How Does Energy Misallocation Affect Carbon Emission Efficiency in China? An Empirical Study Based on the Spatial Econometric Model

Abstract

As an essential factor of production, energy is receiving increased attention. Yet, other than some fundamental policy suggestions towards China’s energy issues, there have been very few investigations into energy misallocation so far. The measurements of energy misallocation index and carbon emission efficiency were made based on the panel data from 30 provinces in China. To empirically study the impact of energy misallocation on carbon emission efficiency, a spatial econometric model was built. It is found that during the survey period, there was a certain degree of energy misallocation in all regions of China, and the differences between the regions were obvious. There is an inverted U-shaped relationship between the impact of energy misallocation and carbon emission efficiency in which intensified allocation distortion accelerates the arrival of the critical point that is not conducive to energy conservation and emission reduction. The results viewed by regions show that due to a low degree o*f misallocation, the impact of carbon emission efficiency in the east region is positive, while that of the central and west regions are mostly negative. Accordingly, it is necessary to accelerate the marketization process of the energy market and improve the ecological quality.

Does Renewable Energy Consumption Successfully Promote the Green Transformation of China’s Industry?

“…Threshold variable: Energy misallocation(τ). This paper measures the regional energy misallocation index by calculating energy output elasticity and energy price distortion coefficient [27][28][29]. The specific calculation steps are provided in the Abbreviations.…”

Analysis of Regional Differences and Influencing Factors on China’s Carbon Emission Efficiency in 2005–2015

“…SBM has been widely applied to evaluate carbon emissions efficiency and abatement potential recently. Chu and Geng et al in 2019 applied the SBM to measure the carbon emission efficiency in 30 provinces of China from 2005 to 2017 [11]. Some other scholars also have conducted relevant research using SBM DEA model [21,43,44].…”

“…This paper investigated 30 provinces, municipalities, or autonomous regions (except Tibet) in China from 2005 to 2015. We selected the annual data of capital stock, labor force, and energy consumption as three inputs according to production processes and the prior research results [6,11,21,43,44]. We treated gross domestic product (GDP) as a desirable output and CO 2 emission as an undesirable output.…”

“…Their evidence is also consistent with the recent finding on the regional low-carbon economic development by Chu and Geng et al in 2019. The recent study also showed that the eastern region still had a higher degree of low-carbon economic development than the central and western regions [11]. Zhong et al in 2012 also discovered that China's total-factor carbon emission performance contains significant regional characteristics, and low carbon emission performance in the central and west regions [12].…”

“…This paper calculated the carbon emissions from seven types of fossil energy, such as coal, coke, gasoline, kerosene diesel, fuel oil, and natural gas referring to the National Greenhouse Gas Emissions Inventory introduced by IPCC in 2006. The types of the fuels are classified according to the prior research results [6,8,11,20]. The formula for calculating CO 2 emissions from fossil fuels is [62]…”