9 datasets found
  1. g

    Jobs Proximity Index | gimi9.com

    • gimi9.com
    Updated Mar 1, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). Jobs Proximity Index | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_jobs-proximity-index
    Explore at:
    Dataset updated
    Mar 1, 2024
    Description

    The Jobs Proximity Index quantifies the accessibility of a given residential neighborhood (Census Block Group) as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location.

  2. d

    Jobs Proximity Index

    • datasets.ai
    • s.cnmilf.com
    • +1more
    21, 57
    Updated Sep 22, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Housing and Urban Development (2024). Jobs Proximity Index [Dataset]. https://datasets.ai/datasets/jobs-proximity-index
    Explore at:
    21, 57Available download formats
    Dataset updated
    Sep 22, 2024
    Dataset authored and provided by
    Department of Housing and Urban Development
    Description

    The Jobs Proximity Index quantifies the accessibility of a given residential neighborhood (Census Block Group) as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location.

  3. Jobs Proximity Index 2020

    • catalog.data.gov
    Updated Mar 1, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    U.S. Department of Housing and Urban Development (2024). Jobs Proximity Index 2020 [Dataset]. https://catalog.data.gov/dataset/jobs-proximity-index-2020
    Explore at:
    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    The Jobs Proximity Index quantifies the accessibility of a given residential neighborhood (Census Block Group) as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location.

  4. l

    Jobs Proximity Index 2020

    • data.lojic.org
    • hub.arcgis.com
    • +1more
    Updated Aug 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Housing and Urban Development (2023). Jobs Proximity Index 2020 [Dataset]. https://data.lojic.org/datasets/HUD::jobs-proximity-index-2020
    Explore at:
    Dataset updated
    Aug 21, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    North Pacific Ocean, Pacific Ocean
    Description

    JOBS PROXIMITY INDEXSummaryThe jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. E represents the number of jobs in block-group j, and L is the number of workers in block-group j. The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts. InterpretationValues are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood. Data Source: ACS 2017 - 2021 5 year summary data. Longitudinal Employer-Household Dynamics (LEHD) data, 2017. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 8. To learn more about the Jobs Proximity Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 2017 - 2021 ACSDate Updated: 10/2023

  5. a

    Jobs Proximity Index

    • opendata.atlantaregional.com
    Updated Aug 10, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Housing and Urban Development (2017). Jobs Proximity Index [Dataset]. https://opendata.atlantaregional.com/datasets/4e2ef54b88084fb5a2554281b2d89a8b
    Explore at:
    Dataset updated
    Aug 10, 2017
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    Description

    The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. E represents the number of jobs in block-group j, and L is the number of workers in block-group j. The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts. Interpretation Values are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood. Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2014. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 8. To learn more about the Jobs Proximity Index visit: https://www.hudexchange.info/resource/4868/affh-raw-data/ Date of Coverage: 02/2020 Data Updated: Annually

  6. Jobs Proximity Index, U.S. Department of Housing and Urban Development (HUD)...

    • datalumos.org
    delimited
    Updated Apr 19, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States. Department of Housing and Urban Development (2017). Jobs Proximity Index, U.S. Department of Housing and Urban Development (HUD) [Dataset]. http://doi.org/10.3886/E100558V2
    Explore at:
    delimitedAvailable download formats
    Dataset updated
    Apr 19, 2017
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    United States. Department of Housing and Urban Development
    License

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

    Time period covered
    Nov 2017
    Area covered
    United States
    Description

    The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: (see attached image)Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. Erepresents the number of jobs in block-group j, and L is the number of workers in block-group j.The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts.InterpretationValues are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood.Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2014Data Current as of: 8/5/2020DATASET ATTRIBUTESGEOIDTextSTATETextCOUNTYTextTRACTTextBLOCKGROUPTextjobs_idxNumberjobs_alt_idxNumberschl_idxNumberShape_AreaNumbermin: 4.54 max: 1,248,999,331,413.33 avg: 97,385,218.81 count: 220,032Shape_LengthNumber

  7. a

    Jobs Proximity Index 2014 2017 HUD Block Group

    • affh-data-and-mapping-resources-v-2-0-cahcd.hub.arcgis.com
    Updated Mar 10, 2021
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Housing and Community Development (2021). Jobs Proximity Index 2014 2017 HUD Block Group [Dataset]. https://affh-data-and-mapping-resources-v-2-0-cahcd.hub.arcgis.com/datasets/c0de1bf7b05c4e128ef9ed3644c5f6e9
    Explore at:
    Dataset updated
    Mar 10, 2021
    Dataset authored and provided by
    Housing and Community Development
    Area covered
    Description

    The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. E represents the number of jobs in block-group j, and L is the number of workers in block-group j. The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts. Interpretation Values are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood. Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2014. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 8. To learn more about the Jobs Proximity Index visit: https://www.hudexchange.info/resource/4868/affh-raw-data/ Date of Coverage: 02/2020 Data Updated: AnnuallyOriginal Data sourced from: https://hudgis-hud.opendata.arcgis.com/datasets/4e2ef54b88084fb5a2554281b2d89a8b_0

  8. l

    Jobs Proximity Index

    • data.lojic.org
    • hudgis-hud.opendata.arcgis.com
    Updated Jul 5, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Department of Housing and Urban Development (2023). Jobs Proximity Index [Dataset]. https://data.lojic.org/datasets/HUD::jobs-proximity-index
    Explore at:
    Dataset updated
    Jul 5, 2023
    Dataset authored and provided by
    Department of Housing and Urban Development
    Area covered
    North Pacific Ocean, Pacific Ocean
    Description

    JOBS PROXIMITY INDEXSummaryThe jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. E represents the number of jobs in block-group j, and L is the number of workers in block-group j. The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts. InterpretationValues are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood. Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2017. Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 8. To learn more about the Jobs Proximity Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdfDate of Coverage: 07/2020

  9. Jobs Proximity Index, U.S. Department of Housing and Urban Development (HUD)...

    • datalumos.org
    Updated Apr 19, 2017
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    United States. Department of Housing and Urban Development (2017). Jobs Proximity Index, U.S. Department of Housing and Urban Development (HUD) [Dataset]. http://doi.org/10.3886/E100558V1
    Explore at:
    Dataset updated
    Apr 19, 2017
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Authors
    United States. Department of Housing and Urban Development
    License

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

    Time period covered
    Nov 2017
    Area covered
    United States
    Description

    The jobs proximity index quantifies the accessibility of a given residential neighborhood as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location. More formally, the model has the following specification: (see attached image)Where i indexes a given residential block-group, and j indexes all n block groups within a CBSA. Distance, d, is measured as “as the crow flies” between block-groups i and j, with distances less than 1 mile set equal to 1. Erepresents the number of jobs in block-group j, and L is the number of workers in block-group j.The Longitudinal Employer-Household Dynamics (LEHD) has missing jobs data in all of Puerto Rico and a concentration of missing records in Massachusetts.InterpretationValues are percentile ranked with values ranging from 0 to 100. The higher the index value, the better the access to employment opportunities for residents in a neighborhood.Data Source: Longitudinal Employer-Household Dynamics (LEHD) data, 2014Data Current as of: 2/22/2017DATASET ATTRIBUTESGEOIDTextSTATETextCOUNTYTextTRACTTextBLOCKGROUPTextjobs_idxNumberjobs_alt_idxNumberschl_idxNumberShape_AreaNumbermin: 4.54 max: 1,248,999,331,413.33 avg: 97,385,218.81 count: 220,032Shape_LengthNumber

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

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2024). Jobs Proximity Index | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_jobs-proximity-index

Jobs Proximity Index | gimi9.com

Explore at:
Dataset updated
Mar 1, 2024
Description

The Jobs Proximity Index quantifies the accessibility of a given residential neighborhood (Census Block Group) as a function of its distance to all job locations within a CBSA, with larger employment centers weighted more heavily. Specifically, a gravity model is used, where the accessibility (Ai) of a given residential block- group is a summary description of the distance to all job locations, with the distance from any single job location positively weighted by the size of employment (job opportunities) at that location and inversely weighted by the labor supply (competition) to that location.

Search
Clear search
Close search
Google apps
Main menu