Zheming Yan

Bio: Zheming Yan is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Economics & Energy consumption. The author has an hindex of 4, co-authored 6 publications receiving 151 citations. Previous affiliations of Zheming Yan include Shaanxi Normal University.

Urban Residential Energy Demand and Rebound Effect in China: A Stochastic Energy Demand Frontier Approach

Abstract: China is at the stage of rapid urbanization. The residential energy consumption has been dramatically increasing with the substantially rising population in urban regions. To combat climate change, China has made ambitious plans for energy demand control and energy conversion, including the control over residential energy consumption. According to those plans, one of the fundamental ideas is to improve energy use efficiency through different measures. However, the existence of the energy rebound effect might make the achievement of energy-use reduction plans in the residential sector full of uncertainty. Thus, estimating the energy rebound effect in China’s urban residential sector is of importance for designing effective energy-saving policies. Also, China is a vast country with evident uneven development levels of regional economies. This motivates us to uncover the regional differences regarding the energy rebound effects, in order to understand the rebound effect in China’s residential sector more profoundly and to provide some policy references for implementing the region-specific measures of energy conservation. Based on the pioneering contribution of Orea et al. (2015) in the methodology, we estimate the energy efficiency and rebound effect in the urban residential sector for China’s 30 provincial-level regions using an adapted stochastic frontier model, i.e., the stochastic energy demand frontier approach. This approach can simultaneously estimate the energy efficiency and energy rebound effect by one step. Thus, we can be free from the restrictions in the methods using price elasticity or using the proxy of energy efficiency change to improve the estimated accuracy of the rebound effect. Furthermore, we examine the influencing factors of residential energy consumption and identify the determinants of the rebound effect. The results show that residents’ income level, temperature deviation, population scale, and household size are positively correlated with urban residential energy consumption. On the contrary, the district heating system, energy price, and technology progress contribute to reducing residential energy consumption. Regarding the energy rebound effect, an inverted U-shaped relationship between residents’ income level and rebound-effect size exists. Additionally, we find that energy price is negatively correlated with the rebound effect. Regarding the magnitude of the rebound effect, the estimated values vary to a large extent across provinces and regions, with the first, median, and third quartiles approximately equal to 40%, 70%, and 95%, respectively. By grouping provincial-level regions based on their time average values of the rebound effect, we find the group with the largest rebound effect only consists of eastern and developed provincial-level regions. In contrast, the group with the smallest rebound effect mainly consists of northwest and northeast provincial-level regions that are relatively poor. Furthermore, there is an evident “north-south” difference in the rebound effect size. For instance, the central north region and central south region are geographically nearby regions and similar in both the level and growth rate of residential income. However, the average regional size of the rebound effect increases to a large extent from the central north (42.19%) to the central south (70.32%).

The role of green production process innovation in green manufacturing: empirical evidence from OECD countries

Abstract: ABSTRACT Under the climate change background, green manufacturing is a critical path to realizing a low-carbon economy. The role of green products from manufacturing in economy-wide green transition has been discussed in the literature. In contrast, innovation in the industrial process, an important driver of climate change, has seldom been studied. This paper investigates the impact of green production process innovation on green manufacturing production using a fixed-effect SFA model. Furthermore, we discuss whether the impact of green production process innovation is conditioned on the economic development level, using a newly developed partial linear functional model. The results show that green production process innovation benefits green manufacturing, promoting sectoral carbon and energy efficiency. This paper further proposes policy implications, based on the findings that the green production process innovation’s marginal effects vary with economic development level.