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Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach

Despite the growing awareness and interest in the impact of energy poverty on depression, studies in developing economies are relative limited, and there is a gap of knowledge of such impact among rural individuals in China. In this study, we investigate the impact of energy poverty on depression am...

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Autores principales: Zhang, Jun, He, Yuang, Zhang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776053/
https://www.ncbi.nlm.nih.gov/pubmed/35055829
http://dx.doi.org/10.3390/ijerph19021006
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author Zhang, Jun
He, Yuang
Zhang, Jing
author_facet Zhang, Jun
He, Yuang
Zhang, Jing
author_sort Zhang, Jun
collection PubMed
description Despite the growing awareness and interest in the impact of energy poverty on depression, studies in developing economies are relative limited, and there is a gap of knowledge of such impact among rural individuals in China. In this study, we investigate the impact of energy poverty on depression among rural Chinese individuals aged 16 and above, and our sample includes 13,784 individuals from 6103 households. With data from the 2018 China Family Panel Studies, we apply the instrumental variable (IV) quantile regression approach to address the potential endogeneity of energy poverty and allow for heterogeneous effects of energy poverty on depression across individuals with different levels of depression. Our estimates from the IV quantile regression suggest a strong positive impact of energy poverty on depression at the upper quantile of depression scores, but no impact at the middle and lower quantiles. The primary results are robust and consistent with alternative energy poverty measures, and we find that energy poverty does not affect depression of low-risk individuals (with low depression scores), but it does affect that of high-risk individuals. We also find individual socio-demographic factors of age, gender, household size, religious belief, education, marriage and employment status play roles in affecting depression. The findings of this study generate policy implications for energy poverty alleviation and mental health promotion.
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spelling pubmed-87760532022-01-21 Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach Zhang, Jun He, Yuang Zhang, Jing Int J Environ Res Public Health Article Despite the growing awareness and interest in the impact of energy poverty on depression, studies in developing economies are relative limited, and there is a gap of knowledge of such impact among rural individuals in China. In this study, we investigate the impact of energy poverty on depression among rural Chinese individuals aged 16 and above, and our sample includes 13,784 individuals from 6103 households. With data from the 2018 China Family Panel Studies, we apply the instrumental variable (IV) quantile regression approach to address the potential endogeneity of energy poverty and allow for heterogeneous effects of energy poverty on depression across individuals with different levels of depression. Our estimates from the IV quantile regression suggest a strong positive impact of energy poverty on depression at the upper quantile of depression scores, but no impact at the middle and lower quantiles. The primary results are robust and consistent with alternative energy poverty measures, and we find that energy poverty does not affect depression of low-risk individuals (with low depression scores), but it does affect that of high-risk individuals. We also find individual socio-demographic factors of age, gender, household size, religious belief, education, marriage and employment status play roles in affecting depression. The findings of this study generate policy implications for energy poverty alleviation and mental health promotion. MDPI 2022-01-17 /pmc/articles/PMC8776053/ /pubmed/35055829 http://dx.doi.org/10.3390/ijerph19021006 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Jun
He, Yuang
Zhang, Jing
Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title_full Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title_fullStr Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title_full_unstemmed Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title_short Energy Poverty and Depression in Rural China: Evidence from the Quantile Regression Approach
title_sort energy poverty and depression in rural china: evidence from the quantile regression approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8776053/
https://www.ncbi.nlm.nih.gov/pubmed/35055829
http://dx.doi.org/10.3390/ijerph19021006
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