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The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model

China’s pursuit of economic growth, rapid industrialization, and urbanization over the past few decades has resulted in high energy consumption, which in turn has caused serious environmental pollution problems, such as CO(2) and PM(2.5) emissions, the long-term exposure to which can seriously affec...

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Autores principales: Li, Ying, Chiu, Yung-ho, Liu, Yabin, Lin, Tai-Yu, Chang, Tzu-Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503011/
https://www.ncbi.nlm.nih.gov/pubmed/32942931
http://dx.doi.org/10.1177/0046958020921070
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author Li, Ying
Chiu, Yung-ho
Liu, Yabin
Lin, Tai-Yu
Chang, Tzu-Han
author_facet Li, Ying
Chiu, Yung-ho
Liu, Yabin
Lin, Tai-Yu
Chang, Tzu-Han
author_sort Li, Ying
collection PubMed
description China’s pursuit of economic growth, rapid industrialization, and urbanization over the past few decades has resulted in high energy consumption, which in turn has caused serious environmental pollution problems, such as CO(2) and PM(2.5) emissions, the long-term exposure to which can seriously affect resident health. To resolve these air pollution problems, the Chinese government has put in place several policies to reduce air and environmental pollution. Past studies on energy and environmental efficiency have been mostly static, have ignored the dynamic changes over time and regional differences, and have rarely considered human health factors. Therefore, this study employed a modified meta 2-stage Epsilon-Based Measure (EBM) Malmquist model to explore the relationships between the economy, energy, the environment, health and media, and the regional differences in 31 Chinese cities from 2014 to 2016. It was found that (1) Haikou and Lhasa’s efficiencies were 1 and were the best in all 3 years, and Shijiazhuang, Jinan and Shenyang’s were the most improved; (2) there was a gap between the eastern, central and western technological frontiers, with Chengdu, Hohhot, Chongqing, and Nanchang having technological gap ratios below 0.70 in the western and central Chinese regions, and Haikou, Guangzhou, and Shanghai in eastern China having technological gap ratios above 0.90 in all 3 years; and (3) the variations in the health treatment stage were greater than in the production stage, indicating that technological changes and efficiency improvements in the health treatment stages in each city were not stable.
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spelling pubmed-75030112020-09-28 The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model Li, Ying Chiu, Yung-ho Liu, Yabin Lin, Tai-Yu Chang, Tzu-Han Inquiry Original Research China’s pursuit of economic growth, rapid industrialization, and urbanization over the past few decades has resulted in high energy consumption, which in turn has caused serious environmental pollution problems, such as CO(2) and PM(2.5) emissions, the long-term exposure to which can seriously affect resident health. To resolve these air pollution problems, the Chinese government has put in place several policies to reduce air and environmental pollution. Past studies on energy and environmental efficiency have been mostly static, have ignored the dynamic changes over time and regional differences, and have rarely considered human health factors. Therefore, this study employed a modified meta 2-stage Epsilon-Based Measure (EBM) Malmquist model to explore the relationships between the economy, energy, the environment, health and media, and the regional differences in 31 Chinese cities from 2014 to 2016. It was found that (1) Haikou and Lhasa’s efficiencies were 1 and were the best in all 3 years, and Shijiazhuang, Jinan and Shenyang’s were the most improved; (2) there was a gap between the eastern, central and western technological frontiers, with Chengdu, Hohhot, Chongqing, and Nanchang having technological gap ratios below 0.70 in the western and central Chinese regions, and Haikou, Guangzhou, and Shanghai in eastern China having technological gap ratios above 0.90 in all 3 years; and (3) the variations in the health treatment stage were greater than in the production stage, indicating that technological changes and efficiency improvements in the health treatment stages in each city were not stable. SAGE Publications 2020-09-18 /pmc/articles/PMC7503011/ /pubmed/32942931 http://dx.doi.org/10.1177/0046958020921070 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Li, Ying
Chiu, Yung-ho
Liu, Yabin
Lin, Tai-Yu
Chang, Tzu-Han
The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title_full The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title_fullStr The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title_full_unstemmed The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title_short The Impact of the Media and Environmental Pollution on the Economy and Health Using a Modified Meta 2-Stage EBM Malmquist Model
title_sort impact of the media and environmental pollution on the economy and health using a modified meta 2-stage ebm malmquist model
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503011/
https://www.ncbi.nlm.nih.gov/pubmed/32942931
http://dx.doi.org/10.1177/0046958020921070
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