Semantic Scholar Open Access 2019 238 sitasi

Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach

Shaojian Wang Jingyuan Zeng Xiaoping Liu

Abstrak

Abstract Whilst a plethora of literature has viewed technological progress as one of the critical influencing factors in relation to energy consumption and CO2 emissions, little effort has been made to identify the sectoral differences in the relationship between technological progress and CO2 emissions. Thereby, this paper remedies the inadequacies in the extant literature by empirically investigating the impact of technological progress on CO2 emissions, specifically taking into account its heterogeneous effect in various economic sectors. This paper first decomposes the effect of technological progress as taking place in heavy industry, in light industry, in construction industry, and in service industry. A panel quantile regression approach and a balanced city panel data model are then applied, covering the period 2001–2013 in China. The empirical results show that technological progress in heavy industry and light industry surprisingly facilitates a higher level of CO2 emissions, despite its prominent contribution to energy efficiency improvement. Meanwhile, as distinct from the effect it shows in the heavy and light industries, technological progress in construction and service industries exerts a negative effect on CO2 emissions. Additionally, this paper further discovers that the strength of the multiple impacts of technological progress also varies with the level of emitters. By studying the heterogeneous effect brought about by technological progress in different economic sectors and emitters, this paper provides a comprehensive understanding of the relationship between CO2 emissions and technological progress.

Topik & Kata Kunci

Penulis (3)

S

Shaojian Wang

J

Jingyuan Zeng

X

Xiaoping Liu

Format Sitasi

Wang, S., Zeng, J., Liu, X. (2019). Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach. https://doi.org/10.1016/J.RSER.2018.12.046

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Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
Total Sitasi
238×
Sumber Database
Semantic Scholar
DOI
10.1016/J.RSER.2018.12.046
Akses
Open Access ✓