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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8776053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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