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| 1 |
ID:
054134
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| 2 |
ID:
121338
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| Publication |
2013.
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| Summary/Abstract |
Using provincial panel data from the period 1995-2009 to analyze the relationship between the industrial structural transformation and carbon dioxide emissions in China, we find that the first-order lag of industrial structural adjustment effectively reduced the emissions; technical progress itself did not reduce the emissions, but indirectly led to decreasing emissions through the upgrading and optimization of industrial structure. Foreign direct investment and intervention by local governments reduced carbon dioxide emissions, but urbanization significantly increased the emissions. Thus, industrial structural adjustment is an important component of the development of a low-carbon economy. In the context of industrial structural transformation, an effective way to reduce a region's carbon dioxide emissions is to promote the upgrading and optimization of industrial structure through technical progress. Tighter environmental access policies, selective utilization of foreign direct investment, and improvements in energy efficiency can help to reduce carbon dioxide emissions.
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| 3 |
ID:
108128
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| Publication |
2011.
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| Summary/Abstract |
This paper focuses on the relationship between technology spillovers in the context of the evolution of China's regional industrial structure. Based on a theoretical model, we have formally shown the impact of the evolution of the regional industrial structure and have also empirically tested technology spillovers for the period 1991-2007 in the context of the evolution of the regional industrial structure in China. The findings provide an important theoretical and practical basis for the government to formulate regional economic policies and industrial development strategies.
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| 4 |
ID:
179717
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| Summary/Abstract |
Urban industrial transformation is crucial for resource-based cities to break through the lock-in effect of natural resources dependence and achieve economic, environmental and energy sustainability. This paper proposes a rough set-based rule mining technique of learning, validation and generalisation to identify what influential factors, under which synergetic combination methods and influencing levels lead to successful industrial structural transformation in resource-based cities. The extracted decision rules reveal the transformation patterns from the rationalisation and optimisation of industrial structure, as well as the potential path transmission mechanism that help prevent the negative effects of resource dependence. The results from China's 115 resource-based cities during 2004–2017 show resource curses that may hinder industrial structural transformation are not absolute existence but conditional appearance. Abundant resources in superior urban transformation cases promote the rationalisation and optimisation of industrial structure by driving material and human capital investment under a reasonable government policy intervention. However, resource dependence squeezes out the technological innovation and marketing competition for developing private enterprises, challenging transformations that improve resource allocation efficiency based on marketisation. The identified patterns inspire policy-makers to adjust urban industrial structure through developing urban resource advantages and bypassing insufficiencies in historical transformation.
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