Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers
Zixiang Weia b, Botang Hana b, Xiuzhen Pana b, Muhammad Qaiser Shahbaza, Muhammad Wasif Zafarc✉
- aSchool of Management and Economics, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
- bSustainable Development Research Institute for Economy and Society of Beijing, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing 100081, China
- cCollege of Management, Shenzhen University, Shenzhen 518060, China
- ✉Corresponding author
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Abstract
Unparalleled, wide-spread, innovative, even intrusive are all words regularly used to describe the tremendous growth that has seen China has a well-established manufacturing system. It happened so quickly that it is often easy to lose sight of the factors that led to this success and, moreover, the costs that may have been paid by the environment. The burgeoning “Made in China 2025” strategy is firmly based on the premise of modernizing manufacturing and becoming a mode for environmentally-friendly practice. But these are goals that cannot reasonably be separated from the need to improve total factor energy efficiency (TFEE) across the manufacturing. Therefore, we investigated the impact of foreign direct investment (FDI) and trade on the TFEE of China's manufacturing at the sub-sector level. Specifically, we assessed capital stocks with a heterogeneous non-fixed depreciation method and used multi stochastic frontier analysis (SFA) models with linear-form inefficient variables to measure credited TFEE in 26 sectors of manufacturing from 2000 to 2016. To deepen our analysis, we also conducted an overall and period-by-period analysis with a modified STRIPAT model and feasible generalized least squares (FGLS) estimation. Our analysis shows an average TFEE of 0.7471 for China's manufacturing, but with several significant differences between the 26 sectors. Trade and FDI spillovers showed an overall increase across the period, with the highest export elasticity at 0.0607%. High-tech industries were generally quite efficient, while the elasticity coefficient of 0.0276% shows that increasing imports is an effective method of improving TFEE for energy-intensive sub-sectors. The regression analysis by periods reveals that the positive effect of imports gradually improved over time but, of the three FDI spillover effects modeled, only backward spillovers had a positive impact.