Tag Archives: Atlanta neighborhoods

Census 2020 LUCA Program and You

.. what would be the financial impact of a one-percent understatement in the Census 2020 population count? Many political districts are drawn based upon population change and shifts, and allocations of government funding and services are made based upon official population data. Consider this one specific example. For each one-percent of the Atlanta MSA population missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be on the order of $414 million per year. How and why? At margin, each person not counted in the decennial census results in a per capita disposable income loss for the area in the magnitude of $5,494 in 2000, and $6,770 per person in 2020. 61,100 people undercounted times $6,770 yields $414 million.

This section is about the Censue 2020 Local Update of Census Addresses (LUCA) program and how it might impact the reduction in undercount .. and make the data more accurate for wide-ranging needs and uses. Read on for details about the LUCA program.

Atlanta-Sandy Springs-Roswell, GA MSA
The Atlanta metro shown with black bold boundary. More about this metro.

– View developed with CV XE GIS software.
– Click graphic to view patterns of neighborhood economic prosperity.

Financial Impact Details … the 2015 per capita current transfer payments (PCTP) in the Atlanta-Sandy Springs-Marietta MSA were $6,132, up from $5,494 in 2010. The PCTP figure in 2020 may be $6,770. For each one-percent of the Atlanta MSA population (61,100 people) missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be in the order of $414 million (61,100 x $6,770) per year as of Census 2020.  $414 million per year based on the 2020 population and PCTP.

Financial Impact in Your Areas of Interest
Estimate the financial impact in your areas of interest. Get the 2010 and 2015 population and PCTP data from the REIS Interactive Table for any county or state.  Compute the 2020 population and PCTP values, potential undercount to determine the financial impact on an area of interest

Census 2020 LUCA Overview
The Census 2020 LUCA program is an initiative of the Census Bureau, partnering with thousands of state and local governments across the U.S. At the core of this program, Census provides address list data to communities; those communities compare those data with their own data and provide address/geographic updates back to the Census Bureau.  The updated address and geographic data are integrated into the TIGER/Line files  — geographic backbone for collecting and tabulating the Census results. This important MAF/TIGER address-plus update program will help insure improved accuracy for Census 2020. LUCA is a geographic data development program engaging local communities across the U.S.

ProximityOne works with local areas to improve the TIGER/Line files leading up to Census 2020. Using the CV XE GIS software and specialized expertise, we helped hundreds of governmental units, including all of the State of Georgia, improve the coverage and content of the TIGER/Line files and thus the accuracy and completeness of Census 2010.

The Census 2020 LUCA program is starting now in 2016.  See the full schedule and related details in the LUCA Web section.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Tip of the Day — Census Tract Data Analytics

.. tip of the day .. a continuing weekly or more frequent tip on developing, integrating, accessing and using geographic, demographic, economic and statistical data. Join in .. tip of the day posts are added to the Data Analytics Blog on an irregular basis, normally weekly. Follow the blog to receive updates as they occur.

This section is focused on tools and methods to access and use census tract demographic-economic measures. Median household income ($MHI), median housing value ($MHV) and other selected items are used to illustrate operations and options.

This section illustrates use of census tract data from the 2014 American Community Survey (ACS1014) 5-year estimates. These are the most comprehensive demographic-economic data from the Census Bureau at the census tract level. These “5-year estimates” are centric to mid-2012. See more about 2010-2021 annual estimates and projections.

Methods described here apply to many other geographies; see related tip sections. See related section on ZIP code applications.

Five data access and use options are reviewed. Each method illustrates how $$MHI, $MHV and other data can be analyzed/used in different contexts.

Option 1 – View the data as a thematic pattern map.
Option 2 – View, compare, rank query data in interactive tables.
Option 3 – Access data using API Tools; create datasets.
Option 4 – View $MHI in structured profile in context of related data.
Option 5 – Site analysis – view circular area profile from a location.

Related sections:
Census tracts main section
Evolution of Census Tracts: 1970-2010
Demographic-Economic Estimates & Projections
Census tract and ZIP code equivalencing
Using census tracts versus ZIP code areas
Single year of age demographics

Option 1. View the data as a thematic pattern map; use the GIS tools:
Patterns of Economic Prosperity ($MHI) by Census Tract … the following graphic shows $MHI for a portion of the Los Angeles metro. Accommodating different demographic-economic thresholds/patterns, different legend color/data intervals are used. The pattern layer is set to 80% transparency enabling a view of earth features. Click graphic for larger view, more detail and legend color/data intervals; expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.

See details about each option in the related Web page.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.