| Title |
Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect |
| ID_Doc |
31783 |
| Authors |
Cui, HR; Wang, HR; Zhao, QZ |
| Title |
Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect |
| Year |
2019 |
| Published |
Greenhouse Gases-Science And Technology, 9, 3 |
| DOI |
10.1002/ghg.1874 |
| Abstract |
As an important evaluation transformation index, exploring green total factor productivity (GTFP) trend and related key factors is significant for China's economy entering into high-quality development and green transformation. In this study, stochastic frontier analysis (SFA) and kernel density function are used to evaluate GTFP growth trend for 36 China's industrial sectors during 2000-2016, and system generalized method of moment is used to explore their key driving factors. The results are as follows: First, SFA supplies efficient estimation for GTFP growth information. The 36 industrial sectors are classified into three emission types, that is, high-, moderate-, and low emission. Second, GTFP growth differs significantly in three types of sectors. With kernel density results for 36 sectors, the curve of GTFP growth has shifted upward and toward the left since 2010. For high-emission type sectors, their kernel curve has also moved upward and toward the left. The curve of moderate-emission type sectors significantly shifted toward the left, whereas the curve of low-emission type moved upward. Third, based on regression estimation results, environmental regulatory policy, resource input structure, foreign direct investment, and energy-type structure significantly influence GTFP growth. Technology innovation makes insignificant impact on GTFP for industrial sectors. In conclusion, sectorial heterogeneity should be paid more focus in order to improve their growth, especially for high-emission type sectors. Green technology innovation is the most potential factor in the future to stimulate GTFP growth in China. (c) 2019 Society of Chemical Industry and John Wiley & Sons, Ltd. |
| Author Keywords |
green total factor productivity; industrial heterogeneity; stochastic frontier analysis; system generalized method of moments |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000471126900005 |
| WoS Category |
Energy & Fuels; Engineering, Environmental; Environmental Sciences |
| Research Area |
Energy & Fuels; Engineering; Environmental Sciences & Ecology |
| PDF |
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