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Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

1
School of Economics and Resource Management, Beijing Normal University, Beijing 100875, China
2
School of Statistics, Beijing Normal University, Beijing 100875, China
3
School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China
*
Author to whom correspondence should be addressed.
Sustainability 2018, 10(4), 1052; https://doi.org/10.3390/su10041052
Received: 26 February 2018 / Revised: 29 March 2018 / Accepted: 31 March 2018 / Published: 2 April 2018
(This article belongs to the Section Economic, Business and Management Aspects of Sustainability)
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Abstract

This paper employs directional distance function (DDF) and the global Malmquist–Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China’s 36 industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all industrial sectors, which indicates that the growth of industrial economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor. View Full-Text
Keywords: China’s industrial economy; green total factor productivity; determinants; directional distance function; global Malmquist–Luenberger index; dynamic panel data model China’s industrial economy; green total factor productivity; determinants; directional distance function; global Malmquist–Luenberger index; dynamic panel data model
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Chen, C.; Lan, Q.; Gao, M.; Sun, Y. Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy. Sustainability 2018, 10, 1052.

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