Interprovincial two-stage water resource utilization efficiency under environmental constraint and spatial spillover effects in China

Zhao, Liangshi; Sun, Caizhi; Liu, Fengchao

doi:10.1016/j.jclepro.2017.06.252

Cited by 87 publications

(44 citation statements)

References 22 publications

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“…It should be noted that water efficiency analysis aims to not only evaluate the water efficiency of regions, but also reveal determinants for regional differences so that policymakers could focus on those factors when formulating policies and measures to improve water efficiency. Literature on the analysis of factors influencing water efficiency is abundant [15,[37][38][39][40][41][42][43]. For instance, Ding et al [42] and Wang et al [43] both utilized the DEA-Tobit model to investigate water use efficiency and its contributing factors in China.…”

Section: Introductionmentioning

confidence: 99%

“…Despite its strengths, DEA is a nonparametric technique that does not take statistical noises into consideration, which may make the results very sensitive to data quality and even result in biased efficiency estimates [44]. Besides, DEA cannot analyze the influencing factors of technical efficiency directly, so researchers have to adopt two-step methods such as the DEA-Tobit model to study water efficiency and its determinants [37][38][39][40][41][42][43]. In view of the deficiency of DEA in this field, some scholars have chosen the stochastic frontier Water 2018, 10, 1286 3 of 15 analysis (SFA) approach based on distance function to study technical efficiency and its influencing factors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Re-Examining Regional Total-Factor Water Efficiency and Its Determinants in China: A Parametric Distance Function Approach

Zheng

Zhang

Xing

2018

Water

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It is accepted that improving water efficiency is a key task for China in achieving water sustainability, as the knowledge of water efficiency and its determinants can provide critical information for water policy formulation. To this end, this paper presents a parametric frontier approach to analyze water efficiency performance and its influencing factors in one step. The proposed approach first introduces the Shephard water distance function to construct total-factor water efficiency (TFWE) index and then adopts the stochastic frontier analysis (SFA) technique to compute the index and its determinants. A case study of regions in China from 2000 to 2015 is presented. The main findings are summarized as follows: (1) Both the overall China and most of the regions still have room for improvement in water efficiency. SFA and data envelopment analysis (DEA) might lead to different results in benchmarking water efficiency. Moreover, SFA has higher discriminating power than DEA in this regard. (2) There exists significant disparity of water efficiency among the regions of China, and the difference in TFWE takes on a U-shaped evolution trend, which first decreases in a fluctuation way and then increases monotonically. (3) Factors like industrial structure, import and export trade, environmental regulation and urbanization level have a positive impact on water efficiency, while resource endowment and economic level exhibit negative and nonlinear effects, respectively. Finally, several policy recommendations are made to improve water efficiency levels and promote water sustainability.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Re-Examining Regional Total-Factor Water Efficiency and Its Determinants in China: A Parametric Distance Function Approach

Zheng

Zhang

Xing

2018

Water

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“…Later, many studies began to divide the industrial water consumption process into two stages, namely, the water consumption stage and wastewater treatment stage, to truly reflect the actual process of industrial water consumption. Since then, many studies have applied the same concept to obtain detailed results [11][12][13]. Most studies, though, have focused on the hierarchical relationship between the industrial water consumption stage and wastewater treatment stage.…”

Section: Of 17mentioning

confidence: 99%

Does Urbanization Improve Industrial Water Consumption Efficiency?

Liu

Hou

et al. 2019

Sustainability

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Although some studies have focused on the logical connection between industrial water consumption in the industrial economic development (IED) and industrial wastewater treatment (IWT) stages, the master–slave game relationship between these stages has not been considered. This study selected panel data from 30 provinces in China from 2011 to 2015, divided these provinces into IED- and IWT-dominated regions, and developed a two-stage data envelopment analysis (DEA) model based on the master–slave game relationship between the IED and IWT stages. In addition, a regression model based on the Simar–Wilson approach was constructed to reveal the effects of urbanization on industrial water consumption efficiency. The results show that the industrial water consumption efficiency in China slightly fluctuated from 2011 to 2015, and there was no significant efficiency improvement. The efficiency of the IED stage was generally higher than that of the IWT stage, and the efficiency gap between stages was smaller in IED-dominated regions than in IWT-dominated regions. Urbanization has different effects on industrial water consumption efficiency, and the same factor can have significantly different effects in different regions. Some policy implications are proposed for the different types of regions.

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“…To sum up, water shortage, water pollution and poor water management have seriously threatened the sustainable development of YREB, and thus it is imperative to take powerful commitments to rectify this passive situation. In this context, improving water use efficiency and reducing wastewater emissions, have been recognized as two better ways to alleviate the ongoing water crisis and support sustainable development in the YREB [4,5]. Therefore, it is of considerable importance to scientifically measure the water use efficiency incorporating wastewater emissions (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Deng et al [6] employed SBM-DEA model to evaluate water use efficiency of 31 provinces in China with the sewage as undesirable output. Zhao et al [5] adopted two-stage SBM model to estimate water resource utilization efficiency with taking environmental constraint into account and investigated the spatial spillover effect. Song et al [17] applied Malmquist-Luenberger productivity index to measure provincial water resource efficiency in China and used panel Tobit model to explore the factors that affect water resource efficiency.…”

Section: Introductionmentioning

confidence: 99%

Investigating the spatiotemporal differences and influencing factors of green water use efficiency of Yangtze River Economic Belt in China

et al. 2020

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Combining freshwater consumption and wastewater emissions into a unified analysis framework and utilizing the epsilon-based measure (EBM) model with the characteristics of radial model and non-radial model, this paper evaluates green water use efficiency (GWUE) of 11 provincial-regions in the Yangtze River Economic Belt (YREB) and investigates its spatiotemporal differences during the period 2005-2014, on basis of which the contribution rate of each input-specific green water use inefficiency in the overall green water use efficiency and the potential of freshwater-saving and wastewater emissions reduction are also calculated. The Theil index is used to explore the sources of the provincial gap of green water use inefficiency, and a random-effect panel Tobit model is applied to test the impact of the influencing factors of green water use inefficiency in the YREB. It is found that green water use inefficiency of the YREB is relatively low and regional differences is significant during the sample period, indicating a large potential of water-saving and water pollution reduction, and narrowing BGAP and WGAP of the Upstream is the key for improving green water use inefficiency in the YREB. The panel Tobit regression results show that economic development, technological innovation, water use structure, water resources endowment, environmental regulation and regional differences all play positive/negative effects on green water use inefficiency in the YREB, while these factors' influencing direction, degree and significance are significantly different. The conclusions of our study can provide considerably valuable information for the YREB to reserve water resources and reduce wastewater emissions.

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Interprovincial two-stage water resource utilization efficiency under environmental constraint and spatial spillover effects in China

Cited by 87 publications

References 22 publications

Re-Examining Regional Total-Factor Water Efficiency and Its Determinants in China: A Parametric Distance Function Approach

Re-Examining Regional Total-Factor Water Efficiency and Its Determinants in China: A Parametric Distance Function Approach

Does Urbanization Improve Industrial Water Consumption Efficiency?

Investigating the spatiotemporal differences and influencing factors of green water use efficiency of Yangtze River Economic Belt in China

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