Spatial Econometric Study on the Impact of Industrial Upgrading on Green Total Factor Productivity
Tao Ma,
Xiaoxi Cao and
Stefan Cristian Gherghina
Mathematical Problems in Engineering, 2022, vol. 2022, 1-11
Abstract:
Under the background of high-quality development led by the new development concept in China, it is imperative to change the development mode, optimize the economic structure, and transform the driving force, and industrial upgrading is the necessary way to promote the optimization of the industrial structure and achieve high-quality economic development. Based on data covering 284 prefecture-level cities in China, this paper first calculates the green total factor productivity (GTFP) of each prefecture-level city and then constructs three spatial econometric models (SLM, SEM, and SDM) based on four spatial weight matrices to empirically analyze the impact of industrial upgrading on GTFP. The results show that the GTFP of all cities in China shows a fluctuating upward trend and significant spatial spillover effect. Both full-sample and regional heterogeneity tests show that industrial upgrading can promote growth in GTFP, but the promoting effect on different regions is different. Regarding the control variables, GTFP has an inverted U-shaped relationship with economic development; additionally, human capital and financial development play a driving role in GTFP, while population density plays a restraining role. Finally, based on the empirical findings, we propose a multipronged policy of differentiated industrial policy and a variety of complementary measures to promote GTFP growth.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1133340
DOI: 10.1155/2022/1133340
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