77 datasets found
  1. Alternative measures of UK households' income and saving

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Oct 8, 2018
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    Office for National Statistics (2018). Alternative measures of UK households' income and saving [Dataset]. https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/datasets/alternativemeasuresofrhdiandsavingratiotable1
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    xlsxAvailable download formats
    Dataset updated
    Oct 8, 2018
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    United Kingdom
    Description

    Annual and quarterly data on the impact of removing "imputed" transactions from real household disposable income and the saving ratio to better represent the economic experience of UK households.

  2. Alternative measures of real households disposable income and the saving...

    • data.wu.ac.at
    • data.europa.eu
    html
    Updated Jul 4, 2018
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    Office for National Statistics (2018). Alternative measures of real households disposable income and the saving ratio [Dataset]. https://data.wu.ac.at/odso/data_gov_uk/MmI3NDVkNTQtODIxMC00MGY4LTk1ZGItMGMzYzIwNjMwNGQ5
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    htmlAvailable download formats
    Dataset updated
    Jul 4, 2018
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    This article investigates the impact of removing “imputed” components to construct measures of RHDI and the saving ratio to better represent the economic experience of households.

  3. Food Access USDA

    • arc-garc.opendata.arcgis.com
    Updated Jun 16, 2015
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    Georgia Association of Regional Commissions (2015). Food Access USDA [Dataset]. https://arc-garc.opendata.arcgis.com/datasets/fc012a756cdb40f58ba28e3f534509d8
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    Dataset updated
    Jun 16, 2015
    Dataset provided by
    The Georgia Association of Regional Commissions
    Authors
    Georgia Association of Regional Commissions
    License

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

    Area covered
    Description

    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

  4. D

    ACP Households by Zip Code

    • detroitdata.org
    • data.detroitmi.gov
    • +2more
    Updated Jan 18, 2024
    + more versions
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    City of Detroit (2024). ACP Households by Zip Code [Dataset]. https://detroitdata.org/dataset/acp-households-by-zip-code
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    zip, geojson, csv, kml, arcgis geoservices rest api, htmlAvailable download formats
    Dataset updated
    Jan 18, 2024
    Dataset provided by
    City of Detroit
    Description
    Discounts for Internet service through the Affordable Connectivity Program (ACP) ended June 1, 2024 due to lack of additional funding. Whether the program will receive additional funding in the future is uncertain. Please see ACP program information from the FCC for more details.

    The Affordable Connectivity Program (ACP) households data set summarizes household enrollments and subscriptions by month and zip code for beneficiary households located in Detroit zip codes. The Affordable Connectivity Program (ACP) is a U.S. government program to help low-income households pay for Internet services and connected devices. Households that participate in ACP receive discounts on qualifying broadband Internet services of up to $30 per month and can also receive a one-time discount of up to $100 to purchase a laptop, desktop computer, or tablet. Households can qualify for ACP based on participation in Lifeline or other service provider programs for low-income households, income at or below 200% of the federal poverty guidelines, participation in other Lifeline-qualifying programs such as SNAP or Medicaid, or participation in free and reduced-price school lunch and breakfast programs. Additionally, service providers can ask the FCC to approve an alternative verification process and use that approved process to check consumer eligibility. ACP program discounts first became available to eligible enrolled households on January 1, 2022. The ACP claims process is built on the Lifeline Claims System and this data set is derived from snapshots of all subscribers entered in the National Lifeline Accountability Database (NLAD) as of the first of each month.
    The ACP was created under the Infrastructure Investment and Jobs Act, also known as the Bipartisan Infrastructure Law, and is administered by the independent not-for-profit Universal Service Access Co. under the direction of the Federal Communications Commission (FCC). Eligible beneficiaries who participated in the Emergency Broadband Benefit (EBB) program that was funded by the Coronavirus Aid, Relief, and Economic Security (CARES) Act, were transitioned to ACP between January 1 and March 1, 2022. EBB was ACP's predecessor program and ran from May 12, 2021 until it was phased out on February 28, 2022. Due to the granularity of available data, households located in communities adjacent to Detroit that share a zip code such as Hamtramck and Highland Park are included in this data set.

    Fields
    program - Associated program for the data (ACP or EBB)

    data_month - Data month is associated with the subscriber snapshot for each claim month. If data month is listed as '5/1/2022', then the subscriber snapshot was captured on June 1, and the data represents the number of households in ACP as of June 1. This is the universe of subscribers that providers can claim for the May 2022 data month.

    zipcode - Zip code where the enrolled household is located.

    net_new_enrollments_alternative_verification_process - Difference between the current month Total Subscribers who qualified using an alternative verification process and prior month Total Subscribers who qualified using an alternative verification process.

    net_new_enrollments_verified_by_school - Difference between the current month Total Subscribers who qualified using school lunch program verification and prior month Total Subscribers who qualified using school lunch program verification.

    net_new_enrollments_lifeline - Difference between the current month Total Subscribers who qualified using the Lifeline program and prior month Total Subscribers who qualified using the Lifeline program.

    net_new_enrollments_national_verifier_application - Difference between the current month Total Subscribers who qualified using a National Verifier application and prior month Total Subscribers who qualified using a National Verifier application.

    net_new_enrollments_total - Difference between the total number of subscribers in the current and prior months. Calculated based on the sum of net new monthly enrollments verified by the school, lifeline, alternative verification process, and national verifier application programs.

    total_alternative_verification_process - Number of households in the ACP on the first of the month snapshot whose eligibility was determined via an FCC-approved alternative verification process.

    total_verified_by_school - Number of households in the ACP on the first of the month snapshot whose eligibility was verified based on participation in a school lunch program.

    total_lifeline - Number of households in the ACP on the first of the month snapshot whose eligibility was determined based on participation in Lifeline, a federal program that lowers the monthly cost of phone or Internet services.

    total_national_verifier_application - Number of households in the ACP on of the first of the month snapshot whose eligibility was determined via the National Eligibility Verifier (National Verifier) system.

    total_subscribers - Number of total households participating in ACP on the first of the month snapshot. If, for example, there were 100 subscribers enrolled as of the June 1, 2022 snapshot, then Total Subscribers for the 05/01/2022 (May 2022) data month would be 100.
  5. Alternative measures of UK real households disposable income and the saving...

    • gov.uk
    Updated Jul 5, 2018
    + more versions
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    Office for National Statistics (2018). Alternative measures of UK real households disposable income and the saving ratio: January to March 2018 [Dataset]. https://www.gov.uk/government/statistics/alternative-measures-of-uk-real-households-disposable-income-and-the-saving-ratio-january-to-march-2018
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    Dataset updated
    Jul 5, 2018
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Office for National Statistics
    Area covered
    United Kingdom
    Description

    Official statistics are produced impartially and free from political influence.

  6. U.S. adults who were familiar with the term "ultra-processed food", 2024, by...

    • statista.com
    Updated Jul 8, 2025
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    Statista (2025). U.S. adults who were familiar with the term "ultra-processed food", 2024, by income [Dataset]. https://www.statista.com/statistics/1491326/adults-familiar-with-the-term-ultra-processed-food-by-income/
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    Dataset updated
    Jul 8, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 22, 2024 - Apr 9, 2024
    Area covered
    United States
    Description

    In 2024, only around ** percent of adults in the United States said they were familiar with the term "ultra-processed food". Those from high-income households were more likely to report they knew this term than those from lower income households. The consumption of ultra-processed foods such as potato chips, candy, and soft drinks has been linked to an increased risk of a number of health issues including certain cancers, cardiovascular disease, and type 2 diabetes. These foods are often cheaper than healthier alternatives. This statistic shows the percentage of adults in the United States who were familiar with the term "ultra-processed food" as of 2024, by household income.

  7. Alternative Measures of Real Household Disposable Income and the Saving...

    • gov.uk
    Updated Jul 14, 2016
    + more versions
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    Office for National Statistics (2016). Alternative Measures of Real Household Disposable Income and the Saving Ratio: June 2016 [Dataset]. https://www.gov.uk/government/statistics/alternative-measures-of-real-household-disposable-income-and-the-saving-ratio-june-2016
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    Dataset updated
    Jul 14, 2016
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Office for National Statistics
    Description

    Official statistics are produced impartially and free from political influence.

  8. v

    Egypt Manufactured Homes Market By Type (Single-Family Homes, Multifamily...

    • verifiedmarketresearch.com
    pdf,excel,csv,ppt
    Updated May 16, 2025
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    Verified Market Research (2025). Egypt Manufactured Homes Market By Type (Single-Family Homes, Multifamily Units), By Price Range (Low-Cost Manufactured Homes, Medium-Cost Manufactured Homes, High-Cost Manufactured Homes), By End-User (Individuals, Real Estate Developers, Government Agencies) & Region for 2026-2032 [Dataset]. https://www.verifiedmarketresearch.com/product/egypt-manufactured-homes-market/
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    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    May 16, 2025
    Dataset authored and provided by
    Verified Market Research
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2026 - 2032
    Area covered
    Egypt
    Description

    The Egypt Foodservice Market was valued at USD 1.58 Billion in 2024 is anticipated to reach USD 2.33 Billion by 2032, growing at a CAGR of 5% from 2026 to 2032.

    Definition/ Overview

    Manufactured homes are factory-built homes that are transported to a designated location for installation. Unlike traditional homes that are constructed on-site, manufactured homes are assembled in a controlled environment, which helps reduce construction time and cost. These homes are built according to specific building codes set by the U.S. Department of Housing and Urban Development (HUD), ensuring they meet safety, durability, and quality standards. Manufactured homes come in various sizes and layouts, from single-section to larger multi-section units.

    Manufactured homes provide a cost-effective housing solution, particularly for individuals and families who are looking for affordable alternatives to traditional homes.

  9. D

    Manufactured Homes Modular Homes and Mobile Homes Sales Market Report |...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Manufactured Homes Modular Homes and Mobile Homes Sales Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-manufactured-homes-modular-homes-and-mobile-homes-sales-market
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    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Manufactured Homes, Modular Homes, and Mobile Homes Sales Market Outlook



    The manufactured homes, modular homes, and mobile homes sales market size is projected to witness robust growth, with a compound annual growth rate (CAGR) of 6.2% from 2024 to 2032. In 2023, the global market size was valued at approximately USD 25 billion and is anticipated to reach around USD 41.5 billion by 2032. This growth is driven by several factors including increasing demand for affordable housing solutions, advancements in construction technology, and rising awareness about the benefits of modular and manufactured homes.



    One of the primary growth factors for the market is the escalating demand for affordable housing. With urbanization on the rise and more people moving to cities, the need for cost-effective housing solutions has never been higher. Manufactured homes, modular homes, and mobile homes offer a lower-cost alternative to traditional housing, making them highly attractive to first-time homebuyers, retirees, and those looking to downsize. In addition, the quicker build times associated with these types of homes make them a viable solution to housing shortages prevalent in many urban areas.



    Technological advancements in construction methods have significantly contributed to the market's growth. Innovations such as improved materials, automation in manufacturing processes, and advanced design software have made it possible to produce high-quality manufactured and modular homes that meet stringent building codes and customer expectations. These advancements also contribute to reducing construction time and cost, thereby enhancing market attractiveness. Moreover, the ability to customize homes according to individual preferences and local building codes further fuels market demand.



    Environmental concerns and the push for sustainable living have also played a critical role in market expansion. Manufactured and modular homes are often more energy-efficient than traditional homes due to better insulation and the use of sustainable materials. These homes can be built to meet or exceed energy efficiency standards, which not only helps in reducing the carbon footprint but also significantly lowers utility bills for homeowners. This environmental advantage appeals to a growing segment of environmentally conscious consumers.



    The Single-family Detached Home Business is an emerging trend within the broader housing market, offering unique opportunities for entrepreneurs and investors. This segment focuses on standalone homes that are not attached to any other dwelling, providing privacy and space that many homeowners desire. As urban areas continue to expand, the demand for single-family detached homes is expected to rise, driven by families seeking more personal space and a connection to nature. This business model allows for customization and personalization, catering to the specific needs and preferences of individual buyers. Additionally, the flexibility in design and construction methods makes it possible to incorporate sustainable practices, appealing to environmentally conscious consumers. The growth of this sector is further supported by favorable government policies and incentives aimed at promoting homeownership and sustainable development.



    From a regional perspective, North America holds a significant share of the market, primarily due to the high rate of adoption of these housing types in the United States and Canada. The Asia Pacific region is anticipated to witness the highest growth rate during the forecast period, driven by rapid urbanization, government initiatives promoting affordable housing, and increasing disposable incomes. Europe, Latin America, and the Middle East & Africa also present substantial growth opportunities, although the market dynamics vary significantly across these regions due to differences in economic conditions, regulatory frameworks, and consumer preferences.



    Product Type Analysis



    The product type segment of the manufactured homes, modular homes, and mobile homes sales market is categorized into single-wide homes, double-wide homes, and triple-wide homes. Single-wide homes are a popular choice among budget-conscious buyers due to their affordability and compact size. These homes are typically narrower and can be transported in one piece, making them an ideal option for individuals and small families looking for economical living solutions without compromising on essential amenities.

    <br

  10. f

    Details of households with partial matching status.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Jessica E. Graber; Douglas Williams; Jason Clark (2023). Details of households with partial matching status. [Dataset]. http://doi.org/10.1371/journal.pone.0277017.t006
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    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Jessica E. Graber; Douglas Williams; Jason Clark
    License

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

    Description

    Details of households with partial matching status.

  11. e

    The effects of taxes and benefits on household income

    • data.europa.eu
    • cloud.csiss.gmu.edu
    • +1more
    html
    Updated Feb 1, 2001
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    Office for National Statistics (2001). The effects of taxes and benefits on household income [Dataset]. https://data.europa.eu/data/datasets/the_effects_of_taxes_and_benefits_on_household_income/
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    htmlAvailable download formats
    Dataset updated
    Feb 1, 2001
    Dataset authored and provided by
    Office for National Statistics
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    Examines how taxes and benefits redistribute income between various groups of households in the UK. The study shows where different types of households and individuals are in the income distribution and looks at the changing levels of income inequality over time.

    Source agency: Office for National Statistics

    Designation: National Statistics

    Language: English

    Alternative title: household income

  12. W

    Households Below Average Income

    • cloud.csiss.gmu.edu
    • data.wu.ac.at
    html
    Updated Dec 26, 2019
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    United Kingdom (2019). Households Below Average Income [Dataset]. https://cloud.csiss.gmu.edu/uddi/dataset/households_below_average_income
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    htmlAvailable download formats
    Dataset updated
    Dec 26, 2019
    Dataset provided by
    United Kingdom
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    Statistics and commentary which give an insight into the standard of living of the household population in Great Britain, focusing on the lower part of income distribution.

    Source agency: Work and Pensions

    Designation: National Statistics

    Language: English

    Alternative title: Households Below Average Income

  13. f

    Unconditional mean comparison moderate and severe food insecurity.

    • plos.figshare.com
    bin
    Updated Aug 15, 2023
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    Andres Silva; Andres Astorga; Rodrigo Faundez; Karla Santos (2023). Unconditional mean comparison moderate and severe food insecurity. [Dataset]. http://doi.org/10.1371/journal.pone.0287593.t003
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    binAvailable download formats
    Dataset updated
    Aug 15, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Andres Silva; Andres Astorga; Rodrigo Faundez; Karla Santos
    License

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

    Description

    Unconditional mean comparison moderate and severe food insecurity.

  14. V

    Evaluation of Child Care Subsidy Strategies: Washington Site Public Use...

    • data.virginia.gov
    • healthdata.gov
    • +1more
    html
    Updated Feb 3, 2025
    + more versions
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    ACF (2025). Evaluation of Child Care Subsidy Strategies: Washington Site Public Use Files, 2005 [Dataset]. https://data.virginia.gov/dataset/evaluation-of-child-care-subsidy-strategies-washington-site-public-use-files-2005
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    htmlAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    ACF
    Description

    The Evaluation of Child Care Subsidy Strategies is a multi-site, multi-year effort to determine whether and how different child care subsidy policies and procedures and quality improvement efforts help low-income parents obtain and hold onto jobs and improve outcomes for children. Funding from the Child Care and Development Fund (CCDF) administered by the Child Care Bureau are divided into two purposes. The vast majority are aimed at assisting children of low-income working parents whose eligibility is determined by states within broad federal guidelines, while a much smaller portion (4 percent) work with state matching funds to improve the quality of child care for all children. For this study series, four experiments were conducted, two test alternative subsidy policies for low-income families and two test approaches to the use of set-aside funds for improving child care quality for all children. The four study sites and focus of evaluation include: (1) the effectiveness of three language and literacy curricula on teaching practices and children's language and literacy outcomes (Miami Dade County, Florida); (2) the impact of alternative eligibility and re-determination child care subsidy policies on parental employment outcomes (Illinois); (3) the impact of alternative child care co-payment structures on use of child care subsidies and employment outcomes (Washington) and (4) the effectiveness of training on Learning Games curriculum in changing care-giving practices in family child care homes and children's developmental outcomes (Massachusetts).

    Units of Response: Washington state families receiving child care subsidies.

    Type of Data: Administrative

    Tribal Data: No

    Periodicity: One-time

    Demographic Indicators: Household Income;Household Size;Race

    SORN: https://www.federalregister.gov/documents/2022/09/19/2022-20139/privacy-act-of-1974-system-of-records

    Data Use Agreement: Yes

    Data Use Agreement Location: https://www.icpsr.umich.edu/web/ICPSR/studies/29002/datadocumentation

    Granularity: Family;Household

    Spatial: States

    Geocoding: Unavailable

  15. f

    Comparison of per capita energy acquired (kcal) and nutrients densities (per...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 13, 2023
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    Yu Chen; Biing‐Hwan Lin; Lisa Mancino; Michele Ver Ploeg; Chen Zhen (2023). Comparison of per capita energy acquired (kcal) and nutrients densities (per 100 kcal of FAH purchases) between SNAP and low-income non-SNAP households. [Dataset]. http://doi.org/10.1371/journal.pone.0240263.t004
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yu Chen; Biing‐Hwan Lin; Lisa Mancino; Michele Ver Ploeg; Chen Zhen
    License

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

    Description

    Comparison of per capita energy acquired (kcal) and nutrients densities (per 100 kcal of FAH purchases) between SNAP and low-income non-SNAP households.

  16. g

    The effects of taxes and benefits on household income | gimi9.com

    • gimi9.com
    Updated Feb 1, 2001
    + more versions
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    (2001). The effects of taxes and benefits on household income | gimi9.com [Dataset]. https://gimi9.com/dataset/uk_the_effects_of_taxes_and_benefits_on_household_income
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    Dataset updated
    Feb 1, 2001
    Description

    Examines how taxes and benefits redistribute income between various groups of households in the UK. The study shows where different types of households and individuals are in the income distribution and looks at the changing levels of income inequality over time. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: household income

  17. D

    Manufactured & Mobile Homes Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Sep 23, 2024
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    Dataintelo (2024). Manufactured & Mobile Homes Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-manufactured-mobile-homes-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Sep 23, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Manufactured & Mobile Homes Market Outlook



    The global manufactured and mobile homes market size was valued at USD 25 billion in 2023 and is projected to reach USD 45 billion by 2032, growing at a compound annual growth rate (CAGR) of 6.5% from 2024 to 2032. This market is primarily driven by increasing demand for affordable housing solutions and the rising cost of traditional home construction, making manufactured and mobile homes a viable alternative for many consumers.



    One of the key growth factors for the manufactured and mobile homes market is the affordability it offers compared to conventional housing. With rising property prices and urbanization, many individuals and families are seeking cost-effective living solutions. Manufactured homes offer a lower cost per square foot, which appeals to budget-conscious consumers. Additionally, advancements in manufacturing technology have significantly improved the quality and aesthetic appeal of these homes, making them an attractive option for a broader audience.



    Another significant driver is the speed and efficiency of manufactured home construction. Traditional home building can take several months to over a year, subject to weather conditions and other delays. In contrast, manufactured homes are built in controlled factory environments, which greatly reduces construction time and minimizes weather-related delays. This rapid production capability addresses the urgent demand for housing in many markets, particularly in regions facing housing shortages.



    Sustainability and environmental concerns are also propelling the market. Manufactured and mobile homes are often built with energy-efficient materials and techniques, reducing their ecological footprint. The controlled manufacturing environment allows for more precise use of resources, reducing waste. Additionally, these homes can be equipped with sustainable features such as solar panels and energy-efficient appliances, appealing to environmentally conscious consumers.



    Regionally, North America is a significant player in the manufactured and mobile homes market, driven by the need for affordable housing and favorable government policies. The Asia Pacific region is also experiencing robust growth due to rapid urbanization and population growth, particularly in countries like China and India. Europe shows steady demand, particularly in areas facing housing shortages and high real estate prices.



    Product Type Analysis



    The product type segment in the manufactured and mobile homes market includes single-wide, double-wide, and triple-wide homes. Single-wide homes are usually the most affordable option and consist of a single section. These homes are easy to transport and set up, making them a popular choice for budget-conscious buyers. The simplicity and cost-effectiveness of single-wide homes contribute significantly to their market demand, especially in regions with lower disposable incomes.



    Double-wide homes are composed of two sections that are joined together on-site. These homes offer more space and amenities compared to single-wide homes and are often more customizable. The increased living space and the improving design aesthetics make double-wide homes a preferred choice for families. The market for double-wide homes is growing as consumers seek more spacious and comfortable living environments without the high costs associated with traditional housing.



    Triple-wide homes are the largest in this category, consisting of three joined sections. These homes offer the most space and luxury features, making them comparable to traditional homes. They are often chosen by consumers seeking a more permanent housing solution with ample living space and high-end amenities. The triple-wide segment is expected to witness steady growth, driven by demand from higher-income consumers looking for quality and spaciousness in their homes.



    Advancements in manufacturing technology have also played a crucial role in the evolution of these product types. Modern design and construction techniques have improved the durability, energy efficiency, and aesthetic appeal of both single, double, and triple-wide homes. This technological progress is expected to attract a wider range of consumers, further bolstering market growth across all product segments.



    Report Scope


    <br /&

  18. e

    Farm Household Income and Household Composition, England

    • data.europa.eu
    • cloud.csiss.gmu.edu
    • +1more
    html
    Updated Oct 11, 2021
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    Department for Environment, Food and Rural Affairs (2021). Farm Household Income and Household Composition, England [Dataset]. https://data.europa.eu/data/datasets/farm_household_income_and_household_composition_england
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Oct 11, 2021
    Dataset authored and provided by
    Department for Environment, Food and Rural Affairs
    License

    http://reference.data.gov.uk/id/open-government-licencehttp://reference.data.gov.uk/id/open-government-licence

    Description

    Information on farm household income and farm household composition. Source agency: Environment, Food and Rural Affairs Designation: National Statistics Language: English Alternative title: Farm Household Income and Household Composition, England

    If you require the datasets in a more accessible format, please contact fbs.queries@defra.gsi.gov.uk

    Background and guidance on the statistics

    Information on farm household income and farm household composition was collected in the Farm Business Survey (FBS) for England for the first time in 2004/05. Collection of household income data is restricted to the household of the principal farmer from each farm business. For practical reasons, data is not collected for the households of any other farmers and partners. Two-thirds of farm businesses have an input only from the principal farmer’s household (see table 5). However, details of household composition are collected for the households of all farmers and partners in the business, but not employed farm workers.

    Data on the income of farm households is used in conjunction with other economic information for the agricultural sector (e.g. farm business income) to help inform policy decisions and to help monitor and evaluate current policies relating to agriculture in the United Kingdom by Government. It also informs wider research into the economic performance of the agricultural industry.

    This release gives the main results from the income and composition of farm households and the off-farm activities of the farmer and their spouse (Including common law partners) sections of the FBS. These sections include information on the household income of the principal farmer’s household, off-farm income sources for the farmer and spouse and incomes of other members of their household and the number of working age and pensionable adults and children in each of the households on the farm (the information on household composition can be found in Appendix B).

    This release provides the main results from the 2013/14 FBS. The results are presented together with confidence intervals.

    Survey content and methodology

    The Farm Business Survey (FBS) is an annual survey providing information on the financial position and physical and economic performance of farm businesses in England. The sample of around 1,900 farm businesses covers all regions of England and all types of farming with the data being collected by face to face interview with the farmer. Results are weighted to represent the whole population of farm businesses that have at least 25 thousand Euros of standard output as recorded in the annual June Survey of Agriculture and Horticulture. In 2013 there were just over 58 thousand farm businesses meeting this criteria.

    Since 2009/10 a sub-sample of around 1,000 farms in the FBS has taken part in both the additional surveys on the income and composition of farm households and the off-farm activities of the farmer and their spouse. In previous years, the sub-sample had included over 1,600 farms. As such, caution should be taken when comparing to earlier years.

    The farms that responded to the additional survey on household incomes and off-farm activities of the farmer and spouse had similar characteristics to those farms in the main FBS in terms of farm type and geographical location. However, there is a smaller proportion of very large farms in the additional survey than in the main FBS. Full details of the characteristic of responding farms can be found at Appendix A of the notice.

    For further information about the Farm Business Survey please see: https://www.gov.uk/government/organisations/department-for-environment-food-rural-affairs/series/farm-business-survey

    Data analysis

    The results from the FBS relate to farms which have a standard output of at least 25,000 Euros. Initial weights are applied to the FBS records based on the inverse sampling fraction for each design stratum (farm type by farm size). These weights are then adjusted (calibration weighting) so that they can produce unbiased estimators of a number of different target variables. Completion of the additional survey on household incomes and off-farm activities of the farmer and spouse was voluntary and a sample of around 1,000 farms was achieved. In order to take account of non-response, the results have been reweighted using a method that preserves marginal totals for populations according to farm type and farm size groups. As such, farm population totals for other classifications (e.g. regions) will not be in-line with results using the main FBS weights, nor will any results produced for variables derived from the rest of the FBS (e.g. farm business income).

    Accuracy and reliability of the results

    We show 95% confidence intervals against the results. These show the range of values that may apply to the figures. They mean that we are 95% confident that this range contains the true value. They are calcula

  19. v

    Italy Manufactured Homes Market Size By Product Type (Modular Homes,...

    • verifiedmarketresearch.com
    pdf,excel,csv,ppt
    Updated Jul 3, 2025
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    Verified Market Research (2025). Italy Manufactured Homes Market Size By Product Type (Modular Homes, Panel-Built), By Application (Residential Housing, Tourism And Hospitality), By Distribution Channel (Direct Sales, Dealership And Retailers), And Region For 2026-2032 [Dataset]. https://www.verifiedmarketresearch.com/product/italy-manufactured-homes-market/
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    Verified Market Research
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2026 - 2032
    Area covered
    Italy, Europe
    Description

    The Italy manufactured homes market is expanding as demand for low-cost, adaptable housing alternatives develops. Manufactured homes offer a cheap alternative to traditional living, especially in light of escalating real estate prices. The market benefits from enhanced building quality, energy efficiency and customization possibilities, which appeal to first-time buyers and retirees alike. This is likely to enable the market size surpass USD 458.6 Million valued in 2024 to reach a valuation of around USD 742.3 Million by 2032.As the advantages of manufactured houses become more widely recognized, they are being integrated into a variety of housing alternatives, including urban projects and vacation homes. The rising demand for Italy Manufactured Homes is enabling the market grow at a CAGR of 6.2% from 2026 to 2032.

  20. D

    Baking Fat And Margarine Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Baking Fat And Margarine Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/baking-fat-and-margarine-market
    Explore at:
    pptx, csv, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Baking Fat And Margarine Market Outlook



    The global market size for baking fat and margarine was valued at USD 8.5 billion in 2023 and is projected to reach USD 12.3 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 4.1% during the forecast period. This growth can be attributed to increasing consumer demand for bakery and confectionery products, expanding urbanization, and evolving dietary preferences towards plant-based alternatives. The rising inclination towards home baking, fueled by social media trends and lockdown measures during the pandemic, has also significantly contributed to market growth.



    One of the key growth factors driving the baking fat and margarine market is the burgeoning bakery and confectionery industry. As consumers' tastes become more sophisticated, there is an increasing demand for a variety of baked goods ranging from bread and pastries to cakes and cookies. This demand is not only seen in developed countries but also in emerging economies where disposable incomes are rising and lifestyles are changing. Moreover, the trend towards convenience foods that are easy to prepare and consume further bolsters the market for baking fats and margarine.



    Another important growth factor is the shift towards healthier and sustainable food options. Consumers are becoming more health-conscious and are seeking products with lower saturated fat and cholesterol levels. This has led to an increased preference for margarine and plant-based fats, which are perceived as healthier alternatives to traditional animal fats like butter and lard. Additionally, the environmental impact of food production is a growing concern, pushing both consumers and manufacturers towards sustainable and plant-based ingredients.



    The technological advancements in food processing and the development of innovative products are also vital growth drivers. The introduction of new formulations and enhanced flavors in margarine and baking fats is attracting a broader consumer base. Manufacturers are investing in research and development to create products that not only meet dietary needs but also enhance the taste and texture of baked goods. These innovations are expected to drive market expansion over the forecast period.



    Household Hard Margarine Sales have seen a notable increase as consumers continue to explore various baking and cooking options at home. This trend is largely driven by the growing interest in home-cooked meals and the desire to experiment with different recipes, especially during times when dining out is less feasible. Hard margarine, known for its stability and longer shelf life, offers a convenient and cost-effective alternative for households looking to maintain a steady supply of baking essentials. The versatility of hard margarine in both sweet and savory dishes makes it a popular choice among home bakers and cooks, contributing to its rising sales figures. Additionally, the availability of fortified and health-oriented variants of hard margarine is appealing to health-conscious consumers, further boosting its demand in the household segment.



    Regional outlook for the baking fat and margarine market shows significant growth potential across different geographical areas. Asia Pacific, in particular, is expected to witness substantial growth due to increasing urbanization, rising disposable incomes, and growing westernization of diets. North America and Europe continue to dominate the market due to high consumption rates of bakery and convenience foods, along with a strong focus on health and wellness trends. The Middle East & Africa and Latin America are also experiencing steady growth, driven by increasing consumer spending on premium and imported food products.



    Product Type Analysis



    The baking fat and margarine market is segmented by product type, which includes butter, margarine, shortening, lard, and other types of fats. Butter, traditionally a staple in many households and bakeries, continues to hold a significant market share. Its rich flavor and texture make it a preferred choice for a variety of baked goods. However, rising health concerns over saturated fats and cholesterol have led some consumers to seek healthier alternatives.



    Margarine has emerged as a popular substitute for butter due to its lower saturated fat content and versatility in both household and industrial baking. It is often fortified with vitamins and can be made from various plant oils, mak

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Office for National Statistics (2018). Alternative measures of UK households' income and saving [Dataset]. https://www.ons.gov.uk/economy/nationalaccounts/uksectoraccounts/datasets/alternativemeasuresofrhdiandsavingratiotable1
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Alternative measures of UK households' income and saving

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3 scholarly articles cite this dataset (View in Google Scholar)
xlsxAvailable download formats
Dataset updated
Oct 8, 2018
Dataset provided by
Office for National Statisticshttp://www.ons.gov.uk/
License

Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically

Area covered
United Kingdom
Description

Annual and quarterly data on the impact of removing "imputed" transactions from real household disposable income and the saving ratio to better represent the economic experience of UK households.

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