Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach
This paper investigated the factors driving the changes in industrial wastewater emission intensity (IWEI) across provinces in China. To do this, we proposed a Super-efficiency Slacks-based Measure-Global Malmquist Index (SSBM-GMI) to decompose the change in IWEI into the effects from efficiency cha...
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doaj-9902ebaa52ca40359bd462c855c7984d2020-11-24T23:31:29ZengMDPI AGInternational Journal of Environmental Research and Public Health1660-46012018-12-011512277910.3390/ijerph15122779ijerph15122779Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI ApproachYongyi Cheng0Liheng Lu1Tianyuan Shao2Manhong Shen3Laiqun Jin4School of Business, Ningbo University, Ningbo 315211, ChinaSchool of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, ChinaSchool of Business, Ningbo University, Ningbo 315211, ChinaSchool of Business, Ningbo University, Ningbo 315211, ChinaSchool of Business, Ningbo University, Ningbo 315211, ChinaThis paper investigated the factors driving the changes in industrial wastewater emission intensity (IWEI) across provinces in China. To do this, we proposed a Super-efficiency Slacks-based Measure-Global Malmquist Index (SSBM-GMI) to decompose the change in IWEI into the effects from efficiency change (ECE), technological change (TCE), capital⁻wastewater substitution (KWE) and labor⁻wastewater substitution (LWE). The method was applied to conduct an empirical study using Chinese provincial data from 2003⁻2015. The main findings include the following: firstly, TCE was the dominant driving force behind the reduction in IWEI with an average annual contribution of −6.4% at the national level, followed by KWE (−5.3%), LWE (−1.8%) and ECE (1.2%). Secondly, significant differences exist in the driving factors behind the reduction in IWEI across regions. The reduction in IWEIs in the Northeast area and the Great Northwest area was mainly driven by productivity growth, while the reduction in IWEIs in the other areas was mainly driven by factor substitution. Thirdly, the shortage of KWE and LWE has impeded IWEI reduction in the Great Northwest area, the Middle Reaches of the Yellow River, the Northeast area and the North area. Finally, some particular policy implications were also recommended for reducing industrial wastewater emission in China.https://www.mdpi.com/1660-4601/15/12/2779industrial wastewater emission intensityindustrial economic growthsustainable developmentgreen total factor productivitydriving factorproduction-theoretical decomposition analysis (PDA)slack-based measure (SBM) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yongyi Cheng Liheng Lu Tianyuan Shao Manhong Shen Laiqun Jin |
spellingShingle |
Yongyi Cheng Liheng Lu Tianyuan Shao Manhong Shen Laiqun Jin Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach International Journal of Environmental Research and Public Health industrial wastewater emission intensity industrial economic growth sustainable development green total factor productivity driving factor production-theoretical decomposition analysis (PDA) slack-based measure (SBM) |
author_facet |
Yongyi Cheng Liheng Lu Tianyuan Shao Manhong Shen Laiqun Jin |
author_sort |
Yongyi Cheng |
title |
Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach |
title_short |
Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach |
title_full |
Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach |
title_fullStr |
Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach |
title_full_unstemmed |
Decomposition Analysis of Factors Affecting Changes in Industrial Wastewater Emission Intensity in China: Based on a SSBM-GMI Approach |
title_sort |
decomposition analysis of factors affecting changes in industrial wastewater emission intensity in china: based on a ssbm-gmi approach |
publisher |
MDPI AG |
series |
International Journal of Environmental Research and Public Health |
issn |
1660-4601 |
publishDate |
2018-12-01 |
description |
This paper investigated the factors driving the changes in industrial wastewater emission intensity (IWEI) across provinces in China. To do this, we proposed a Super-efficiency Slacks-based Measure-Global Malmquist Index (SSBM-GMI) to decompose the change in IWEI into the effects from efficiency change (ECE), technological change (TCE), capital⁻wastewater substitution (KWE) and labor⁻wastewater substitution (LWE). The method was applied to conduct an empirical study using Chinese provincial data from 2003⁻2015. The main findings include the following: firstly, TCE was the dominant driving force behind the reduction in IWEI with an average annual contribution of −6.4% at the national level, followed by KWE (−5.3%), LWE (−1.8%) and ECE (1.2%). Secondly, significant differences exist in the driving factors behind the reduction in IWEI across regions. The reduction in IWEIs in the Northeast area and the Great Northwest area was mainly driven by productivity growth, while the reduction in IWEIs in the other areas was mainly driven by factor substitution. Thirdly, the shortage of KWE and LWE has impeded IWEI reduction in the Great Northwest area, the Middle Reaches of the Yellow River, the Northeast area and the North area. Finally, some particular policy implications were also recommended for reducing industrial wastewater emission in China. |
topic |
industrial wastewater emission intensity industrial economic growth sustainable development green total factor productivity driving factor production-theoretical decomposition analysis (PDA) slack-based measure (SBM) |
url |
https://www.mdpi.com/1660-4601/15/12/2779 |
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