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

The 1940 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, 1940, although some persons were missed. The 1940 census population schedules were digitized by the National Archives and Records Administration (NARA) and released publicly on April 2, 2012. The 1940 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 1940 Census enumeration district descriptions contain written descriptions of census districts, subdivisions, and enumeration districts.

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 IPUMS 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.

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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.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 1940 census data was collected in April 1940. 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 IPUMS 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 SPLIT40, reconstructed using the variable SERIAL40, and the original count is found in the variable NUMPREC40.
• Some variables are missing from this data set for specific enumeration districts. The enumeration districts with missing data can be identified using the variable EDMISS. These variables will be added in a future release.
• Coded variables derived from string variables are still in progress. These variables include: occupation, industry and migration status.
• Missing observations have been allocated and some inconsistencies have been edited for the following variables: Missing observations have been allocated and some inconsistencies have been edited for the following variables: SURSIM, SEX, SCHOOL, RELATE, RACE, OCC1950, MTONGUE, MBPL, FBPL, BPL, MARST, EMPSTAT, CITIZEN, OWNERSHP. 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 many variables. In particular, the variables GQ, and GQTYPE have known inconsistencies and will be improved with the next r

The 1940 Census Public Use Microdata Sample Project was assembled through a collaborative effort between the United States Bureau of the Census and the Center for Demography and Ecology at the University of Wisconsin. The collection contains a stratified 1-percent sample of households, with separate records for each household, for each "sample line" respondent, and for each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1940 Census of Population. Geographic identification of the location of the sampled households includes Census regions and divisions, states (except Alaska and Hawaii), standard metropolitan areas (SMAs), and state economic areas (SEAs). Accompanying the data collection is a codebook that includes an abstract, descriptions of sample design, processing procedures and file structure, a data dictionary (record layout), category code lists, and a glossary. Also included is a procedural history of the 1940 Census. Each of the 20 subsamples contains three record types: household, sample line, and person. Household variables describe the location and condition of the household. The sample line records contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, wage deductions for Social Security, and occupation. Person records also contain variables describing demographic characteristics including nativity, marital status, family membership, education, employment status, income, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08236.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

1940 US Census contains records from Montpelier, Washington, Vermont, USA by Ancestry.com. 1940 United States Federal Census [database on-line]. Provo, UT, USA: Ancestry.com Operations, Inc., 2012.; Year: 1940; Census Place: Montpelier, Washington, Vermont; Roll: m-t0627-04238; Page: 3B; Enumeration District: 12-31; Original data: United States of America, Bureau of the Census. Sixteenth Census of the United States, 1940. Washington, D.C.: National Archives and Records Administration, 1940. T627, 4,643 rolls. - .

1940 United States Federal Census contains records from Philadelphia, Pennsylvania, USA by United States of America, Bureau of the Census. Sixteenth Census of the United States, 1940. Washington, D.C.: National Archives and Records Administration, 1940. T627, 4,643 rolls. Year: 1940; Census Place: Upper Dublin, Montgomery, Pennsylvania; Roll: m-t0627-03585; Page: 20B; Enumeration District: 46-208 - .

1940 United States Federal Census contains records from Caribou, Aroostook, Maine, USA by Year: 1940; Census Place: Caribou, Aroostook, Maine; Roll: m-t0627-01471; Page: 10A; Enumeration District: 2-9 - .

This dataset includes all households from the 1940 US census.

The Veterans’ Grandchildren Mortality Plus sample consists of the records of more than 35,700 total grandchildrenboth male and female in nearly equal numbers,about 28,000 of which survived to age 45,who were born after the war to 16,791 children of 2,825 veterans,and contains an oversample of ex-POW veterans.The primary purpose of the project was to explore how grandfathers’ trauma affects the longevity and overweight of descendants. The dataset contains birth and death dates of grandchildren, census information on their parents' household, select socioeconomic and education information from the 1930 and 1940 census, and height and weight information from WWII draft cards for the grandsons. This multigenerational dataset can be used for researching the intergenerational transmission of longevity, overweight and socioeconomic status and the sex-specific pathways of this transmission and for testing mechanical linkage algorithms. Researchers built on a previously collected NIA-funded project containing census and death information of children of ex-POW and non-POW veterans (“Early Indicators, Intergenerational Processes, and Aging,” NIA grant P01AG10120, PI: Costa). The Veterans’ Grandchildren Mortality Plus data set contains the newly collected records of the veterans’ grandchildren, as well as the previously collected data of the veterans and their children.

This dataset includes all individuals from the 1940 US census.

The 1940 Census Tract files were originally created by keypunching the data from the printed publications prepared by the Bureau of the Census. The work was done under the direction of Dr. Donald Bogue, whose wife, Elizabeth Mullen Bogue, completed much of the data work. Subsequently, the punchcards were converted to data files and transferred to the National Archive and Records Administration (NARA). ICPSR received copies of these files from NARA and converted the binary block length records to ASCII format.

1940 Ancestry Census Data for Baltimore, Maryland. Refer to the 1940 codebook (codebook_1940.pdf) for more information. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The CenSoc WWII Army Enlistment Dataset is a cleaned and harmonized version of the National Archives and Records Administration’s Electronic Army Serial Number Merged File, ca. 1938 - 1946 (2002). It contains enlistment records for over 9 million men and women who served in the United States Army, including the Army Air Corps, Women's Army Auxiliary Corps, and Enlisted Reserve Corps. We publish links between men in the CenSoc WWII Army Enlistment Dataset, Social Security Administration mortality data, and the 1940 Census. The CenSoc Enlistment-Census-1940 file links these enlistment records to the complete 1940 Census, and may be merged with IPUMS-USA census data using the HISTID identifier variable. The CenSoc Enlistment-Numident file links enlistment records to the Berkley Unified Numident Mortality Database (BUNMD), and the CenSoc Enlistment-DMF file links enlistment records to the Social Security Death Master File. For enlistment records in the Enlistment-Numident and Enlistment-DMF datasets that have been independently and additionally linked to the 1940 Census, we include the HISTID identifier variable that can be used to merge the data with IPUMS census data.

This dataset includes variable names, variable labels, variable values, and corresponding variable value labels for the IPUMS 1940 datasets.

BackgroundAddressing contemporary anti-Asian racism and its impacts on health requires understanding its historical roots, including discriminatory restrictions on immigration, citizenship, and land ownership. Archival secondary data such as historical census records provide opportunities to quantitatively analyze structural dynamics that affect the health of Asian immigrants and Asian Americans. Census data overcome weaknesses of other data sources, such as small sample size and aggregation of Asian subgroups. This article explores the strengths and limitations of early twentieth-century census data for understanding Asian Americans and structural racism.MethodsWe used California census data from three decennial census spanning 1920–1940 to compare two criteria for identifying Asian Americans: census racial categories and Asian surname lists (Chinese, Indian, Japanese, Korean, and Filipino) that have been validated in contemporary population data. This paper examines the sensitivity and specificity of surname classification compared to census-designated “color or race” at the population level.ResultsSurname criteria were found to be highly specific, with each of the five surname lists having a specificity of over 99% for all three census years. The Chinese surname list had the highest sensitivity (ranging from 0.60–0.67 across census years), followed by the Indian (0.54–0.61) and Japanese (0.51–0.62) surname lists. Sensitivity was much lower for Korean (0.40–0.45) and Filipino (0.10–0.21) surnames. With the exception of Indian surnames, the sensitivity values of surname criteria were lower for the 1920–1940 census data than those reported for the 1990 census. The extent of the difference in sensitivity and trends across census years vary by subgroup.DiscussionSurname criteria may have lower sensitivity in detecting Asian subgroups in historical data as opposed to contemporary data as enumeration procedures for Asians have changed across time. We examine how the conflation of race, ethnicity, and nationality in the census could contribute to low sensitivity of surname classification compared to census-designated “color or race.” These results can guide decisions when operationalizing race in the context of specific research questions, thus promoting historical quantitative study of Asian American experiences. Furthermore, these results stress the need to situate measures of race and racism in their specific historical context.

1940 United States Federal Census contains records from Montpelier, Washington, Vermont, USA by Year: 1940; Census Place: Montpelier, Washington, Vermont; Roll: m-t0627-04238; Page: 3B; Enumeration District: 12-31 - .

1940 Education Census Data for Baltimore, Maryland. Refer to the 1940 codebook (codebook_1940.pdf) for more information. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Those residing in Japan as of 0:00h, civilians in military employ residing abroad, etc.

These data comprise Census records relating to the Alaskan people's population demographics for the State of Alaskan Salmon and People (SASAP) Project. Decennial census data were originally extracted from IPUMS National Historic Geographic Information Systems website: https://data2.nhgis.org/main (Citation: Steven Manson, Jonathan Schroeder, David Van Riper, and Steven Ruggles. IPUMS National Historical Geographic Information System: Version 12.0 [Database]. Minneapolis: University of Minnesota. 2017. http://doi.org/10.18128/D050.V12.0). A number of relevant tables of basic demographics on age and race, household income and poverty levels, and labor force participation were extracted. These particular variables were selected as part of an effort to understand and potentially quantify various dimensions of well-being in Alaskan communities. The file "censusdata_master.csv" is a consolidation of all 21 other data files in the package. For detailed information on how the datasets vary over different years, view the file "readme.docx" available in this data package. The included .Rmd file is a script which combines the 21 files by year into a single file (censusdata_master.csv). It also cleans up place names (including typographical errors) and uses the USGS place names dataset and the SASAP regions dataset to assign latitude and longitude values and region values to each place in the dataset. Note that some places were not assigned a region or location because they do not fit well into the regional framework. Considerable heterogeneity exists between census surveys each year. While we have attempted to combine these datasets in a way that makes sense, there may be some discrepancies or unexpected values. The RMarkdown document SASAPWebsiteGraphicsCensus.Rmd is used to generate a variety of figures using these data, including the additional file Chignik_population.png. An additional set of 25 figures showing regional trends in population and income metrics are also included.

Census Population: Rural: Arequipa data was reported at 113,789.000 Person in 2017. This records a decrease from the previous number of 155,308.000 Person for 2007. Census Population: Rural: Arequipa data is updated yearly, averaging 122,653.000 Person from Jun 1940 (Median) to 2017, with 7 observations. The data reached an all-time high of 155,308.000 Person in 2007 and a record low of 107,933.000 Person in 1940. Census Population: Rural: Arequipa data remains active status in CEIC and is reported by National Institute of Statistics and Informatics. The data is categorized under Global Database’s Peru – Table PE.G003: Population: Census by Department.