A complete total-factor CO2 emissions efficiency measure and “2030•60 CO2 emissions targets” for Shandong Province, China

Li, Shuangjie; Diao, Hongyu; Wang, Liming; Li, Li

doi:10.1016/j.jclepro.2022.132230

Cited by 20 publications

(9 citation statements)

References 51 publications

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“…This requirement is beyond the ability of the classical DEA model. 29,30 For undesirable output indicators, common approaches include converting the undesirable output into inputs for the production function 31 and converting undesirable output into desirable output, but these methods are inconsistent with production function theory. Another approach is to calculate desirable and undesirable outputs separately and then take their ratios.…”

Section: Performance Analysis Methodsmentioning

confidence: 99%

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Total‐factor generation performance analysis of China's thermal power industry using meta‐frontier nonradial distance function approach

Meng

Pang

2023

Energy Science & Engineering

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Thermal power is the main source of China's electricity supply. Improving total‐factor generation performance (TFGP) is essential for the development of this industry in the current deteriorating operating environment. This study adopts the meta‐frontier nonradial direction distance function approach to measure the static and dynamic TFGPs of the thermal power industry in China's 30 provinces in 2011–2019, and then discusses the regional distribution characteristics and the impact factors using spatial econometric model and Tobit regression method, respectively. Empirical results show that: (I) The TFGPs in central and west China are relatively close, but both are remarkably lower than that in east China. (II) The TFGPs in central and west China have generally remained stable since 2011, whereas that in west China has declined mainly because this region is more susceptible to the situation of electricity supply‐demand. (III) A significant spatial positive correlation exists among provincial TFGPs. High TFGP provinces are mostly in the eastern seaboard region and low TFGP provinces are in southwest China. (IV) Economic development, power structure, fuel prices, and environmental regulation have positive impacts on China's TFGP, while the impacts of technological innovation and energy endowment are not significant.

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Section: Performance Analysis Methodsmentioning

confidence: 99%

“…However, different from the aforementioned research objects, the thermal power industry has nonnegligible undesirable outputs (e.g., CO 2 ), which should be introduced into the TFGP measurement. This requirement is beyond the ability of the classical DEA model 29,30 …”

Section: Literature Reviewmentioning

confidence: 99%

Total‐factor generation performance analysis of China's thermal power industry using meta‐frontier nonradial distance function approach

Meng

Pang

2023

Energy Science & Engineering

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“…The primary sources of data used in the study are the "China Industrial Statistics Yearbook", "China Urban Statistics Yearbook", various provincial and municipal statistical yearbooks, and China's Carbon Emissions Accounts and Datasets (CEADs). In this paper, drawing on the selection of input-output variables by Li and colleagues [29], we consider industrial gross output as the desirable output and CO 2 emissions as the undesirable output. The inputs include capital stock, labor, and energy consumption.…”

Section: Datamentioning

confidence: 99%

A Slacks-Based Measure Model for Computing Game Cross-Efficiency

Huang,

Li,

Liu

et al. 2024

Systems

Self Cite

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This paper introduces an improved slack-based game cross-efficiency measurement model that enhances the existing cross-efficiency framework and integrates it with the Data Envelopment Analysis (DEA) game cross-efficiency. The model ensures the fairness of its results through the implementation of a more stringent selection of frontier face weights. It accounts for the competitive relationships among Decision Making Units (DMUs), achieving a Nash equilibrium solution through continuous iterations. Furthermore, the model accounts for undesirable outputs and various strategic orientations, enhancing its applicability. The model’s effectiveness is validated through comparative analyses of diverse case studies. Additionally, the model’s practical utility is demonstrated through the analysis of industrial data from various Chinese provinces between 2010 and 2019. Analysis results show that the proposed model measures production efficiency with greater precision and comparability than alternative models.

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“…Nevertheless, certain scholars argue that the existing system of input-output variables does not conform to the actual production process, and the inconsistency between the input value and value-added measures will make the efficiency deviate from the actual value. Therefore, the existing input-output variables of TFCEE were refined by S. Li et al (2022), and the SBM-DEA model was introduced to evaluate the TFCEE of 17 cities in a survey of Shandong Province, China, from 2006 to 2017.…”

Section: Measurement Of Ceementioning

confidence: 99%

Exploring the impact of renewable energy investment and energy resource endowment on carbon emission efficiency: A spatial econometric analysis based on 60 BRI countries

Yuan

Wang

et al. 2022

Preprint

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With climate change caused by massive greenhouse gas emissions emerging as an issue of global concern, it is urgent to improve carbon emission efficiency (CEE) for countries along the Belt and Road (BRI). The super-efficiency slacks-based measure (SBM) model is adopted to evaluate the CEE of 60 BRI countries from 2010 to 2019, while the Global Malmquist-Luenberger (GML) index, Theil index, and coefficient of variation (CV) are coupled to quantify the spatial and temporal variation and dynamic evolution of CEE. Subsequently, the spatial Durbin model (SDM) provides an empirical investigation regarding the impact of renewable energy investment and energy resource endowment on CEE given the spatial spillover effect. It is found that (1) From a static perspective, the CEE of BRI countries is generally poor and unevenly distributed in terms of temporal and spatial dimensions. The regional variation of CEE in Southeast Asia is narrowing, while it is widening in other regions. (2) Referring to the dynamic level, the GML index is featured U-shaped fluctuations, and both technical efficiency and technological progress contribute to the improvement of CEE in BRI countries. (3) The CEE of BRI countries exhibits significant spatial dependence, with high-high aggregation as well as low-low aggregation. (4) There is a significant positive influence of renewable energy investment on CEE in the country and neighboring countries, while energy resource endowment presents a remarkable adverse correlation. Consequently, it is suggested that the inter-regional cooperation among BRI countries should be strengthened to reinforce renewable energy investment, exert the technology and knowledge spillover effect sufficiently, and break the resource curse in the environmental field.

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A complete total-factor CO2 emissions efficiency measure and “2030•60 CO2 emissions targets” for Shandong Province, China

Cited by 20 publications

References 51 publications

Total‐factor generation performance analysis of China's thermal power industry using meta‐frontier nonradial distance function approach

Total‐factor generation performance analysis of China's thermal power industry using meta‐frontier nonradial distance function approach

A Slacks-Based Measure Model for Computing Game Cross-Efficiency

Exploring the impact of renewable energy investment and energy resource endowment on carbon emission efficiency: A spatial econometric analysis based on 60 BRI countries

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