Exploring the spatial effect of China's carbon emission trading scheme on green total factor productivity: An SBM-MML measurement and its decomposition

Abstract

To obtain a detailed evaluation of green total factor productivity (GTFP), a novel measurement, Slack Based Measure-Meta-frontier Malmquist Luenberger (SBM-MML) model, is proposed in this paper. Instead of decomposing the growth rate of GTFP, it can directly decompose the GTFP into three components representing technical efficiency, technological innovation and technical leadership, respectively. Taking the provincial data of China from 2005 to 2020, it is found that eastern China, followed by central China, northeast China and western China, has the highest level of GTFP, efficiency, technological innovation and technical leadership. Moreover, the technological level of eastern China is far ahead of the national average level. In 2013, to explore the mechanism of carbon emission reduction, the Chinese government launched a carbon emissions trading scheme (CETS) in seven pilot regions. In this paper, the spatial difference-in-differences (SDID) model is used to measure the direct effect and the spatial effect of the CETS pilot policy on the GTFP and its components. It is found that the CETS pilot policy has a positive effect and a positive spillover effect on the GTFP, whereas a negative siphon effect on technological innovation is also indicated. Finally, based on the results, several policy implications are put forward.