Census tracts are designated as urban, rural center, or rural through SB 1000 analysis. These designations are being used for the REV 2.0 and Community Charging in Urban Areas GFOs. Rural centers are contiguous urban census tracts with a population of less than 50,0000. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Rural communities are census tracts where less than 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria. Urban communities are contiguous urban census tracts with a population of 50,000 or greater. Urban census tracts are tracts where at least 10 percent of the tract’s land area is designated as urban by the Census Bureau using the 2020 urbanized area criteria.Data Dictionary:OBJECTID: Unique IDSTATEFP: State FIPS CodeCOUNTYFP: County FIPS CodeTRACTCE: Census Tract IDGEOID: Geographic IdentifierName: Census Tract ID Name (short)NAMELSAD: Census Tract ID Name (long)ALAND: Land Area (square meters)AWATER: Water Area (square meters)DAC: Whether or not a census tract is a disadvantaged community as defined by SB 535 and designated by CalEPA using CalEnviroScreen 4.0 (May 2022 update)Income_Group: Whether or not a census tract is low-, middle-, or high-income as defined by AB 1550 and designated by CARB and the CEC (June 2023 update)Urban_Rural_RuralCenter: Whether or not a census tract is urban, rural, or rural center as defined and designated by the CEC through the SB 1000 Assessment (2024 update)PerCap_100k_L2DCFC: Number of public Level 2 and DC fast chargers per 100,000 people in a census tractDAC_andor_LIC: Whether or not a census tract is a disadvantaged or low-income community as defined by SB 535 and AB 1550 and designated by CalEPA and CARBUCC_eligible: Whether or not the census tract is an eligible area for the Community Charging in Urban Areas GFO. For a site to be eligible, it must be in a census tract that is either a disadvantaged or low-income community, and urban, and has below the state average for per capita public Level 2 and DC fast chargers as defined by the CEC.REV2_eligible: Whether or not the census tract is an eligible area for the Rural Electric Vehicle Charging 2.0 GFO. For a site to be eligible, it must be in a rural or rural center census tract as defined by the CEC.Shape_Area: Census tract shape area (square meters)Shape_Length: Census tract shape length (square meters)

description: Census Tract Data - Census 2000 This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic entities include blocks, blockgroups and tracts. Tiger line files are the source of the geometry representing the Census blocks. Attributes include total population counts, racial/ethnic, and poverty/income information. Racial/ethnic classifications are represented in units of blocks, blockgroups and tracts. Poverty and income data are represented in units of blockgroups and tracts. Percentages of each racial/ethnic group have been calculated from the population counts. Total Minority counts and percentages were compiled from each racial/ethnic non-white category. Categories compiled to create the Total Minority count includes the following: African American, Asian, American Indian, Pacific Islander, White Hispanic, Other and all mixed race categories. The percentage poverty attribute represents the percent of the population living at or below poverty level. The per capita income attribute represents the sum of all income within the geographic entity, divided by the total population of that entity. Special fields designed to be used for EJ analysis have been derived from the PL data and include the following: Percentage difference of block, blockgroup and total minority from the state and county averages, percentile rank for each percent total minority within state and county entities. Food Desert Locator Documenation The Healthy Food Financing Initiative (HFFI) Working Group defines a food desert as a low-income census tract where a substantial number or share of residents has low access to a supermarket or large grocery store. To qualify as low-income, census tracts must meet the Treasury Department's New Markets Tax Credit (NMTC) program eligibility criteria. Furthermore, to qualify as a food desert tract at least 33% of the tract's population (or a minimum of 500 people) must have low access to a supermarket or large grocery store. Low access to a healty food retail outlet is defined as more than 1 mile from a supermarket or large grocery store in urban ares and as more than 10 miles in rural areas. The Food Desert Locator includes characteristics only for census tracts that qualify as food deserts. All store data come from the 2006 directory of stores, and all population and household data come from the 2000 Census of Population and Housing. For the 140 urban census tracts for which grid-level data are not available, all people in the tract are assumed to have low-access to a supermarket or large grocery store.; abstract: Census Tract Data - Census 2000 This data layer represents Census 2000 demographic data derived from the PL94-171 redistricting files and SF3. Census geographic entities include blocks, blockgroups and tracts. Tiger line files are the source of the geometry representing the Census blocks. Attributes include total population counts, racial/ethnic, and poverty/income information. Racial/ethnic classifications are represented in units of blocks, blockgroups and tracts. Poverty and income data are represented in units of blockgroups and tracts. Percentages of each racial/ethnic group have been calculated from the population counts. Total Minority counts and percentages were compiled from each racial/ethnic non-white category. Categories compiled to create the Total Minority count includes the following: African American, Asian, American Indian, Pacific Islander, White Hispanic, Other and all mixed race categories. The percentage poverty attribute represents the percent of the population living at or below poverty level. The per capita income attribute represents the sum of all income within the geographic entity, divided by the total population of that entity. Special fields designed to be used for EJ analysis have been derived from the PL data and include the following: Percentage difference of block, blockgroup and total minority from the state and county averages, percentile rank for each percent total minority within state and county entities. Food Desert Locator Documenation The Healthy Food Financing Initiative (HFFI) Working Group defines a food desert as a low-income census tract where a substantial number or share of residents has low access to a supermarket or large grocery store. To qualify as low-income, census tracts must meet the Treasury Department's New Markets Tax Credit (NMTC) program eligibility criteria. Furthermore, to qualify as a food desert tract at least 33% of the tract's population (or a minimum of 500 people) must have low access to a supermarket or large grocery store. Low access to a healty food retail outlet is defined as more than 1 mile from a supermarket or large grocery store in urban ares and as more than 10 miles in rural areas. The Food Desert Locator includes characteristics only for census tracts that qualify as food deserts. All store data come from the 2006 directory of stores, and all population and household data come from the 2000 Census of Population and Housing. For the 140 urban census tracts for which grid-level data are not available, all people in the tract are assumed to have low-access to a supermarket or large grocery store.

The Federal Housing Enterprises Financial Safety and Soundness Act of 1992 (Safety and Soundness Act) provides for the establishment of single-family and multifamily goals each year, including a single-family purchase money mortgage goal for families residing in low-income areas. The Safety and Soundness Act defines "low-income area" as: (a) census tracts or block numbering areas in which the median income does not exceed 80 percent of area median income (AMI), (b) families with income not greater than 100 percent of AMI who reside in minority census tracts, and (c) families with income not greater than 100 percent of AMI who reside in designated disaster areas. A “minority census tract” is a census tract that has a minority population of at least 30 percent and a median income of less than 100 percent of the AMI. Census tract level data identifying these areas are available below for 2010 and 2011 based on 2000 Census tract geography, for 2012 through 2021 based on 2010 Census tract geography, and for 2022 and subsequent years based on 2020 Census tract geography.​As in the previous underserved area definition, low-income area and minority census tract definitions are based on prior year metropolitan area definitions as determined by OMB. Designated disaster areas are identified by FHFA based on the three most recent years' declarations by the Federal Emergency Management Agency​ (FEMA), where individual assistance payments were authorized by FEMA. Each file includes a map of the counties identified as designated disaster areas and a description of the data layout, also available separately.To learn more about the Underserver Areas Dataset visit: Underserved Areas Data | Federal Housing Finance Agency (fhfa.gov), for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Underserved Areas DataDate of Coverage: 10/2023 - 09/2024Last Updated: 11/2023

This story is about the number and percentage of linear miles of newly constructed sidewalks and urban trails that lie within census tracts with no leisure-time physical activity among adults aged 18 years or older

The U.S. Housing and Urban Development (HUD) maintains data for Qualified Census Tracts (QCT). Low-Income Housing Tax Credit Qualified Census Tracts must have 50 percent of households with incomes below 60 percent of the Area Median Gross Income (AMGI) or have a poverty rate of 25 percent or more. This layer contains all Census Tracts in LA County, with QCT marked as "Yes" and tracts that are not QCT as "No."This layer is an export of the 2025 data. Source data is updated annually. Data are at the 2020 census tract geography level. These have been joined to Supervisorial Districts 2021 and SPAs 2022, based on a "majority in" spatial join.To learn more: https://www.huduser.gov/portal/datasets/qct.htmlFor more information, please contact egis@isd.lacounty.gov.

USA Census Block Groups (CBG) for Urban Search and Rescue. This layer can be used for search segment planning. Block groups generally contain between 600 and 5,000 people and the boundaries generally follow existing roads and waterways. The field segment_designation is the last 6 digits of the unique identifier and matches the field in the SARCOP Segment layer.Data download date: August 12, 2021Census tables: P1, P2, P3, P4, H1, P5, HeaderDownloaded from: Census FTP siteProcessing Notes:Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the 2020 TIGER/Line Geodatabases. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". The following alterations have been made to the tabular data:Joined all tables to create one wide attribute table:P1 - RaceP2 - Hispanic or Latino, and not Hispanic or Latino by RaceP3 - Race for the Population 18 Years and OverP4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and OverH1 - Occupancy Status (Housing)P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)HeaderAfter joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGRECNO, GEOVAR, GEOCOMP, LSADC, and BLOCK.GEOCOMP was renamed to GEOID and moved be the first column in the table, the original GEOID was dropped.Placeholder fields for future legislative districts have been dropped: CD118, CD119, CD120, CD121, SLDU22, SLDU24, SLDU26, SLDU28, SLDL22, SLDL24 SLDL26, SLDL28.P0020001 was dropped, as it is duplicative of P0010001. Similarly, P0040001 was dropped, as it is duplicative of P0030001.In addition to calculated fields, County_Name and State_Name were added.The following calculated fields have been added (see long field descriptions in the Data tab for formulas used): PCT_P0030001: Percent of Population 18 Years and OverPCT_P0020002: Percent Hispanic or LatinoPCT_P0020005: Percent White alone, not Hispanic or LatinoPCT_P0020006: Percent Black or African American alone, not Hispanic or LatinoPCT_P0020007: Percent American Indian and Alaska Native alone, not Hispanic or LatinoPCT_P0020008: Percent Asian alone, Not Hispanic or LatinoPCT_P0020009: Percent Native Hawaiian and Other Pacific Islander alone, not Hispanic or LatinoPCT_P0020010: Percent Some Other Race alone, not Hispanic or LatinoPCT_P0020011: Percent Population of Two or More Races, not Hispanic or LatinoPCT_H0010002: Percent of Housing Units that are OccupiedPCT_H0010003: Percent of Housing Units that are VacantPlease note these percentages might look strange at the individual block group level, since this data has been protected using differential privacy.* *To protect the privacy and confidentiality of respondents, data has been protected using differential privacy techniques by the U.S. Census Bureau. This means that some individual block groups will have values that are inconsistent or improbable. However, when aggregated up, these issues become minimized. The pop-up on this layer uses Arcade to display aggregated values for the surrounding area rather than values for the block group itself.Download Census redistricting data in this layer as a file geodatabase.Additional links:U.S. Census BureauU.S. Census Bureau Decennial CensusAbout the 2020 Census2020 Census2020 Census data qualityDecennial Census P.L. 94-171 Redistricting Data Program

This layer represents USDA Food Access Research Atlas data at the census tract geography. Low Income is defined as tracts with a poverty rate of 20% or higher, or tracts with median family income less than 80% of median family income of the state or metropolitan area. Low Access is defined as tracts where a significant number or share of residents is more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket.http://www.ers.usda.gov/data-products/food-access-research-atlas/go-to-the-atlas.aspxFood accessLimited access to supermarkets, supercenters, grocery stores, or other sources of healthy and affordable food may make it harder for some Americans to eat a healthy diet. There are many ways to measure food store access for individuals and for neighborhoods, and many ways to define which areas are food deserts—neighborhoods that lack healthy food sources. Most measures and definitions take into account at least some of the following indicators of access:Accessibility to sources of healthy food, as measured by distance to a store or by the number of stores in an area.Individual-level resources that may affect accessibility, such as family income or vehicle availability.Neighborhood-level indicators of resources, such as the average income of the neighborhood and the availability of public transportation.In the Food Access Research Atlas, several indicators are available to measure food access along these dimensions. For example, users can choose alternative distance markers to measure low access in a neighborhood, such as the number and share of people more than half a mile to a supermarket or 1 mile to a supermarket. Users can also view other census-tract-level characteristics that provide context on food access in neighborhoods, such as whether the tract has a high percentage of households far from supermarkets and without vehicles, individuals with low income, or people residing in group quarters.Low-income neighborhoodsThe criteria for identifying a census tract as low income are from the Department of Treasury’s New Markets Tax Credit (NMTC) program. This program defines a low-income census tract as any tract where:The tract’s poverty rate is 20 percent or greater; orThe tract’s median family income is less than or equal to 80 percent of the State-wide median family income; orThe tract is in a metropolitan area and has a median family income less than or equal to 80 percent of the metropolitan area's median family income.Low-access census tractsIn the Food Access Research Atlas, low access to healthy food is defined as being far from a supermarket, supercenter, or large grocery store ("supermarket" for short). A census tract is considered to have low access if a significant number or share of individuals in the tract is far from a supermarket.In the original Food Desert Locator, low access was measured as living far from a supermarket, where 1 mile was used in urban areas and 10 miles was used in rural areas to demarcate those who are far from a supermarket. In urban areas, about 70 percent of the population was within 1 mile of a supermarket, while in rural areas over 90 percent of the population was within 10 miles (see Access to Affordable and Nutritious Food: Updated Estimates of Distance to Supermarkets Using 2010 Data). Updating the original 1- and 10-mile low-access measure shows that an estimated 18.3 million people in these low-income and low-access census tracts were far from a supermarket in 2010.Three additional measures of food access based on distance to a supermarket are provided in the Atlas:One additional measure applies a 0.5-mile demarcation in urban areas and a 10-mile distance in rural areas. Using this measure, an estimated 52.5 million people, or 17 percent of the U.S. population, have low access to a supermarket;A second measure applies a 1.0-mile demarcation in urban areas and a 20-mile distance in rural areas. Under this measure, an estimated 16.5 million people, or 5.3 percent of the U.S. population, have low access to a supermarket; andA slightly more complex measure incorporates vehicle access directly into the measure, delineating low-income tracts in which a significant number of households are located far from a supermarket and do not have access to a vehicle. This measure also includes census tracts with populations that are so remote, that, even with a vehicle, driving to a supermarket may be considered a burden due to the great distance. Using this measure, an estimated 2.1 million households, or 1.8 percent of all households, in low-income census tracts are far from a supermarket and do not have a vehicle. An additional 0.3 million people are more than 20 miles from a supermarket.For each of the first three measures that are based solely on distance, a tract is designated as low access if the aggregate number of people in the census tract with low access is at least 500 or the percentage of people in the census tract with low access is at least 33 percent. For the final measure using vehicle availability, a tract is designated as having low vehicle access if at least one of the following is true:at least 100 households are more than ½ mile from the nearest supermarket and have no access to a vehicle; orat least 500 people or 33 percent of the population live more than 20 miles from the nearest supermarket, regardless of vehicle access.Methods used to assess distance to the nearest supermarket are the same for each of these measures. First, the entire country is divided into ½-km square grids, and data on the population are aerially allocated to these grids (see Access to Affordable and Nutritious Food: Updated Estimates of Distance to Supermarkets Using 2010 Data). Then, distance to the nearest supermarket is measured for each grid cell by calculating the distance between the geographic center of the ½-km square grid that contains estimates of the population (number of people and other subgroup characteristics) and the center of the grid with the nearest supermarket.Once the distance to the nearest supermarket is calculated for each grid cell, the estimated number of people or housing units that are more than 1 mile from a supermarket in urban tracts, or 10 miles in rural census tracts, is aggregated at the census-tract level (and similarly for the alternative distance markers). A census tract is considered rural if the population-weighted centroid of that tract is located in an area with a population of less than 2,500; all other tracts are considered urban tracts.Food desertsThe Food Access Research Atlas maps census tracts that are both low income (li) and low access (la), as measured by the different distance demarcations. This tool provides researchers and other users multiple ways to understand the characteristics that can contribute to food deserts, including income level, distance to supermarkets, and vehicle access.Additional tract-level indicators of accessVehicle availabilityA tract is identified as having low vehicle availability if more than 100 households in the tract report having no vehicle available and are more than 0.5 miles from the nearest supermarket. This corresponds closely to the 80th percentile of the distribution of the number of housing units in a census tract without vehicles at least 0.5 miles from a supermarket (the 80th percentile value was 106 housing units). This means that about 20 percent of all census tracts had more than 100 housing units that were 0.5 miles from a supermarket and without a vehicle. This indicator was applied to both urban and rural census tracts.Overall, 8.8 percent of all housing units in the United States do not have a vehicle, and 4.2 percent of all housing units are at least 0.5 mile from a store and without a vehicle. Vehicle availability is defined in the American Community Survey as the number of passenger cars, vans, or trucks with a capacity of 1-ton or less kept at the home and available for use by household members. The number of available vehicles includes those vehicles leased or rented for at least 1 month, as well as company, police, or government vehicles that are kept at home and available for non-business use.Whether a vehicle is available to a household for private use is an important additional indicator of access to healthy and affordable food. For households living far from a supermarket or large grocery store, access to a private vehicle may make accessing these retailers easier than relying on public or alternative means of transportation.Group quarters populationUsers may be interested in highlighting tracts with large shares of people living in group quarters. Group quarters are residential arrangements where an entity or organization owns and provides housing (and often services) for individuals residing in these buildings. This includes college dormitories, military quarters, correctional facilities, homeless shelters, residential treatment centers, and assisted living or skilled nursing facilities. These living arrangements frequently provide dining and food retail solely for their residents. While individuals living in these areas may appear to be far from a supermarket or grocery store, they may not truly experience difficulty accessing healthy and affordable food. Tracts in which 67 percent of individuals or more live in group quarters are highlighted.General tract characteristicsPopulation, tract totalGeographic level: census tractYear of data: 2010Definition: Total number of individuals residing in a tract.Data sources: Data are from the 2012 report, Access to Affordable and Nutritious Food: Updated Estimates of Distances to Supermarkets Using 2010 Data. Population data are reported at the block level from the 2010 Census of Population and Housing. These data were aerially allocated down to ½-kilometer-square grids across the United States.Low-income tractGeographic level: census tractYear of data: 2010Definition: A tract with either a poverty rate of 20

Release Date: 2023-05-11.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY23-0262)...Key Table Information:.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series)...Data Items and Other Identifying Records:.Data include estimates on:.Number of nonemployer firms (firms without paid employees). Sales and receipts of nonemployer firms (reported in $1,000s of dollars)...These data are aggregated by the following demographic classifications of firm for:.All firms. Classifiable (firms classifiable by sex, ethnicity, race, and veteran status). . Sex. Female. Male. Equally male/female. . Ethnicity. Hispanic. Equally Hispanic/non-Hispanic. Non-Hispanic. . Race. White. Black or African American. American Indian and Alaska Native. Asian. Native Hawaiian and Other Pacific Islander. Minority (Firms classified as any race and ethnicity combination other than non-Hispanic and White). Equally minority/nonminority. Nonminority (Firms classified as non-Hispanic and White). . Veteran Status (defined as having served in any branch of the U.S. Armed Forces). Veteran. Equally veteran/nonveteran. Nonveteran. . . . Unclassifiable (firms not classifiable by sex, ethnicity, race, and veteran status). ...The data are also shown for the urban or rural classification of the firm:. Urban. Rural. Not classified...Data Notes:.. Business ownership is defined as having 51 percent or more of the stock or equity in the business. Data are provided for firms owned equally (50% / 50%) by men and women, by Hispanics and non-Hispanics, by minorities and nonminorities, and by veterans and nonveterans. Firms not classifiable by sex, ethnicity, race, and veteran status are counted and tabulated separately.. The detail may not add to the total or subtotal because a Hispanic firm may be of any race; because a firm could be tabulated in more than one racial group; or because the number of nonemployer firm's data are rounded.. Firms are classified as urban or rural based on the population of the Census block of its physical location or mailing address. Firms without an assigned Census block are designated as "Not classified". Firms with a physical location or mailing address on a Census block with at least 2,500 inhabitants are classified as "Urban". All other firms are classified as "Rural"....Industry and Geography Coverage:.The data are shown for the total for all sectors (00) and 2-digit NAICS code levels for:..United States. States and the District of Columbia. Metropolitan Statistical Areas...Data are also shown for the 3-digit NAICS code for:..United States...Data are excluded for the following NAICS industries:.Crop and Animal Production (NAICS 111 and 112). Rail Transportation (NAICS 482). Postal Service (NAICS 491). Monetary Authorities-Central Bank (NAICS 521). Funds, Trusts, and Other Financial Vehicles (NAICS 525). Management of Companies and Enterprises (NAICS 55). Private Households (NAICS 814). Public Administration (NAICS 92). Industries Not Classified (NAICS 99)...For more information about NAICS, see NAICS Codes & Understanding Industry Classification Systems. For information about geographies used by economic programs at the Census Bureau, see Economic Census: Economic Geographies...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/abs/data/2019/AB1900NESD05.zip...API Information:.Nonemployer Demographic Statistics data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2019/absnesd.html...Symbols:. D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals. 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.. N - Not available or not comparable. X - Not applicable..The following symbols are used to identify the level of noise applied to the data:. G - Low noise: The cell value was changed by less than 2 percent by the application of noi...

The US Department of Housing and Urban Development (HUD) designates Qualified Census Tracts (QCTs) for purposes of the Low-Income Housing Tax Credit (LIHTC) program. The LIHTC program is defined in Section 42 of the Internal Revenue Code of 1986. The LIHTC is a tax incentive intended to increase the availability of affordable rental housing. The LIHTC statute provides two criteria for QCT eligibility. A census tract must have either: 1) a poverty rate of at least 25 percent; or 2) 50 percent or more of its householders must have incomes below 60 percent of the area median household income. The area corresponds to a metropolitan or a non-metropolitan area. Further, the LIHTC statute requires that no more than 20 percent of the metropolitan area population reside within designated QCTs (This limit also applies collectively to the nonmetropolitan counties in each state). Thus, it is possible for a tract to meet one or both of the above criteria, but not be designated as a QCT. With respect to the census tracts, the Census Bureau defines them in cooperation with local authorities every ten years for the purposes of the decennial census and, following a public comment period, has recently completed defining tract boundaries for the 2010 Census. Note that when census tract boundaries are set, they remain unchanged for the next decade. Thus, tract boundaries will not be changed until the 2020 Decennial Census.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/BusinessEconomy/MD_HousingDesignatedAreas/FeatureServer/1

Abstract

This survey provides information on household income and expenditure to be able to measure the levels and changes in the living condition of the people and to observe the consumption patterns .

Key objectives of the survey - To identify the income patterns in Urban, Rural and Estate Sectors & provinces. - To identify the income patterns by income levels. - Average consumption of food items and non food items - Expenditure patterns by sector and by different income levels.

Geographic coverage

National coverage.

Analysis unit

Household, Individuals

Universe

For this survey a sample of buildings and the occupants therein was drawn from the whole island

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design A two stage stratified random sample design was used in this survey. Bach domain for which separate estimates were required was made a separate stratum. As such each sector (Urban, Rural, Estate) within each district was considered as a separate stratum.

Sample Size In this design the first stage units (FSU) were the census blocks prepared at the 1981 Census of Population and the second stage units (SSU) were the housing units. It was decided to select 10 housing units from each selected census block. Thus, a first stage sample of about 2,500 census blocks have to be selected from the entire island.

Sample Allocation and Method of Selection The allocation of 2,500 census blocks to each district was made proportional. to the square root of the population· ( as at 1981 Census ) in that district. These values have been rounded to multiples of twelve. ( Refer page 5 of the final report attached in the external resources section) It was decided to over sample the urban sector in each district in comparison to the rural and estate sectors with the objective of allocating roughly by one-third of the total sample. Allocation between the rural and estate sectors in each district was proportional to 1981 population. Within each stratum, the assigned number of FSU's were selected with probability proportionate to size (using the Census or adjusted housing unit counts ) with replacement. The lists of census units prepared for the Census of Population and Housing 1981, of each selected block were updated to include new ·housing units and to exclude ones which are no longer in existence. This updating operation was also staggered over a period of twelve months starting from May 1990 to April 1991. For each FSU, updating was done about one month prior to the scheduled interviewing.

Sampling deviation

Non-Response Of a sample of 25080 housing units selected only 19,401 households were covered in the survey. Northern and Eastern provinces were excluded in the survey due to the prevailing conditions in the area.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires

The survey schedule was designed to collect data on household basis and separate schedules were used for each household (identified according to the definition of the household) within the housing units selected for the survey. The survey Schedule consists of three main sections .

       1. Demographic section 
       2. Expenditure
       3. Income

The demographic characteristics and usual activities of the inmates belonging to the household are reported in the Demographic section of the schedule and close relatives temporarily living away are also listed in the section. Expenditure section has two sub sections to report food and non-food consumption data separately. Expenditure incurred on their own decisions by boarders and servants are recorded in the sub section under the expenditure section. The income has seven sub sections categorized according to the main sources of income.

Response rate

Out of 19401 households 95 percent the households were fully completed while 0.2 percent have refused. Sector wise completion rates show that Urban sector had 93 percent, Rural sector 96 percent and the Estate sector 97 percent.

Sampling error estimates

Refer the pages 7 to 10 of the final report attached in the External Resources section.

This dataset contains segment-level data for construction of sidewalks and urban trails within the full purpose jurisdiction of the City of Austin beginning in calendar year 2017. This dataset supports SD23 performance measure HE.C.5: Number and percentage of linear miles of newly constructed sidewalks and urban trails that lie within census tracts with no low levels of leisure-time physical activity among adults aged 18 years or older. View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/22ei-wafp More detailed data for urban trail segments can be found in the dataset Strategic Measure_Urban Trails Segment Data. More details data for sidewalk segments can be found in the dataset Strategic Measure_Sidewalk Segment Data.

This dataset provides detailed data for urban trail segments constructed within the full purpose jurisdiction of the City of Austin starting in calendar year 2017. This dataset supports the SD23 performance measure HE.C.5: Number and percentage of linear miles of newly constructed sidewalks and urban trails that lie within census tracts with no low levels of leisure-time physical activity among adults aged 18 years or older.

description: 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.

This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for block groups. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

The name for table 'ACS10INCBGMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.; abstract: 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.

This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for block groups. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

The name for table 'ACS10INCBGMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

description: 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.

This table contains housing data, including building age, value and/or rent, length of occupation, number of units, home heating type, and number of vehicles from the American Community Survey 2006-2010 database for block groups. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).; abstract: 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.

This table contains housing data, including building age, value and/or rent, length of occupation, number of units, home heating type, and number of vehicles from the American Community Survey 2006-2010 database for block groups. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

Abstract

The 2009 MDHS was designed to provide data to monitor the population and health situation in Maldives. Specifically, the MDHS collected information on fertility levels and preferences, marriage, sexual activity, knowledge and use of family planning methods, breastfeeding practices, nutrition status of women and young children, childhood mortality, maternal and child health, and awareness and behaviour regarding AIDS and other sexually transmitted infections. At the household level, the survey collected information on domains of physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the impact of the tsunami of 2004, health expenditures, and care and support for physical activity of adults age 65 and older. At the individual level, the survey assessed additional features of blood pressure, diabetes, heart attack, and stroke.

Geographic coverage

National

Analysis unit

• Households
• Children age under 5
• Women age 15-49
• Men age 15-64

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN

The population of the republic of Maldives is distributed on 195 inhabited islands among a total of 202 inhabited islands; seven islands have no residents (MPND, 2008). Each inhabited island is an administrative unit with an island office that handles island-based affairs. The islands are regrouped to form atolls, a higher-level administrative unit with an atoll office and an atoll chief. There are 20 atolls in total in the republic. The capital city of Malé and the two surrounding islands, Villingili and Hulhumale, form a special atoll. The 21 atolls are regrouped to form six geographic regions according to their location. Malé atoll alone forms a region. In Maldives, there is no urbanrural designation for residential households within an atoll. All residential households in the 20 atolls outside of Malé are considered rural; all residential households in Malé are considered urban.

The 2009 Maldives DHS is based on a probability sample of 7,515 households. The sample was designed to produce representative data on households, women, and children for the country as a whole, for urban and rural areas, for the six geographical regions, and for each of the atolls of the country. The male and youth surveys were designed to produce representative results for the country as a whole, for urban and rural areas, and for each of the six geographical regions.

The 2006 Maldives Population and Housing Census provided the sampling frame for the 2009 MDHS. The MDHS sample was a stratified multistage sample selected in two stages from the census frame. In the first stage, 270 census blocks were selected using a systematic selection, with probability proportional to the number of residential households residing in the block. Stratification was achieved by treating each of the 21 atolls as a sampling stratum. Samples were selected independently in each stratum according to an appropriate allocation.

In the second stage of sampling, residential households were selected in each of the selected census blocks. Household selection involved an equal probability systematic selection of a fixed number of households: 28 households per block. Households were selected from the household listings created in the census, but to allow all households an opportunity to be included in the sample, listings were sent to island offices for updating prior to making household selections for the MDHS.

All ever-married women age 15-49 in the total sample of MDHS households, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In half of the households selected for the ever-married sample of women, all ever-married men age 15-64, who were either usual residents of the household or visitors present in the household on the night before the survey, were eligible to be interviewed. In the same half of households selected for the ever-married sample of men, never-married women and nevermarried men age 15-24, who were either usual residents of the household or visitors present in the household on the night before the survey, were also eligible to be interviewed. The MDHS was for the most part limited to Maldivian citizens; non-Maldivians were included in the survey only if they were the spouse, son, or daughter of a Maldivian.

Note: See detailed sample implementation information in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

Four questionnaires were used for the 2009 MDHS: the Household Questionnaire, the Women’s Questionnaire, the Men’s Questionnaire, and the Youth Questionnaire. The contents of the Household, Women’s, and Men’s questionnaires were based on model questionnaires developed by the MEASURE DHS programme. The DHS model questionnaires were modified to reflect concerns pertinent to the Maldives in the areas of population, women and children’s health, family planning, and others. Questionnaires were translated from English into Dhivehi.

The Household Questionnaire was used to list all the usual members and visitors in the selected households and to identify women and men who were eligible for the individual interview. Basic information was collected on the characteristics of each person listed, including their age, sex, education, and relationship to the head of the household. The Household Questionnaire was also designed to collect information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, water shortage, materials used for the floor and roof of the house, and ownership of various durable goods. In addition, height and weight measurements of ever-married women age 15-49 and children age 6-59 months were recorded in the Household Questionnaire to assess their nutritional status.

Topics added to the Household Questionnaire to reflect issues relevant in the Maldives include physical disability among those age 5 and older, developmental disability among young children, support for early learning, children at work, the tsunami of 2004, health expenditures, and care and support for physical activities of adults age 65 and older.

The Women’s Questionnaire was used to collect information from ever-married women age 15-49. These women were asked questions on the following topics: - Background characteristics (education, media exposure, etc.) - Reproductive history - Knowledge and use of family planning methods - Fertility preferences - Antenatal and delivery care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant and child feeding practices - Childhood mortality - Awareness and behaviour about AIDS and other sexually transmitted infections (STIs) - Knowledge of blood pressure, diabetes, heart attack, and stroke

The Men’s Questionnaire was administered to all ever-married men age 15-64 living in every second household in the MDHS sample. The Men’s Questionnaire collected much of the same information as the Women’s Questionnaire, but it was shorter because it did not contain questions on reproduction, maternal and child health, and nutrition.

The Youth Questionnaire was administered to all never-married women and men age 15-24 living in every second household in the MDHS sample (the same one-half selected for the Men’s survey). The Youth Questionnaire focuses on priorities of the MOHF that pertain to young adults: reproductive health, knowledge and attitudes about HIV/AIDS, sexual activity, and tobacco, alcohol, and drug use.

Response rate

A total of 7,515 households were selected in the sample, of which 7,137 were found to be occupied at the time of data collection. The difference between the number of households selected and the number occupied usually occurs because some structures are found to be vacant or non-existent. The number of occupied households successfully interviewed was 6,443, yielding a household response rate of 90 percent.

In the households interviewed in the survey, a total of 8,362 ever-married women were identified as eligible for the individual interview; interviews were completed with 7,131 women, yielding a female response rate of 85 percent. In the one-half sub-sample of MDHS households, a total of 3,224 evermarried men age 15-64 were identified as eligible for the individual interview; interviews were completed with 1,727 men, yielding a male response rate of 54 percent. In the same sub-sample of households, a total of 3,205 never-married women and men age 15-24 (youth) were identified as eligible for individual interview; interviews were completed with 2,240 youth, yielding a youth response rate of 70 percent. The response rate was higher for female youth (80 percent) than male youth (61 percent).

The urban household response rate of 83 percent is lower than the 92 percent response rate among rural households. The same is true for individual interviews with ever-married respondents; response rates are somewhat lower among urban women (79 percent) and men (47 percent) than among their rural counterparts (87 percent and 55 percent, respectively). The difference in response rates between urban and rural youth is negligible.

Note: See summarized response rates by residence (urban/rural) in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling

Abstract

The primary objective of the 2012 Indonesia Demographic and Health Survey (IDHS) is to provide policymakers and program managers with national- and provincial-level data on representative samples of all women age 15-49 and currently-married men age 15-54.

The 2012 IDHS was specifically designed to meet the following objectives: • Provide data on fertility, family planning, maternal and child health, adult mortality (including maternal mortality), and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs; • Measure trends in fertility and contraceptive prevalence rates, and analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception; • Evaluate the achievement of goals previously set by national health programs, with special focus on maternal and child health; • Assess married men’s knowledge of utilization of health services for their family’s health, as well as participation in the health care of their families; • Participate in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the areas of family planning, fertility, and health in general

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49
• Ever married men age 15-54
• Never married men age 15-24

Kind of data

Sample survey data [ssd]

Sampling procedure

Indonesia is divided into 33 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts, and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The 2012 IDHS sample is aimed at providing reliable estimates of key characteristics for women age 15-49 and currently-married men age 15-54 in Indonesia as a whole, in urban and rural areas, and in each of the 33 provinces included in the survey. To achieve this objective, a total of 1,840 census blocks (CBs)-874 in urban areas and 966 in rural areas-were selected from the list of CBs in the selected primary sampling units formed during the 2010 population census.

Because the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated in proportion to the population of the province or its urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains. A minimum of 43 CBs per province was imposed in the 2012 IDHS design.

Refer to Appendix B in the final report for details of sample design and implementation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2012 IDHS used four questionnaires: the Household Questionnaire, the Woman’s Questionnaire, the Currently Married Man’s Questionnaire, and the Never-Married Man’s Questionnaire. Because of the change in survey coverage from ever-married women age 15-49 in the 2007 IDHS to all women age 15-49 in the 2012 IDHS, the Woman’s Questionnaire now has questions for never-married women age 15-24. These questions were part of the 2007 Indonesia Young Adult Reproductive Survey questionnaire.

The Household and Woman’s Questionnaires are largely based on standard DHS phase VI questionnaires (March 2011 version). The model questionnaires were adapted for use in Indonesia. Not all questions in the DHS model were adopted in the IDHS. In addition, the response categories were modified to reflect the local situation.

The Household Questionnaire was used to list all the usual members and visitors who spent the previous night in the selected households. Basic information collected on each person listed includes age, sex, education, marital status, education, and relationship to the head of the household. Information on characteristics of the housing unit, such as the source of drinking water, type of toilet facilities, construction materials used for the floor, roof, and outer walls of the house, and ownership of various durable goods were also recorded in the Household Questionnaire. These items reflect the household’s socioeconomic status and are used to calculate the household wealth index. The main purpose of the Household Questionnaire was to identify women and men who were eligible for an individual interview.

The Woman’s Questionnaire was used to collect information from all women age 15-49. These women were asked questions on the following topics: • Background characteristics (marital status, education, media exposure, etc.) • Reproductive history and fertility preferences • Knowledge and use of family planning methods • Antenatal, delivery, and postnatal care • Breastfeeding and infant and young children feeding practices • Childhood mortality • Vaccinations and childhood illnesses • Marriage and sexual activity • Fertility preferences • Woman’s work and husband’s background characteristics • Awareness and behavior regarding HIV-AIDS and other sexually transmitted infections (STIs) • Sibling mortality, including maternal mortality • Other health issues

Questions asked to never-married women age 15-24 addressed the following: • Additional background characteristics • Knowledge of the human reproduction system • Attitudes toward marriage and children • Role of family, school, the community, and exposure to mass media • Use of tobacco, alcohol, and drugs • Dating and sexual activity

The Man’s Questionnaire was administered to all currently married men age 15-54 living in every third household in the 2012 IDHS sample. This questionnaire includes much of the same information included in the Woman’s Questionnaire, but is shorter because it did not contain questions on reproductive history or maternal and child health. Instead, men were asked about their knowledge of and participation in health-careseeking practices for their children.

The questionnaire for never-married men age 15-24 includes the same questions asked to nevermarried women age 15-24.

Cleaning operations

All completed questionnaires, along with the control forms, were returned to the BPS central office in Jakarta for data processing. The questionnaires were logged and edited, and all open-ended questions were coded. Responses were entered in the computer twice for verification, and they were corrected for computeridentified errors. Data processing activities were carried out by a team of 58 data entry operators, 42 data editors, 14 secondary data editors, and 14 data entry supervisors. A computer package program called Census and Survey Processing System (CSPro), which was specifically designed to process DHS-type survey data, was used in the processing of the 2012 IDHS.

Response rate

The response rates for both the household and individual interviews in the 2012 IDHS are high. A total of 46,024 households were selected in the sample, of which 44,302 were occupied. Of these households, 43,852 were successfully interviewed, yielding a household response rate of 99 percent.

Refer to Table 1.2 in the final report for more detailed summarized results of the of the 2012 IDHS fieldwork for both the household and individual interviews, by urban-rural residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2012 Indonesia Demographic and Health Survey (2012 IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2012 IDHS is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling error is a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2012 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2012 IDHS is a SAS program. This program used the Taylor linearization method

Geographic coverage

The survey covers the whole of the Indian Union except (i) interior villages of Nagaland situated beyond five kilometres of the bus route and (ii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

For Leh (Ladakh) and Kargil districts of Jammu & Kashmir there is no separate sample first-stage units (FSUs) for "central sample". For these two districts, sample FSUs drawn as "state sample" will also be treated as central sample. The state directorate of economics and statistics (DES) will provide a copy of the filled-in schedules to Data Processing Division of NSSO for processing.

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

Outline of sample design: A stratified multi-stage design has been adopted for the 66th round survey. The first stage units (FSU) are the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. In addition, two non-UFS towns of Leh and Kargil of Jammu & Kashmir are also treated as FSUs in the urban sector. The ultimate stage units (USU) are households in both the sectors. In case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (henceforth the term "village" would mean Panchayat wards for Kerala) constitutes the sampling frame. For the urban sector, the list of latest available UFS blocks is considered as the sampling frame. For non-UFS towns, frame consists of the individual towns (only two towns, viz., Leh & Kargil constitute this frame).

Stratification: Within each district of a State/ UT, generally speaking, two basic strata have been formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, wherever there are one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them forms a separate basic stratum and the remaining urban areas of the district are considered as another basic stratum.

Sub-stratification: There is no sub-stratification in the urban sector. However, to net adequate number of child workers, for all rural strata, each stratum has been divided into 2 sub-strata as follows: sub-stratum 1: all villages with proportion of child workers (p) >2P (where P is the average proportion of child workers for the sate/ UT as per Census 2001) sub-stratum 2: remaining villages

Total sample size (FSUs): 12784 FSUs for central sample and 15132 FSUs for state sample have been allocated at all-India level. Further, data of 24 state sample FSUs of Leh and Kargil districts of J & K surveyed by DES, J & K will be included in the central sample

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators has been kept in view.

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size is allocated between two sectors in proportion to population as per census 2001 with double weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 16 FSUs (to the extent possible) is allocated to each state/ UT separately for rural and urban areas. Further the State level allocations for both rural and urban have been adjusted marginally in a few cases to ensure that each stratum/ sub-stratum gets a minimum allocation of 4 FSUs.

Allocation to strata/ sub-strata: Within each sector of a State/ UT, the respective sample size is allocated to the different strata/ sub-strata in proportion to the population as per census 2001. Allocations at stratum/ sub-stratum level are adjusted to multiples of 4 with a minimum sample size of 4 and equal number of samples has been allocated among the four sub rounds.

Selection of FSUs: For the rural sector, from each stratum/ sub-stratum, required number of sample villages has been selected by probability proportional to size with replacement (PPSWR), size being the population of the village as per Census 2001. For urban sector, from each stratum FSUs have been selected by using Simple Random Sampling Without Replacement (SRSWOR). Both rural and urban samples have been drawn in the form of two independent sub-samples.

More information on sampling and estimation procedure is available in the document " Note on Sample Design and Estimation Procedure of NSS 66th Round". including information on: - Formation and selection of hamlet-groups/ sub-blocks - Listing of households - Formation of second stage strata and allocation of households - Selection of households - Estimation Procedure

Mode of data collection

Face-to-face [f2f]

Research instrument

During this round, the following schedules of enquiry were canvassed: - Schedule 0.0 : list of households
- Schedule 1.0 : consumer expenditure (Type 1 and Type 2) - Schedule 10 : employment and unemployment

In the present round, Schedule 10 on employment-unemployment consists of 16 blocks.

The first three blocks, viz. Blocks 0, 1 and 2, are used to record identification of sample households and particulars of field operations, as is the common practice in usual NSS rounds. The last two blocks, viz., Blocks 10 and 11 are to record the remarks of investigator and comments by supervisory officer(s), respectively.

Block 3 will be used for recording the household characteristics, like household size, religion, social group, land possessed, land cultivated, etc. For the rural households information will also be collected, in Block 3, on whether the household has NREG job card, whether got work in NREG works during the last 365 days, number of days got work in NREG works and mode of payment of the wages earned in NREG works. Besides, some particulars about holding of specified Post Office accounts and use of specified Postal services will also be collected in this block.

Block 3.1 is for recording particulars of indebtedness of rural labour households.

Block 4 will be used for recording the demographic particulars and attendance in educational institutions of the household members. Particulars of vocational training being received/received by the household members will also be collected in this block.

In Block 5.1, particulars of usual principal activity of all the household members will be recorded along with some particulars of the enterprises in which the usual status workers (excluding those in crop and plantation activities) are engaged. In this block information for all the workers about the location of workplace will also be collected. For the self-employed persons who are working under specifications (wholly or mainly), information will also be collected about "who provided credit/raw materials/equipments", "basis of payment" and "number of outlets of disposal". Information on informal employment will also be collected in Block 5.1. Similarly, the particulars of one subsidiary economic activity of the household members along with some particulars of the enterprises, informal employment and details of the self-employed persons in their subsidiary activity will be recorded in Block 5.2. The daily time disposition for the seven days preceding the date of survey along with the corresponding activity particulars will be recorded for each household member in Block 5.3. Besides this, the current weekly status (CWS) will be derived from the daily time disposition data and will be recorded in this block. As in the past, wage and salary earnings and mode of payment will also be collected for regular salaried/wage employees and for the casual labourers in this block. Block 6 will be used to record the responses to the probing questions to the persons who were unemployed on all the seven days of the reference week.

Blocks 7.1 and 7.2 contain the probing questions which are related to the under-utilisation of labour time and labour mobility, respectively.

For the members of the household classified as engaged in 'domestic duties' as per their usual principal status, some follow-up questions have been framed and listed in Block 8, with a view to collecting some additional information which might explain as to whether their usual attachment to domestic duties was voluntary or involuntary and also to throw light on their participation in some specified activities for family gain.

A worksheet to obtain the total monthly household consumer expenditure has been provided in Block 9.

Abstract

The surveys on 'Household Social Consumption: Education' conducted by NSSO covers both qualitative and quantitative aspects related to educational attainment of the household members and educational services used by them. Qualitative aspects include literacy, educational level attained, type of institution, current attendance/enrolment, whether received free education, reason for 'never enrolled'/'ever enrolled but currently not attending', etc. On quantitative aspects, information was collected on 'expenditure incurred/to be incurred on education' of the household member by the household itself, by other households or by any institutions/organizations other than Government.

Reference period : July 2017-June 2018

Period of survey and work programme: The survey period of the round will be divided into four sub-rounds of three months’ duration each as follows: sub-round 1 : July - September 2017 sub-round 2 : October - December 2017 sub-round 3 : January - March 2018 sub-round 4 : April - June 2018

Objective of Survey on 'Household Social Consumption: Education' (Schedule 25.2): The main objective of the survey on “Household Social Consumption: Education” conducted by NSSO is to build indicators on participation of the persons in the education system, expenditure incurred on education of the household members and on various aspects of those currently not attending education (i.e., for the persons who never enrolled or who ever enrolled but currently not attending education). The surveys on ‘Household Social Consumption: Education’ conducted by NSSO covers both qualitative and quantitative aspects related to educational attainment of the household members and educational services used by them. Qualitative aspects include literacy, educational level attained, type of institution, nature of institution, current attendance/enrolment, whether received free education, reason for never enrolled/ever enrolled but currently not attending, etc. On quantitative aspects, information is collected on expenditure incurred/to be incurred on education of the household member by the household itself, by other households or by any institutions/organizations other than Government.

Geographic coverage

The survey cover's the whole of the Indian Union except except the villages in Andaman and Nicobar Islands which are difficult to access

Analysis unit

Randomly selected households based on sampling procedure and members of the household.

Universe

The survey used the interview method of data collection from a sample of randomly selected households and members of the household.

Sampling procedure

Sample Design 3.1 Outline of sample design: A stratified multi-stage design has been adopted for the 75th round survey. The first stage units (FSU) are the Census villages (Panchayat wards for Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. The ultimate stage units (USU) are households in both the sectors. In the case of large FSUs, one intermediate stage of sampling is the selection of two hamlet-groups (hgs)/ sub-blocks (sbs) from each rural/ urban FSU. 3.2 Sampling Frame for First Stage Units: For the rural sector, the list of 2011 Population Census villages constitutes the sampling frame. However, for Kerala, the latest available updated list of Panchayat wards constitutes the sampling frame. For the urban sector, the latest available list of UFS blocks has been considered as the sampling frame. 3.3 Stratification: (a) Each district is a stratum. Within each district of a State/UT, generally speaking, two basic strata have been formed: (i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there are one or more towns with population one million or more as per Census 2011, each of them formed as a separate basic stratum and the remaining urban areas of the district have been considered as another basic stratum. (b) In the case of rural sectors of Nagaland another special stratum has been formed within the State consisting of all the villages which are difficult to access. 3.4 Sub-stratification: 3.4.1 Rural sector: If ‘r’ be the sample size allocated for a rural stratum, ‘r/4’ sub-strata are formed in that stratum. The villages within a stratum (district) as per frame are first arranged in ascending order of population. Then sub-strata 1 to ‘r/4’ have been demarcated in such a way that each substratum comprises a group of villages of the arranged frame and has more or less equal population. 3.4.2 Urban sector: Each urban stratum has been divided into two parts - ‘Affluent part’ consisting of UFS blocks identified as ‘Affluent Area’ and ‘Non-Affluent part’ consisting of the remaining UFS blocks within the stratum. Sample allocation of a stratum is then allocated to Affluent and Non-Affluent parts in proportion to total number of households in the UFS blocks with double weightage to Affluent part subject to a maximum of 8 FSUs in ‘Affluent part’ of any stratum. If ‘u’ be the sample size allocated for an urban stratum consisting of both affluent area UFS Blocks and non affluent area UFS Blocks. ‘u/4’ sub-strata are formed within each stratum. Out of these ‘u/4’ substrata, the first two sub-strata ‘01’ and ‘02’ are earmarked for those UFS blocks which are identified as ‘Affluent Area’ and the remaining sub-strata, ‘03’, ‘04’,…... and so on, are assigned to the nonaffluent UFS blocks. If any stratum does not have any Affluent Area UFS block then also the substratum number starts from ‘03’ for that stratum. For all strata, if u/4 >1, implying formation of 2 or more sub-strata, all the UFS blocks within the stratum are first arranged in ascending order of total number of households in the UFS Blocks as per the latest UFS phase. Then sub-strata 1 to ‘u/4’ are demarcated in such a way that each sub-stratum has more or less equal number of households. This procedure has been done separately for Affluent-part and Non-Affluent part of the stratum (if two sub-strata are required to be formed in the Affluent part). The following three cases arise while doing the sub-stratification: i) If there is no ‘Affluent Area’ UFS block in the stratum, all the UFS blocks are divided into ‘u/4’ sub-strata and numbered as ‘03’, ‘04’, ….., ‘(u/4)+2’. ii) If only one sub-stratum is formed with the ‘Affluent Area’ UFS blocks, then all the remaining non-affluent blocks are divided into ‘(u-4)/4’ sub-strata and numbered as ‘03’, ‘04’, ….., ‘(u/4)+1’. iii) If two sub-strata are formed with the ‘Affluent Area’ blocks, then all the remaining non-affluent UFS blocks are divided into ‘(u-8)/4’ sub-strata and numbered as ‘03’, ‘04’, ….., ‘u/4’. 3.5 Total sample size (FSUs): 14300 FSUs have been allocated for the central sample at all-India level. For the state sample, there are 16492 FSUs allocated for all-India. 3.6 Allocation of total sample to States and UTs: The total number of sample FSUs has been allocated to the States and UTs in proportion to population as per Census 2011 subject to a minimum sample allocation to each State/UT. 3.7 Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample size has been allocated between two sectors in proportion to population as per Census 2011 with 1.5 weightage to urban sector depending on population share. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) have been allocated to each State/ UT. 3.8 Allocation to strata: Within each sector of a State/ UT, the respective sample size has been allocated to the different strata in proportion to the population as per Census 2011. Stratum level allocation has been adjusted to multiples of 4 with a minimum sample size of 4. For special stratum formed in rural areas of Nagaland as discussed in para 3.3 (b), 12 FSUs have been allocated. 3.9 Allocation to sub-strata: Allocation for each sub-stratum has been made as 4 in both rural and urban sectors. 3.10 Selection of FSUs: 3.10.1 For the rural sector, from each stratum/sub-stratum, required number of sample villages has been selected by Probability Proportional to Size With Replacement (PPSWR), size being the population of the village as per Census 2011. 3.10.2 For the urban sector, from each stratum/sub-stratum, FSUs have been selected by Probability Proportional to Size With Replacement (PPSWR), size being the number of households of the UFS Block. Both rural and urban samples are drawn in the form of two independent sub-samples. 3.11 Selection of hamlet-groups/ sub-blocks - important steps 3.11.1 Criterion for hamlet-group/ sub-block formation: After identification of the boundaries of the FSU, it is to be determined whether listing is to be done in the whole sample FSU or not. In case the approximate present population of the selected FSU is found to be 1200 or more, it is divided into a suitable number (say, D) of ‘hamlet-groups’ in the rural sector and ‘sub-blocks’ in the urban sector by more or less equalising the population as stated below. approximate present population of the sample FSU no. of hgs/sbs formed less than 1200 (no hamlet-group/sub-block) 1 1200 to 1799 3 1800 to 2399 4 2400 to 2999 5 3000 to 3599 6 …...and so on - For rural areas of Himachal Pradesh, Sikkim, Andaman & Nicobar Islands, Uttarakhand (except four districts Dehradun, Nainital, Hardwar and Udham Singh Nagar), Punch, Rajouri, Udhampur, Reasi, Doda, Kishtwar, Ramban, Ladakh region (Leh and Kargil districts) of Jammu and Kashmir and Idukki district of Kerala, the number of hamlet-groups to be formed as

Abstract

This is the fourth Labor Force Survey of Tonga. The first one was conducted in 1990. Earlier surveys were conducted in 1990, 1993/94, and 2003 and the results of those surveys were published by the Statistics Department.

The objective of the LFS survey is providing information on not only well-known employment and unemployment as well as providing comprehensive information on other standard indicators characterizing the country labour market. It covers those age 10 and over in the whole Kingdom. Information includes age, sex, activity, current and usual employment status, hours worked and wages and in addition included a seperate Food Insecurity Experiences Survey (FIES) questionniare module at the Household Level.

The conceptual framework used in this labour force survey in Tonga aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statistician.

Geographic coverage

National coverage.

There are six statistical regions known as Division's in Tonga namely Tongatapu urban area, Tongatapu rural area, Vava'u, Ha'pai, Eua and the Niuas.Tongatapu Urban refers to the capital Nuku'alofa is the urban area while the other five divisions are rural areas. Each Division is subdivided into political districts, each district into villages and each village into census enumeration areas known as Census Blocks. The sample for the 2018 Labour Force Survey (LFS) was designed to cover at least 2500 employed population aged 10 years and over from all the regions. This was made mainly to have sufficient cases to provide information on the employed population.

Analysis unit

• Households (for food insecurity module questionnaire)
• Individuals.

Universe

Population living in private households in Tonga. The labour force questionnaire is directed to the population aged 10 and above. Disability short set of questions is directed to all individuals age 2 and above and the food insecurity experience scale is directed to the head of household.

Kind of data

Sample survey data [ssd]

Sampling procedure

2018 Tonga Labour force survey aimed at estimating all the main ILO indicators at the island group level (geographical stratas). The sampling strategy is based on a two stages stratified random survey.

1. Computation of the survey parameters: Total sample size per strata, number of households to interview in each Primary Sampling Unit (PSU = census block) and number of PSUs to select The stratification of the survey is the geographical breakdown by island group (6 stratas Tongatapu urban, Tongatapu rural, Vava'u, Ha'apai, 'Eua, Niuas)
2. The selection strategy is a 2 stages random survey where: Random selection of census blocks within each
3. Census blocks are randomly selected in first place, using probability proportional to size

4. 15 households per block are randomly selected using uniform probability

5. The sampling frame used to select PSUs (census blocks) and household is the 2016 Tonga population census.

The computation of sample size required the use of: - Tonga 2015 HIES dataset (labour force section) - Tonga 2016 population census (distribution of households across the stratas) The resource variable used to compute the sample size is the labour force participation rate from the 2015 HIES. The use of the 2015 labour force section of the Tonga HIES allows the computation of the design effect of the labour force participation rate within each strata. The design effect and sampling errors of the labour force participation rate estimated from the 2015 HIES in combination with the 2016 household population distribution allow to predict the minimum sample size required (per strata) to get a robust estimate from the 2018 LFS.

Total sample size: 2685 households Geographical stratification: 6 island groups Selection process: 2 stages random survey where census blocks are selected using Probability Proportional to Size (Primary Sampling Unit) in the first place and households are randomly selected within each selected blocks (15 households per block) Non response: a 10% increase of the sample happened in all stratas to account for non-response Sampling frame: the household listing from the 2016 population census was used as a sampling frame and the 2015 labour force section of the HIES was used to compute the sample size (using labour force participation rate.

Sampling deviation

No major deviation from the original sample has taken place.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2018 Tonga Labour Force Survey questionnaire included 15 sections:

IDENTIFICATION SECTION B: INDIVIDUAL CHARACTERISTICS SECTION C: EDUCATION (AGE 3+) SECTIONS B & C: EMPLOYMENT IDENTIFICATION AND TEMPORARY ABSENCE (AGE 10+) SECTION D: AGRICULTURE WORK AND MARKET DESTINATION SECTION E1: MAIN EMPLOYMENT CHARACTERISTICS SECTION E2: SECOND PAID JOB/ BUSINESS ACTIVITY CHARACTERISTICS SECTION F: INCOME FROM EMPLOYMENT SECTION G: WORKING TIME SECTION H: JOB SEARCH SECTION I: PREVIOUS WORK EXPERIENCE SECTION J: MAIN ACTIVITY SECTION K: OWN USE PRODUCTION WORK FOOD INSECURITY EXPERIENCES GPS + PHOTO

The questionniares were developed and administered in English and were translated into Tongan language. The questionnaire is provided as external resources.

The draft questionnaire was pre-tested during the supervisors training and during the enumerators training and it was finally tested during the pilot test. The pilot testing was undertaken on the 27th of May to the 1st of June 2018 in Tongatapu Urban and Rural areas. The questionnaire was revised rigorously in accordance to the feedback received from each test. At the same time, a field operations manual for supervisors and enumerators was prepared and modified accordingly for field operators to use as a reference during the field work.

Cleaning operations

The World Bank Survey Solutions software was used for Data Processing, STATA software was used for data cleaning, tabulation tabulation and analysis.

Editing and tabulation of the data will be undertaken in February/March 2019 in collaboration with SPC and ILO.

Response rate

A total, 2,685 households were selected for the sample. Of these existing households, 2,584 were successfully interviewed, giving a household response rate of 96.2%.

Response rates were higher in urban areas than in the rural area of Tongatapu.

-1 Tongatapu urban: 97.30%
-2 Tongatapu rural: 93.00%
-3 Vava'u: 100.00% -4 Ha'pai: 100.00% -5 Eua: 95.20% -6 Niuas: 80.00% -Total: 96.20%.

Sampling error estimates

Sampling errors were computed and are presented in the final report.

The sampling error were computed using the survey set package in Stata. The Finite Population Correction was included in the sample design (optional in svy set Stata command) as follow: - Fpc 1: total number of census blocks within the strata (variable toteas) - Fpc 2: Here is a list of some LF indicators presented with sampling error

-RSE: Labour force population: 2.2% Employment - population in employment: 2.2% Labour force participation rate (%): 1.7% Unemployment rate (%): 13.5% Composite rate of labour underutilization (%): 7.3% Youth unemployment rate (%): 18.2% Informal employment rate (%): 2.7% Average monthly wages - employees (TOP): 12%.

-95% Interval: Labour force population: 28,203 => 30,804 Employment - population in employment: 27,341 => 29,855 Labour force participation rate (%): 45.2% => 48.2% Unemployment rate (%): 2.2% => 3.9% Composite rate of labour underutilization (%): 16% => 21.4% Youth unemployment rate (%): 5.7% => 12.1% Informal employment rate (%): 44.3% => 49.4% Average monthly wages - employees (TOP): 1,174 => 1,904.