October 2022 .. examining county and regional income and poverty trends .. the 2020 county poverty rate ranged from Douglas County, CO (3.0%) and Loudoun County, VA (3.2%) to Mitchell County, GA (42.5%) and Oglala Lakota County, SD (39.6%). These data are based on Census Bureau sourced annual model-based estimates. We have developed an annual time series of those data from 2010 through 2020. This section updates with 2021 estimates in December 2022.
The official poverty rate in 2021 was 11.6 percent, with 37.9 million people in poverty. Neither the rate nor the number in poverty was significantly different from 2020.
Our focus is on using these data, and variations of these data, to identify and apply tools to mitigate poverty. A first step is understanding how poverty manifests itself for a small area geography, such as counties. A second step is to organize a time series of poverty estimates that can be analyzed using a model. By examining cause and effect relationships, we then seek to project/forecast poverty incidence into the future under alternative scenarios. The alternative scenarios reflect different assumptions and policy tools. By knowing more about expected outcomes in 2030, we might better know what tools, methods work to mitigate poverty by county/region. Examining different small area geographic granularity, such as census tracts, might be a next step.
Here the focus is on counties and tools that can be used to examine income and poverty, over time, in context of other wide-ranging geography and subject matter. The county income and poverty dataset used in this section has been developed using the Demographic Economic Data Explorer DEDE. See list of subject matter fields below. DEDE can also be used to examine these data as a part of the Situation & Outlook (S&O). See this illustrative section in the Fresno County S&O report.
Patterns of Poverty Rate, All Ages, 2020, by County
Accessing/Analyzing Income & Poverty using VDA Web GIS
Use the VDA Web GIS with the MetroDynamics project to use the County Income and Poverty layer/data. VDA Web GIS is developed and maintained by Warren Glimpse/ProximityOne/Alexandria, VA USA and Takashi Hamilton/Tsukasa/Osaka, Japan.
Using VDA Web GIS: Patterns of Poverty Rate, All Ages, 2020, by County
The graphic shown below, developed using VDA Web GIS with the MetroDynamics project, is similar to the above view. It illustrates use of the table feature to show/examine counties as rows with selected poverty related attributes. Counties are ranked in descending order based on the 2020 poverty rate rightmost column (POVR20). Compare the 2010 poverty rate to the 2020 (or other) annual rate. Selected other age groups or related demographics.
Subject Matter Items
The record layout for the county poverty dataset created by DEDE is shown below. A standardized set of income and poverty-related fields is repeated for each year, 2010 through 2020/2021.
NAME .. area name
STAB .. state USPS abbreviation
GEOID .. state+conty FIPS code
-- 2010 --
MHI10 Median Household Income
POV017E10 Population age 0-17 in poverty, 2010
POV017R10 Population age 0-17 poverty rate, 2010
POV017U10 Population age 0-17 poverty universe, 2010
POV517E10 Population age 5-17 in poverty, 2010
POV517R10 Population age 5-17 poverty ratev
POV517U10 Population age 5-17 poverty universe, 2010
POVE10 Population all ages in poverty, 2010
POVR10 Population all ages poverty rate, 2010
POVU10 Population all ages poverty universe, 2010
-- 2011 --
-- 2012 --
-- 2013 --
-- 2014 --
-- 2015 --
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-- 2017 --
-- 2018 --
-- 2019 --
-- 2020 --
-- 2021 -- coming in December 2022
Related database details. More in general, not all county codes/areas are constant over time or annually. The dataset is initially developed based on the 2020 counties and codes. Prior year data is integrated into these records. Where there is no matching prior year code (mainly Alaska) those fields are not populated (show zero value).
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Support Using these Resources
Learn more about accessing and using demographic-economic data and related analytical tools. Join us in a Data Analytics Lab session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants.
ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.
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