Abstract

The main aim and objectives of the census is to provide benchmark statistics and a comprehensive profile of the population and households of Niue at a given time. This information obtained from the census is very crucial and useful in providing evidence to decision making and policy formulation for the Government, Business Community, Local Communities or Village Councils, Non Government Organisations of Niue and The International Communities who have an interest in Niue and its people.

Geographic coverage

National

Analysis unit

• Household
• Individual/Person
• Members Oversea

Universe

All households in Niue and all persons in the household including those temporarily overseas and those absent for not more than 12 months.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionaire was published in English, a translated questionnaire was on hand when on demand by the respondent.

The questionnaire design differed slightly from the design of previous census questionnaires. As usual, government departments were asked to submit a list of questions on any specific topic they would like to add. Responses were not forthcoming in this census, although a few new questions were included.

There were two types of questionaires used in the census: the household questionaire and the individual questionnaire. An enumerator manual was prepared to assist the enumerators in their duties.

The questionnaire was pre-tested by the enumerators before they were to go out for field enumeration.

Cleaning operations

Census processing began as soon as questionaires were checked and coded. Forms were checked, edited and coded before being entered into the computer database.

Data processing was assisted by the Secretariat of the Pacific Community (SPC) using the computer software program CSPro for data entry and for generating tables. Tables were then exported to Excel for analysis.

Occupation and Industry were coded using the United Nations International Standard Classification of Occupation and International Standard Industrial Classification.

It is standard practice that as each area was completed the forms were first checked by the field supervisors for missing information and obvious inconsistencies. Omissions and errors identified at this stage were corrected by the enumerators.

The next stage was for the field supervisors to go through the completed forms again in the office to check in more detail for omissions and logical inconsistencies. Where they were found, the supervisors were responsible to take the necessary action.

Once the questionnaires had been thoroughly checked and edited, they were then coded in preparation for data processing.

Checking, editing and coding of the questionnaires in office were done after normal working hours as to ensure that the confidentiality of the survey is well observed.

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: A census building is a free standing structure which is fixed on earth or on water permanently or temporarily (regardless the material used in building it) and it is used for residence or doing any activity in it (work, sport, pious work….etc.). - Households: Consist of one person or a group of persons (related or non related to each other) sharing their housing unit and food together. A household includes: a) servants and the like who are living with the household; b) visitors who spent the census night with the household (except military persons); c) household members who spent the census night apart from their household, like members of armed forces and persons who always or temporarily work at night shifts or otherwise would not be counted by the census elsewhere; d) workers on Egyptian or foreign means of transporation who were present within or out of the territorial boundaries but have no residing place outside the country. - Group quarters: Not applicable

Universe

All individuals (Egyptians and foreigners) who were present within the political boundaries of Egypt at census night.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Central Agency for Public Mobilisation and Statistics

SAMPLE SIZE (person records): 5902243.

SAMPLE DESIGN: Sample of private households drawn by Egyptian statistical office. Sample method unknown.

Mode of data collection

Face-to-face [f2f]

Research instrument

Special Households Questionnaires; Public Living Quarters Questionnaire; Household and Housing Condition Questionnaire

Abstract

The 2000 Republic of Palau Census of Population and Housing was the second census collected and processed entirely by the republic itself. This monograph provides analyses of data from the most recent census of Palau for decision makers in the United States and Palau to understand current socioeconomic conditions. The 2005 Census of Population and Housing collected a wide range of information on the characteristics of the population including demographics, educational attainments, employment status, fertility, housing characteristics, housing characteristics and many others.

Geographic coverage

National

Analysis unit

• Household;
• Individual.

Universe

The 1990, 1995 and 2000 censuses were all modified de jure censuses, counting people and recording selected characteristics of each individual according to his or her usual place of residence as of census day. Data were collected for each enumeration district - the households and population in each enumerator assignment - and these enumeration districts were then collected into hamlets in Koror, and the 16 States of Palau.

Kind of data

Census/enumeration data [cen]

Sampling procedure

No sampling - whole universe covered

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000 censuses of Palau employed a modified list-enumerate procedure, also known as door-to-door enumeration. Beginning in mid-April 2000, enumerators began visiting each housing unit and conducted personal interviews, recording the information collected on the single questionnaire that contained all census questions. Follow-up enumerators visited all addresses for which questionnaires were missing to obtain the information required for the census.

Cleaning operations

The completed questionnaires were checked for completeness and consistency of responses, and then brought to OPS for processing. After checking in the questionnaires, OPS staff coded write-in responses (e.g., ethnicity or race, relationship, language). Then data entry clerks keyed all the questionnaire responses. The OPS brought the keyed data to the U.S. Census Bureau headquarters near Washington, DC, where OPS and Bureau staff edited the data using the Consistency and Correction (CONCOR) software package prior to generating tabulations using the Census Tabulation System (CENTS) package. Both packages were developed at the Census Bureau's International Programs Center (IPC) as part of the Integrated Microcomputer Processing System (IMPS).

The goal of census data processing is to produce a set of data that described the population as clearly and accurately as possible. To meet this objective, crew leaders reviewed and edited questionnaires during field data collection to ensure consistency, completeness, and acceptability. Census clerks also reviewed questionnaires for omissions, certain inconsistencies, and population coverage. Census personnel conducted a telephone or personal visit follow-up to obtain missing information. The follow-ups considered potential coverage errors as well as questionnaires with omissions or inconsistencies beyond the completeness and quality tolerances specified in the review procedures.

Following field operations, census staff assigned remaining incomplete information and corrected inconsistent information on the questionnaires using imputation procedures during the final automated edit of the data. The use of allocations, or computer assignments of acceptable data, occurred most often when an entry for a given item was lacking or when the information reported for a person or housing unit on an item was inconsistent with other information for that same person or housing unit. In all of Palau’s censuses, the general procedure for changing unacceptable entries was to assign an entry for a person or housing unit that was consistent with entries for persons or housing units with similar characteristics. The assignment of acceptable data in place of blanks or unacceptable entries enhanced the usefulness of the data.

Sampling error estimates

Human and machine-related errors occur in any large-scale statistical operation. Researchers generally refer to these problems as non-sampling errors. These errors include the failure to enumerate every household or every person in a population, failure to obtain all required information from residents, collection of incorrect or inconsistent information, and incorrect recording of information. In addition, errors can occur during the field review of the enumerators' work, during clerical handling of the census questionnaires, or during the electronic processing of the questionnaires. To reduce various types of non-sampling errors, Census office personnel used several techniques during planning, data collection, and data processing activities. Quality assurance methods were used throughout the data collection and processing phases of the census to improve the quality of the data.

Census staff implemented several coverage improvement programs during the development of census enumeration and processing strategies to minimize under-coverage of the population and housing units. A quality assurance program improved coverage in each census. Telephone and personal visit follow-ups also helped improve coverage. Computer and clerical edits emphasized improving the quality and consistency of the data. Local officials participated in post-census local reviews. Census enumerators conducted additional re-canvassing where appropriate.

This study arose out of the Kingston Local History Project. The purpose of this project is to construct a database detailing major aspects of Kingston's economic and social evolution during the second half of the nineteenth century. The study contains complete census enumerator' books for the census years 1851, 1861, 1871, 1891.

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.

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We will check your cell sizes and citations.

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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.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 1910 census data was collected in April 1910. 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.

Section 2

This dataset was created on 2020-01-10 23:47:27.924 by merging multiple datasets together. The source datasets for this version were:

IPUMS 1910 households: The Integrated Public Use Microdata Series (IPUMS) Complete Count Data are historic individual and household census records and are a unique source for research on social and economic change.

IPUMS 1910 persons: This dataset includes all individuals from the 1910 US census.

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: no - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: Independent and separate space with areas of exclusive use, inhabited or designed to be inhabited by one or more persons. - Households: A person or group of people, related or not, who occupy all or part of a dwelling; attend to basic needs charged to a common budget, and they generally share food. - Group quarters: An institution in which a group of people generally not related lives and sleeps; done for reasons of study, work, religion, military discipline, administrative labors, rehabilitation, and others.

Universe

The entire population of the country, including all households and dwellings. In addition, an inventory was made of economic establishments and agricultural units associated with the rural dwelling. The microdata sample consists of the 20% survey. It excludes population in group quarters.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Departmento Administrativo Nacional de Estadística (DANE)

SAMPLE SIZE (person records): 4117607.

SAMPLE DESIGN: Systematic sample of every other private dwelling. Drawn by the IPUMS from 20% microdata of private dwellings. The census office described the method for the original sample as a Bernoulli stratified design for elements of households, Poisson for dwellings, and of conglomerates for persons.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three enumeration questionnaires were used: 1. Questionnaire for the Urban environment. This is carried out by the field supervisor, through observation at the block level. It seeks to provide and overview of the predominant urban setting, based on criteria of habitat which are fundamentally physical. 2. Questionnaire of Census Units. This is carried out by the enumerator starting with the information reported directly by the units. It is divided into sections for: dwellings, households, persons, economic units and agricultural units. 3. Questionnaire for Special Housing Units (LEA). In the case of military barracks and penitentiary centers, this is carried out by resident personnel, trained for this purpose by the municipal coordinator. In the remaining cases, it is the responsibility of the enumerator.

Abstract

The Census is the official count of population and dwellings in Tonga, providing a ‘snapshot’ of the society and its most precious resource, its people, at a point in time. The official reference period of the census was midnight, the 30th of November, 2006.

The census provides a unique source of detailed demographic, social and economic data relating the entire population at a single point in time. Census information is used for policy setting and implementation, research, planning and other decision-making. The census is often the primary source of information used for the allocation of public funding, especially in areas such as health, education and social policy. The main users of this information are the government, local authorities, education facilities (such as schools and tertiary organizations), businesses, community organizations and the public in general.

The 2006 Census was taken under the authority of Section 8 of Statistical Act Chap. 53 of 1978 which empowers the Minister of Finance to make regulations necessary to conduct the population Census. This regulation was approved by the Cabinet and cited as Census Regulation 2006. The Census regulations also indicate that the Government Statistician would be responsible for the administration and completion of the Census. In addition, the regulations enabled the Statistics Department to carry out the necessary activities required to plan, manage and implement all the necessary Census activities.

Census planning and management

From a planning and management perspective, the Census had two main objectives. Firstly, it was to ensure that the process of collecting, compiling, evaluating, analyzing and disseminating of demographic, economic and social data was conducted in a timely and accurate manner. The development of procedures and processes for the 2006 Census of Population and Housing made use of the lessons learned in previous censuses, and built upon recommendations for improvements.

Secondly, it was a valuable opportunity for building the capacities of employees of the Statistics Department (SD), thus resulting in enhancing the image, credibility and reputation of the Department and at the same time, strengthening its infrastructure. Emphasis was placed on having a senior staff with a wide perspective and leadership qualities. Through the use of vision, planning, coordination, delegation of responsibility and a strong team spirit, the census work was conducted in an effective and efficient manner. Staffs at all levels were encouraged to have an innovative mindset in addressing issues. Incentives for other parties to participate, both within Statistics Department Tonga Tonga 2006 Census of Population and Housing viii and outside the government, were encouraged. As a result, the wider community including donors such as AusAID, the Secretariat of the Pacific Community (SPC) in Noumea, that provided the technical assistance and the general public, were able to support the census project.

Extensive and detailed planning is needed to conduct a successful census. Areas that required planning include: enumeration procedures and fieldwork, public communication, data processing and output systems, mapping and the design of census block boundaries, dissemination procedures, content determination and questionnaire development and training. These aspects, and how they interacted with each other, played a crucial role in determining the quality of all of the census outputs. Each phase therefore required careful, methodical planning and testing. The details of such activities, and their implementation and responsibilities were assigned to 5 subcommittees composed of staff members of the SD.

Organizational structure of the Census

A census organizational structure is designed to implement a number of interrelated activities. Each of these activities was assigned to a specific sub-committee. The census manuals provided guidelines on processes, organizational structures, controls for quality assurance and problem solving. The challenge for managers was developing a work environment that enabled census personnel to perform all these tasks with a common goal in mind. Each sub-committee was responsible for its own outputs, and specific decisions for specific situations were delegated to the lowest level possible. Problem situations beyond the scope of the sub-committee were escalated to the next higher level.

The organizational structure of the census was as follows: a) The Steering Committee (consisting of the Head of both Government and nongovernment organizations), chaired by Secretary for Finance with the Government Statistician (GS) as secretary. b) The Census Committee (consisted of all sub-committee leaders plus the GS, and chaired by the Assistant Government Statistician (AGS) who was the officer in charge of all management and planning of the Census 2006 operations. c) There were five Sub-committees (each sub-committee consisted of about 5 members and were chaired by their Sub-committee leader). These committees included: Mapping, Publicity, Fieldwork, Training and Data Processing. In this way, every staff member of the SD was involved with the census operation through their participation on these committees.

The census steering committee was a high level committee that approved and endorsed the plans and activities of the census. Policy issues that needed to be addressed were submitted to the steering committee for approval prior to the census team and sub-committees designation of the activities necessary to address the tasks.

Part of the initial planning of the 2006 Census involved the establishment of a work-plan with specific time frames. This charted all activities that were to be undertaken and, their impact and dependencies on other activities. These time frames were an essential part of the overall exercise, as they provided specific guides to the progress of each area, and alerted subcommittees’ team leaders (TL) to areas where problems existed and needed to be addressed. These also provided the SD staff with a clear indication of where and how their roles impacted the overall Census process.

Monitoring of the timeframe was an essential part of the management of the Census program. Initially, weekly meetings were held which involved the GS, AGS and team leaders (TL) of the Census committee. As the Census projects progressed, the AGS and TL’s met regularly with their sub-committees to report on the progress of each area. Decisions were made on necessary actions in order to meet the designated dates. Potential risks that could negatively affect the deadlines and actions were also considered at these meetings.

For the 5 sub-committees, one of their first tasks was to verify and amend their terms of reference using the “Strengths, Weaknesses, Opportunities and Threats” (SWOT) analysis methodology, as it applied to past censuses. Each committee then prepared a work-plan and listed all activities for which that particular sub-committee was responsible. This listing included the assignment of a responsible person, together with the timeline indicating the start and end dates required to complete that particular activity. These work-plans, set up by all the 5 sub-committees, were then used by the AGS to develop a detailed operational plan for all phases of the census, the activities required to complete these phases, start and end dates, the person responsible and the dependencies, - all in a Ghant chart format. These combined work-plans were further discussed and amended in the Census team and reported to the Steering committee on regular basis as required.

Geographic coverage

National coverage, which includes the 5 Divisions and both Urban and Rural Areas of Tonga.

Analysis unit

Individual and Households.

Universe

All individuals in private and institutional households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The National Population Census was a complete enumeration census, hence no sampling procedure was employed. A Mapping Sub-committee was formed to ensure complete coverage of the country.

The Mapping Sub-committee

Led by Mr. Winston Fainga'anuku, this committee's mandate was to ensure that good quality maps were produced. The objective was to ensure that the maps provided complete coverage of the country, were designed to accommodate a reasonable workload of one census enumerator and, that geographic identifiers could be used for dissemination purposes by the PopGIS system. Collaborations with the Ministry of Land, Survey and Natural Resources (MLSNR) began in 2004 to ensure that digitized maps for Tonga could be used for 2006 Census. Mr. Fainga'anuku was attached to the MLSNR in April 2005 to assist 'Atelea Kautoke, Samuela Mailau, Lilika and others to complete the task of digitizing the maps for Tonga. In addition, frequent visits by Mr. Scott Pontifex from the Secretariat of the Pacific Community (SPC) in Noumea, assisted to ensure that quality digitized maps were prepared. SPC also assisted by lending its digitizer which was used in this mapping project. The staff of the Statistics Department (SD) visited household sites throughout Tongatapu and the main outer islands. This exercise was to redesign the Census Block boundaries by amalgamating or splitting existing census blocks to achieve an average of 50 households per census block. Various updates within the census block maps were made. These included the names of the head of household; roads and other landmarks to ensure that current and accurate information was provided to the enumerators. Reliable maps, both for enumerators and supervisors are necessary ingredients to assist in avoiding any under or over - counting during

Race is a social and historical construct, and the racial categories counted by the census change over time so the process of constructing stable racial categories for these 50 years out of census data required complex and imperfect decisions. Here we have used historical research on early 20th century southern California to construct historic racial categories from the IPUMS full count data, which allows us to track groups that were not formally classified as racial groups in some census decades like Mexican, but which were important racial categories in southern California. Detailed explanation of how we constructed these categories and the rationale we used for the decisions we made can be found here. Layers are symbolized to show the percentage of each of the following groups from 1900-1940:AmericanIndian Not-Hispanic, AmericanIndian Hispanic, Black non-Hispanic, Black-Hispanic, Chinese, Korean, Filipino and Japanese, Mexican, Hispanic Not-Mexican, white non-Hispanic. The IPUMS Census data is messy and includes some errors and undercounts, making it hard to map some smaller populations, like Asian Indians (in census called Hindu in 1920) and creating a possible undercount of Native American populations. The race data mapped here also includes categories that may not have been socially meaningful at the time like Black-Hispanic, which generally would represent people from Mexico who the census enumerator classified as Black because of their dark skin, but who were likely simply part of Mexican communities at the time. We have included maps of the Hispanic not-Mexican category which shows very small numbers of non-Mexican Hispanic population, and American Indian Hispanic, which often captures people who would have been listed as Indian in the census, probably because of skin color, but had ancestry from Mexico (or another Hispanic country). This category may include some indigenous Californians who married into or assimilated into Mexican American communities in the early 20th century. If you are interested in mapping some of the other racial or ethnic groups in the early 20th century, you can explore and map the full range of variables we have created in the People's History of the IE IE_ED1900-1940 Race Hispanic Marriage and Age Feature layer.Suggested Citation: Tilton, Jennifer. People's History Race Ethnicity Dot Density Map 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. 2025Feature Layer CitationTilton, Jennifer, Tessa VanRy & Lisa Benvenuti. Race and Demographic Data 1900-1940. A People's History of the Inland Empire Census Project 1900-1940 using IPUMS Ancestry Full Count Data. Program in Race and Ethnic Studies University of Redlands, Center for Spatial Studies University of Redlands, UCR Public History. 2023. Additional contributing authors: Mackenzie Nelson, Will Blach & Andy Garcia Funding provided by: People’s History of the IE: Storyscapes of Race, Place, and Queer Space in Southern California with funding from NEH-SSRC Grant 2022-2023 & California State Parks grant to Relevancy & History. Source for Census Data 1900- 1940 Ruggles, Steven, Catherine A. Fitch, Ronald Goeken, J. David Hacker, Matt A. Nelson, Evan Roberts, Megan Schouweiler, and Matthew Sobek. IPUMS Ancestry Full Count Data: Version 3.0 [dataset]. Minneapolis, MN: IPUMS, 2021. Primary Sources for Enumeration District Linework 1900-1940 Steve Morse provided the full list of transcribed EDs for all 5 decades "United States Enumeration District Maps for the Twelfth through the Sixteenth US Censuses, 1900-1940." Images. FamilySearch. https://FamilySearch.org: 9 February 2023. Citing NARA microfilm publication A3378. Washington, D.C.: National Archives and Records Administration, 2003. BLM PLSS Map Additional Historical Sources consulted include: San Bernardino City Annexation GIS Map Redlands City Charter Proposed with Ward boundaries (Not passed) 1902. Courtesy of Redlands City Clerk. Redlands Election Code Precincts 1908, City Ordinances of the City of Redlands, p. 19-22. Courtesy of Redlands City Clerk Riverside City Charter 1907 (for 1910 linework) courtesy of Riverside City Clerk. 1900-1940 Raw Census files for specific EDs, to confirm boundaries when needed, accessed through Family Search. If you have additional questions or comments, please contact jennifer_tilton@redlands.edu.

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.

%3C!-- --%3E

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.

Abstract

The Census of Agriculture investigates information on agricultural establishments and agricultural activities developed inside them, including characteristics of the producers and establishments, economy and employment in the rural area, livestock, cropping and agribusiness. Its data collection unit is every production unit dedicated, either entirely or partially, to agricultural, forest or aquaculture activities, subordinated to a single administration – producer or administrator –, regardless of its size, legal nature or location, aiming at producing either for living or sales.

The first Census of Agriculture dates back to 1920, and it was conducted as part of the General Census. It did not take place in the 1930s due to reasons of political and institutional nature. From 1940 onward, the survey was decennial up to 1970 and quinquennial later on, taking place in the beginning of the years ending in 1 and 6 and relating to the years ending in 0 and 5. In the 1995-1996 Census of Agriculture, the information was related to the crop year (August 1995 to July 1996). In the 2006 Census of Agriculture, the reference for the data returned to be the calendar year. The 2006 edition was characterized both by the technological innovation introduced in the field operation, in which the paper questionnaire was replaced by the electronic questionnaire developed in Personal Digital Assistants - PDAs and by the methodological refinement, particularly concerning the redesign of its contents and incorporation of new concepts. That edition also implemented the National Address List for Statistical Purposes - Cnefe, which gathers the detailed description of the addresses of housing units and agricultural establishments, geographic coordinates of every housing unit and establishment (agricultural, religious, education, health and other) in the rural area, bringing subsidies for the planning of future IBGE surveys. The 2017 Census of Agriculture returned to reference the crop year – October 2016 to September 2017 –, though in a different period than that adopted in the 1995-1996 Census of Agriculture. New technologies were introduced in the 2017 survey to control the data collection, like: previous address list, use of satellite images in the PDAs to better locate the enumerator in relation to the terrain, and use of coordinates of the address and location where the questionnaire is open, which allowed a better coverage and assessment of the work.

The survey provides information on the total agricultural establishments; total area of those establishments; characteristics of the producers; characteristics of the establishments (use of electricity, agricultural practices, use of fertilization, use of agrotoxins, use of organic farming, land use, existence of water resources, existence of warehouses and silos, existence of tractors, machinery and agricultural implements, and vehicles, among other aspects); employed personnel; financial transactions; livestock (inventories and animal production); aquaculture and forestry (silviculture, forestry, floriculture, horticulture, permanent crops, temporary crops and rural agribusiness).

The periodicity of the survey is quinquennial, though the surveys in 1990, 1995, 2000 and 2005, 2010 and 2015 were not carried out due to budget restrictions from the government; the 1990 Census of Agriculture did not take place; the 1995 survey was carried out in 1996 together with the Population Counting; the 2000 survey did not take place; that of 2005 was carried out in 2007, together with the Population Counting once again; that of 2010 did not take place and that of 2015 was carried out in 2017. Its geographic coverage is national, with results disclosed for Brazil, Major Regions, Federation Units, Mesoregions, Microregions and Municipalities. The results of the 2006 Census of Agriculture, which has the calendar year as the reference period, are not strictly comparable with those from the 1995-1996 Census of Agriculture and 2017 Census of Agriculture, whose reference period is the crop year in both cases.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as any production unit dedicated wholly or partially to agricultural, forestry and aquaculture activities, subject to a single management, with the objective of producing for sale or subsistence, regardless of size, legal form (own, partnership, lease, etc.) or location (rural or urban). The agricultural holdings were classified according to the legal status of the producer as: individual holder, condominium, consortium or partnership; cooperative; incorporated or limited liability company; public utility institutions (church, NGO, hospital), or government.

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Frame The 2000 Population and Housing Census and the cartographic documentation constituted the source of the AC 2006 frame. No list frames were available in digital media with georeferenced addresses of the holdings. Census coverage was ensured on the basis of the canvassing of the EAs by enumerators.

(b) Complete and/or sample enumeration methods The AC 2006 was a complete enumeration operation of all agricultural holdings in the country.

Mode of data collection

Face-to-face [f2f]

Research instrument

An electronic questionnaire was used for data collection on:

Total agricultural establishments Total area of agricultural establishments Total area of crops Area of pastures Area of woodlands Total tractors Implements Machinery and vehicles Characteristics of the establishment and of the producer Total staff employed Total cattle, buffallo, goats, Sheep, pigs, poultry (chickens, fowls, chickens and chicks) Other birds (ducks, geese, teals, turkeys, quails, ostriches, partridges, pheasants and others) Plant production

The AC 2006 covered all 16 items recommended by FAO under the WCA 2010.

Cleaning operations

(a) DATA PROCESSING AND ARCHIVING The entire data collection and supervision software was developed in house by IBGE, using the Visual Studio platform in the Microsoft Operations Manager 2005 environment and Microsoft SQL Server 2000, with the assistance of Microsoft Brazil consulting. In addition, the GEOPAD application was installed to view, navigate and view maps and use GPS guidance. Updated versions of the software were installed automatically as soon as census enumerators connected the PDAs to the central server to transmit the data collected. Once internally validated by the device, the data were immediately transmitted to the database at the IBGE state unit. The previous AC (1996) served as the basis for defining the parameter values for the electronic editing process.

(b) CENSUS DATA QUALITY Automatic validation was incorporated into PDAs. Previously programmed skip patterns and real-time edits, performed during enumeration, ensured faster and more reliable interviews. In addition, the Bluetooth® technology incorporated into the PDAs allowed for direct data transmission to IBGE's central mainframe by each of enumerators on a weekly basis.

Data appraisal

The preliminary census results were published in 2007. The final results were released in 2009 through a printed volume and CD-ROMs. The census results were disseminated at the national and subnational scope (country, state and municipality) and are available online at IBGE's website.

Analysis unit

Persons and households

UNITS IDENTIFIED: - Dwellings: no - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: no

UNIT DESCRIPTIONS: - Dwellings: Separated space with independent access that serves as a human lodging - Households: Individuals living in the same dwelling. For indigenous population definition of household requires sharing at least one meal. - Group quarters: Group of persons who share a common roof and food because of work, health, religion, etc.

Universe

Population census included people in territories, sailors, diplomats and their families. The indigenous population was enumerated. Due to guerrilla activity, approximately 3,000 dwellings (out of 6 million) could not be enumerated. The microdata sample consists of the 10% survey. It excludes population in group quarters and indigenous population.

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: Departmento Administrativo Nacional de Estadística (DANE)

SAMPLE SIZE (person records): 2643125.

SAMPLE DESIGN: Systematic sample of dwellings pre-selected before fieldwork based on pre-census enumeration. In rural areas selection was determined in the field by the enumerator.

Mode of data collection

Face-to-face [f2f]

Research instrument

5 enumeration forms applied to 5 different target populations: (f1) short form for private dwellings (90%) of the population, requested information on age, sex, and relationship to householder; (f2) long form for private dwellings (10%); (f3) group quarters, 0.17% of dwellings; (f4) indigenous private dwellings (100%), representing 0.95% of dwellings; and (f5) indigenous group-quarters, 0.01% of dwellings.

Abstract

The 2009 Population and Housing Census was implemented according to Prime Ministerial Decision No. 94/2008/QD-TTg dated 10 July, 2008. This was the fourth population census and the third housing census implemented in Vietnam since the nation was reunified in 1975. The Census aimed to collect basic data on the population and housing for the entire territory of the Socialist Republic of Vietnam, to provide data for research and analysis of population and housing developments nationally and for each locality. It responded to information needs for assessing implementation of socio-economic development plans covering the period 2001 to 2010, for developing the socio-economic development plans for 2011 to 2020 and for monitoring performance on Millennium Development Goals of the United Nations to which the Vietnamese Government is committed.

Geographic coverage

National

Analysis unit

Households Individuals Dwelling

Universe

The 2009 Population and Housing Census enumerated all Vietnamese regularly residing in the territory of the Socialist Republic of Vietnam at the reference point of 0:00 on 01 April, 2009; Vietnamese citizens given permission by the authorities to travel overseas and still within the authorized period; deaths (members of the household) that occurred between the first day of the Lunar Year of the Rat (07 February, 2008) to 31 March, 2009; and residential housing of the population.

Population and housing censuses were implemented simultaneously taking the household as the survey unit. The household could include one individual who eats and resides alone or a group of individuals who eat and reside together. For household with 2 persons and over, its members may or may not share a common budget; or be related by blood or not; or marital or adoptive relationship or not; or in combination of both. The household head was the main respondent. For information of which the head of household was unaware, the enumerator was required to directly interview the survey subject. For information on labour and employment, the enumerator was required to directly interview all respondents aged 15 and older; for questions on births, the enumerator was required to directly interview women in childbearing ages (from 15 to 49 years of age) to determine the responses. For information on housing, the enumerator was required to directly survey the household head and/or combine this with direct observation to determine the information to record in the forms.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Sample size In the 2009 Population and Housing Census, besides a full enumeration, some indicators were collected in a sample survey. The census sample survey was designed to: (1) expand survey contents; (2) improve survey quality, especially for sensitive and complicated questions; and (3) save on survey costs. To improve the efficiency and reliability of the census sample data, the sample size was 15% of the total population of the country. The sample of the census is a single-stage cluster sample design with stratification and systematic sample selection. Sample selection is implemented in two steps: Step 1, select the strata to determine the sample size for each district. Step 2, independently and systematically select from the sample frame of enumeration areas in each district to determine the specific enumeration areas in the sample.

The sample size of the two census sample surveys in 1989 and 1999 was 5% and 3% respectively, only representative at the provincial level; sample survey indicators covered fertility history of women aged 15-49 years and deaths in the household in the previous 12 months. In the 2009 Census, besides the above two indicators, many other indicators were also included in the census sample survey. The census sample survey provides data representative at the district level. When determining sample size and allocation, the frequency of events was taken into account for various indicators including birth and deaths in the 12 months prior to the survey, and the number of people unemployed in urban areas, etc.; efforts were also made to ensure the ability to compare results between districts within the same province/municipality and between provinces/ municipalities.

Stratification and sample allocation across strata To ensure representativeness of the sample for each district throughout the country and because the population size is not uniform across districts or provinces, the Central Steering Committee decided to allocate the sample directly to 682 out of 684 districts (excluding 2 island districts) throughout the country in 2 steps:

Step 1: Determine the sampling rate f(r) for 3 regions including: - Region 1: including 132 urban districts; - Region 2: including 294 delta and coastal rural districts; - Region 3: including 256 mountainous and island districts.

Step 2: Allocate the sample across districts in each region based on the sampling rates for each region as determined in Step 1 using the inverse sampling allocation method. Through applying to this allocation method, the number of sampling units in each small district is increased adequately to ensure representativeness. The formula used to calculate the sample rate for each district in each region is provided on page 22 of the Census Report (Part1) provided as external resources.

Sampling unit and method The sampling unit is the enumeration area that was ascertained in the step to delimit enumeration areas. The sampling frame is the list of all enumeration areas that was made following the order of the list of administrative units at the commune level within each district. In this way, the whole country has 682 sample frames (682 strata).

The provincial steering committee was responsible for selecting sample enumeration areas using systematic random sampling as follows: Step 1: Take the total of all enumeration areas in the district, divide by the number of enumeration areas needed in the sampleto determine the skip (k), which is calculated with precision up to 1 decimal point. Step 2: Select the first enumeration area (b, with b = k), corresponding to the first enumeration area to be selected. Each successive enumeration area to be selected will correspond to the order number: bi = b + i x k ; here i = 1, 2, 3…. Stopping when the number of enumeration areas needed has been selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires and survey materials were designed and tested three times before final approval.

Cleaning operations

The 2009 Population and Housing Census applied Intelligent Character Recognition technology/scanning technology for direct data entry from census forms to the computer to replace the traditional keyboard data entry that is commonly used in Vietnam at present. This is an advanced technology, and the first time it had been applied in a statistical survey in Vietnam. Preparatory work had to be done carefully and meticulously. Through organization of many workshops and 7 pilot applications with technical and financial assistance from the UNFPA, the new technology was mastered, and the Census Steering Committee Standing Committee approved use of this technology to process the entire results of the 2009 Population and Housing Census. The Government decided to allocate funds through the project on Modernization of the General Statistics Office using World Bank Loan funds to procure the scanning system equipment, software and technical assistance. The successful use of this technology will create a precedent for continued use of scanning technology in other statistical surveys

After checking and coding at the Provincial/municipal steering committee office, (both the complete census and the census sample survey), forms were checked and accepted then transferred for processing to one of three Statistical Computing Centres in Hanoi, Ho Chi Minh City and Da Nang. Data processing was implemented in only a few locations, following standard procedures and a fixed timeline. The steering committee at each level and processing centres fully implemented their assigned responsibilities, especially the checking, transmitting and maintenance of survey forms in good condition. The Central Steering Committee collaborated with the Statistical Computer Centres to set up a plan for processing and compiling results, setting up tabulation plans, interpreting and synthesizing output tables, and developing options for extrapolating from sample to population estimates.

The General Statistics Office completed the work of developing software applications and training using ReadSoft software (the one used in pilot testing), organized training on network management and training on systems and programs for logic checks and data editing, developed a data processing protocol, integrated these systems and completed data flow management programs. The General Statistics Office collaborated with the contractor, FPT, to develop software applications, train staff, testl the system and complete the programs using the new TIS and E-form software.

Compilation of results was implemented in 2 stages. In stage 1 data were compiled from the Census Sample Survey by the end of October, 2009, and in stage 2, data were compiled from the completed census forms, with work finalized in May 2010.

Sampling error estimates

Estimates from the Census sample survey were affected by two types of error: (1) non-sampling error, and (2) sampling error. Non-sampling error is the result of errors in implementation of data collection and processing such as visiting the

The manual contains a list of mandatory requirements for conducting a census, as well as a number of guidelines and recommendations. The first sections of the manual describe the authority for conducting a municipal census, the role of the municipal council, and how to apply the Freedom of Information and Protection of Privacy Act (FOIP) to a municipal census. The subsequent sections describe the roles of census coordinator and the census enumerator. The final section provides a set of additional census questions that municipalities may choose to use in their census. The appendices contain various sample census materials. The methodologies, terms, and techniques for census-taking described in this manual are accepted by Alberta Municipal Affairs for determining the population of municipalities as described in the Determination of Population Regulation. The statistical concepts and principles reflected in this manual are based on those recognized by Statistics Canada and other statistical agencies.

The 1891 Census of Canada was enumerated by the Department of Agriculture in April of 1891. It aimed to collect information for every permanent resident and household in the country. Enumerators recorded information for each individual at their permanent residence, in the de jure style. The enumeration began in April 1891, and while in most areas of the country it was completed within a couple of days, it continued for weeks and even months in parts of the country that were difficult to access. The enumerator entered information about people and dwellings which were checked and, if necessary, corrected by a district commissioner. The commissioner then forwarded the sheets Ottawa for tabulation and, in some cases, further modification. The sheets were microfilmed from 1938-1940, and then destroyed. The microfilm reels survive as part of the collection of the National Archives of Canada (NAC reference number to catalogued collection: HA742 P8323 1987). Between 2003 and 2010 staff and students at the University of Guelph digitized a random 5% sample (10% in cities and in the West) of the 1891 population records. This database represents an individual-level sample of the 1891 Census of Canada, produced by researchers at the University of Guelph.

Abstract

The October Household Survey is an annual survey based on a probability sample of a large number of households (ranging from 16 000 in 1996 through to 30 000 in 1997 and 1998, depending on the availability of funding). It covers a range of development indicators, including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).

Geographic coverage

The survey had national coverage

Analysis unit

Households and individuals

Universe

The survey covered households and household members in the nine provinces of South Africa

Kind of data

Survey data

Sampling procedure

A sample of 30 000 households was drawn in 3 000 enumerator areas (EAs) (that is 10 households per enumerator area). A two-stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirements of probability sampling. The sample was based on the 1996 Population Census enumerator areas and the estimated number of households from the 1996 Population Census The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province and area type (urban/rural). Within each explicit stratum the EAs were stratified by simply arranging them in geographical order by District Council, Magisterial District and, within the magisterial district, by average household income (for formal urban areas and hostels) or EA. The allocated number of EAs was systematically selected with probability proportional to size in each stratum. The measure of size was the estimated number of households in Each EA. A systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face

Research instrument

The data files in the October Household Survey 1999 correspond to the following sections in the questionnaire:

Person: Data from Section 1 and Section 4 Births: Data from Section 2 Children: Data from Section2 Worker: Data from Section 3 Migrant: Data from Section 5 House: Data from Section 6 Farming: Data from Section 7

Data appraisal

Researchers should note that the birth data in the OHS 1999 is not comparable with the birth data in OHS for the years 1994-1998 because the birth history question was phrased differently in 1999.

The question on birth history in the questionnaires for OHS 1996-1998 was: 2.1 How many children (live births) have you ever given birth to?

In the 1999 OHS questionnaire the question asked was: 2.1 How many children (live births) has …… given birth to in the last 12 months?

The 1999 data does not therefore include a full birth history, only births in the 12 months before the survey interview.

The dataset contains economic census information for 6+ Metros conducted in 2012-2013. You will find separate files for each Metro. Below is the breakdown of data points for respective Metro file.

• Mumbai: 261259
• Ahmedabad: 353015
• Chennai: 333049
• Delhi: 875308
• Hyderabad: 215737
• Kolkata: 543081
• Mumbai-Suburban: 465416
• Pune: 514469

Data Description -

There are 20+ variables in each Metro File. Below is the brief details about each of them. For more details please refer Data Labels file. It will give you understanding of coding details for nominal variables.

Abstract

The October Household Survey (OHS) of 1995 is the second official survey undertaken by Statistics South Africa (Stats SA) with the specific aim of making data available for the South African government's Reconstruction and Development Programme (RDP). Data collected includes population data, particulars of dwellings and data on services and on perceived quality of life.

Geographic coverage

The survey had national coverage

Analysis unit

Units of analysis in the survey are households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 30 000 households was drawn in 3 000 enumerator areas (EA's) (that is 10 households per Enumerator Area). A two stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirement of probability sampling. The sample was based on the 1991 Population Census enumerator areas. The sampled population excluded all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent). The sample was explicitly stratified by province, Magisterial District, Urban/rural and Population group. The allocated number of EA's was systematically selected with probability proportional to size in each stratum The measure of size was the estimated number of people. In each EA, a systematic sample of 10 households was drawn.

Mode of data collection

Face-to-face [f2f]

Abstract

The 2021 NPHC is tthe first census conducted under the federal structure of Nepal. The main census enumeration was originally scheduled to take place over 15 days- from June 8 to 22, 2021, but due to the COVID-19 pandemic, the enumeration was postponed for five months. Once the impact of the pandemic subsided, the enumeration was carried out according to a new work plan for a 15 dya period from November 11 to 25, 2021.

This report contains statistical tables at the national, provincial, district and municipal levels, derived from the topics covered in the census questionaires. The work of the analyzing the data in detail is still in progress. The report provides insights into the different aspects of the census operation, including its procedure, concepts, methodology, quality control, logistics, communication, data processing, challenges faced, and other management aspects.

This census slightly differs from the previous censuses mainly due to the following activities: i. three modes of data collection (CAPI, PAPI and e-census); ii. a full count of all questions instead of sampling for certain questions, as was done in the previous two censuses, iii. collaboration with Ministry of Health and Population to ascertain the likely maternal mortality cases reported in the census by skilled health personnel; iv. data processing within its premises; v. recuitment of fresh youths as supervisor and enumerators; and vi. using school teachers as master trainers, especially for the local level training of enumerators.

The objectives of the 2021 Population Census were:

a) to develop a set of benchmark data for different purposes. b) to provide distribution of population by demographic, social and economic characteristics. c) to provide data for small administrative areas of the country on population and housing characteristics. d) to provide reliable frames for different types of sample surveys. e) to provide many demographic indicators like birth rates, death rates and migration rates. f) to project population for the coming years.

The total population of Nepal, as of the census day (25 November 2021) is 29,164,578, of which the number of males is 14,253,551 (48.87 %) and the number of females is 14,911,027 (51.13 %). Accordingly, the sex ratio is 95.59 males per 100 females. Annual average population growth rate is 0.92 percent in 2021.

Geographic coverage

National Level, Ecological belt, Urban and Rural, Province, District, Municipality, Ward Level

Analysis unit

The census results provide information up to the ward level (the lowest administrative level of Nepal), household and indivisual.

Universe

The census covered all modified de jure household members (usual residents)

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f] and online

Research instrument

In this census three main questionnaires were developed for data collection. The first was the Listing Form deveoped mainly for capturing the basic household informatioin in each Enumeration area of the whole country. The second questionnaire was the main questionnaire with eight major Sections as mentioned hereunder.

Listing Questionaire Section 1. Introduction Section 2. House information Section 3. Household information Section 4. Agriculture and livestock information Section 5. Other information

Main Questionaire Section 1. Introduction Section 2. Household Information Section 3. Individual Information Section 4. Educational Information Section 5. Migration Section 6. Fertility Section 7.Disability Section 8. Economic Activity

For the first time, the NPHC, 2021 brougt a Community Questionnaire aiming at capturing the socio-economic and demographic characteristics of the Wards (the lowest administrative division under Rural/Urban Municipalities). The Community Questionnaire contains 6 Chapters. The information derived from community questionnaire is expected to validate (cross checks) certain information collected from main questionnaire.

Community questionaire Section 1. Introduction Section 2. Basic information of wards Section 3. Caste and mother tongue information Section 4. Current status of service within wards Section 5. Access of urban services and facilities within wards Section 6. Status of Disaster Risk

It is noteworty that the digital version of questionnare was applied in collecting data within the selected municipalities of Kathmandu Valley. Enumerators mobilized in Kathmandu Valley were well trained to use tablets. Besides, online mode of data collection was adpoted for all the Nepalese Diplomatic Agencies located abroad.

Cleaning operations

For the concistency of data required logics were set in the data entry programme. For the processing and analysis of data SPSS and STATA programme were employed.

Abstract

The LFS is a twice-yearly rotating panel household survey, specifically designed to measure the dynamics of employment and unemployment in South Africa. It measures a variety of issues related to the labour market,including unemployment rates (official and expanded), according to standard definitions of the International Labour Organisation (ILO).

All editions of the LFS have been updated (some more than once) since their release. These version changes are detailed in a document available from DataFirst (in the "external documents" section titled "LFS 2000-2008 Collated Version Notes on the South African LFS").

Geographic coverage

National Coverage

Analysis unit

Households (dwellings) and individuals

Universe

The LFS sample covers the non-institutional population except for workers' hostels. However, persons living in private dwelling units within institutions are also enumerated. For example, within a school compound, one would enumerate the schoolmaster's house and teachers' accommodation because these are private dwellings. Students living in a dormitory on the school compound would, however, be excluded.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling procedure for the LFS was a two-stage complex sample. The first stage was the selection with probability proportional to size of PSUs from the 1996 Census list of Enumerator Areas (EAs), to form the Master Sample of 1999. The 1999 Master Sample is thus based on the 1996 Population Census list of EAs and the measure of size used was the number of dwelling units per PSU. The second stage involved the systematic selection of 10 dwelling units from each of the selected PSUs. The Master Sample was stratified into 18 strata, i.e. 9 provinces and within each province by urban / non-urban.

The LFS is a twice-yearly rotating panel household survey. A rotating panel sample involves visiting the same dwelling units on a number of occasions (in this instance, five at most), and replacing a proportion of these dwelling units each round. New dwelling units are added to the sample to replace those that are taken out. The Master Sample is based on the 1996 Population Census of enumeration areas (EA) and the estimated number of dwelling units from the 1996 Population Census. A sample of 30 000 dwelling units was drawn from 3000 primary sampling units (PSUs) (that is 10 dwellingunits per enumerator area (EA)) from the Master Sample. A two-stage sampling procedure was applied and the sample was stratified, clustered and selected to meet the requirements of probability sampling. The Master Sample is based on the 1996 Population Census enumerator areas and the estimated number of dwelling units from the 1996 Population Census. The EAs were grouped within a province by urban/rural, and a disproportional sample of EAs was taken from each group (stratum). Within each explicit stratum the PSUs were stratified by simply arranging them in geographical order by District Council, Magisterial District and, within the magisterial district, by average household income (for formal urban areas and hostels) or EA. The allocated number of EAs was systematically selected with probability proportional to size in each stratum. The sample was explicitly stratified by province and area type (urban/rural).

The careful and scientific selection of the PSUs is the first stage of the sample selection. These identified PSUs must match those areas selected from 1996 census records. After boundary identification, the next stage was to list accurately all the dwelling units in the PSU. A PSU is either one EA from the Census or several EAs when the number of dwelling units in the base or originally selected EA from the census was found to have less than 100 dwelling units. Each EA should have approximately 150 dwelling units but it was found that many contained less than that. Thus, in some cases it has been found necessary to add EAs to the original EA to give our minimum requirement of 100 dwelling units in the first stage of primary sampling units (PSUs). PSUs in the Master Sample consist of 100 to 2445 dwelling units. Special dwellings such as all prisoners in prisons, patients in hospitals, people residing in boarding houses and hotels (whether temporary or semi-permanent), guest houses (whether catering or self-catering), schools and churches are excluded from the sample. The second stage of the sample selection is from the dwelling unit listing. A systematic sample of 10 dwelling units was drawn from each PSU. However, if there was growth of more than 20% in a PSU, then the sample size was increased systematically according to the proportion of growth in the PSU. The same dwellings will be visited on, at most, five different occasions. After this, new dwelling units will be included for interviewing from the same PSU.

The first pilot round of LFS fieldwork took place in February 2000, based on a probability sample of 10 000 dwelling units. The sample was increased to 30 000 dwelling units in September 2000. Both of these surveys were published as discussion documents. The third round took place in February 2001, using the same 30 000 dwelling units.

Mode of data collection

Face-to-face [f2f]

Abstract

This dataset includes all individuals from the 1870 US census.

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:

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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