TY - JOUR
T1 - Cumulative impacts in environmental justice
T2 - Insights from economics and policy
AU - Bakkensen, Laura A.
AU - Ma, Lala
AU - Muehlenbachs, Lucija
AU - Benitez, Lina
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/7
Y1 - 2024/7
N2 - Disparities in health and socioeconomic well-being are a result of the cumulative impacts from multiple coinciding environmental, health, and social stressors. Addressing cumulative impacts is seen as a crucial step toward environmental justice (EJ). Using the case of the United States, we compare different methods to operationalize the concept for real-world application. We empirically demonstrate the extent to which non-White and low-income neighborhoods are subject to a wide array of burdens and how these burdens are reflected in national EJ indices and housing prices. We find that non-White and low-income neighborhoods are correlated with measures of multiple environmental burdens and social stressors but correlate to a lesser extent with natural disaster risk. Two existing EJ indices are only moderately correlated and more correlated with low-income status than with percent non-White. Models that employ the housing market for benefits estimation may fail to capture preferences to avoid multiple stressors due to issues including data availability and market frictions, such as discrimination. Finally, we highlight the challenges in cumulative impacts analysis for research and policy-making.
AB - Disparities in health and socioeconomic well-being are a result of the cumulative impacts from multiple coinciding environmental, health, and social stressors. Addressing cumulative impacts is seen as a crucial step toward environmental justice (EJ). Using the case of the United States, we compare different methods to operationalize the concept for real-world application. We empirically demonstrate the extent to which non-White and low-income neighborhoods are subject to a wide array of burdens and how these burdens are reflected in national EJ indices and housing prices. We find that non-White and low-income neighborhoods are correlated with measures of multiple environmental burdens and social stressors but correlate to a lesser extent with natural disaster risk. Two existing EJ indices are only moderately correlated and more correlated with low-income status than with percent non-White. Models that employ the housing market for benefits estimation may fail to capture preferences to avoid multiple stressors due to issues including data availability and market frictions, such as discrimination. Finally, we highlight the challenges in cumulative impacts analysis for research and policy-making.
KW - Cumulative impacts
KW - Environmental burdens
KW - Environmental justice
KW - Impact indices
KW - Policy response
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U2 - 10.1016/j.regsciurbeco.2024.103993
DO - 10.1016/j.regsciurbeco.2024.103993
M3 - Article
AN - SCOPUS:85187988573
SN - 0166-0462
VL - 107
JO - Regional Science and Urban Economics
JF - Regional Science and Urban Economics
M1 - 103993
ER -