Understanding how population change is associated with community sociodemographics and economic outcomes across the United States

This study examines how population change is associated with changes in sociodemographics and economic outcomes across diverse geographic contexts in the United States from 2000 to 2020. Using Census Tract-level data and generalized additive models (GAMs), we found that communities experiencing population growth showed significant improvements in socioeconomic indicators: for example, a 50% population increase in Northeast metropolitan non-coastal areas was associated with a $10,062 rise [95% confidence interval (CI) = $9,181, $10,944] in median household income. Conversely, areas with population decline faced increasing challenges to community composition: communities experiencing a 50% population decline in West coastal metropolitan areas saw their median age increase by 2.556 years (95% CI = 2.23, 2.89 years), indicating an accelerated aging population. We observed a positive relationship between population growth and local economic growth, with areas experiencing population decline or slow growth showing below-average economic growth. While population change alone explained 10.1% of the variance in county-level GDP growth, incorporating sociodemographic shifts alongside population change using a partial least squares regression (PLSR) more than doubled the explanatory power to 21.4%. Overall, we often found the strength of relationships and sometimes the direction varied by geographic context: coastal areas showed distinct patterns from inland regions, and metropolitan areas responded differently than rural ones. For instance, the percentage of owner-occupied housing was negatively associated with population growth in metropolitan areas, but positively associated in non-metropolitan areas. Our research provides valuable insights for policymakers and planners working to address community changes, particularly in the context of anticipated climate-induced migration. The results suggest that strategies for maintaining economic vitality need to consider not just population retention, but also demographic profiles and socioeconomic opportunities across different geographic contexts.

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Publication Details

Journal
Frontiers in Human Dynamics
Published
2024-12-11
DOI
https://doi.org/10.3389/fhumd.2024.1465218
Citations
5
Primary Topic
Urban Transport and Accessibility
Type
article
Field-Weighted Citation Impact
3.42
Controls
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article

Understanding how population change is associated with community sociodemographics and economic outcomes across the United States

Jeremy R. Porter, Danielle N. Medgyesi, Zachary M. Hirsch, Jasmina M. Buresch
5 citations
Frontiers in Human Dynamics
Urban Transport and Accessibility
3.42
article

Understanding how population change is associated with community sociodemographics and economic outcomes across the United States

Jeremy R. Porter, Danielle N. Medgyesi, Zachary M. Hirsch, Jasmina M. Buresch
article en
5 citations

Abstract

This study examines how population change is associated with changes in sociodemographics and economic outcomes across diverse geographic contexts in the United States from 2000 to 2020. Using Census Tract-level data and generalized additive models (GAMs), we found that communities experiencing population growth showed significant improvements in socioeconomic indicators: for example, a 50% population increase in Northeast metropolitan non-coastal areas was associated with a $10,062 rise [95% confidence interval (CI) = $9,181, $10,944] in median household income. Conversely, areas with population decline faced increasing challenges to community composition: communities experiencing a 50% population decline in West coastal metropolitan areas saw their median age increase by 2.556 years (95% CI = 2.23, 2.89 years), indicating an accelerated aging population. We observed a positive relationship between population growth and local economic growth, with areas experiencing population decline or slow growth showing below-average economic growth. While population change alone explained 10.1% of the variance in county-level GDP growth, incorporating sociodemographic shifts alongside population change using a partial least squares regression (PLSR) more than doubled the explanatory power to 21.4%. Overall, we often found the strength of relationships and sometimes the direction varied by geographic context: coastal areas showed distinct patterns from inland regions, and metropolitan areas responded differently than rural ones. For instance, the percentage of owner-occupied housing was negatively associated with population growth in metropolitan areas, but positively associated in non-metropolitan areas. Our research provides valuable insights for policymakers and planners working to address community changes, particularly in the context of anticipated climate-induced migration. The results suggest that strategies for maintaining economic vitality need to consider not just population retention, but also demographic profiles and socioeconomic opportunities across different geographic contexts.

Frontiers in Human DynamicsVol. 6
Health First (US), Foundation for Ichthyosis and Related Skin Types (US), Columbia University (US)
Climate action
Openalex Percentile: Top 8%
Urban Transport and Accessibility
3.42
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