Abstract:Inclusive green growth is a sustainable development mode in pursuit of economic growth, social equity, and environmental protection. At present, a large number of articles have discussed the impact of foreign direct investment (FDI) on economic growth, green growth, and inclusive growth. However, the research about inclusive green growth is mainly descriptive. This paper constructs China's inclusive green growth index and analyzes the impact of FDI on inclusive green growth in China. Specifically, by constructing a super efficiency slacks-based measure model (which has two undesirable outputs: income disparity and environmental pollution) to calculate the Inclusive green growth index, this paper compares and analyses the differences and regional characteristics of China's total factor productivity, inclusive total factor productivity, green total factor productivity, and inclusive green total factor productivity. We find that total factor productivity is decreasing after considering undesirable output, and the traditional total factor productivity is higher than the inclusive green total factor productivity by 0.112; at the regional level, the trend of the total factor productivity is gradually decreasing from east to west, which indicates that there are regional differences in inclusive green growth of China, and there is room for improvement. Meanwhile, we construct a panel vector autoregressive model (PVAR) and use generalized impulse response function and variance decomposition to analyse the influence of FDI on China's inclusive green total factor productivity. The results show that FDI is beneficial to the promotion of inclusive green total factor productivity in China, and environmental pollution in the FDI process is an important factor hindering the inclusive green total factor productivity.
The reverse technology spillover effect of Outward Foreign Direct Investment (OFDI) has been widely discussed. In the context of pursuing green growth, a few scholars began to study the impact of OFDI on home country green technological progress or green total factor productivity. However, few of these papers have made a thorough analysis of how OFDI affects the home country’s green technological progress, and have not considered the impact of different types of OFDI on green technological progress. This paper extends the basic analysis framework of technological progress to green technological progress, and discusses for the first time the ways for China to invest in developed and developing countries to achieve green technological progress. Specifically, this paper combines the global Malmquist productivity concept with the directional distance function to construct the global Malmquist Luenberger (GML) index to describe green technological progress of China’s provinces, and uses panel data model from 2003 to 2016 to study the impact of China’s investment in different types of countries. The results show that: (1) China’s investment in developed countries can bring reverse green technology spillovers and promote China’s green technology progress. But this is also affected by China’s domestic human capital stock, the increase in human capital stock is conducive to the absorption of green technology. (2) OFDI flows to transition or developing countries have failed to bring about green technological progress, but domestic R&D capital stock can produce a control response. (3) Environmental regulation, import trade and domestic R&D capital stock can bring positive effects on green technology progress, while foreign direct investment, fiscal decentralization and economic growth hinder green technology progress. (4) There is regional heterogeneity in the impact of OFDI with different directions on green technological progress. Because of environmental regulation and economic development, the eastern region of China is easier to obtain reverse green technology progress than the central and western regions in the process of OFDI.
To clarify the relations between low-carbon green transition, consumption upgrading, and industrial structure change, this paper firstly builds a dynamic model of the three, then uses the PVAR Model and panel data of 30 Chinese provinces from 2008 to 2020 to carry out empirical study from the rationalization and upgrading dimensions of industrial structural change, respectively. The results are as follows: (1) Low-carbon green transition and consumption upgrading are Granger causes of each other. In this causal relationship, low-carbon green transition hinders consumption upgrading, but consumption upgrading significantly promotes low-carbon green transition. (2) Low-carbon green transition plays a facilitating and hindering role in industrial structure rationalization and upgrading, respectively. However, from the different dimensions of industrial structure change, only industrial structure upgrading has a significant reverse hindering effect on low-carbon green transition, and the reverse effect of industrial structure rationalization on low-carbon green transition is not significant. (3) Consumption upgrading has a hindering and promoting effect on the rationalization of industrial structure in the short- and long-run respectively, and a promoting and hindering effect on the industrial structure upgrading respectively; however, only industrial structure upgrading significantly promotes consumption upgrading in the opposite direction, while industrial structure rationalization has no significant effect on consumption upgrading. These findings propose some suggestions such as advocating the new way of green consumption, constructing and improving the green whole industry chain, and strengthening the synergy between imitative innovation and independent innovation.
To explore the relationship between consumption upgrading and agricultural green total factor productivity in the context of green and high-quality development of agriculture in China. Based on the construction of a composite index of consumption upgrading and the Malmquist index of non-expected output in the SBM-DEA model to measure agricultural green total factor productivity, this paper uses the PVAR model and panel data from 30 Chinese provinces from 2008 to 2020 to empirically analyze the mechanism of the effect of consumption upgrading on agricultural green total factor productivity under high-quality development. The results are as follows: (1) Both the real economy and consumption upgrading are ahead of the change in agricultural green total factor productivity and have a negative short-run impact on agricultural green total factor productivity but a continuous boosting effect in the long-run. (2) In terms of specific impact paths, the real economy boosts agricultural green total factor productivity through technical efficiency and technical change paths and has a negative impact through scale efficiency, whereas consumption upgrading has inhibitory and sustained promotional effects in the short- and long-run, respectively, through technical efficiency and technical change paths and has opposite impact effects in the scale efficiency path.
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