(For a Shiny Version of this report, please check out: https://analysisinsightdata.shinyapps.io/capsc5w3/.)

The US Census Bureau released their apportionment results at the end of April 2021, revealing the 13 states that need to undergo redistricting.

Texas looks like the biggest winner with two additional seats, while California actually lost a seat this time?

If we took a longer time frame and evaluated seat changes since the 1970 Census, we feel less sorry for California. Montana gained a seat with the 2020 Census, but that just brings it back to zero changes in seats after six decades.

The long term trend suggests a flow towards the South and West.

Data from Center for Effective Lawmaking includes a field called “DW Nominate 1”, where negative values are liberal and positive values are conservative, centered at zero. This will be our proxy for ideology.

If we are to assume that people generally vote for politicians who reflect their own views, this Ideology score might give us some sense about how politics is trending at the affected states. The average score for House of Representatives in states with increasing house seats appear to be trending towards conservatism. No causality is implied in either direction, and this might just be an overall shift caused by the balance of power in Congress for the last few cycles.

We can look at a more detailed distribution of individual lawmaker Ideology scores for the most recent Congressional data extract available. Feel free to engage with these interactive charts.

Apportionments are tied to population growth, but counts are just one dimension. Using US Census Bureau 5-year surveys conducted in 2010 and 2019, let us take a look at changes in Ethnicity and Race categories as a share of total population.

US Census Bureau descriptions cross reference:

US Census Defintion Short Code
Hispanic or Latino hispanic_lat_eth
White alone, not Hispanic or Latino white_nhisp
Black or African American alone, not Hispanic or Latino black_nhisp
American Indian and Alaska Native alone, not Hispanic or Latino native_nhisp
Asian alone, not Hispanic or Latino asian_nhisp
Native Hawaiian and Other Pacific Islander alone, not Hispanic or Latino nhpi_nhisp
Some other race alone, not Hispanic or Latino oth_races_nhisp
Two or more races, not Hispanic or Latino oth_races_nhisp

Within each State of interest, the ethnicity + race group with the largest share of the population showed a shift away from White Alone, Non-Hispanic. California appears to have turned into a Hispanic or Latino majority some time between the 2010 and 2019 surveys.

For the 13 States currently affected or the 9 most affected states over a longer time span, the ethnicity + race share of total population has shifted over the last decade.

Sources / Acknowledgements

US Census, 2020 Census Apportionment Results - April 26, 2021
https://www.census.gov/data/tables/2020/dec/2020-apportionment-data.html; also https://2020census.gov/en.html

(*Please note that 5 Year Surveys (ACS5) only provide estimates, and have corresponding margins of error.) https://www.census.gov/data/developers/data-sets/acs-5year.html

USDA State FIPS Codes
https://nrcs.usda.gov/wps/portal/nrcs/detail/?cid=nrcs143_013696

Center for Effective Lawmaking, University of Virginia & Vanderbilt University
Congressional data from 1973-2020, Ideology (dwnominate1)
https://thelawmakers.org/

NOMINATE (scaling method), Wikipedia
https://en.wikipedia.org/wiki/NOMINATE_(scaling_method)

tidycensus R package, by Kyle Walker
https://walker-data.com/tidycensus/

tigris R package, by Kyle Walker
https://journal.r-project.org/archive/2016/RJ-2016-043/index.html

Data Visualization Capstone, part of a specialization offered through Coursera and Johns Hopkins University
https://www.coursera.org/learn/data-visualization-capstone

Thank you!