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Release Date: 2021-03-11.Release Schedule:.The data in this file come from the 2017 Economic Census. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll...Data Items and Other Identifying Records:.Number of establishments.Number of establishments in business at end of year.Sales, value of shipments, or revenue ($1,000).Total under-roof floor space (1,000 square feet).Under-roof selling space (1,000 square feet).Sales, value of shipments, or revenue per square foot of under-roof selling space (dollars).Under-roof selling space as percent of total under-roof floor space (%).Response coverage of total under-roof floor space inquiry (%).Response coverage of under-roof selling space inquiry (%)..Geography Coverage:.The data are shown for employer establishments at the U.S. and state levels. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown for 2017 NAICS codes 445110, Supermarkets and other grocery (except convenience) stores; 445120, Convenience stores; 452210, Department stores; and 452311, Warehouse clubs and supercenters. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector44/EC1744FLSPACE.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.
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.
The Population Census covers the whole of the Kingdom of Tonga, which includes the 5 Divisions and both Urban and Rural Areas.
Individuals, families and private households
All individuals in private and institutional households.
Census/enumeration data [cen]
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
Annual Resident Population Estimates by Age Group, Sex, Race, and Hispanic Origin: April 1, 2010 to July 1, 2018 // Source: U.S. Census Bureau, Population Division // The contents of this file are released on a rolling basis from December through June. // Note: 'In combination' means in combination with one or more other races. The sum of the five race-in-combination groups adds to more than the total population because individuals may report more than one race. Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. Responses of 'Some Other Race' from the 2010 Census are modified. This results in differences between the population for specific race categories shown for the 2010 Census population in this file versus those in the original 2010 Census data. For more information, see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/modified-race-summary-file-method/mrsf2010.pdf. // The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see https://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2017) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: https://www.census.gov/programs-surveys/popest.html.
This layer contains data on the number of establishments, total employment, and total annual payroll for for 20 selected 4- and 5-digit North American Industry Classification System (NAICS) codes. This is shown by county and state boundaries. The full CBP data set (available at census.gov) is updated annually to contain the most currently released CBP data. This layer is symbolized to show the total number of establishments depicted by size, and the average annual pay per employee, depicted by color.
Current Vintage: 2017
CBP Table: CB1700CBP
Data downloaded from: Census Bureau's API for County Business Patterns
Date of API call: June 1, 2019
The United States Census Bureau's County Business Patterns Program (CBP):
About this Program Data Technical Documentation News & Updates
This ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census Bureau and CBP when using this data.
Data Processing Notes: Boundaries come from the US Census Bureau TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census Bureau. These are Census Bureau boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 56 records - all US states, Washington D.C., Puerto Rico, and U.S. Island Areas Blank values represent industries where there either were no businesses in that industry and that geography OR industries where the data had to be withheld to avoid disclosing data for individual companies. Users should visit data.census.gov or Census Business Builder for more details on these withheld records.
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Summary Testadsfadsf
A broad and generalized selection of 2011-2015 US Census Bureau 2015 5-year American Community Survey housing data estimates, obtained via Census API and joined to the appropriate geometry (in this case, New Mexico Census tracts). The selection is not comprehensive, but allows a first-level characterization of housing prices, years of construction, rental information, and occupancy versus vacancy. The determination of which estimates to include was based upon level of interest and providing a manageable dataset for users.The U.S. Census Bureau's American Community Survey (ACS) is a nationwide, continuous survey designed to provide communities with reliable and timely demographic, housing, social, and economic data every year. The ACS collects long-form-type information throughout the decade rather than only once every 10 years. The ACS combines population or housing data from multiple years to produce reliable numbers for small counties, neighborhoods, and other local areas. To provide information for communities each year, the ACS provides 1-, 3-, and 5-year estimates. ACS 5-year estimates (multiyear estimates) are “period” estimates that represent data collected over a 60-month period of time (as opposed to “point-in-time” estimates, such as the decennial census, that approximate the characteristics of an area on a specific date). ACS data are released in the year immediately following the year in which they are collected. ACS estimates based on data collected from 2009–2014 should not be called “2009” or “2014” estimates. Multiyear estimates should be labeled to indicate clearly the full period of time. While the ACS contains margin of error (MOE) information, this dataset does not. Those individuals requiring more complete data are directed to download the more detailed datasets from the ACS American FactFinder website. This dataset is organized by Census tract boundaries in New Mexico. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.
A global database of Census Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.
Leverage up-to-date census data with population trends for real estate, market research, audience targeting, and sales territory mapping.
Self-hosted commercial demographic dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The global Census Data is standardized, unified, and ready to use.
Use cases for the Global Census Database (Consumer Demographic Data)
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Our consumer demographic data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.
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Historical population data (55 years)
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Note: Custom population data packages are available. Please submit a request via the above contact button for more details.
This layer shows housing units by year built by tenure (owner or renter). This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is modified every few years to change the top-end and bottom-end categories of the years.This layer is symbolized to show the predominant period that housing units were built in. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B25034, B25036, B25035, B25037 (Not all lines of ACS table B25036 are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
Annual Estimates of the Resident Population by Single Year of Age and Sex for Puerto Rico: April 1, 2010 to July 1, 2013 // File: 7/1/2013 Puerto Rico Commonwealth Population Estimates // Source: U.S. Census Bureau, Population Division // Release Date: June 2014 // Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. // For detailed information about the methods used to create the population estimates, see http://www.census.gov/popest/methodology/index.html. // Each year, the Census Bureau's Population Estimates Program (PEP) utilizes current data on births, deaths, and migration to calculate population change since the most recent decennial census, and produces a time series of estimates of population. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2013) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population Estimates Program provides additional information including historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: http://www.census.gov/popest/index.html.
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This is a copy of the statewide Census Block Group GIS Tiger file. It is used to determine if a block group (BG) is DAC or not by adding ACS (American Community Survey) Median Household Income (MHI) data at the BG level. The IRWM web based DAC mapping tool uses this GIS layer. Every year this table gets updated after ACS publishes their updated MHI estimates. Created by joining ACS 2016-2020 5 year estimates to the Census 2020 Block Group feature class. The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block Groups (BGs) are defined before tabulation block delineation and numbering, but are clusters of blocks within the same census tract that have the same first digit of their 4-digit census block number from the same decennial census. For example, Census 2000 tabulation blocks 3001, 3002, 3003,.., 3999 within Census 2000 tract 1210.02 are also within BG 3 within that census tract. Census 2000 BGs generally contained between 600 and 3,000 people, with an optimum size of 1,500 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where the PSAP participant declined to delineate BGs or where the Census Bureau could not identify any local PSAP participant. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within census tract. Within the standard census geographic hierarchy, BGs never cross county or census tract boundaries, but may cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. BGs have a valid code range of 0 through 9. BGs coded 0 were intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. For Census 2000, rather than extending a census tract boundary into the Great Lakes or out to the U.S. nautical three-mile limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore. The Census Bureau assigned a default census tract number of 0 and BG of 0 to these offshore, water-only areas not included in regularly numbered census tract areas.
The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.3, dated April 13, 2022. This data set was not produced by DWR. Data were originally developed and supplied by US Bureau of Census. DWR makes no warranties or guarantees - either expressed or implied - as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to the official GIS steward as available and appropriate at gis@water.ca.gov.
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Key Table Information.Table Title.Island Areas: NAPCS Statistics for American Samoa, Commonwealth of the Northern Mariana Islands, Guam, Puerto Rico, and U.S. Virgin Islands: 2022.Table ID.ISLANDAREASNAPCS2022.IA2200NAPCS01.Survey/Program.Economic Census of Island Areas.Year.2022.Dataset.ECNIA Economic Census of Island Areas.Release Date.2024-12-19.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.2022 Economic Census of Island Areas tables are released on a flow basis from June through December 2024.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in Puerto Rico, the U.S. Virgin Islands, Guam, the Commonwealth of the Northern Mariana Islands, or America Samoa, have paid employees, and are classified in one of eighteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Sponsor.U.S. Department of Commerce.Methodology.Data Items and Other Identifying Records.Number of establishmentsTotal sales, value of shipments, or revenue of establishments with the NAPCS collection code ($1,000)Sales, value of shipments, or revenue ($1,000)NAPCS collection code sales, value of shipments, or revenue as % of total sales, value of shipments, or revenue of establishments with the NAPCS collection code (%)NAPCS collection code sales, value of shipments, or revenue as % of industry sales, value of shipments, or revenue (%)Range indicating imputed percentage of total sales, value of shipments, or revenueThe data are shown for NAPCS services codes.Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the Economic Census of Island Areas are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed..Geography Coverage.The data are shown for employer establishments and firms that vary by industry:At the Territory level for American SamoaAt the Territory level for GuamAt the Territory level for the Commonwealth of the Northern Mariana IslandsAt the Territory level for Puerto RicoAt the Territory level for US Virgin IslandsFor information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown for American Samoa, Guam, the Commonwealth of the Northern Mariana Islands, Puerto Rico, and US Virgin Islands at the 2- through 4-digit 2022 NAICS code level.For information about NAICS, see Economic Census Code Lists..Sampling.The Economic Census of Island Areas is a complete enumeration of establishments located in the islands (i.e., all establishments on the sampling frame are included in the sample). Therefore, the accuracy of tabulations is not affected by sampling error..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0044).The primary method of disclosure avoidance protection is noise infusion. Under this method, the quantitative data values such as sales or payroll for each establishment are perturbed prior to tabulation by applying a random noise multiplier (i.e., factor). Each establishment is assigned a single noise factor, which is applied to all its quantitative data value. Using this method, most published cell totals are perturbed by at most a few percentage points.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. For more information on disclosure avoidance, see Methodology for the 2022 Economic Census- Island Areas..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, see Methodology for the 2022 Economic Census- Island Areas.For more information about survey questionnaires, Primary Business Activity/NAICS codes, and NAPCS codes, see Economic Census Technical Documentation..Weights.Because the Economic Census of Island Areas is a complete enumeration, there is no sample weighting..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this ta...
The Census data API provides access to the most comprehensive set of data on current month and cumulative year-to-date imports using the Hi-Tech classification system. The Hi-Tech endpoint in the Census data API also provides value, shipping weight, and method of transportation totals at the district level for all U.S. trading partners. The Census data API will help users research new markets for their products, establish pricing structures for potential export markets, and conduct economic planning. If you have any questions regarding U.S. international trade data, please call us at 1(800)549-0595 option #4 or email us at eid.international.trade.data@census.gov.
The Juvenile Residential Facility Census (JRFC) collected basic information on facility characteristics, including size, structure, security arrangements, and ownership. It also collected information on the use of bedspace in the facility to indicate whether the facility was experiencing crowding. The JRFC included questions about the type of facility, such as detention center, training school, ranch, or group home. This information was complemented by a series of questions about other residential services provided by the facility, such as independent living, foster care, or other arrangements. In 2000, the JRFC used four modules to collect information on the physical health services, educational services, substance abuse treatment, and mental health treatment provided to youth in these facilities. While not evaluating the effectiveness or quality of these services, the JRFC gathered important information about the youth the services were directed toward and how the services were provided. The census indicated the use of screenings or tests conducted to determine counseling, education, health, or substance abuse needs, and also examined prominent issues about conditions of confinement, including the restraint of youth and improper absences from the facility. Congress requires the Office of Juvenile Justice and Delinquency Prevention (OJJDP) to report annually on the number of deaths of juveniles in custody; JRFC collected information on such deaths for the one-year period just prior to the census reference date. The census reference date was the fourth Wednesday in October.
BAS Submissions Read Me
This shapefile includes the annexation polygons that the Office of Financial Management (OFM) has sent to the Census Bureau since March 2020 as part of the Boundary and Annexation Survey (BAS). The Census Bureau uses these polygons to update Washington State’s city limits. Field names follow Census BAS guidelines, and an outline of relevant field names is below. More information about BAS can be found here: https://www.census.gov/programs-surveys/bas.html
The polygons include the quarterly annexations and other boundary corrections that effect the Census city boundaries, as well as several county boundary adjustments for King, Kittitas, Pierce, Spokane, and Stevens County. The annexation polygons were originally created by Washington’s Department of Transportation, and then edited by OFM to align with the latest BAS city boundary file available. These polygons to not follow the strict legal description of the annexation, as their intent is to make clear delineations between jurisdictions for population allocation. The following are the main differences between BAS annexation polygons and the originals:
<!--· The edges and vertices of polygons are snapped first to contiguous Census city limits and then to county parcels
<!--·
Where an annexation moves a city boundary to be
either adjacent or across a right of way, the polygon is drawn to the
centerline of the right of way
<!--· Annexations that are only include a right of way are often omitted, as they will not change the Census Bureau boundary
This file is updated quarterly. For questions or for data from earlier years, please contact Nate Chase nate.chase@ofm.wa.gov.
Relevant Field Names:
<!--·
CHNG_TYPE- Type of area update. A is
annexation, D is deannexation, and B is a boundary correction
which is a newly discovered boundary discrepancy
<!--· Eff_date- the local effective date
<!--· AUTHYPE- O is ordinance or resolution; X is for boundary correction; L signifies a county boundary correction
<!--· DOCU- the legal ordinance or resolution for the annexation. If there is a blank, then the entry is a correction polygon.
<!--· RELATE- Changing from in or out of jurisdiction
<!--· JUSTIFY- OFM’s reason for submitting the change polygon
<!--· A_Date- this is the date that OFM approves the annexation. OFM cannot legally approve annexations until all state requirements are met. The approval date cannot be earlier than the effective date, but it can be on the same day. OFM’s population determinations use the approval date of annexations. BAS submissions are only submitted after this date.
<!--· Source- The file in which the change polygon was originally submitted. Examples:
o
2022_Q1 submitted
in December 2021
o 2022_Q2 submitted in March 2022
o
2022_Q3 submitted
in June 2022
o
2022_Q4 submitted
in September 2022
This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 28, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.
VITAL SIGNS INDICATOR
Poverty (EQ5)
FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit
LAST UPDATED
January 2023
DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.
DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000
U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002
CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov
METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.
For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).
For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.
For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.
American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.
To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.
Annual Housing Unit Estimates for the United States, States, and Counties // Source: U.S. Census Bureau, Population Division // Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 housing units due to the Count Question Resolution program and geographic program revisions. For the housing unit estimates methodology statement, see http://www.census.gov/popest/methodology/index.html.// Each year, the Census Bureau's Population and Housing Unit Estimates Program utilizes current data on new residential construction, placements of manufactured housing, and housing unit loss to calculate change in the housing stock since the most recent decennial census, and produces a time series of housing unit estimates.. The annual time series of estimates begins with the most recent decennial census data and extends to the vintage year. The vintage year (e.g., V2015) refers to the final year of the time series. The reference date for all estimates is July 1, unless otherwise specified. With each new issue of estimates, the Census Bureau revises estimates for years back to the last census. As each vintage of estimates includes all years since the most recent decennial census, the latest vintage of data available supersedes all previously produced estimates for those dates. The Population and Housing Unit Estimates Program provides additional information including population estimates, historical and intercensal estimates, evaluation estimates, demographic analysis, and research papers on its website: http://www.census.gov/popest/index.html.
Health indicators, two-year period estimates, by age group and sex, Canada, provinces, territories, census metropolitan areas and influence zones.
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Household type, Education, Disability, Language, Computer/Internet Use, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: Census Tracts. Current Vintage: 2019-2023. ACS Table(s): DP02. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.
The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block Groups (BGs) are defined before tabulation block delineation and numbering, but are clusters of blocks within the same census tract that have the same first digit of their 4-digit census block number from the same decennial census. For example, Census 2000 tabulation blocks 3001, 3002, 3003,.., 3999 within Census 2000 tract 1210.02 are also within BG 3 within that census tract. Census 2000 BGs generally contained between 600 and 3,000 people, with an optimum size of 1,500 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where the PSAP participant declined to delineate BGs or where the Census Bureau could not identify any local PSAP participant. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within census tract. Within the standard census geographic hierarchy, BGs never cross county or census tract boundaries, but may cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. BGs have a valid code range of 0 through 9. BGs coded 0 were intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. For Census 2000, rather than extending a census tract boundary into the Great Lakes or out to the U.S. nautical three-mile limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore. The Census Bureau assigned a default census tract number of 0 and BG of 0 to these offshore, water-only areas not included in regularly numbered census tract areas.
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Release Date: 2021-03-11.Release Schedule:.The data in this file come from the 2017 Economic Census. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments of firms with payroll...Data Items and Other Identifying Records:.Number of establishments.Number of establishments in business at end of year.Sales, value of shipments, or revenue ($1,000).Total under-roof floor space (1,000 square feet).Under-roof selling space (1,000 square feet).Sales, value of shipments, or revenue per square foot of under-roof selling space (dollars).Under-roof selling space as percent of total under-roof floor space (%).Response coverage of total under-roof floor space inquiry (%).Response coverage of under-roof selling space inquiry (%)..Geography Coverage:.The data are shown for employer establishments at the U.S. and state levels. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown for 2017 NAICS codes 445110, Supermarkets and other grocery (except convenience) stores; 445120, Convenience stores; 452210, Department stores; and 452311, Warehouse clubs and supercenters. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector44/EC1744FLSPACE.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.