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.
Highlights
As the largest developing country in the world, since reform and opening up, China has created phenomenal rates of growth with an average annual rate of 9.8% for 34 consecutive years [1]
If we have considered energy consumption and the pollutant emissions correctly, the green total factor productivity (TFP) of China’s industry goes backwards by 0.02% per year on average, which means that energy consumption and pollutant emissions have caused a loss of performance of the industrial economy; i.e., China’s industrial growth is largely at the expense of energy consumption and environmental pollution, which further demonstrates that most studies have overestimated China’s industrial TFP growth
The Monte Carlo simulation experiment indicates that differenced generalized method of moments (DIF–GMM) is affected by weak instrumental variables, while this problem is effectively solved by SYS–GMM through adding the quantity of instrumental variables
Summary
As the largest developing country in the world, since reform and opening up, China has created phenomenal rates of growth with an average annual rate of 9.8% for 34 consecutive years [1]. China’s economy has entered into the “New Normal”, which has three main characteristics: the economy has shifted gear from the previous high-speed to medium-to-high speed growth, the economic structure is constantly being improved and upgraded, and the economy is increasingly driven by innovation instead of input and investment. Against this background, China’s industrial economy is being confronted with internal and external constraints and challenges. It is essential to develop a new growth pattern that can break the resources and environment constraints and improve sustainable industrial competitiveness. In July 2016, China issued the “industrial green development plan (2016–2020)”, which is the first guiding document for industrial green development in the new period
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