Government corruption, resource misallocation, and ecological efficiency

Wang, Shuhong; Zhao, Danqing; Chen, Hanxue

doi:10.1016/j.eneco.2019.104573

Cited by 159 publications

(52 citation statements)

References 52 publications

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“…In this regard, an increase in the rating of corruption of the country by 1% produces a decrease in environmental sustainability by 0.056%. Thus, for Southern African countries, it is quite evident that the harmonizing and congruent results contained in regression 1 and 2 by the GMM approach demonstrate that corruption practices degrade the natural environment in the short-term thereby in line with Wang et al (2020) and Candau and Dienesch (2017) surveys. For this study, it is also important to note that CORI (0.1069%) has the greatest impact on ENS than CORRA (0.056%).…”

Section: Findings About Correlations Of the Variablesmentioning

confidence: 60%

“…Moreover, transformations in institutional quality (proxy is corruption) generate less effect on energy and environmental policy. Wang et al. (2020) China 2006–2015 Ecological efficiency level (EFL); Resource misallocation (RM); Corruption cases (CC); Government regulation (GR); Logistics level (LL) and Industrial structure (IS).…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this regard, there is greater empirical literature that has established the reciprocal influence of corruption and the natural environment ( Akhbari and Nejati, 2019 ; Sinha et al., 2019 ; Wang et al., 2020 ; Candau and Dienesch, 2017 ). As such, evidence supports that corruption is one of the determining variables which impacts the procedure of natural environment preservation and lessening this cause has much influence on the rate of green economic development along with sustainability.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The influence of corruption on environmental sustainability in the developing economies of Southern Africa

Ganda

2020

Heliyon

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This paper analyses the impact of corruption on environmental sustainability in all 16 countries in the Southern region of Africa from 2010-2017. The paper uses two proxies of corruption: the Corruption Index and Corruption Ranking. Using two econometric methods, namely, the Dumitrescu and Hurlin (2012) Granger causality test and the Generalised Method of Moments (GMM) techniques this study found largely congruent results on both causation and relationships, respectively. Firstly, the two indicators of corruption harmoniously show that corruption Granger causes the existing state of environmental sustainability in Southern African economies, and vice-versa. Moreover, in the short-run corruption was also found to worsen environmental sustainability for both regression models deployed using the two corruption indicators. In the long-term, the two measures of corruption conflicted with their findings. In this regard, though the relationship is contradicting in the long-run the corruption negative (becoming bad) effect of corruption ranking surpasses the corruption positive (becoming clean) effect of corruption index by nearly three times. This show how detrimental corruptible actions are to the natural environment. Overall, this paper consent to global reports explaining how Southern African environments are gradually deteriorating by putting corruption as one central practice causing extensive damage.

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Section: Findings About Correlations Of the Variablesmentioning

confidence: 60%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The influence of corruption on environmental sustainability in the developing economies of Southern Africa

Ganda

2020

Heliyon

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“…Subsequently, Tone proposed a slacks-based measure (SBM) model to solve this problem well [20]. More and more scholars use SBM model to study environmental efficiency [21,22,23,24]. Xiao Chengming et al used SBM model to calculate that the EE of CMI fluctuates greatly and there is huge space for energy conservation and emission reduction [25];Zhou Yan used CCR model(DEA model under constant returns to scale) and improved SBM model to measure the EE of CMI, respectively, and found that the efficiency score measured based on improved SBM model was lower compared to that measured based on CCR model [26].…”

Section: Related Workmentioning

confidence: 99%

China’s Provincial Environmental Efficiency Evaluation and Influencing Factors of the Mining Industry Considering Technology Heterogeneity

Xia

Wang

et al. 2020

IEEE Access

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The mining industry has promoted the process of industrialization in China, and the current consumer demand for mineral products is still very large. Since the development of mineral resources has caused serious environmental pollution and waste of resources, the country has raised the development of green mining to a strategic level. Based on China's provincial data over the 2007-2016 period, this paper measured environmental efficiency (EE) of China's mining industry (CMI) using Meta-frontier slacksbased measure (SBM) method and reveals the root causes of environmental inefficiency (EI). Then, a panel Tobit regression model was established to discuss the differential impact of relevant factors on the metafrontier environmental efficiency (MFEE) of CMI in the regional heterogeneity perspective. The results show that: (1) The MFEE of CMI exhibits low score and there is significant regional heterogeneity, with the highest in Eastern China, followed by Central China, and Western China. (2) The technology gap ratio (TGR) in the three regions shows that Eastern China ranks the highest, followed by Central China, and Western China. TGI is the main contributor to the EI of CMI. (3) the overall MFEE of CMI, the MFEE of CMI in Eastern, Central and Western area are negatively related to the environmental regulation intensity, are positively related to the resource utilization rate, respectively. The economic development level, innovative ability, education level, industrial structure and state-owned capital proportion differently effect on China's overall EE of the mining industry and the EE of the mining industry in different regions of China, respectively. INDEX TERMS China's mining industry, environmental efficiency. technological heterogeneity, meta frontier SBM model, Tobit model

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“…Low EE due to resource misallocation leads to high emissions of sulfur dioxide (SO 2 ), soot, and suspended particulate matter (PM 2.5 ) (Bian et al, 2019). Wang et al (2020) used the provincial panel data from 2006 to 2015 in China to empirically study the impact of corruption and resource misallocation on ecological efficiency. The research concludes that corruption directly reduces ecological efficiency and intensifies resource misallocation, leading to a further decline in ecological efficiency.…”

Section: Literature Review and The Theoretical Influencing Mechanismmentioning

confidence: 99%

Does Anti-corruption Policy Influence Energy Efficiency in China?

et al. 2021

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The Chinese government has stepped up its anti-corruption efforts since 2013; the National Energy Administration (NEA), an energy regulatory agency, has been hard hit by corruption. This paper analyzes the impact of government corruption on energy efficiency (EE) from a perspective of energy regulations and also a mechanism of the impact of corruption on EE, and then adopts statistical methods to estimate the impact of corruption on EE in China. The results show that government corruption generally has a negative effect on EE in China. The establishment of dispatched energy regulatory agencies in eastern China can significantly reduce the adverse effects of corruption on EE. Furthermore, a single threshold effect was found between corruption and EE. Finally, based on the results of an empirical analysis, suggestions for a constructive policy are put forward.

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Government corruption, resource misallocation, and ecological efficiency

Cited by 159 publications

References 52 publications

The influence of corruption on environmental sustainability in the developing economies of Southern Africa

The influence of corruption on environmental sustainability in the developing economies of Southern Africa

China’s Provincial Environmental Efficiency Evaluation and Influencing Factors of the Mining Industry Considering Technology Heterogeneity

Does Anti-corruption Policy Influence Energy Efficiency in China?

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