The influence of local officials' promotion incentives on carbon emission in Yangtze River Delta, China

Meng, Hao; Huang, Xianjin; Yang, Hong; Chen, Zhigang; Yang, Jun; Zhou, Yan; Li, Jianbao

doi:10.1016/j.jclepro.2018.12.036

Cited by 56 publications

(23 citation statements)

References 46 publications

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“…Kahn, Li and Zhao [12] found that officials' green performance appraisal system, including environmental governance indicators, incentivize local governors to increase their effort to reduce water. Meng et al [16] used the multiple linear regression model to determine the relationship between local officials' characteristics and total carbon emissions and carbon emissions from different sectors. The results showed that the promotion incentives, tenure and age of local officials have a significant impact on total carbon emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Liu

Zhang

Xu³

et al. 2021

Sustainability

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As for the academics and policymakers, more attention has been given to the issue on how to reduce environmental pollution through the cooperation of environmental regulation and local officials’ promotion incentives. With the use of a city-level panel data of 266 Chinese cities from 2005 to 2016, this study preliminary explores the impacts of environmental regulations, local officials’ promotion incentives, and their interaction terms on urban environmental pollution at national and regional levels by using the spatial Durbin model. The results indicate that the impacts of environmental regulations and local officials’ promotion incentives on urban environmental pollution have achieved the desired goal with the other’s cooperation, and their interaction term’s coefficients on urban environmental pollution are significantly negative. Moreover, spatial heterogeneity is established, and the uneven development of urban environmental pollution among different regions deserves more attention. In order to effectively reduce the level of urban environmental pollution in China, the government should focus on such solutions as enhancing the implementation and supervision efficiency of environmental regulation, optimizing the performance appraisal system of local officials, improving the synergistic effects of environmental regulations and local officials’ promotion incentives, and establishing a multi-scale spatial cooperation mechanism based on both geographical and economic correlations.

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Section: Literature Reviewmentioning

confidence: 99%

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Liu

Zhang

Xu³

et al. 2021

Sustainability

View full text Add to dashboard Cite

show abstract

“…Ma et al [33] further note that wealth, economic structure, energy structure, population structure, and the development of technology are also major influential factors of China's carbon emission. Meng et al [34] investigate the impact of local officials' promotion incentives on China's CO 2 emission. e results indicated the significant influence of age, tenure, and local officials' promotion sources on total CO 2 emissions.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting Carbon Emissions with Dynamic Model Averaging Approach: Time-Varying Evidence from China

Zhang

Chen

2020

Discrete Dynamics in Nature and Society

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Although energy-related factors, such as energy intensity and energy consumption, are well recognized as major drivers of carbon dioxide emission in China, little is known about the time-varying impacts of other macrolevel nonenergy factors on carbon emission, especially those from macroeconomic, financial, household, and technology progress indicators in China. This paper contributes to the literature by investigating the time-varying predictive ability of 15 macrolevel indicators for China’s carbon dioxide emission from 1982 to 2017 with a dynamic model averaging (DMA) method. The empirical results show that, firstly, the explanatory power of each nonenergy predictor changes significantly with time and no predictor has a stable positive/negative impact on China’s carbon emissions throughout the whole sample period. Secondly, all these predictors present a distinct predictive ability for carbon emission in China. The proportion of industry production in GDP (IP) shows the greatest predictive power, while the proportion of FDI in GDP has the smallest forecasting ability. Interestingly, those Chinese household features, such as Engel’s coefficient and household savings rate, play very important roles in the prediction of China’s carbon emission. In addition, we find that IP are losing its predictive power in recent years, while the proportion of value-added of the service sector in GDP presents not only a leading forecasting weight, but a continuous increasing prediction power in recent years. Finally, the dynamic model averaging (DMA) method can produce the most accurate forecasts of carbon emission in China compared to other commonly used forecasting methods.

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“…In the study of Jotzo and Pezzey [10], according to the expected GDP growth in different regions, a model of government low-carbon technology subsidies linked to GDP has been established. Part of the literature uses real corporate data and cases to verify the incentives of local officials' characteristics and government low-carbon technology subsidies for regional carbon emission reduction [11,12].…”

Section: Introductionmentioning

confidence: 99%

Incentive Contract Design considering Fairness Preferences and Carbon Emission Reduction Multiobjective Tasks

Zhu

Cao

2021

Mathematical Problems in Engineering

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Considering the multitargets of corporate carbon emission reduction and the fairness preference psychology of the company, a government incentive model for corporate carbon emission reduction was constructed. The impact of corporate fairness preferences on government carbon emission reduction incentive strategies is studied. In addition, numerical simulation is used to analyze the impact of changes in correlation coefficients, fairness preference coefficients, and discount rates on the optimal enterprise effort coefficient and the government optimal incentive coefficient. Research shows that the degree of fairness preference of a company has a direct impact on the degree of corporate effort, while the discount rate will only have an impact on the company’s long-term effort. In order to improve corporate carbon emission reduction efforts, the government must not only consider the impact of fairness preference on corporate efforts but also flexibly adjust the incentive coefficient of long-term and short-term tasks based on the discount rate.

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The influence of local officials' promotion incentives on carbon emission in Yangtze River Delta, China

Cited by 56 publications

References 46 publications

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

How Promotion Incentives and Environmental Regulations Affect China’s Environmental Pollution?

Forecasting Carbon Emissions with Dynamic Model Averaging Approach: Time-Varying Evidence from China

Incentive Contract Design considering Fairness Preferences and Carbon Emission Reduction Multiobjective Tasks

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