7 datasets found
  1. j

    1930 Population Census of Japan (Full-Scale): Survey Outline, Questionnaire,...

    • jdcat.jsps.go.jp
    • d-repo.ier.hit-u.ac.jp
    application/x-yaml +2
    Updated Sep 21, 2021
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    内閣統計局 (2021). 1930 Population Census of Japan (Full-Scale): Survey Outline, Questionnaire, etc. [Dataset]. https://jdcat.jsps.go.jp/records/8396
    Explore at:
    txt, text/x-shellscript, application/x-yamlAvailable download formats
    Dataset updated
    Sep 21, 2021
    Authors
    内閣統計局
    Time period covered
    Oct 1, 1930
    Area covered
    日本, Japan
    Description

    The 3rd Population Census. In order to clarify the state of Japan’s population and households, the population census has been conducted in Japan almost every five years.More details on the "Population Census of Japan" overall including other years can be found here: https://d-infra.ier.hit-u.ac.jp/Japanese/statistical-yb/b001.html.      The census introduced separate classifications for the type of occupation and the industry of occupation.

  2. Census of Agriculture, 2007 - United States Virgin Islands

    • microdata.fao.org
    Updated Nov 16, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States Department of Agriculture, National Agriculture Statistical Service (USDA/NASS) (2020). Census of Agriculture, 2007 - United States Virgin Islands [Dataset]. https://microdata.fao.org/index.php/catalog/1608
    Explore at:
    Dataset updated
    Nov 16, 2020
    Dataset provided by
    United States Department of Agriculturehttp://usda.gov/
    National Agricultural Statistics Servicehttp://www.nass.usda.gov/
    Authors
    United States Department of Agriculture, National Agriculture Statistical Service (USDA/NASS)
    Time period covered
    2007
    Area covered
    U.S. Virgin Islands
    Description

    Abstract

    For more than 150 years, the U.S. Department of Commerce, Bureau of the Census, conducted the census of agriculture. However, the 2002 Appropriations Act transferred the responsibility from the Bureau of the Census to the U.S. Department of Agriculture (USDA), National Agricultural Statistics Service (NASS). The 2007 Census of Agriculture for the U.S. Virgin Islands is the second census in the U.S. Virgin Islands conducted by NASS. The census of agriculture is taken to obtain agricultural statistics for each county, State (including territories and protectorates), and the Nation. The first U.S. agricultural census data were collected in 1840 as a part of the sixth decennial census. From 1840 to 1920, an agricultural census was taken as a part of each decennial census. Since 1920, a separate national agricultural census has been taken every 5 years. The 2007 census is the 14th census of agriculture of the U.S. Virgin Islands. The first, taken in 1920, was a special census authorized by the Secretary of Commerce. The next agriculture census was taken in 1930 in conjunction with the decennial census, a practice that continued every 10 years through 1960. The 1964 Census of Agriculture was the first quinquennial (5-year) census to be taken in the U.S. Virgin Islands. In 1976, Congress authorized the census of agriculture to be taken for 1978 and 1982 to adjust the data-reference year to coincide with the 1982 Economic Censuses covering manufacturing, mining, construction, retail trade, wholesale trade, service industries, and selected transportation activities. After 1982, the agriculture census reverted to a 5-year cycle. Data in this publication are for the calendar year 2007, and inventory data reflect what was on hand on December 31, 2007. This is the same reference period used in the 2002 census. Prior to the 2002 census, data was collected in the summer for the previous 12 months, with inventory items counted as what was on hand as of July 1 of the year the data collection was done.

    Objectives: The census of agriculture is the leading source of statistics about the U.S. Virgin Islands’s agricultural production and the only source of consistent, comparable data at the island level. Census statistics are used to measure agricultural production and to identify trends in an ever changing agricultural sector. Many local programs use census data as a benchmark for designing and evaluating surveys. Private industry uses census statistics to provide a more effective production and distribution system for the agricultural community.

    Geographic coverage

    National coverage

    Analysis unit

    Households

    Universe

    The statistical unit was a farm, defined as "any place from which USD 500 or more of agricultural products were produced and sold, or normally would had been sold, during the calendar year 2007". According to the census definition, a farm is essentially an operating unit, not an ownership tract. All land operated or managed by one person or partnership represents one farm. In the case of tenants, the land assigned to each tenant is considered a separate farm, even though the landlord may consider the entire landholding to be one unit rather than several separate units.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    (a) Method of Enumeration As in the previous censuses of the U.S. Virgin Islands, a direct enumeration procedure was used in the 2007 Census of Agriculture. Enumeration was based on a list of farm operators compiled by the U.S. Virgin Islands Department of Agriculture. This list was compiled with the help of the USDA Farm Services Agency located in St. Croix. The statistics in this report were collected from farm operators beginning in January of 2003. Each enumerator was assigned a list of individuals or farm operations from a master enumeration list. The enumerators contacted persons or operations on their list and completed a census report form for all farm operations. If the person on the list was not operating a farm, the enumerator recorded whether the land had been sold or rented to someone else and was still being used for agriculture. If land was sold or rented out, the enumerator got the name of the new operator and contacted that person to ensure that he or she was included in the census.

    (b) Frame The census frame consisted of a list of farm operators compiled by the U.S. Virgin Islands DA. This list was compiled with the help of the USDA Farm Services Agency, located in St. Croix.

    (c) Complete and/or sample enumeration methods The census was a complete enumeration of all farm operators registered in the list compiled by the United States of America in the CA 2007.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaire (report form) for the CA 2007 was prepared by NASS, in cooperation with the DA of the U.S. Virgin Islands. Only one questionnaire was used for data collection covering topics on:

    • Land owned
    • Land use
    • Irrigation
    • Conservation programs and crop insurance
    • Field crops
    • Bananas, coffee, pineapples and plantain crops
    • Hay and forage crops
    • Nursery, Greenhouse, Floriculture, Sod and tree seedlings
    • Vegetables and melons
    • Hydroponic crops
    • Fruit
    • Root crops
    • Cattle and calves
    • Poultry
    • Hogs and pigs
    • Aquaculture
    • Other animals and livestock products
    • Value of sales
    • Organic agriculture
    • Federal and commonwealth agricultural program payments
    • Income from farm-related sources
    • Production expenses
    • Farm labour
    • Fertilizer and chemicals applied
    • Market value of land and buildings
    • Machinery, equipment and buildings
    • Practices
    • Type of organization
    • Operator characteristics

    The questionnaire of the 2007 CA covered 12 of the 16 core items' recommended for the WCA 2010 round.

    Cleaning operations

    DATA PROCESSING The processing of the 2007 Census of Agriculture for the U.S. Virgin Islands was done in St. Croix. Each report form was reviewed and coded prior to data keying. Report forms not meeting the census farm definition were voided. The remaining report forms were examined for clarity and completeness. Reporting errors in units of measures, illegible entries, and misplaced entries were corrected. After all the report forms had been reviewed and coded, the data were keyed and subjected to a thorough computer edit. The edit performed comprehensive checks for consistency and reasonableness, corrected erroneous or inconsistent data, supplied missing data based on similar farms, and assigned farm classification codes necessary for tabulating the data. All substantial changes to the data generated by the computer edits were reviewed and verified by analysts. Inconsistencies identified, but not corrected by the computer, were reviewed, corrected, and keyed to a correction file. The corrected data were then tabulated by the computer and reviewed by analysts. Prior to publication, tabulated totals were reviewed by analysts to identify inconsistencies and potential coverage problems. Comparisons were made with previous census data, as well as other available data. The computer system provided the capability to review up-to-date tallies of all selected data items for various sets of criteria which included, but were not limited to, geographic levels, farm types, and sales levels. Data were examined for each set of criteria and any inconsistencies or potential problems were then researched by examining individual data records contributing to the tabulated total. W hen necessary, data inconsistencies were resolved by making corrections to individual data records.

    Sampling error estimates

    The accuracy of these tabulated data is determined by the joint effects of the various nonsampling errors. No direct measures of these effects have been obtained; however, precautionary steps were taken in all phases of data collection, processing, and tabulation of the data in an effort to minimize the effects of nonsampling errors.

  3. f

    Census of Agriculture, 2010-2011 - Lao People's Democratic Republic

    • microdata.fao.org
    Updated Nov 25, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ministry of Agriculture and Forestry (MAF) (2020). Census of Agriculture, 2010-2011 - Lao People's Democratic Republic [Dataset]. https://microdata.fao.org/index.php/catalog/1632
    Explore at:
    Dataset updated
    Nov 25, 2020
    Dataset provided by
    Ministry of Agriculture and Forestry (MAF)
    National Statistics Centre (NSC)
    Time period covered
    2011
    Area covered
    Laos
    Description

    Abstract

    Most people in Lao PDR live in rural areas and make their living from agriculture. The Government needs detailed and up-to-date statistics on agriculture to help develop the agricultural sector and improve the welfare of the people. The Government already has statistics on the area and production of rice and other major crops, as well as livestock numbers. However, there is little information available on such things as: the different types of rice grown, the number of rice farmers, the area planted to minor crops, the use of different inputs, the use of farm machinery, farm size, farm labour, and the age/sex structure of livestock. The Lao Agricultural Census will provide these and many other data. The Lao Agricultural Census is part of a world-wide programme of agricultural censuses, which started in the 1930’s. Over 120 countries are now participating in that programme; many of these undertake agricultural censuses every ten years. The Lao Agricultural Census is the first such census undertaken in Lao PDR. It is being conducted in all 141 districts and is one of the largest and most important statistical collections ever undertaken in the country.

    Objectives of Lao Agricultural Census:

    1. To provide data on the structure of agriculture, agricultural land (land use for agricultural crops; livestock).

      Land issue: there is strong need for land use and other related data to guide land policy formulation .

    2. To obtain community-level data (at the village level) for examining the infrastructure and services available to farm holdings.

    3. To provide data to use as benchmarks for current agricultural statistics.

    4. To strengthen national capacity and provide frames for future agricultural sample surveys.

    Geographic coverage

    National coverage

    Analysis unit

    Households

    Universe

    The statistical unit was the farm household (holding), defined as an economic unit of agricultural production under single management, comprising all livestock raised and all agricultural land operated, regardless of ownership, which engages agricultural operation above certain established thresholds of land, livestock or aquaculture.

    Kind of data

    Census/enumeration data [cen]

    Sampling procedure

    Sample design and selection

    The sample for the sample farm household component was selected using two-stage sampling: a sample of villages was first selected, and then a sample of farm households was selected in each sample village. In most districts, a sample of between 16 and 22 villages was selected, with 16 farm households selected in each sample village; that is, a sample of between 256 and 352 sample farm households in each district. The more villages or farm households in a district, the bigger the sample that was taken. A smaller sample was taken in urban districts and districts containing few villages or households. In each district, the sample of villages was selected using stratified systematic probability proportional to size (PPS) sampling. A list of all villages in Lao PDR was prepared. Villages were divided into urban and rural strata, with rural strata being sampled more heavily than urban strata because of their agricultural importance. The estimated number of households in each village was used as the size measure for PPS sampling. The sample of farm households in each sample village was selected using stratified systematic random sampling based on a list of all farm households in each village prepared following the household component of the census. Altogether, 2,620 villages and 41,660 sample farm households were selected in the sample.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Four questionnaires were used in the CA 2010/2011, as follows:

    (i) a form for listing the households in the village, Form 1;

    (ii) a questionnaire for the household component, Form 4;

    (iii) a questionnaire for the farm household (holding) component, Form 5;

    (iv) a questionnaire for the village component, Form 3.

    The 2010/2011 CA census questionnaires covered all 16 core items recommended for the WCA 2010 roundn namely;

    0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

    See questionnnares in external materials tab

    Cleaning operations

    Census processing

    Completed questionnaires were returned to ACO in Vientiane for processing. Processing involved:

    • checking that the census enumeration was complete;
    • manually checking that questionnaires had been correctly filled out; coding of descriptive responses (such as crop types);
    • entering data into the computer (using keyboard methods); running computer checks to identify and correct errors; and producing tabulations of census data.

    There were nearly 1.2 million questionnaires and therefore it took some for the processing to be completed. Preliminary checking and coding was done from May-September 2011; data entry was done from June-December 2011; and error checking was done from August 2011-February 2012. Tabulations were prepared by April 2012.

    Response rate

    village component- 99 percent

    household component - 99. 4 percent

    sample farm household componen - 99.9 percent

    Sampling error estimates

    The census data presented from the sample farm household component are based on a sample and are therefore subject to sampling errors. Because of the sample design used, sampling errors on provincial and national estimates are generally quite small.

    Data appraisal

    To ensure census data quality, supervision was done at the central, provincial and district level. The data were confronted with external sources, such as the data from the previous census and current agricultural surveys. For the sampling component, statistical errors were computed.

  4. o

    Historic Redlining Scores for 2010 and 2020 US Census Tracts

    • openicpsr.org
    spss
    Updated May 25, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Helen C.S. Meier; Bruce C. Mitchell (2021). Historic Redlining Scores for 2010 and 2020 US Census Tracts [Dataset]. http://doi.org/10.3886/E141121V2
    Explore at:
    spssAvailable download formats
    Dataset updated
    May 25, 2021
    Dataset provided by
    National Community Reinvestment Coalition
    University of Michigan. Institute for Social Research. Survey Research Center
    Authors
    Helen C.S. Meier; Bruce C. Mitchell
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    The Home Owners’ Loan Corporation (HOLC) was a U.S. federal agency that graded mortgage investment risk of neighborhoods across the U.S. between 1935 and 1940. HOLC residential security maps standardized neighborhood risk appraisal methods that included race and ethnicity, pioneering the institutional logic of residential “redlining.” The Mapping Inequality Project digitized the HOLC mortgage security risk maps from the 1930s. We overlaid the HOLC maps with 2010 and 2020 census tracts for 142 cities across the U.S. using ArcGIS and determined the proportion of HOLC residential security grades contained within the boundaries. We assigned a numerical value to each HOLC risk category as follows: 1 for “A” grade, 2 for “B” grade, 3 for “C” grade, and 4 for “D” grade. We calculated a historic redlining score from the summed proportion of HOLC residential security grades multiplied by a weighting factor based on area within each census tract. A higher score means greater redlining of the census tract. Continuous historic redlining score, assessing the degree of “redlining,” as well as 4 equal interval divisions of redlining, can be linked to existing data sources by census tract identifier allowing for one form of structural racism in the housing market to be assessed with a variety of outcomes. The 2010 files are set to census 2010 tract boundaries. The 2020 files use the new census 2020 tract boundaries, reflecting the increase in the number of tracts from 12,888 in 2010, to 13,488 in 2020. Use the 2010 HRS with decennial census 2010 or ACS 2010-2019 data. As of publication (10/15/2020) decennial census 2020 data for the P1 (population) and H1 (housing) files are available from census.

  5. o

    Interwar Technology Transfer Agreements Between U.S. Firms and the Soviet...

    • openicpsr.org
    delimited
    Updated Nov 5, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Jacob Weber; Jerry Jiang (2024). Interwar Technology Transfer Agreements Between U.S. Firms and the Soviet Union: 1920-1940 [Dataset]. http://doi.org/10.3886/E210261V1
    Explore at:
    delimitedAvailable download formats
    Dataset updated
    Nov 5, 2024
    Dataset provided by
    University of California-Berkeley
    Federal Reserve Bank of New York
    Authors
    Jacob Weber; Jerry Jiang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This repository contains the data and replication files for Jiang and Weber (2024)[1] who provide data on 173 Technology Transfer Agreements signed between U.S. firms and the Soviet Union during the interwar period, along with locations of the signing firm (for 139 agreements) and the year each firm signed (for 131 agreements). This data is available both as individual agreements (listing the city each signing firm was located in) and as county-level aggregates which are then matched to demographic data from the 1930 Census and data on bank failures from the FDIC for the period 1920 to 1936 to form a yearly panel dataset used for the analysis in the paper. [1] Jiang, Jerry and Jacob Weber. “Who Collaborates with the Soviets? Financial Distress and Technology Transfer during the Great Depression.” http://dx.doi.org/10.2139/ssrn.4769743, 2024.

  6. c

    Integrated Public Use Microdata Series (IPUMS) 1850 - 1990

    • archive.ciser.cornell.edu
    Updated Feb 21, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Steven Ruggles; Mathew Sobek (2020). Integrated Public Use Microdata Series (IPUMS) 1850 - 1990 [Dataset]. http://doi.org/10.6077/j5/gsubqj
    Explore at:
    Dataset updated
    Feb 21, 2020
    Authors
    Steven Ruggles; Mathew Sobek
    Variables measured
    Individual
    Description

    This data collection contains information relating to the historical censuses of the United States that make up the Integrated Public Use Microdata Series (IPUMS) disseminated through the Minnesota Population Center at the University of Minnesota. Drawn from original census enumeration forms, the data collections in this series include samples of the American population taken from the censuses of 1850 to 1990 (excluding 1890 and 1930). Data files comprise both individual and household records and include information on a broad range of population characteristics, including fertility, nuptiality, life-course transitions, immigration, internal migration, labor-force participation, occupational structure, education, ethnicity, and household composition. Also available is IPUMS-International, a preliminary database describing 48 million persons in six countries: Colombia, France, Kenya, Mexico, United States, and Vietnam. Information about the IPUMS-International samples and variables, and other supporting documentation, are available on the IPUMS website, but researchers must apply for access to the data. (Source: ICPSR, retrieved 06/29/2011)

  7. Population of Germany 1800-2020

    • statista.com
    Updated Aug 9, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Population of Germany 1800-2020 [Dataset]. https://www.statista.com/statistics/1066918/population-germany-historical/
    Explore at:
    Dataset updated
    Aug 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Germany
    Description

    In 1800, the region of Germany was not a single, unified nation, but a collection of decentralized, independent states, bound together as part of the Holy Roman Empire. This empire was dissolved, however, in 1806, during the Revolutionary and Napoleonic eras in Europe, and the German Confederation was established in 1815. Napoleonic reforms led to the abolition of serfdom, extension of voting rights to property-owners, and an overall increase in living standards. The population grew throughout the remainder of the century, as improvements in sanitation and medicine (namely, mandatory vaccination policies) saw child mortality rates fall in later decades. As Germany industrialized and the economy grew, so too did the argument for nationhood; calls for pan-Germanism (the unification of all German-speaking lands) grew more popular among the lower classes in the mid-1800s, especially following the revolutions of 1948-49. In contrast, industrialization and poor harvests also saw high unemployment in rural regions, which led to waves of mass migration, particularly to the U.S.. In 1886, the Austro-Prussian War united northern Germany under a new Confederation, while the remaining German states (excluding Austria and Switzerland) joined following the Franco-Prussian War in 1871; this established the German Empire, under the Prussian leadership of Emperor Wilhelm I and Chancellor Otto von Bismarck. 1871 to 1945 - Unification to the Second World War The first decades of unification saw Germany rise to become one of Europe's strongest and most advanced nations, and challenge other world powers on an international scale, establishing colonies in Africa and the Pacific. These endeavors were cut short, however, when the Austro-Hungarian heir apparent was assassinated in Sarajevo; Germany promised a "blank check" of support for Austria's retaliation, who subsequently declared war on Serbia and set the First World War in motion. Viewed as the strongest of the Central Powers, Germany mobilized over 11 million men throughout the war, and its army fought in all theaters. As the war progressed, both the military and civilian populations grew increasingly weakened due to malnutrition, as Germany's resources became stretched. By the war's end in 1918, Germany suffered over 2 million civilian and military deaths due to conflict, and several hundred thousand more during the accompanying influenza pandemic. Mass displacement and the restructuring of Europe's borders through the Treaty of Versailles saw the population drop by several million more.

    Reparations and economic mismanagement also financially crippled Germany and led to bitter indignation among many Germans in the interwar period; something that was exploited by Adolf Hitler on his rise to power. Reckless printing of money caused hyperinflation in 1923, when the currency became so worthless that basic items were priced at trillions of Marks; the introduction of the Rentenmark then stabilized the economy before the Great Depression of 1929 sent it back into dramatic decline. When Hitler became Chancellor of Germany in 1933, the Nazi government disregarded the Treaty of Versailles' restrictions and Germany rose once more to become an emerging superpower. Hitler's desire for territorial expansion into eastern Europe and the creation of an ethnically-homogenous German empire then led to the invasion of Poland in 1939, which is considered the beginning of the Second World War in Europe. Again, almost every aspect of German life contributed to the war effort, and more than 13 million men were mobilized. After six years of war, and over seven million German deaths, the Axis powers were defeated and Germany was divided into four zones administered by France, the Soviet Union, the UK, and the U.S.. Mass displacement, shifting borders, and the relocation of peoples based on ethnicity also greatly affected the population during this time. 1945 to 2020 - Partition and Reunification In the late 1940s, cold war tensions led to two distinct states emerging in Germany; the Soviet-controlled east became the communist German Democratic Republic (DDR), and the three western zones merged to form the democratic Federal Republic of Germany. Additionally, Berlin was split in a similar fashion, although its location deep inside DDR territory created series of problems and opportunities for the those on either side. Life quickly changed depending on which side of the border one lived. Within a decade, rapid economic recovery saw West Germany become western Europe's strongest economy and a key international player. In the east, living standards were much lower, although unemployment was almost non-existent; internationally, East Germany was the strongest economy in the Eastern Bloc (after the USSR), though it eventually fell behind the West by the 1970s. The restriction of movement between the two states also led to labor shortages in t...

  8. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
内閣統計局 (2021). 1930 Population Census of Japan (Full-Scale): Survey Outline, Questionnaire, etc. [Dataset]. https://jdcat.jsps.go.jp/records/8396

1930 Population Census of Japan (Full-Scale): Survey Outline, Questionnaire, etc.

Explore at:
txt, text/x-shellscript, application/x-yamlAvailable download formats
Dataset updated
Sep 21, 2021
Authors
内閣統計局
Time period covered
Oct 1, 1930
Area covered
日本, Japan
Description

The 3rd Population Census. In order to clarify the state of Japan’s population and households, the population census has been conducted in Japan almost every five years.More details on the "Population Census of Japan" overall including other years can be found here: https://d-infra.ier.hit-u.ac.jp/Japanese/statistical-yb/b001.html.      The census introduced separate classifications for the type of occupation and the industry of occupation.

Search
Clear search
Close search
Google apps
Main menu