mathewhauer / county_projections_official

Complete replication code for county-level population projections
MIT License
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Introduction

Here I provide the code for: Population projections for all U.S. counties by age, sex, and race controlled to the Shared Socioeconomic Pathways

Citation

Hauer, M.E. Open Science Framework. (DOI 10.17605/OSF.IO/9YNFC) (YEAR ACCESSED).

Abstract

Small area and subnational population projections are important for understanding long-term demographic changes. I provide county-level population projections by age, sex, and race in five-year intervals for the period 2015-2100 for all U.S. counties. Using historic U.S. census data in temporally rectified county boundaries and race groups for the period 1990-2015, I calculate cohort-change ratios (CCRs) and cohort-change differences (CCDs) for eighteen five-year age groups (0-85+), two sex groups (Male and Female), and four race groups (White NH, Black NH, Other NH, Hispanic) for all U.S counties. I then project these CCRs/CCDs using ARIMA models as inputs into Leslie matrix population projection models and control the projections to the Shared Socioeconomic Pathways. I validate the methods using ex-post facto evaluations using data from 1969-2000 to project 2000-2015. My results are reasonably accurate for this period. These data have numerous potential uses and can serve as inputs for addressing questions involving sub-national demographic change in the United States.

Main Figure Projected numeric population changes for the five SSPs between 2020 and 2100 for counties in the continental United States.

Organization

Use

Data

The projected populations by age/sex/race/county/year/SSP for all US counties for the period 2020-2100 are available at the Open Science Foundation https://dx.doi.org/10.17605/OSF.IO/9YNFC.

Data resulting from these projections can be found in the file SSP_asrc.csv.zip.

Codebook

YEAR

STATE

COUNTY

GEOID

AGE

SEX

RACE

Correspondence

For any issues with the functionality of these scripts please create an issue.

License

The data collected and presented is licensed under the Creative Commons Attribution 3.0 license, and the underlying code used to format, analyze and display that content is licensed under the MIT license.