Population Projection: Block Group Level P2 Based on 2010 Census Data HaystaqDNA population projections ##Redistricting Data Hub (RDH) Retrieval Date 12/17/2020 Dataset updated: 03/01/2021 ##Sources Projections courtesy of HaystaqDNA ##Fields P2 Table - Census Block Group Level Population Projections for Non-Hispanic and Hispanic by Race corresponding to variable names from the P2 Table of the PL 94-171 Redistricting Summary Files (https://api.census.gov/data/2010/dec/sf1/variables.html) Field Name Description geoid 12-character Census Block Group GEOID state_fips State FIPS Code p19_nh_tot 2019 projected population corresponding to P005002 p19_nh_wh 2019 projected population corresponding to P005003 p19_nh_aa 2019 projected population corresponding to P005004 p19_nh_ai 2019 projected population corresponding to P005005 p19_nh_asi 2019 projected population corresponding to P005006 p19_nh_pac 2019 projected population corresponding to P005007 p19_nh_oth 2019 projected population corresponding to P005008 p19_nh_tom 2019 projected population corresponding to P005009 p19_h_tot 2019 projected population corresponding to P005010 p19_h_wh 2019 projected population corresponding to P005011 p19_h_aa 2019 projected population corresponding to P005012 p19_h_ai 2019 projected population corresponding to P005013 p19_h_asi 2019 projected population corresponding to P005014 p19_h_pac 2019 projected population corresponding to P005015 p19_h_oth 2019 projected population corresponding to P005016 p19_h_tom 2019 projected population corresponding to P005017 ...The same sequence of columns for 2020-2029 p30_nh_tot 2030 projected population corresponding to P005002 p30_nh_wh 2030 projected population corresponding to P005003 p30_nh_aa 2030 projected population corresponding to P005004 p30_nh_ai 2030 projected population corresponding to P005005 p30_nh_asi 2030 projected population corresponding to P005006 p30_nh_pac 2030 projected population corresponding to P005007 p30_nh_oth 2030 projected population corresponding to P005008 p30_nh_tom 2030 projected population corresponding to P005009 p30_h_tot 2030 projected population corresponding to P005010 p30_h_wh 2030 projected population corresponding to P005011 p30_h_aa 2030 projected population corresponding to P005012 p30_h_ai 2030 projected population corresponding to P005013 p30_h_asi 2030 projected population corresponding to P005014 p30_h_pac 2030 projected population corresponding to P005015 p30_h_oth 2030 projected population corresponding to P005016 p30_h_tom 2030 projected population corresponding to P005017 ##Processing The RDH did not do any additional processing to the files from HaystaqDNA. ##Additional Notes **Overview from Haystaq's metadata on their Block and Block Group projections: ** These projections are at the 2010 Census Block Group level and the 2010 Census Block level, which is the most granular level of geography currently available. The projections update the current population data to match Census projections for overall statewide totals from 2020 and 2030. They project population nationally, from 2020 to 2030, with total population, as well as Census race groups and Hispanic origin categories. Although the US Census has generated population projections for 2020 and 2030, these projections are at the state level. While it would be simple to apply the statewide growth rate to each Census Block in a given state, we know that population growth is not uniform statewide. In order to generate projections at the Block and Block Group level, we need to estimate where in each state the population growth is occurring. A large share of population growth comes from new housing developments built in Census Blocks that were previously undeveloped and had zero population in 2010. We addressed the question of population growth in new housing developments using a combination of Census American Community Survey (ACS) Block Group level population estimates, and geocoded commercial data files from which we can find individuals currently living in Census Blocks that had zero population in 2010. **Haystaq Projection Methodology ** STEP 1 Aggregate 2010 Census Block data to the Block Group level. Update the 2018 ACS 5-year estimates at the state level to match the Census Population Estimates for 2018. Use the updated 2018 ACS 5-year estimates to calculate a rate of change at the Block Group level. Calculate this rate of change for total population, as well as for every race category and hispanic origin category, so as not to assume a standard rate of change across race categories. STEP 2 Use geocoded voter file and commercial file data to identify areas of new development – areas that are now inhabited that were previously unpopulated in the 2010 Census. Calculate the rate of change for total population, and race and hispanic origin categories, at the county level for the counties that have areas of new development, excluding the Block Groups with new development. We found that by using the county rate of change for these areas, we can estimate a rate of change that is more stable and geographically accurate than a Block Group level average for the area, for example. STEP 3 Update 2010 Census Block Group data using the calculated rates of change from STEP 1, for areas that are not new developments. For new developments, update the 2010 Census Block Group data using the county-level rates of change calculated in STEP 2. STEP 4 Disaggregate population projections at the Block Group level to the Block level. Use the commercial file data to find the Block to Block Group population proportions, as this data is from 2020. For Block Groups that contain Blocks that do not have population on the 2020 commercial file, use the 2010 Census Block to Block Group proportions to disaggregate the Block Group level projections. STEP 5 Use the Largest Remainder Method to round the population projections for the race and hispanic origin categories to sum to the total projected population at the Block and Block Group levels. ##Disclaimer The HaystaqDNA population projections are intended to help users approximate populations for the coming decade. Because the data is a statistical estimate, the Redistricting Data Hub cannot guarantee the accuracy of any of the numbers within, and will not match any Census/ACS data. Please contact info@redistrictingdatahub.org for more information.