Domestic R&D activities, technology absorption ability, and energy intensity in China

By Junbing Huang, Xiang Chen. 2020

84 citations recorded by the source corpus.

Domestic research and development (R&D) activities are critical for the development of China's low-carbon economy. The higher level of R&D inputs, the more advanced technology will generate, therefore contributing to the energy intensity reduction. In empirical studies, the effect of R&D activities on energy intensity has been investigated extensively, however, most studies consider R&D activities as a whole. Consequently, we lack detailed information on the role of each R&D player and stage for appropriate policy consideration. Furthermore, the effects of R&D activities may be determined by factors affecting technology absorptive ability. To understand the influence of R&D activities on energy intensity, we employ linear and nonlinear analyses using a Chinese provincial dataset covering 2000–2016. The linear analysis suggests that domestic R&D is powerful in reducing energy intensity. However, this positive effect is mainly from experimental and developmental R&D activities rather than basic R&D and application activities. Further, R&D activities by industrial enterprises have a stronger effect on energy intensity reduction than those of higher education and independent R&D institutions. Additional study using panel threshold models suggests that the effects are not linear but experience structural breaks when human capital stock and full-time equivalent (FEP) R&D personnel are at different levels.

Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/37889d1f299296e77a067d1a6d734b6ea993084c

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In Economics and Econometrics

1. Kun Yang
2. Liang Liu
3. Jun Liu
4. Hidemichi Fujii

In Environmental Engineering

1. Kun Yang
2. Liang Liu
3. Jun Liu
4. Hidemichi Fujii

In Renewable Energy, Sustainability and the Environment

1. Kun Yang
2. Liang Liu
3. Jun Liu
4. Hidemichi Fujii

Citations in the corpus

• Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel (2021, background): “Therefore, identifying the factors that drive energy intensity in China has become a subject of interest to researchers and to the government in recent years, and clarifying the related influencing factors is helpful for making more effective energy policies (Huang and Chen, 2020).”