).

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (18 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (3 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Quincy, WA, 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 Quincy, WA 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 Quincy households based on income levels.

Key observations

• For Family Households: In Quincy, the majority of family households, representing 17.36%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $10,000 to $14,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Quincy, the majority of non-family households, accounting for 37.59%, have income $75,000 to $99,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.0%, earn $10,000 to $14,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Quincy, WA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Quincy, WA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Quincy, WA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Quincy, WA

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 Quincy median household income. You can refer the same here

Family Income and Benefits data with margins of error for Alaskan Communities/Places and aggregation at Borough/CDA and State level for recent 5-year American Community Survey (ACS) intervals. The 5-year interval data sets are published approximately 1/2 a period later than the End Year listed - for instance the interval ending in 2019 is published in mid-2021.Source: US Census Bureau, American Community SurveyThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: US Census ACS Income PublicationsUSE CONSTRAINTS: The Alaska Department of Commerce, Community, and Economic Development (DCCED) provides the data in this application as a service to the public. DCCED makes no warranty, representation, or guarantee as to the content, accuracy, timeliness, or completeness of any of the data provided on this site. DCCED shall not be liable to the user for damages of any kind arising out of the use of data or information provided. DCCED is not the authoritative source for American Community Survey data, and any data or information provided by DCCED is provided "as is". Data or information provided by DCCED shall be used and relied upon only at the user's sole risk.For information about the American Community Survey, click here.

The average American household consisted of 2.51 people in 2023.

Households in the U.S.

As shown in the statistic, the number of people per household has decreased over the past decades.

The U.S. Census Bureau defines a household as follows: “a household includes all the persons who occupy a housing unit as their usual place of residence. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live and eat separately from any other persons in the building and which have direct access from outside the building or through a common hall. The occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated persons who share living arrangements. (People not living in households are classified as living in group quarters.).”

The population of the United States has been growing steadily for decades. Since 1960, the number of households more than doubled from 53 million to over 131 million households in 2023.

Most of these households, about 34 percent, are two-person households. The distribution of U.S. households has changed over the years though. The percentage of single-person households has been on the rise since 1970 and made up the second largest proportion of households in the U.S. in 2022, at 28.88 percent.

In concordance with the rise of single-person households, the percentage of family households with own children living in the household has declined since 1970 from 56 percent to 40.26 percent in 2022.

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Stone County, MS, 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 Stone County, MS 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 Stone County households based on income levels.

Key observations

• For Family Households: In Stone County, the majority of family households, representing 18.49%, earn $75,000 to $99,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 2.26%, have incomes falling $150,000 to $199,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Stone County, the majority of non-family households, accounting for 16.49%, have income $15,000 to $19,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.79%, earn $150,000 to $199,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Stone County, MS (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Stone County, MS
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Stone County, MS
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Stone County, MS

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 Stone County median household income. You can refer the same here

About this dataset

Context

The dataset presents a breakdown of households across various income brackets in Smithfield, VA, 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 Smithfield, VA 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 Smithfield households based on income levels.

Key observations

• For Family Households: In Smithfield, the majority of family households, representing 25.8%, earn $150,000 to $199,999, showcasing a substantial share of the community families falling within this income bracket. Conversely, the minority of family households, comprising 0.0%, have incomes falling $15,000 to $19,999, representing a smaller but still significant segment of the community.
• For Non-Family Households: In Smithfield, the majority of non-family households, accounting for 13.55%, have income $40,000 to $44,999, indicating that a substantial portion of non-family households falls within this income bracket. On the other hand, the minority of non-family households, comprising 0.92%, earn $15,000 to $19,999, representing a smaller, yet notable, portion of non-family households in the community.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income Levels:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Income Level: The income level represents the income brackets ranging from Less than $10,000 to $200,000 or more in Smithfield, VA (As mentioned above).
• All Households: Count of households for the specified income level
• % All Households: Percentage of households at the specified income level relative to the total households in Smithfield, VA
• Family Households: Count of family households for the specified income level
• % Family Households: Percentage of family households at the specified income level relative to the total family households in Smithfield, VA
• Non-Family Households: Count of non-family households for the specified income level
• % Non-Family Households: Percentage of non-family households at the specified income level relative to the total non-family households in Smithfield, VA

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 Smithfield median household income. You can refer the same here