A Study on the Effects of Energy and Environmental Efficiency at China’s Provincial Level

Ma, Liang-Han; Hsieh, Jin-chi; Chiu, Yung‐ho

doi:10.3390/en12040591

Cited by 9 publications

(4 citation statements)

References 19 publications

(46 reference statements)

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“…The abovementioned wastewater discharge (WD), COD, other major pollutants (OMP) are bad outputs. We refer to Hsieh et al and Ma et al [26,27] to adjust bad outputs, as good output variables, and utilize the maximum emission value of each bad output in all DMUs as the base; whereby the adjustment value equals (maximum value of DMUs -original emissions value of each DMU) + 1 to become good outputs. These results illustrate the relationships among rapid economic growth, water resources' use policy, and environmental degradation in China at the provincial level, thus spurring local governments to make a careful assessment of appropriate related policies when actively targeting economic development at the same time.…”

Section: Introductionmentioning

confidence: 99%

Assessing China’s Use Efficiency of Water Resources from the Resampling Super Data Envelopment Analysis Approach

Hsieh

Chiu

2019

Water

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Water resources’ use efficiency is an important issue under China’s rapid economic growth. This is because some provinces’ economic development may be delayed due to lack of adequate water resources. Whereas, high economically developed provinces may overuse water resources in order to achieve their economic goals; while also creating a large amount of pollutants. To assess water resources’ use efficiency from the resampling super data envelopment analysis (DEA) approach, our research comprehensively utilizes the following as inputs and outputs: (1) water resources: supply of water (SW), per capita water consumption (PCWC), and total water resources (TWR); (2) economic development: gross domestic product (GDP); (3) environmental issues: governance wastewater investment (GWI), wastewater discharge (WD), chemical oxygen demand (COD), and other major pollutants (OMP). The results show that Tibet, Beijing, Guangdong, Qinghai, Shandong, Sichuan, Yunnan, Tianjin, Jiangsu, and Henan have relatively good water resources’ use efficiency with efficiency values larger than 1. The best efficiency is in 2015, while the worst is in 2017. Water resources’ use efficiency shows significant regional differences in 2013–2017, with the best average efficiency value in southwest China (1.4355) and the worst in north China (0.2987). The results of the Wilcoxon test present that PCWC, GDP, COD, and OMP exhibit very significant differences, PN and WD have significant differences, and SW and TWR have no significant influence. These results imply that China’s regional governments must formulate a better water resource strategy based on the water resource distribution of each region. Lastly, the emissions of environmental pollutants must be strictly monitored.

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Section: Introductionmentioning

confidence: 99%

Assessing China’s Use Efficiency of Water Resources from the Resampling Super Data Envelopment Analysis Approach

Hsieh

Chiu

2019

Water

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“…In order to evaluate the GEEE and energy environmental productivity change (EEPC), we took capital stock and labor as non-energy input x , energy consumption as energy input e , actual regional GDP as desirable output g [ 16 , 39 ], and three waste emissions as undesired output b . The selection and processing of input-output indicators are as follows:…”

Section: Methodsmentioning

confidence: 99%

Energy and Environment Performance of Resource-Based Cities in China: A Non-Parametric Approach for Estimating Hyperbolic Distance Function

Yan

Chen

2020

IJERPH

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Scientific determination of energy and environmental efficiency and productivity is the key foundation of green development policy-making. The hyperbolic distance function (HDF) model can deal with both desirable output and undesirable output asymmetrically, and measure efficiency from the perspective of “increasing production and reducing pollution”. In this paper, a nonparametric linear estimation method of an HDF model including uncontrollable index and undesirable output is proposed. Under the framework of global reference, the changes of energy environmental efficiency and productivity and their factorization of 107 resource-based cities in China from 2003 to 2018 are calculated and analyzed. With the classification of resource-based cities by resource dependence (RD) and region, we discuss the feature in green development quality of those cities. The results show that: (1) On the whole, the average annual growth rate of energy and environmental productivity of resource-based cities in China is 2.6%, which is mainly due to technological changes. The backward of relative technological efficiency hinders the further growth of productivity, while the scale diseconomy is the main reason for the backward of relative technological efficiency. (2) For the classification of RD, the energy and environmental efficiency of the high-dependent group are significantly lower than the other two, and the growth of productivity of the medium-dependent group is the highest. (3) In terms of classification by region, the energy and environmental efficiency of the eastern region is the highest, and that of the middle and western regions is not as good as that of the eastern and northeastern regions. The middle region shows the situation of “middle collapse” in both static efficiency and dynamic productivity change, and the main reason for its low productivity growth is the retreat of relatively pure technical efficiency. This conclusion provides practical reference for the classification and implementation of regional energy and environmental policies.

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“…Chen and Jia (2017) used SBM by considering undesired output in order to measure environmental efficiency of different regions in China. Ma et al (2019) employed the DN‐DEA method to evaluate and analyze China's energy efficiency and environmental efficiency from 2014 to 2017 and found that annual energy efficiency is higher than environmental efficiency. Xu et al (2021) measured the environmental efficiency of China's heavily polluting industries from both dynamic and static perspectives using SBM and considering undesired outputs and the Malmquist index (MI).…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of quality of life on industrial and agricultural production and environmental efficiency in China's provinces

Chiu

Chang

2022

Manage Decis Econ

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While most related topics focus on industrial production, economics, and environmental pollution, few studies discuss industrial production, economic development, environmental pollution, and quality of life together, and those that do fail to recognize how QoL influences agriculture and industry development issues. This research thus takes QoL as an exogenous variable and places agricultural production efficiency and industrial production efficiency as two parallel stages into one stage. The finding is that its addition modifies the overall efficiency of the region, as none of the 30 provinces has reached the efficiency frontier, and there is room for improvement in all of them.

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A Study on the Effects of Energy and Environmental Efficiency at China’s Provincial Level

Cited by 9 publications

References 19 publications

Assessing China’s Use Efficiency of Water Resources from the Resampling Super Data Envelopment Analysis Approach

Assessing China’s Use Efficiency of Water Resources from the Resampling Super Data Envelopment Analysis Approach

Energy and Environment Performance of Resource-Based Cities in China: A Non-Parametric Approach for Estimating Hyperbolic Distance Function

The impact of quality of life on industrial and agricultural production and environmental efficiency in China's provinces

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