Literature DB >> 34625900

Convergence or divergence? The effects of economic openness on low-carbon innovation in Chinese manufacturing industry.

Chaojun Yang1, Liju Liu1, Zhaoran Wang1, Lishan Liu2.   

Abstract

Low-carbon innovation can address both economic and environmental concerns; patterns of low-carbon innovation convergence can determine the effectiveness of mitigating the adverse consequences of climate change. Considering that economic openness has a huge impact on the development of innovation capability, this paper uses a conditional β convergence model to examine the convergence of low-carbon innovation in Chinese manufacturing industry and its relationship with economic openness. We incorporate the spatial spillover effect into the convergence function by constructing spatial error model, spatial lag model, and spatial Durbin model. Based on a panel data set of 30 Chinese provinces over the period 2004-2016, the results show that low-carbon innovation in Chinese manufacturing industry has a strong feature of conditional β convergence. The convergence rate of low-carbon innovation is slightly slowed down by economic openness, and the main reason is that the spillover effect is weak and the convergence rate is slow in lower open areas, so the convergence rate of the whole country is slowed down by that of the lower open areas. Although the economic openness in adjacent areas can contribute to the development of local innovation ability, but generally speaking, economic openness in local areas takes a stronger effect in promoting the convergence of low-carbon innovation than that in adjacent areas. The findings have important policy implications as they suggest the need for a more equal degree of economic openness among Chinese provinces to speed up the convergence of low-carbon innovation.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Conditional β convergence; Economic openness; Low-carbon innovation

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Year:  2021        PMID: 34625900     DOI: 10.1007/s11356-021-16819-6

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


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Authors:  Xiaojun Ma; Yijie Fan; Feng Shi; Yanqi Song; Yuan He
Journal:  Environ Sci Pollut Res Int       Date:  2022-04-11       Impact factor: 5.190

  1 in total

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