Effects of industrial relocation on Chinese regional economic growth disparities: Based on system dynamics modeling

Wu, Aizhi; Li, Guoping; Sun, Tieshan; Liang, Yusheng

doi:10.1007/s11769-014-0664-7

Cited by 16 publications

(8 citation statements)

References 9 publications

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“…However, some differences were noted between Chinese and overseas returnees; for instance, Chinese returnees were found to be more frequently in waged employment, whereas overseas returnees are more inclined to start their own business. This may be because more Chinese manufacturing industries are moving from developed urban areas to less developed areas (Wu, Li, Sun, & Liang, 2014). The concentration of manufacturing factories in cities and towns has prompted returnees to settle in cities and towns.…”

Section: Discussionmentioning

confidence: 99%

Reurbanisation in my hometown? Effect of return migration on migrants' urban settlement intention

Yin

Huang

et al. 2020

Population Space and Place

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Return migration has become a critical socio‐economic phenomenon—both between countries and within countries—and profoundly affects the development prospects in a migrants' country or region of origin. Studies have mainly focused on the return of overseas migrants and their employment transformation and social integration upon return; few studies have investigated internal return migrants and their residential choice and urbanisation effect. To fill this gap, the present study used nationally representative data from China to construct a moderated mediation model for examining the relationship between internal return migration, nonagricultural employment, and urban settlement intention. The empirical results indicated that return migration affected urban settlement intention through two paths. In addition to directly strengthening migrants' urban settlement intention, return migration indirectly strengthened this intention by promoting nonagricultural employment. Compared with those returning to eastern China, returnees to central China were less likely to be in nonagricultural employment and had weaker intention to settle in a town. Among return migrants, the impacts of age at return and workplace during migration on the urban settlement intention were mainly through direct effects.

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Section: Discussionmentioning

confidence: 99%

Reurbanisation in my hometown? Effect of return migration on migrants' urban settlement intention

Yin

Huang

et al. 2020

Population Space and Place

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“…Excluding the influence of trade balance, Zhang et al [31] found that regional carbon spillover is mainly concentrated in the coastal provinces but it contributes to an increase of carbon emissions in the central and western regions, and the coastal and inland provinces contribute to the increase of national carbon emissions through interregional imports and exports. In addition, because of differences in the economic development, technological progress and diffusion effects among regions, industrial transfer has been occurring [32]. Xu et al [33] reveal that for every 1% increase in industrial transfer, there is a 0.327% increase in industrial carbon transfer before passing the turning point.…”

Section: Literature Reviewmentioning

confidence: 99%

The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights

Peng

Tan

2019

Sustainability

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R&D investment plays a great role in achieving China’s low-carbon economy goals, which has a moderating effect on the relationship between income and carbon emissions. Furthermore, such a moderating effect may have spatial differences, given the possible spatial dependence of carbon emissions. Therefore, this paper explores the direct and spatial spillover moderating effects of R&D investment by adopting the panel spatial Durbin model and data of 30 provinces in China during 1998–2015. The empirical results firstly indicate that R&D investment moderates the positive impact of income on local carbon emissions for both the non-spatial and spatial model, and that more R&D investment can make carbon emissions reach the turning point earlier. Secondly, R&D investment in the local province increases the positive influence of local income on neighboring carbon emissions, which mainly results from the transfer effect of carbon emissions rather than the knowledge spillovers effect. The results are indicated to be robust by three types of robustness analyses. Finally, FDI and patents are the main constrained forces of local and neighboring carbon emissions; coal consumption is the main driver of local carbon emissions.

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“…Moreover, the effect of the alternative process of new energy to obtain power-wasting and non-clean energy was greater than the effect of GDP growth in achieving the carbon reduction target (Xu et al, 2006). However, these factors were dependent apparently on income level or on technical progress factors, which can lead to a significant autocorrelation effect (Wu et al, 2013). In addition, the models derived from these factors were commonly highly difficult to interpret.…”

Section: Factors Influencing Carbon Emissionmentioning

confidence: 99%

Impact of regional development on carbon emission: Empirical evidence across countries

Yuan

2014

Chin. Geogr. Sci.

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Global warming is recently an urgent issue worldwide. The increase of carbon emissions induced by human economic activities has become a major driving force behind global climate change. Thus, as a matter of social responsibility, reasonable carbon constraints should be implemented to ensure environmental security and sustainable development for every country. Based on a summary of studies that examined the relationship between carbon emissions and regional development, this paper shows that human activity-led carbon emission is caused by the combination of several influencing factors, including population size, income level, and technical progress. Thus, a quantitative model derived from IPAT-ImPACT-Kaya series and STIRPAT models was established. Empirical analysis using multivariate nonlinear regression demonstrated that the origins of growing global carbon emission included the increasing influencing elasticity of the population size and the declining negative effect of technical progress. Meanwhile, in context of classification of country groups at different income levels, according to the comparison of fluctuating patterns of the influencing elasticity, technical progress was found as the main factor influencing carbon emission levels in high-income countries, and population size might be the controlling factor in middle-income countries. However, for low-income countries, the nonlinear relationship between carbon emission and its influencing factors was not significant, whereas population growth was identified as an important potential driving force in future carbon emissions. This study can therefore provide a reference for the formulation of policies on carbon constraints, especially to develop more efficient carbon mitigating policies for countries at different income levels.

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Effects of industrial relocation on Chinese regional economic growth disparities: Based on system dynamics modeling

Cited by 16 publications

References 9 publications

Reurbanisation in my hometown? Effect of return migration on migrants' urban settlement intention

Reurbanisation in my hometown? Effect of return migration on migrants' urban settlement intention

The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights

Impact of regional development on carbon emission: Empirical evidence across countries

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