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Spatial–temporal modeling of inside and outside factors on energy intensity: evidence from China

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Abstract

As geographic limitation has gradually vanished, many economic activities occurred with apparent spillover on the neighboring regions. To study other social pressures on energy consumption considering spatial spillover effects, this paper constructs STIRPAT spatial model to investigate the relationship among energy intensity, foreign direct investment (FDI), economic growth, population scale, and technology progress in the case of 30 provinces in China over the period of 2001–2016. Spatial correlation test methodologies are applied, and STIRPAT spatial Durbin model (SDM) is preferred to describe the pushing-in and pushing-out effects among regions. We find that there is obvious spatial spillover of energy intensity; economic growth, industrial development, and population scale positively relate to energy intensity in local regions; technology progress is an effective way for energy conservation; the spillover effects of global domestic production (GDP), population size, and technology in adjacent regions are significant on local energy consumption; in China, FDI inflows into the local and neighboring regions negatively affect energy intensity, indicating that FDI would release the pressure of energy consumption.

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Data are available from the China provincial statistical yearbook or can be obtained from authors.

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Acknowledgments

All tables and figures are made by the authors.

Funding

This work was funded by the following projects: National Natural Science Foundation of China (Project No. 71571046) and Fujian College’s Research Base (Project No. IIRC20180104).

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ZLT conducted the quantitative analyses and composed the paper. YAZ guided the direction and ideas. All authors read and approved the final manuscript.

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Correspondence to Azhong Ye.

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The authors declare that they have no competing interests.

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Responsible editor: Muhammad Shahbaz

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Zeng, L., Ye, A. Spatial–temporal modeling of inside and outside factors on energy intensity: evidence from China. Environ Sci Pollut Res 26, 32600–32609 (2019). https://doi.org/10.1007/s11356-019-06401-6

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