The spatial threshold effect and its regional boundary of financial agglomeration on green development: A case study in China

Yuan, Huaxi; Feng, Yidai; Lee, Jay; Liu, Haimeng; Li, Ruzi

doi:10.1016/j.jclepro.2019.118670

Cited by 75 publications

(36 citation statements)

References 46 publications

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“…More critically, we focus on the spatial decomposition effect of explanatory variables on explained variables after treating the spatial econometric model with partial differentiation, including direct effect, spillover effect and the total effect of both. Among them, the direct effect includes the spatial feedback cumulative effect of the spillover effect of the province to its neighboring provinces, that is, it includes the feedback effect of the spillover effect of its own province and the spillover effect of the neighboring provinces (Yuan et al, 2020); The indirect effect refers to the spillover effect, that is, the spatial diffusion of the influence of the province on the neighborhood. And the total spatial effect covers the previous two types of effects in a given province, but it is not simply a summation.…”

Section: Empirical Results Of Spatial Durbin Modelmentioning

confidence: 99%

How does energy technology innovation affect total factor ecological efficiency: Evidence from China.

Shi

Han

2021

Preprint

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Recently, with the dual constraints of resources and environment, to accelerate the transformation of low-carbon energy driven by energy technology innovation has become a global development trend. On account of the provincial data during the period of 2000 to 2017, we creatively incorporate the ecological footprint into the measurement of total factor ecological efficiency so as to infer the coordinated development level of 3E system more precisely. In this paper, the dynamic spatial impact of energy technological innovation on regional total factor eco-efficiency is explored through the spatial Durbin model, and the complex nonlinear relationship between the two is further probed by constructing the panel threshold model. The following conclusions are obtained ultimately. First of all, both China's provincial ecological efficiency and energy technology innovation activities possess significant spatial positive correlation, which manifests as the spatial geographical distribution agglomerated by the similar characteristics; Secondly, the regional energy technology innovation has a remarkable spatial effect on ecological efficiency, which displays a U-shaped trend. And compared with the direct effect, the spatial spillover effect is more intense, along with more stronger long-term influence; Finally, taking the level of regional economic development as the moderating variable, the impact of energy technology innovation on eco-efficiency emerges a conspicuous threshold effect with two threshold values. Only when the level of economic development crosses the double threshold, can energy technology innovation activities significantly improve the regional total factor ecological efficiency. After the robustness test and discussion of the empirical model, relevant policy suggestions are put forward based on the conclusions of the paper.

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Section: Empirical Results Of Spatial Durbin Modelmentioning

confidence: 99%

How does energy technology innovation affect total factor ecological efficiency: Evidence from China.

Shi

Han

2021

Preprint

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“…On the other hand, with the expansion of geographic distance, the cost of obtaining environmental technology spillover across geographic distance increases (Xu, 2015; [39,40]. For each economic unit, there is a distance threshold that it does not want to exceed (Yuan, 2020) [41]. The other is economic linkages such as trade and investment.…”

Section: Literature Reviewmentioning

confidence: 99%

Agglomeration Production, Industry Association and Carbon Emission Performance: Based on Spatial Analysis

Peng

Wang

et al. 2020

Sustainability

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Current emission reduction policies have struggled to adapt to the reality of industrial spatial agglomeration and increasing industrial linkages. In response, this paper incorporates new economic geography factors such as agglomeration production and industrial (trade) association into the analysis framework of carbon emission performance factors through China’s provincial panel data and conducts empirical research. It has been found that large-scale industrial production under economic agglomeration is conducive to improving carbon emission performance and that different forms of agglomeration at different degrees of agglomeration correspond to different carbon emission performances. As the degree of agglomeration increases, the effect of reducing emissions by specialized agglomeration decreases while the effect of reducing emissions by diversified agglomeration increases. Specialized agglomeration externalities and diversified agglomeration externalities can coexist at the same time, depending on the appropriate degree of agglomeration. There is a strong negative environmental efficiency effect in the provinces with close commodity trade links, which has triggered environmental dumping and pollution transfer between provinces. In the work of energy conservation and emission reduction, we must attach great importance to the hidden carbon in domestic merchandise trade and the resulting intergovernmental environmental game, and furthermore, give full play to the “self-purification” effect of aggregate production on energy conservation and emission reduction.

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“…Most of this information is ambiguous, unclear, and hard to understand. After being transmitted, non-standardized information may introduce ambiguity to financial decisions due to distance-decay, thus inhibiting the long-distance spatial spillover of financial agglomeration on green development [84]. As a result, the conclusion of "death of distance" is not valid in the relationship between financial agglomeration and green development [85].…”

Section: Limitation and Further Researchmentioning

confidence: 99%

The Spatio-Temporal Heterogeneity of Financial Agglomeration on Green Development in China Cities Using GTWR Model

2020

Self Cite

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By promoting financial agglomerations to support green development in a region is a keyway for China to resolve the sharp contradiction between economic growth and environmental protection. However, existing research only considered the promotion effect of financial agglomerations on green development, but the spatio-temporal non-stationarity of that effect has been overlooked. Using a panel data of 285 prefecture-level cities in China and based on the evaluation of green development by a Driving-Pressure-State-Impact-Response (DPSIR) model, this paper analyzes the spatial correlation of financial agglomeration on green development. The paper also investigates the differences in the spatio-temporal influence of financial agglomeration on green development from both global and local perspectives by employing a Bivariate Local Indicators of Spatial Association (BLISA) model and a Geographically and Temporally Weighted Regression (GTWR) model. The results indicate that: (1) There exists significant spatial dependency between financial agglomeration and green development from 2003 to 2015, with Low-Low (L-L) and Low-High (L-H) spatial clusters as the main cluster types. (2) From the local perspective, the promoting effect of financial agglomerations on green development has showed significant spatial heterogeneity with a gradually decreasing trend from the southeast coast to the northwest inland of China. This work can help to develop policies for supporting green development by formulating differential strategies for financial agglomerations.

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The spatial threshold effect and its regional boundary of financial agglomeration on green development: A case study in China

Cited by 75 publications

References 46 publications

How does energy technology innovation affect total factor ecological efficiency: Evidence from China.

How does energy technology innovation affect total factor ecological efficiency: Evidence from China.

Agglomeration Production, Industry Association and Carbon Emission Performance: Based on Spatial Analysis

The Spatio-Temporal Heterogeneity of Financial Agglomeration on Green Development in China Cities Using GTWR Model

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