Mountaintop Mining in Appalachia & its Economic and Well-being Impacts on Surrounding Populations

This research seeks to build on the existing literature to determine the impact of mountaintop mining (MTM) on the economic and well-being outcomes of surrounding communities. We utilize satellite imagery data from SkyTruth.org of active MTM sites in Central Appalachia in tandem with data from the American Community Survey from 2012-2021 in order to build a two-way fixed effects linear model with inverse probability weighted group balancing. We observe fixed effects by year as well as at three regional levels: state, public use microdata area (PUMA), and mining versus non-mining areas of a state. Our model seeks to uncover the causal impact of MTM intensity in a given region on that population’s employment, poverty, total income, and instance of disability. We determine significant yet somewhat ambiguous results, indicating a relatively positive impact of increased MTM activity on a PUMA, when compared to itself over the years, but a negative impact of MTM when compared to other MTM PUMAs and non-MTM PUMAs.

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Publication Details

Journal
UNC Libraries
Published
2025-10-28
DOI
https://doi.org/10.17615/83yj-k561
Primary Topic
Mining and Resource Management
Type
article
Field-Weighted Citation Impact
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article

Mountaintop Mining in Appalachia & its Economic and Well-being Impacts on Surrounding Populations

UNC Libraries
Mining and Resource Management
article

Mountaintop Mining in Appalachia & its Economic and Well-being Impacts on Surrounding Populations

article en

Abstract

This research seeks to build on the existing literature to determine the impact of mountaintop mining (MTM) on the economic and well-being outcomes of surrounding communities. We utilize satellite imagery data from SkyTruth.org of active MTM sites in Central Appalachia in tandem with data from the American Community Survey from 2012-2021 in order to build a two-way fixed effects linear model with inverse probability weighted group balancing. We observe fixed effects by year as well as at three regional levels: state, public use microdata area (PUMA), and mining versus non-mining areas of a state. Our model seeks to uncover the causal impact of MTM intensity in a given region on that population’s employment, poverty, total income, and instance of disability. We determine significant yet somewhat ambiguous results, indicating a relatively positive impact of increased MTM activity on a PUMA, when compared to itself over the years, but a negative impact of MTM when compared to other MTM PUMAs and non-MTM PUMAs.

UNC Libraries
University of North Carolina at Chapel Hill (US)
No poverty
Openalex Percentile: Top 47%
Mining and Resource Management
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