Population Projection Geography: Block Group Level P2 Joined to 2010 Census Boundary Data
HaystaqDNA population projections joined to 2010 Decennial Census boundary data (shapefile)
##Redistricting Data Hub (RDH) Retrieval Date
12/17/2020
Dataset updated: 02/24/2021
##Sources
Boundary shapefile retrieved from the Census Cartographic Boundary File website: https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.2010.html
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
NAME Full Geographic Name of the Block Group
STATE Name of the State
COUNTY Name of the County
TOTPOP10 Total Population (P001001)
STATEFP State FIPS Code
COUNTYFP County FIPS Code
TRACTCE Tract Code
BLKGRPCE Block Group 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 population projections were joined with geospatial data from Census TIGER files using the pandas and geopandas libraries in Python on the unique identifier field (GEOID) and extracted as a shapefile.
##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.